understanding early hemophilic arthropathy in children and...

Understanding Early Hemophilic Arthropathy in Childrenand Adolescents Through Magnetic Resonance Imaging

Based on T2 Mapping

by

Haris Majeed

A thesis submitted in conformity with the requirementsfor the degree of Masters of Science

Graduate Department of Institute of Medical SciencesUniversity of Toronto

c© Copyright 2019 by Haris Majeed

Abstract

Understanding Early Hemophilic Arthropathy in Children and Adolescents Through

Magnetic Resonance Imaging Based on T2 Mapping

Haris Majeed

Masters of Science

Graduate Department of Institute of Medical Sciences

University of Toronto

2019

Hemophilia is an X-linked recessive disease, which mainly affects males. This disease

results in bleeding events targeting mainly the joints, which leads to arthropathy and

cartilage degeneration. Human cartilage is primarily composed of water; as a result,

past studies have noted that magnetic resonance imaging through T2 mapping can hold

great promise for assessment of early changes in the cartilage. Hence this cross-sectional

study seeks to validate T2 mapping as a tool for studying children and adolescents with

hemophilic arthropathy. T2 relaxation times of hemophilia and healthy ankle/knee joints

were compared, and found to have significant differences in mean T2 relaxation times.

Furthermore, significant negative associations between age and T2 relaxation times were

noted in both groups. Therefore, this investigation suggests that future studies may be

able to use T2 mapping as a tool to better understand early hemophilic arthropathy in

children and adolescents.

ii

Acknowledgements

I would like to take this opportunity to thank some individuals, who have provided

the guidance and support to complete this thesis and Masters. Firstly, I would like to

thank my supervisor, Dr Andrea Doria. I was very fortunate to come across a mentor

like Dr Doria, who not only provided me with a stepping stone into the field of medical

sciences from my previous background in climatology, but also supported me to strive

for my best throughout my Masters.

Furthermore, I would like to thank Dr Brian Feldman. He provided me with guidance

throughout the Masters project and made time in his busy schedule to help me break

down concepts and ideas to fully comprehend the topic at hand- a strategy that I will

greatly utilize for my future academic career.

Additionally, I would like to thank Dr Christopher Macgowan. Dr Macgowan always

made himself available when I approached him with questions and provided comprehen-

sive direction when I needed help with a particular concept.

I thank Dr Doria, Dr Feldman, and Dr Macgowan for providing me with feedback

in committee meetings and during their busy schedules. Their feedback has further

improved my ability to critically think and engage in a new discipline with an open

mindset. Each of my committee members specializes in different fields, ranging from ra-

diology, rheumatology, to medical physics. This diversity of expertise has led to a thesis

that incorporated multiple fields, from which I learned an immense amount.

I would also like to thank all the individuals who reviewed this thesis and to Siemens

Canada for providing the funding to support this Masters. My sincere gratitude also goes

out to my lab members, diagnostic imaging staff, and the Institute of Medical Sciences

that took time to assist me with minor issues that were present on a day-to-day basis.

iii

Statement of Contributions

This thesis comprises of two cross-sectional clinical investigations, along with one addi-

tional critical appraisal of an existing scoring system (Appendix).

Both clinical investigation presented in this thesis seek to understand the importance of

MRI T2 mapping as a tool for studying healthy and hemophilic children and adolescents.

I have written this thesis, along with constructing the figures. Drs Doria, Feldman, Mac-

gowan helped with the data analysis and revision of this thesis.

As for the critical appraisal of an existing scoring system (Appendix), I collaborated

with the writing and analysis of this manuscript, as a result I am co-author on this

manuscript along with Dr Doria. This critical appraisal manuscript has been submitted

to the journal of Haemophilia.

iv

Contents

1 Introduction 1

1.1 Hemophilia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.1.1 The “Royal Disease” and its Brief History . . . . . . . . . . . . . 2

1.1.2 Blood Coagulation & Bleeding Disorders . . . . . . . . . . . . . . 4

1.1.2.1 Coagulation Cascade . . . . . . . . . . . . . . . . . . . . 4

1.1.2.2 Genetics . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.1.3 Management and Evaluation of Hemophilia . . . . . . . . . . . . 7

1.1.3.1 Severity Groups . . . . . . . . . . . . . . . . . . . . . . . 7

1.1.3.2 Treatment and Prophylactic Regimens . . . . . . . . . . 8

1.1.3.3 Cost and Financial Burden . . . . . . . . . . . . . . . . 10

1.1.4 Transfusion-Transmitted Diseases . . . . . . . . . . . . . . . . . . 12

1.1.5 Global Epidemiology of the Disease . . . . . . . . . . . . . . . . . 14

1.1.6 Arthropathy & Arthritis . . . . . . . . . . . . . . . . . . . . . . . 22

1.1.6.1 Articular Cartilage . . . . . . . . . . . . . . . . . . . . . 22

1.1.6.2 Hemophilic Arthropathy . . . . . . . . . . . . . . . . . . 24

1.2 Evolution of Diagnostic Imaging for Hemophilic Arthropathy . . . . . . . 26

1.2.1 Radiograph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

1.2.2 Magnetic Resonance Imaging . . . . . . . . . . . . . . . . . . . . 27

1.2.2.1 MRI Basics and Classical Mechanics . . . . . . . . . . . 28

1.2.2.2 T2 Mapping . . . . . . . . . . . . . . . . . . . . . . . . . 31

1.2.2.3 International Prophylaxis Study Group Scoring System . 32

1.3 Purpose, Hypothesis, and Aims of Study . . . . . . . . . . . . . . . . . . 34

1.3.1 Study #1 - T2 Mapping of Children and Adolescents with Hemophilic

Arthropathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

1.3.2 Study #2 Characterization of T2 Mapping in Healthy Children

and Adolescents . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

2 Study #1 37

2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

2.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

2.2.1 Study Population . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

v

2.2.2 MRI - T2 Mapping Protocols . . . . . . . . . . . . . . . . . . . . 40

2.2.3 Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 41

2.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

2.3.1 T2 Relaxation Times in Persons with Hemophilia . . . . . . . . . 43

2.3.2 Association of IPSG MRI Scores with T2 Relaxation Times . . . 50

2.3.3 Linear Regression Models for T2 Relaxation Times . . . . . . . . 55

2.4 Discussion & Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

3 Study #2 59

3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

3.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

3.2.1 Study Population . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

3.2.2 MRI - T2 Mapping Protocols . . . . . . . . . . . . . . . . . . . . 62

3.2.3 Data and Statistical Analysis . . . . . . . . . . . . . . . . . . . . 65

3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

3.3.1 Discussion & Limitations . . . . . . . . . . . . . . . . . . . . . . . 77

4 Conclusions and Future Directions 79

4.1 Study #1 - T2 Mapping of Children and Adolescents with Hemophilic

Arthropathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

4.2 Study #2 - Characterization of T2 Mapping in Healthy Children and Ado-

lescents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

5 References 83

6 Appendix A: Critical Appraisal Manuscript 92

7 Appendix B: IPSG MRI scale 111

vi

List of Tables

1 United States age standardized mortality trends for hemophilia A . . . . 20

2 MRI-T2 mapping protocol using a 3.0 T magnet . . . . . . . . . . . . . . 413 Combined ankle and knee cartilage T2 relaxation time data for hemophilia

and healthy subjects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 494 Ankle (tibia-talus) cartilage T2 relaxation times for hemophilia and healthy

subjects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495 Knee (femur-tibia) cartilage T2 relaxation times for hemophilia and healthy

subjects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 496 Trends (P-value) of hemophilic ankle data regressed with IPSG MRI scores. 557 Trends (P-value) of hemophilic knee data regressed with IPSG MRI scores. 558 Regression models using hemophilic ankle/knee age and total IPSG MRI

scores. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569 Regression models using hemophilic ankle/knee age and soft tissue scores. 5610 Regression models using hemophilic ankle/knee age and osteochondral

scores. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

11 MRI parameters for healthy pediatric ankle scan at 3.0 T . . . . . . . . . 6412 Data summary of healthy ankle MRI protocol 1 . . . . . . . . . . . . . . 7513 Data summary of healthy ankle MRI protocol 2 . . . . . . . . . . . . . . 7514 Data summary of healthy ankle MRI high resolution . . . . . . . . . . . 7515 Regression models using protocol 1 . . . . . . . . . . . . . . . . . . . . . 7616 Regression models using protocol 2 . . . . . . . . . . . . . . . . . . . . . 7617 Regression models using high resolution . . . . . . . . . . . . . . . . . . . 76

vii

List of Figures

1 Annual number of persons with hemophilia A and B from 1999-2016 . . . 152 Number of persons with hemophilia A and B by severity in the year 2016

for developed nations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Number of persons with hemophilia A and B by severity in the year 2016

for developing nations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 Time series of United States age standardized mortality rates for hemophilia

A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Annual hospitalization incidence rates for children and adolescents with

hemophilia in Toronto, Canada from 2002-2016 . . . . . . . . . . . . . . 216 Annual emergency incidence rates for children and adolescents with hemophilia

A and B in Toronto, Canada from 2002-2016 . . . . . . . . . . . . . . . . 21

7 Regions of interests in the ankle and knee of a MRI . . . . . . . . . . . . 428 Aggregated data for ankle and knee cartilage T2 relaxation times . . . . 449 Separate ankle and knee cartilage T2 relaxation time data . . . . . . . . 4510 Association between age and ankle cartilage T2 relaxation times for each

selected region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4711 Association between age and knee cartilage T2 relaxation times for each

selected region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4812 Association of age and IPSG soft tissue and osteochondral scores . . . . . 5113 Association between age and total IPSG MRI scores for hemophilic ankles

(top) and knees (bottom). . . . . . . . . . . . . . . . . . . . . . . . . . . 5214 Association between total IPSG MRI scores and ankle cartilage T2 relax-

ation times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5315 Association between total IPSG MRI scores and knee cartilage T2 relax-

ation times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

16 MRI for the ankle (tibia-talus) of an eight year old boy . . . . . . . . . . 6417 MRI of the lateral aspect of a healthy ankle . . . . . . . . . . . . . . . . 6718 MRI of the medial aspect of a healthy ankle . . . . . . . . . . . . . . . . 6819 Bland-Altman plot showing the difference in cartilage T2 relaxation times

between MRI protocol 1 and 2 . . . . . . . . . . . . . . . . . . . . . . . . 6920 Bland-Altman plot showing the difference in cartilage T2 relaxation times

between MRI protocol 1 and high resolution . . . . . . . . . . . . . . . . 7021 Bland-Altman plot showing the difference in cartilage T2 relaxation times

between MRI protocol 2 and high resolution . . . . . . . . . . . . . . . . 71

viii

22 Plots of healthy individual’s BMI and lateral aspect of the ankle underdifferent MRI protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

23 Plots of healthy individual’s BMI and medial aspect of the ankle underdifferent MRI protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

ix

List of Abbreviations and Symbols

Abbreviations Description

ANOVA Analysis of variance statistical testα Flip angle during magnetizationBMI Body mass indexB0 External magnetic field of the magnetBα Local magnetic field strength◦C Degrees CelsiusDNA Deoxyribonucleic acidFDA Food and drug administration of the United StatesFIa Activated recombinant factor 1, also known as fibrinFII Recombinant factor 2, also known as prothrombinFIIa Activated recombinant factor 2, also known as thrombinFIX Recombinant factor 9FV Recombinant factor 5, related to parahemophiliaFVIII Recombinant factor 8HIV Human immunodeficiency virusICD International classification of diseasesIPSG International prophylaxis study groupIU International unitskg Kilogrammg Milligramms MillisecondsMHz MegahertzmL MillilitersMRI Magnetic resonance imagingSD Standard deviationSickKids The Hospital for Sick ChildrenT Tesla, units of magnetic field strengthTE Echo timeTR Repetition timeω Larmor frequencyWB Weight bearing region of the ankle or kneeWFH World federation of hemophiliaWHO World health organizationγ Gyromagnetic ratio

x

Chapter 1

Introduction

1

Chapter 1. Introduction 2

1.1 Hemophilia

1.1.1 The “Royal Disease” and its Brief History

To begin, a brief introduction of the history of hemophilia will be discussed. Early

records that date back to the second century AD, described the symptom of exten-

sive bleeding in boys during surgery. In the tenth century, this excessive bleeding

in boys was noted by an Arab surgeon Abu Al-Zahrawi, who is now known as the

father of modern surgery [Moreno-Otero, 2013]. In particular, Al-Zahrawi noted,

while performing surgeries, that boys in certain areas of residence bled more than

usual, and sometimes died from uncontrolled bleeding after a trauma. It was not

until 1803, that Dr. John Otto, an American physician and politician, published

a report in a weekly newspaper, recognizing that the bleeding disease which pri-

marily affected men only existed in certain families. Another American physician,

Dr. John Hay, published a paper in the year 1813, in the New England Journal of

Medicine and Surgery proposing that affected men could pass the trait for a bleeding

disorder to their unaffected daughters [Hay, 1813]. After this publication, the word

“hemophilia” was coined in 1828 by the German physician, Dr. Johann Schnlein and

his graduate student Friedrich Hopff, who described the condition in his dissertation

at the University of Zurich, Switzerland.

Hemophilia attracted greater public attention in the nineteenth century when

Queen Victoria’s son died of a brain hemorrhage at a young age. The death of a

young royal prince sparked an interest to develop and improve the quality of life and

treatment options for persons with hemophilia. Hemophilia spread in the European

royal families because of the tradition to marry within royalty. Within the royal

family, Queen Victoria was a carrier of hemophilia and passed it down to her two

daughters, three grandsons, and six great-grandsons [Ingram, 1976].

At the beginning of the twentieth century there were deeper studies of blood and

blood related proteins in order to fully understand the disease and its mechanisms.

In 1916, scientists investigated several blood and tissue factors, including fibrinogen,

thrombin, anti-thrombin, a potential clotting inhibitor, calcium, thrombokinase and


prothrombin in both healthy individuals and persons with hemophilia [Schramm,

2014]. Once scientists started to understand the characteristics of this disease, the

focus then began to start understanding the hematological processes by which the

body’s skin reaches hemostasis. In 1937, clinicians at Harvard explored a component

from the plasma in blood, antihemophilic globulin, which they thought could possi-

bly correct for the “clotting issue” in persons with hemophilia (details are provided

in later sections of this chapter). Further research in the 1950’s established two types

of hemophilia: A and B. Both types of hemophilia are characterized by a deficiency

of a specific blood protein; factor VIII (FVIII) for persons with hemophilia A and

factor IX (FIX) for persons with hemophilia B.

In the twenty-first century, scientists and the residents of England, were curious

to know if hemophilia was present in the current British royal family. Queen Victoria

was the last known descendant to carry the hemophilic gene in the royal family. Some

scientists have argued that the importance and acceleration of hemophilia research

expanded throughout Western Europe and United States due to its connection with

the royal family. To this date, clinicians and scientists continue to search for a cure

for hemophilia.


1.1.2 Blood Coagulation & Bleeding Disorders

As mentioned previously, hemophilia A and B are both characterized by the defi-

ciency of circulating coagulation factors, which lead to a disrupted clotting mech-

anism or coagulation cascade. The coagulation cascade refers to a chain of blood

proteins responsible for establishing homeostasis upon an individual’s injury. In-

terestingly, this bleeding or injury repair mechanism of the coagulation cascade in

mammals is highly conserved throughout evolutionary biology, and is thought to be

one of the most extensively researched and best understood processes by scientists

[Schmaier & Lazarus, 2011].

1.1.2.1 Coagulation Cascade

The coagulation pathway starts with an injury which causes damage to the inner

lining of blood vessel walls (i.e. endothelium). Immediately after the damage to

the endothelium, platelets are recruited to the injured site, forming a platelet plug.

One of the main goals of the coagulation cascade is to achieve a fibrin plug at the

site of bleeding through either the extrinsic or intrinsic pathway. Fibrin is a protein

that seals the platelets together. This entire process is known as the coagulation

cascade. In healthy individuals, both intrinsic and extrinsic pathways involve a total

of twenty-one proteins, including thirteen coagulation factors (i.e. FI to FXIII).

During the coagulation cascade, the extrinsic pathway is activated when tissue

factor becomes exposed to the surface of the injured endothelium. Tissue factor then

binds with inactive circulatory FVII, forming an activated complex, FVIIa. Tissue

factor combined with FVIIa which interacts with FX to form FXa, which then com-

bines with FVa to recruit prothrombin (FII) which is converted to thrombin (FIIa).

Finally, thrombin interacts with both FXIII producing FXIIIa and fibrinogen yield-

ing FIa (fibrin). Since FVIIIa is a cofactor, it binds with FIa to form a stable clot,

resulting in complete hemostasis.


1.1.2.2 Genetics

In 1984, the first detailed understanding of FVIII was published in Nature by Gitschier

and colleagues. Their publication came to the conclusion that the gene responsible

for recombinant FVIII is the F8 gene, which is located on the X chromosome at the

most distal band (Xq28) [Lenting et al., 1998; Simpson & Valentino, 2012]. Addi-

tionally, their work described the F8 gene in detail. The F8 gene spans 186 kilobases

divided into 26 exons and 25 introns. Each exon ranges from 0.069-3.106 kilobases,

and each intron is ∼32 kilobases in length [Gitschier et al., 1984]. FVIII is also

known as anti-hemophilic factor, making it a key component for the completion of

hemostasis. FVIII circulates in the plasma as a heterodimeric protein, consisting of

a light chain with a molecular weight of approximately 80 kDa and a heavy chain

with a molecular weight approximately in between 90-200 kDa [Bovenschen et al.,

2005]. In 1952 the discovery of the F9 gene was reported [Briggs et al., 1952]. The

F9 gene is located on the long arm of the X chromosome, closer to the centromere

at Xq27 [Bowen, 2002]. The F9 gene is 34 kilobases in length, divided into eight

exons and seven introns [Simpson & Valentino, 2012]. FVIII and FIX work together

forming an active complex, known as the tenase complex [Bowen et al., 2002].

Each blood coagulation factor and protein play an important part in the co-

agulation cascade. If an individual lacks, or has an insufficient functioning blood

coagulation factor, this deficiency can result in only partial completion of the coag-

ulation cascade. A deficiency of a coagulation factor can lead to a bleeding disorder.

For example, a deficiency in FV results in parahemophilia, because FV is the plasma

cofactor that activates prothrombin to thrombin [Huang & Koerper, 2008]. An in-

sufficient or decreased activity in FVIII results in hemophilia A (the most common

type of hemophilia), and a deficiency of FIX results in hemophilia B. Both FVIII

and FIX are synthesized in the liver by hepatocytes and are processed during their

secretion into the bloodstream [Simpson & Valentino, 2012; Franchini et al., 2013].

The fundamental biochemical process underlying both hemophilia A and B is an in-

sufficiency of the activity of the tenase complex. Hence, it is not surprising that both

hemophilia A and B are clinically similar, because they both arise from perturbation

of the same essential step in the process of fibrin, needed to complete hemostasis


[Bowen et al., 2002]. In essence, hemophilia is classified as an X-linked recessive dis-

ease, whereby males are genetically more likely to acquire this disease than females.

One of the clinical manifestations of patients with hemophilia is their experience of

spontaneous bleeding events and recurrent episodes of hemorrhage and hemarthrosis,

primarily affecting the ankles and knees [Gringeri et al., 2014].


1.1.3 Management and Evaluation of Hemophilia

The diagnosis of hemophilia is based on factor assays in the blood. Measurements

through factor assays identify the concentration of recombinant factors present in

the individual, expressed as international units (IU), where 1 IU is defined as the

concentration of recombinant factor in 1 milliliter (mL) of normal pooled plasma

[Fijnvandraat et al., 2012]. In healthy individuals, plasma concentrations of FVIII

or FIX are found to be in the range of 0.50-1.50 IU/mL [Fijnvandraat et al., 2012]. If

the level of either factor in plasma is less than 0.50 IU/mL, hemophilia is diagnosed,

which can be further classified into three groups: severe, moderate, and mild.

1.1.3.1 Severity Groups

Persons with mild hemophilia have a plasma concentration of FVIII or FIX in the

range of 0.06-0.49 IU/mL (or 6-49%) [Franchini et al., 2010; Fijnvandraat et al.,

2012]. Research has shown that 6-49% of plasma concentration of FVIII or FIX

is generally sufficient for normal hemostasis [Plug et al., 2006]. Persons with mild

hemophilia have a relatively less frequent chance of spontaneous bleeding events. Per-

sons with a plasma concentration of FVIII or FIX in the range of 0.02-0.05 IU/mL

(or 2-5%) are known to have moderate hemophilia [Fijnvandraat et al., 2012]. These

individuals do not develop spontaneous bleeds, unless faced with a trauma or a sur-

gical procedure [Carcao, 2012]. Lastly, persons with severe hemophilia are classified

as having FVIII or FIX plasma concentration of <0.01 IU/mL (or <1%), and these

individuals experience frequent spontaneous bleeding episodes [Carcao, 2012].

Globally, the majority of persons with hemophilia A are known to have severe

type of hemophilia, whereas the majority of persons with hemophilia B are known to

have mild type of hemophilia [Schmaier & Lazarus, 2011]. The number of bleeding

episodes without any treatment varies depending on the category of blood coagu-

lation factor deficiency, the type of hemophilia, and the patient’s age [Schmaier &

Lazarus, 2011]. For example, on average, patients with severe hemophilia typically

experience 20-30 bleeding events annually, while patients with moderate hemophilia

typically experience 4-6 bleeding events annually [Schmaier & Lazarus, 2011].


1.1.3.2 Treatment and Prophylactic Regimens

The mid- to late twentieth century brought improved treatment for persons with

hemophilia. Prior to the 1940’s, there existed no treatment options for persons with

hemophilia. With the lack of treatment options, the expected median survival age

for a person with severe hemophilia was approximately 30 years [Berntorp, 2013].

During World War II fresh frozen plasma became a necessity for treating injured sol-

diers. Fresh frozen plasma is obtained from human blood through centrifuge, which

separates the components of the blood, leaving the plasma as one component. This

plasma is kept frozen below -18◦C, and can be stored for a year. It was not until

the 1960’s and 1970’s that Swedish scientists pioneered early treatment regimens for

persons with hemophilia through factor concentrations derived from human donated

blood plasma. During this time, one of the issues that sparked a global epidemic was

the challenge of hygienically freezing blood plasma, eventually triggering a shortage

of blood plasma donations. Persons with hemophilia relied on blood transfusions

from donated human blood. However due to the lack of safety measures, blood do-

nations were mixed together, which increased the chances of hepatitis C and human

immunodeficiency virus (HIV).

By the late 1980’s and early 1990’s, European and North American governments

introduced safety measures of obtaining blood plasma through blood screening pro-

grams. This reduced the chances of acquiring Hepatitis C and HIV in persons with

hemophilia. The limitations of blood transfusions will be discussed in Section 1.1.4.

In 1992, approval of the first recombinant FVIII molecule for replacement ther-

apy in the United States allowed for safe prophylaxis in persons with hemophilia

[Manco-Johnson et al., 2007]. The World Federation of Hemophilia (WFH) defines

prophylaxis as the regular infusion of clotting factor concentrations in order to pre-

vent spontaneous bleeding. For this reason the World Health Organization (WHO)

and the WFH recommended that governments of developing and developed coun-

tries provide national prophylaxis to persons with hemophilia, especially to children.

This allowed persons with hemophilia to self-administer safe-independent prophy-


laxis [Bolton-Maggs & Pasi, 2003; Coppola & Franchini, 2013; Bhatnagar & Hall,

2018].

In the past few decades, treatment options for persons with hemophilia and its

therapeutic safety have greatly improved [Berntorp & Shapiro, 2012]. The diagnosis

of severe hemophilia can be made immediately after birth by measuring the FVIII or

FIX coagulation activity in the blood [Bhatnagar & Hall, 2018]. Although worldwide

there is considerable variability in the age at which children with severe hemophilia

will experience their first joint bleed, the median age of severe hemophilia diagno-

sis is around 1.8 years [Carcao, 2012; Coppola & Franchini, 2013]. Some clinicians

recommend prophylaxis to be initiated around the age of 4 years, because by this

age most affected children will have experienced their first joint bleed [Bolton-Maggs

& Pasi, 2003]. Some have argued that an early commencement of prophylaxis, as

early as two years of age, improved patients’ overall quality of life [Bolton-Maggs

& Pasi, 2003; Coppola & Franchini, 2013]. However, many factors influence the

first initiation of prophylaxis such as the child’s and families tolerance, healthcare

resources, and perhaps most importantly their socioeconomic status. Depending on

the healthcare system of the nation, the cost of prophylaxis can be a burden on those

families financially less fortunate [Bolton-Maggs & Pasi, 2003; Berntorp & Shapiro,

2012].

Clinical practice regarding most hemophilia prophylactic regimens are tailored to

the patients’ overall needs. A review in The Lancet by Berntorp & Shapiro [2012],

highlights a few standard prophylaxis regimens as well as their advantages and dis-

advantages for persons with hemophilia. A traditional Swedish prophylactic regimen

consists of administering 25-40 IU/kg dose of recombinant FVIII/FIX three times

weekly or 30-40 IU/kg dose of recombinant FVIII/FIX twice weekly. This dose of

recombinant FVIII/FIX is given intravenously in persons with hemophilia usually

within the first year of their birth [Berntorp & Shapiro, 2012; Coppola & Franchini,

2013]. Another prophylactic regimen has been adopted in the Netherlands, where

an intermediate dose (15-25 IU/kg) of recombinant FVIII/FIX is administered three

times a week, upon the occurrence of an initial joint bleed [Berntorp & Shapiro,

2012; Coppola & Franchini, 2013]. In addition, there exists a Canadian prophy-


lactic regimen, which depends on the type of hemophilia (i.e. mild, moderate, or

severe) an individual has and their bleeding frequency [Berntorp & Shapiro, 2012].

Increasing the use of prophylaxis includes benefits for children with hemophilia by

reducing events of spontaneous joint bleeding, emergency hospitalization rates, im-

proving school performance, and overall quality of life [Manco-Johnson et al., 2007].

1.1.3.3 Cost and Financial Burden

Based on the nation’s healthcare system, the benefits of replacement therapy and

prophylaxis for children’s family are usually offset by the substantial financial bur-

den. The annual mean global cost of replacement therapy involving FVIII or FIX

has accelerated in the past two decades, exceeding USD$50,000 per child with either

hemophilia A or B [Blankenship, 2008]. At the turn of the twenty-first century, an-

nual replacement FVIII costs without prophylaxis in Toronto, Canada mounted to

CAD$62,292 per patient [Heemstra et al., 2005]. In the United States and parts of

Europe, the cost of factor replacement is higher on average than Canada, exceeding

USD$200,000 per year per patient, which is not affordable for majority of persons

with hemophilia [Nathwani et al., 2014].

A study in 2014, found that the cost of replacement therapy for persons with

hemophilia in the United States steadily increased over the past three decades, with

the peak annual cost at age 36 years for those with hemophilia A (USD$363,948) and

at the age of 29 years for those with hemophilia B (USD$453,179) [Eldar-Lissai et

al., 2014]. Another recent study assessed the annual cost of replacement therapy for

1,285 severe hemophilia patients residing in the five largest European economic na-

tions (France, Germany, Italy, Spain and the United Kingdom) [O’Hara et al., 2017].

Their findings suggest that the total cost of replacement therapy was estimated to

be e1.4 billion, equating to an average of e199,541 per hemophilic patient per year

[O’Hara et al., 2017]. Approximately 90% of the total annual costs are due to the

consumption of clotting factor replacement therapy [Rocha et al., 2015; O’Hara et

al., 2017; Feldman et al., 2018].

Persons with hemophilia are hindered by the economic burden of costs associated


with factor replacement therapy. An economic burden is well known to be associ-

ated with the individual and their family’s socioeconomic status. The simple fact

is that the average annual family income for those living with severe hemophilia in

any part of the world is far less than that of the costs for clotting factor replace-

ment therapy [Blankenship, 2008]. To increase the quality of life for persons with

hemophilia, experts have recommended an increased accessibility worldwide to cost

effective hemophilic care, especially in the developing nations [Berntorp & Shapiro,

2012]. While the overall quality of life in persons with hemophilia is improving,

about 70% of these individuals are not receiving adequate treatment, particularly

those residing in developing nations [Fijnvandraat et al., 2012].


1.1.4 Transfusion-Transmitted Diseases

From 1840, when the first successful transfusion of human blood was performed, to

the early 1990’s, when the first recombinant FVIII product was registered in Canada,

United States, and Europe, the availability of blood transfusion resulted in a dramatic

improvement in quality of life for persons with hemophilia [Lee, 2009]. Although

blood transfusion therapy improved the quality of life for persons with hemophilia,

for some individuals it resulted in other illnesses due to the lack of safety and in-

appropriate sanitation methods to screen for infections and vector-borne viruses in

donated pools of blood, which primary had hepatitis C and the human immunod-

eficiency virus (HIV) [Bolton-Maggs & Pasi, 2003; Lee, 2009; Berntorp & Shapiro,

2012; Coppola & Franchini, 2013; Bhatnagar & Hall, 2018]. Previously in 1943 a

paper in the Journal of the American Medical Association reported seven cases of

jaundice which had occurred one to four months after transfusion of blood plasma,

later identified as hepatitis C [Beeson, 1943].

Hepatitis C is a chronic medical condition primarily affecting the liver. Despite

the existence in the development for testing hepatitis C in 1991, there are an esti-

mated 184 million individuals worldwide affected by this condition [Hofstraat et al.,

2017]. Prior to 1991 when hepatitis C testing was not available, it was difficult to

characterize the hepatitis C virus in large samples of blood plasma [Lee, 2009]. Once

testing had become available it was possible to characterize hepatitis C in persons

with hemophilia [Lee, 2009]. Approximately 95% of individuals with hepatitis C

can be cleared of the hepatitis C virus by treatment with antiviral drugs. In the

case of untreated chronic hepatitis C, the chances of end-stage liver failure become

prominent [Lee, 2009]. Advanced treatment for chronic hepatitis C includes a liver

transplant [Rosen, 2011]. In the past, a small number of successful liver transplants

have been performed in persons with hemophilia.

Since the late 1970’s over 20,000 donations of human blood were collected globally

from which plasma-derived concentrates were extracted and stored. But due to the

lack of screening in blood products, there was a high probability of acquiring HIV

[Bolton-Maggs & Pasi, 2003]. One-third of persons with hemophilia who had HIV


were also affected by hepatitis C [Lee, 2009]. HIV is a retrovirus, which leads to pro-

gressive failure of the human immune system, and increases the individual’s chances

of life-threatening infections and cancers over time. On average untreated individ-

uals with HIV survive nine to eleven years after being infected with the retrovirus

[Maartens et al., 2014]. In the 1970’s and 1980’s, ∼70-80% of persons with severe

hemophilia in developed nations became infected with HIV [Simpson & Valentino,

2012]. Today, a majority of persons with hemophilia worldwide are free of hepatitis

C and HIV, due to improved blood screening programs [Lee, 2009]. Also, today’s

recombinant factors have prolonged the life expectancy of persons with hemophilia

closer to that of an average healthy adult’s, at the same time decreasing mortality

rates due to hemophilia A and B [Blankenship, 2008].


1.1.5 Global Epidemiology of the Disease

Since hemophilia is a rare disease, and affects predominantly males, the global preva-

lence of hemophilia is small. The prevalence of males with hemophilia A is 1:5,000,

whereas 1:30,000 have hemophilia B [Bhatnagar & Hall, 2018]. Approximately 70%

of hemophilic cases are inherited, whereas the other 30% of cases arise from new and

spontaneous genetic mutations [Bhatnagar & Hall, 2018].

The WHO and WFH have been monitoring the epidemiology of persons with

hemophilia since 1998. Epidemiological data is important to understand the annual

global population statistics of persons with hemophilia for developed and developing

nations. Each year questionnaires are sent to national hematology centers that are

linked with the WFH. The WFH requests that clinicians and healthcare providers in

these centers complete the survey about their patients [WFH, 2017]. Figure 1 reflects

an estimated total number of persons living with hemophilia A and B worldwide over

the past seventeen years. The data demonstrate an annual rise of hemophilic cases

worldwide at 6094 cases/year (P < 0.001). This rise has been primarily attributed

to two reasons. First, the improvement and expansion of hemophilia surveillance

programs worldwide [Stonebraker et al., 2010]. Secondly, the rise in population on a

global scale has increased the number of hemophilic cases reported worldwide [WFH,

2017].

Other global studies have documented the prevalence of hemophilia, from which

they note that this disease varies considerably between nations [Stonebraker et al.,

2010; Stonebraker et al., 2011]. In the past three decades, the average prevalence of

hemophilia A (per 100,000 males) in high-income nations was 12.8, in comparison to

the average global prevalence of 6.6 [Stonebraker et al., 2010]. This suggests that on

average the prevalence of hemophilia A (per 100,000 males) is larger for high-income

nations in comparison to the global average.

At the same time, the average prevalence (per 100,000 males) for hemophilia

B in high-income nations was 2.69 in comparison to the global prevalence of 1.20

[Stonebraker et al., 2011]. For Canada the average prevalence (per 100,000 males)


Figure 1 Annual number of persons with hemophilia A and B worldwide from1999-2016. Data obtained from WFH 2017 global survey.

of hemophilia A ranged from 10.2 in 1989 to 14.2 in 2008 [Stonebraker et al., 2010].

In the past few decades, an increasing prevalence of males with hemophilia A and B

has been documented in high-income nations in comparison to the global prevalence.

The life expectancy of persons with hemophilia is now approaching the national av-

erage life expectancy. This has led to a smaller proportion of hemophilic patients in

the children and adolescent (i.e. <18 years of age) age groups, adding an increasing

burden to global prevalence rates [Stonebraker et al., 2010]. In addition, there is an

effect of migration of persons with hemophilia from nations of poorer healthcare to

nations with better healthcare [Stonebraker et al., 2010].

Healthcare systems of high-income nations allow for accurate reporting, monitor-

ing, and treatment of persons with hemophilia. As for low-income and developing

nations, the majority of persons with hemophilia are under diagnosed owing to the

ineffective management of healthcare systems [Stonebraker et al., 2010]. This further

results in the lack of full treatment options available to persons with hemophilia in

low-income and developing nations [De Kleijn et al., 2012]. Also, a majority of low-

income and developing nations have tropical climates throughout the year, giving

children and adolescents suitable weather to participate in outdoor activities, in-

creasing their chances for injuries. Yet the healthcare systems of developing nations


are less likely able to offer treatment and prophylaxis to avoid regular joint bleeds.

Historically, in the early 1970’s, amongst all high-income nations, the United

Kingdom was known to have the highest prevalence (per 100,000 males) for per-

sons with hemophilia A, approximately 20, versus for example 10 in the United

States [Aledort et al., 1976]. Interestingly, the opposite is true in the past decade,

where the male prevalence of hemophilia A was twice in the United States than

in the United Kingdom [Stonebraker et al., 2010]. According to the most recent

WFH global report incorporating data from 113 nations (i.e. ∼90% of all countries

worldwide), 295,866 individuals were identified with bleeding disorders, out of which

184,723 had hemophilia, which represents more than 62% of all bleeding disorders

worldwide [WFH, 2017]. In developed nations such as Canada and United States,

a total of 3,893 and 16,949, respectively, were reported with hemophilia [WFH, 2017].

The three developing nations with the largest population size of persons with

hemophilia are Brazil, China, and India. Data from the WFH shows that in 2016,

Brazil, China, and India have more persons with severe hemophilia than mild (Fig-

ure 2). The majority of developing nations are known to have inaccurate monitoring

and management in their healthcare system, leading to lower than expected cases

recorded not just for hemophilia, but as well other bleeding disorders [De Kleijn et

al., 2012].

One of the advantages of using large epidemiological data is the ability to conduct

ecological base studies, incorporating a high degree of generalizability. Epidemiolog-

ical studies often rely on International Classification of Diseases (ICD) codes. The

ICD codes were initially created in 1893 and were then adapted by the WHO in

1948. ICD codes are used by clinicians and other healthcare professionals to classify

and record illnesses in individuals receiving hospital or health care through a unique

set of codes [Majeed & Moore, 2017]. The ICD-9 (i.e. years 1979-1998) codes for

hemophilia A (congenital factor VIII disorder) and B (Christmas disease) are 286.0

and 286.1, respectively. The ICD-10 (i.e. years 1999-2018) code for hemophilia A

(congenital factor VIII disorder) and B (Christmas disease) is D66 and D67, respec-

tively.


Figure 2 Number of persons with hemophilia A and B by severity in the year 2016for developed nations. Data obtained from WFH 2017 global survey.


Figure 3 Number of persons with hemophilia A and B by severity in the year 2016for developing nations. Data obtained from WFH 2017 global survey.

These ICD codes for specific health conditions, can be used by scientists to un-

derstand disease epidemics. For example, Figure 4 shows a time series of United

States annual age-standardized mortality rates for hemophilia A, including all age

groups and ethnicities, from 1979-2016 using ICD-9 and ICD-10. A breakpoint is

seen in the figure after a rise in hemophilia A mortality, followed by a decline, and

was determined to be 1992 (± 1 year). Table 1 provides details of the population

cohort included in Figure 4, such as age groups, sexes, and race/ethnicities, along

with the statistical interaction between each characteristic for year 1979 and 1992 as

well as 1992 and 2016. Using a joinpoint [Goel et al., 2018] and root mean square

analysis based on the temporal auto-correlation [Majeed & Moore, 2017]. The de-


cline of age-standardized mortality rates for hemophilia A is seen after 1992, which

is believed to be attributed to the approval of the first recombinant FVIII blood

coagulation products by the Food and Drug Administration (FDA) [Berntorp, 2013;

Schramm, 2014].

Children and adolescents with severe hemophilia may experience bleeding trauma

from vigorous physical activity and involvement in sports, increasing the probability

of hospitalization due to trauma [Broderick et al., 2012]. In Canada, the increase of

factor prophylaxis as a therapeutic regimen has been proven effective, especially for

children and adolescents with hemophilia [Matino et al., 2014; Feldman et al., 2018].

Figures 5 and 6 show the hospitalization of children and adolescents (<18 years) with

hemophilia A and B in Toronto, Canada from 2002-2006. Throughout this period,

the average hospitalization visit and emergency department visit incidence rates (per

100,000) was 1.85 and 11.24, respectively.


Figure 4 This time series in black shows the age-adjusted mortality rates (permillion individuals) due to hemophilia A for the United States, along with the yellowshading to represent the 95% confidence interval (1979-2016). The red and bluetrendlines shows the increase and decrease, respectively in these rates, determinedupon the inflection point found in the year 1992.

Table 1 United States age standardized mortality trends for hemophilia A

Sample Size Noa Mortality Ratesb P for InteractionCharacteristics 1979 1992 2016 1979 1992 2016 1979 to 1992 1992 to 2016

SexMales 35 86 37 0.37 0.75 0.23

<0.001 <0.001Females 4 11 15 0.035 0.074 0.066

Age<19 5 9 1 0.066 0.19 0.009

<0.001 <0.00119-44 11 37 5 0.13 0.36 0.03945-64 10 20 9 0.21 0.42 0.095≥65 13 31 37 0.55 1.01 0.78

RaceWhite 33 79 41 0.18 0.37 0.13

<0.001 <0.001African American 5 15 8 0.19 0.56 0.21Other 1 3 3 0.18 0.30 0.16

a Overall sample size was 39 for 1979, 97 for 1992, and 52 for 2016. b Age-adjusted mortality rates per one million individuals.


Figure 5 Annual hospitalization incidence rates for children and adolescents withhemophilia A and B in Toronto, Canada, declining trend of -0.02/100,000 (P =0.53) from 2002-2016. Data obtained from Public Health Ontario in 2017, based onICD-10.

Figure 6 Annual emergency incidence rates for children and adolescents withhemophilia A and B in Toronto, Canada, declining trend of -0.41/100,000 (P =0.02) from 2002-2016. Data obtained from Public Health Ontario in 2017, based onICD-10.


1.1.6 Arthropathy & Arthritis

Arthropathy refers to any disease that affects the joints. Arthritis is one of the most

common illnesses managed in internal medicine and primary care [Ross, 1997]. Nu-

merous factors can result in different types of arthropathy. Regardless of the type

of arthropathy, the ultimate stage usually results in damage to the cartilage [Prads-

gaard et al., 2013]. While overall arthropathy has a high prevalence in older age

groups, children and adolescents also have arthropathy. A study in Denmark evalu-

ated 67 children with arthritis, and found decreased thickness in cartilage in 27% of

the joints examined [Twilt et al., 2017].

1.1.6.1 Articular Cartilage

Human cartilage is an intricate tissue that withstands numerous dynamic loads and

injuries, helps reduce localized stress concentrations in the underlying bone, and may

reduce the possibility of work load trauma [Ronken et al., 2012]. Human articular

cartilage is a smooth, glossy, and highly specialized avascular connective tissue. The

articular cartilage is composed of a dense extracellular matrix [Fox et al., 2009].

This extracellular matrix is composed of water, collagen, and proteoglycans, as well

as other non-collagenous proteins, and glycoproteins present in miniscule quantities

[Fox et al., 2009]. Glycoproteins are large carbohydrate compounds that are linked

to proteins at the surface of cells, whereas proteoglycans are classified within glyco-

proteins containing chains of amino acids [Fox et al., 2009].

There are mainly three types of articular cartilage throughout the human body:

elastic, fibrous, and hyaline. Each type of cartilage is characterized by their disper-

sion of chondrocytes, embedded in an extracellular matrix, which is formed mainly

of collagen fibers (15-20% by weight), proteoglycan (3-10% by weight), and water

content (65-80% by weight) [Xia, 2000; Matzat et al., 2013]. Elastic cartilage is

comprised of elastic fibers allowing repeated bending and flexibility (i.e. located

throughout the outer ear). Fibrous cartilage is a rigid and strong tissue found pre-

dominantly in intervertebral disks. The main focus of this thesis is based on hyaline

cartilage due to its abundance in joints. The average thickness of hyaline cartilage


varies between ∼2-4 mm throughout the body [Shepherd & Seedhom, 1999; Fox et

al., 2009]. The thickness is also known to decrease over an individual’s life time due

to the breakdown of proteoglycan content [Roughley & White, 1980]. It is widely

accepted that in healthy individuals a larger amount of load is exerted on the an-

kle, specifically on the tibia-talus joint, making this a vulnerable joint to injury and

trauma [Cher et al., 2016].

On a molecular level, chondrocytes help maintain the structure of cartilage,

mainly consisting of collagen and proteoglycans. Proteoglycans have a structure

that contain long chains of covalent polysaccharides, which have a negative charge

due to the abundance of carboxyl and sulfate groups. This negative charge results

in an accumulation of cations, such as sodium, which then draw water into the tis-

sue, generating a swelling pressure on the cartilage [Xia, 2000]. On the other hand,

collagen is a protein in the extracellular matrix [Nassa et al., 2012]. Approximately

90% of the collagen in the human body is type I, which is located in the skin, or-

gans, bones, and teeth [Nassa et al., 2012], whereas cartilage is composed of type II

collagen providing tensile strength to the fibers and the structure [Xia, 2000].

Articular cartilage is highly structured and organized in regards to collagen fibers,

and is subdivided into three meridional layers. The surface of the cartilage or the

superficial zone, contains collagen fibers which are orientated parallel to one another.

The middle layer or transitional zone, has random alignment of collagen fibers. The

deepest layer is the radial zone where the collagen fibers are oriented vertically. There

is little to no proteoglycan present in the superficial layer of the cartilage; primarily it

is present in the transitional and radial zones [Xia, 2000]. Principally, chondrocytes

become bigger and spherical in size towards the deeper layer of cartilage; the surface

of the cartilage only consists of several microns in thickness of collagen fibers, and

as a result the majority of water content is present at the surface of the cartilage in

comparison to the other layers [Xia, 2000]. Approximately 30% of water is associated

with the intrafibrillar space within the collagen, which helps protect against mechan-

ical load and may contribute to the resiliency of the articular cartilage structure [Fox

et al., 2009].


Some experts have mentioned that shear strength of collagen fibers is the greatest

when the fiber is directed parallel to the axis of the tensile stress being applied, as

such the orientations of collagen fibers in the different zones are associated with the

different biomechanical composition of the tissue [Xia, 2000]. Moreover, the articular

cartilage is a sensitive tissue, and damage either through vigorous physical activity,

trauma, or arthropathy over a period of time results in pain and eventually loss of

joint function [Franz et al., 2001].

1.1.6.2 Hemophilic Arthropathy

Persons with hemophilia experience approximately 90% of all spontaneous bleeding

episodes in the joints (i.e. hemarthrosis), out of which nearly 80% occur in the

ankles and knees [Simpson & Valentino, 2012]. The term hemophilic arthropathy

can be defined as a condition that is characterized by repetitive long-term bleeding

episodes, which over time can result in joint damage [Carcao, 2012]. The initial

phase of hemophilic arthropathy is characterized as inflammation to the synovial

tissue (i.e. synovitis) [Bolton-Maggs & Pasi, 2003; Carcao, 2012; Lobet et al., 2014].

It is known that persons with hemophilic arthropathy experience damage to their

cartilage, but the exact molecular process has not been understood [Valentino, 2012].

Researchers believe that repetitive hemarthrosis leads to iron release from hemoglobin,

which induces a chronic inflammatory process mediated by cytokines, leading to pro-

gressive synovial pannus growth and cartilage damage [Nieuwenhuizen et al., 2014;

Melchiorre et al., 2017; Feldman et al., 2018]. Over time inadequately treated persons

with severe hemophilia can become incapacitated by progressive severe arthropa-

thy with fixed flexion deformities, and symptoms mimicking that of osteoarthritis

[Bolton-Maggs & Pasi, 2003; Lobet et al., 2014].

Depending on the nation’s healthcare system, the recommended treatment for

persons with hemophilic arthropathy is the use of prophylaxis through replacement

therapy. In Canada, nearly all persons with severe hemophilia are being treated with

prophylaxis. Persons with severe hemophilic arthropathy require a high dose (>40


IU/kg at least once per week) of recombinant FVIII/FIX which is injected into a vein

[Manco-Johnson et al., 2007]. The initiation of prophylaxis at an early age can delay

the time which cartilage degeneration becomes severe for persons with hemophilic

arthropathy [Carcao, 2012]. A recent study involving hemophilic mice demonstrated

that an oral iron chelator therapy (dose of 30 mg/kg) can be used to reduce excess

iron surrounding the joint from the presence of blood, potentially limiting damage to

the cartilage [Nieuwenhuizen et al., 2014]. From this study, the authors determined

that deferoxamine is a safe drug to treat hemophilic mice [Nieuwenhuizen et al.,

2014]. Deferoxamine has not been studied in humans with hemophilia. In the future

longitudinal clinical trials are needed to verify this association between deferoxamine

and improvement of arthropathy.


1.2 Evolution of Diagnostic Imaging for Hemophilic

Arthropathy

Aside from treatment options, advances in technology have allowed clinicians to

monitor hemophilic arthropathy using non-invasive imaging techniques.

1.2.1 Radiograph

In 1895, Wilhelm Rontgen, a German physicist discovered X-rays, which revolu-

tionized disease diagnosis. X-rays possess short wavelength electromagnetic energy,

ranging from 0.01-10 nanometers. Shorter electromagnetic wavelengths have higher

frequencies. High-energy electromagnetic waves produce ionizing radiation, which

upon long-term exposure can harm the human body. As a result, frequent usage

of X-rays should be avoided, especially in children, which can damage their de-

oxyribonucleic acids (DNA). When X-rays pass through the body, heavier or denser

aspects of the body, such as bones absorb the X-rays. These produced images are

called radiographs [Gunderman, 2006]. Radiography is a non-invasive imaging tech-

nique that uses X-rays for diagnosing anatomical abnormalities.

Studies incorporating radiography have been conducted in the past century to

characterize various diseases. The major advantages of using radiography is its quick

scan time and easy accessibility, primarily due to its low cost [Bansal, 2006]. While

radiography remained a gold standard for diagnosing hemophilic arthropathy in the

twentieth century, it is only able to characterize late arthropathic changes, when joint

damage has most likely become irreversible [Doria, 2010]. One disadvantage of using

radiography in diagnosing hemophilic arthropathy is depicting changes in articular

cartilage. Radiography can only infer cartilage degeneration indirectly through eval-

uation of narrowing joint spaces [Doria, 2010]. As a result, radiography is primarily

used for the purposes of therapeutic planning and follow-up of disease progression

for clinical therapy in the need for joint replacement [Doria, 2010].

Several scoring systems have been developed based on radiography to monitor

the degree of hemophilic arthropathy. The two most widely used radiography based


scoring systems are the Pettersson and Arnold-Hilgartner scales [Leslie & Catherine,

2007]. The Pettersson score was developed by Holger Pettersson and colleagues in

1980 to assess osteochondral changes in the ankles, knees, and elbows of persons

with hemophilic arthropathy [Pettersson et al., 1980]. This is an additive scoring

system consisting of eight items, with a maximum joint score of thirteen [Pettersson

et al., 1980; Foppen et al., 2016]. The Arnold-Hilgartner scale describes five stages

of joint damage to persons with hemophilic arthropathy [Arnold & Hilgartner, 1977].

Stage one is defined by only the presence of swelling in soft tissues. The progression

from the initial stage to the final stage is primarily noted by osteochondral changes

and narrowing of joint spaces [Arnold & Hilgartner, 1977; Leslie & Catherine, 2007].

Stage five or the final stage is characterized by extensive loss in joint cartilage space

and enlargement of the epiphyses [Arnold & Hilgartner, 1977].

The Pettersson and Arnold-Hilgartner scales have been used to evaluate osteo-

chondral changes in adults with hemophilic arthropathy [Ng et al., 2005], how-

ever radiography based scoring systems are inadequate to evaluate early hemophilic

arthropathy [Doria, 2010]. For this reason, clinicians have now been relying on

magnetic resonance imaging (MRI) over radiography for the assessment of early os-

teochondral changes linked to hemophilic arthropathy [Doria, 2010].

1.2.2 Magnetic Resonance Imaging

MRI is preferred over radiography to diagnose early hemophilic arthropathy due

to a few reasons. Firstly, MRI is able to differentiate soft tissue contrast over a

three-dimensional volume [Kotecha et al., 2013]. Secondly, MRI involves the use

of radiofrequency waves, rather than electromagnetic waves employed by radiogra-

phy, whereby the latter technique can act as an exogenous agent that may induce

irreparable DNA damage [Panych & Madore, 2018]. A few disadvantages of using

MRI over radiography are related to its high cost, lack of accessibility, increased scan

time, and in some cases requires the need for sedation in children [Doria, 2010].


1.2.2.1 MRI Basics and Classical Mechanics

MRI relies on hydrogen atoms, which is helpful because the human body as a whole

by chemical composition is mostly comprised of water (∼70%), and utilizes nuclear

magnetic resonance properties to produce images [Berger, 2002]. The MRI technique

is based on the magnetic polarization of the hydrogen atom when placed in a strong

magnetic field [Berger, 2002]. In various hospitals, the MRI system is comprised of

a powerful magnet that is 30,000 to 60,000 times stronger than the surface of the

Earth’s magnetic field [Panych & Madore, 2018].

Prior to the individual entering the magnet, hydrogen nuclei in the body are

randomly oriented, producing a zero net dipole moment. As the individual enters

the magnet, the magnetic field starts to polarize. An external magnetic field is then

applied, and the magnetic moment of each hydrogen proton tends to align with the

external magnetic field. Hydrogen protons aligned in parallel possess a lower energy

state than those in anti-parallel. A net magnetization vector is produced by the

differences in both parallel to anti-parallel magnetic moments. At the same time,

the hydrogen protons are spinning or wobbling about the main magnetic field of the

MRI scanner, a concept recognized as precession. The rate of precession, also known

as the Larmor frequency (ω), which is proportional to the strength of the external

magnetic field (B0) and a constant, gyromagnetic ratio (γ). This relationship is given

below in equation (1).

ω = γB0 (1)

Each dipolar atomic nuclei have different gyromagnetic ratios; for hydrogen it

is 42.58 MHz/T. When an external magnetic field strength of 1 T is applied, the

Larmor frequency for hydrogen will be 42.58 MHz. At a magnetic field strength of 3

T, the Larmor frequency will be 128 MHz, as increasing the external magnetic field

increases the Larmor frequency. Once an external magnetic field has been applied to

orientate the protons, a radiofrequency wave is released towards the individual, which

has a similar frequency to the Larmor frequency. The protons inside the individual

absorb this energy and rotate away from the direction induced by the magnet. Once


the radiofrequency wave is turned off, this causes the hydrogen protons to precess.

In essence, if the radiofrequency wave is applied for longer period of time, the system

will not only produce more energy in the form of heat, but also increase the rotation

of net magnetization away from the main magnetic field, producing a larger flip angle.

Upon the completion of the radiofrequency source, hydrogen protons establish

equilibrium and return to their original state. The protons return to thermal equi-

librium by a process known as relaxation. T2 relaxation leads to a loss of MRI signal

but it is the precession of the magnetization that induces signal in the receiver coils

[Berger, 2002]. The protons of each tissue and chemical composition relax at their

own rates when the radiofrequency is switched off, measured by two sequences, T1

and T2 relaxation.

Recall that the radiofrequency wave adds energy to the MRI system. At this point

upon applying a 90◦ radiofrequency pulse, the net magnetization vector is aligned in

a horizontal plane. When the radiofrequency wave is turned off, the protons loose

energy and slowly return to their initial state, aligned in a vertical plane. The time

duration that the net magnetization vector returns from the horizontal to the vertical

plane is known as T1 relaxation. Whereas, T2 relaxation is the time duration that

describes the loss of spin phase coherence along the horizontal plane.

The two other parameters that are also important to help alter the MRI signal

are the echo time (TE) and repetition time (TR). TE is the duration of time from

the center of the 90◦ radiofrequency pulse to the center of the maximum echo (MR

signal sampling) [Berger, 2002]. To obtain an MR image, multiple radiofrequency

waves are needed over time to create an image. Hence this creates a pulse sequence

which is defined by multiple echoes between each radiofrequency pulse. As such TR

is the duration between the onsets of the first radiofrequency excitation to the onset

of the second radiofrequency excitation.

Tissues with a short T1 relaxation time appear as bright white (i.e. produce a

high MRI signal), such as fat tissues. Tissues with long T1 relaxation times appear

dark, such as water. T1 mapping is often used to depict anatomical changes, since


bones of adolescents and adults contain bone marrow which is comprised of fat [Katti

et al., 2011].

On the contrary, T2 mapping is primarily used to show changes water and soft

tissue contrast. Water has the longest T2 relaxation time and thus appears bright

using T2 mapping [Katti et al., 2011]. Due to our interest in documenting early

cartilage changes in children and adolescents with hemophilic arthropathy, the sole

purpose of this thesis only focuses on T2 mapping.


1.2.2.2 T2 Mapping

To compute T2 relaxation times for particular groups of tissues, one fundamental

and standard method often used in MRI based clinical studies is the spin echo pulse

sequence [Jung & Weigel, 2013]. This consists of a 90◦ excitation pulse followed by a

180◦, to allow refocusing of the signal. The 90◦ excitation pulse completely tilts the

net magnetization vector from the vertical plane (i.e. longitudinal magnetization,

Mz) into the horizontal plane (i.e. transverse magnetization Mxy). The 180◦ excita-

tion pulse causes the spin of the net magnetization vector to rephrase. The reason

for rephasing is primarily required to generate and echo for measurement of rate of

decay of transverse magnetization.

Each tissue precesses (i.e. spinning) at a different rate, governed by the Larmor

frequency. The Larmor frequency dictates how fast or slow the transverse magneti-

zation signal will decay down to zero. At the TE, the spins are completely rephased.

The decay of the MRI signal, S, is exponential, described by equation (2). The

natural logarithm of the MRI signal is taken to perform a linear fit.

S = Ce−TE/T2 (2)

lnS = lnC − TE

T2

The equations above summarize the computation of T2 relaxation time using a

standard spin echo pulse sequence. Where C is an arbitrary constant, followed by

TE and T2 being the echo time and T2 time constant for the tissue, respectively.

The linear fit uses a slope of 1/T2.

In a course of a practical experiment, several images are acquired at different TEs

to monitor the MRI signal decay. The greater the number of TEs results in a more

precise T2 relaxation time for any group of tissues [Jung & Weigel, 2013].


1.2.2.3 International Prophylaxis Study Group Scoring System

Past studies have shown an improvement in the quality of life for persons with

hemophilia using current prophylactic regimens. However in a long-term perspec-

tive, current prophylactic regimens do not fully prevent arthropathy and cartilage

degeneration [Oldenburg, 2015]. The effectiveness of observational and randomized

clinical trials have demonstrated that use of prophylaxis (i.e. factor replacement

therapy) decreases the frequency of joint bleeds [Blanchette et al., 2004; Feldman et

al., 2006; Manco-Johnson et al., 2007]. In order to monitor patient disease status

and treatment effectiveness, validated longitudinal studies will become essential. The

decision to start, alter, or terminate prophylactic factor replacement therapy relies

on a variety of measurements, including physical assessment of the joints, blood level

of disease markers, as well as diagnostic imaging techniques, such as MRI.

The International Prophylaxis Study Group (IPSG) MRI scale was developed in

2001. This imaging expert group has overseen the iterative development of a single

MRI scale to evaluate hemophilic arthropathy [Lundin et al., 2012]. The IPSG bares

the goal of an accurate instrument to measure MRI-based hemophilic arthropathy

at any given time, so that longitudinal changes in disease severity can be identified

to support decisions on treatment management.

In the development of the compatible MRI scales [Lundin et al., 2005] the IPSG

committee had first achieved consensus on the definition of the constructs, specify-

ing its scope to MRI-based hemophilia arthropathy. Item generation and selection

were optimized to efficiently capture the relevant constructs. The compatible in-

dices were then modified and merged into a single IPSG MRI scale which additively

scored ordinal- and categorical-level items separated respectively into soft tissue and

osteochondral domains. After a detailed process of development and testing, the

present version of the IPSG MRI scale was published in 2012 [Lundin et al., 2012]

tailored for scoring early and moderate MRI findings of hemophilic arthropathy. It

incorporates T1, T2 and gradient-recalled echo sequences and aims to assess early

anatomical changes in persons with hemophilic arthropathy [Lundin et al., 2012]

(see Appendix). The IPSG MRI scale is an additive scoring system that incorpo-


rates both soft tissue (maximum score of 9) and osteochondral (maximum score of

8) changes, which results in a total IPSG score of 17.

The IPSG scoring system has known limitations in its incapability to differenti-

ate severe joint damage and arthropathy in the ankle given a “ceiling” effect from

available scores [Hong et al., 2016]. A T2 mapping-based MRI scoring system holds

potential on depicting changes in cartilage of the target joints (i.e. primarily an-

kles and knees) prior to identification of anatomic changes in very early stages of

hemophilic arthropathy.


1.3 Purpose, Hypothesis, and Aims of Study

1.3.1 Study #1 - T2 Mapping of Children and Adolescents

with Hemophilic Arthropathy

Purpose and Aims:

Persons with hemophilia face extreme discomfort from hemarthrosis, which over

time can lead to cartilage degeneration, causing morbidity and impairment in these

patients [Carcao, 2012]. Recent research has used MRI-T2 mapping as a tool to

evaluate early arthropathic changes and cartilage degeneration in children and adults

with arthritis [Nieuwenhuizen et al., 2015; Amirabadi et al., 2015; Keshava et al.,

2015] and on blood-induced arthropathic rabbits [Amirabadi et al., 2015]. However,

to our knowledge, characterization and validation of cartilage T2 relaxation times for

the ankle and knee in male children and adolescents with hemophilia in comparison

to healthy subjects has not been considered.

In order to understand T2 mapping as a tool to evaluate early hemophilic arthropa-

thy in children and adolescents we conducted a cross-sectional study that documents

the association between age, anatomical IPSG MRI scores (soft tissue and osteo-

chondral), and cartilage T2 relaxation times.

Hypothesis:

The human cartilage is primarily composed of water and collagen fibers. Per-

sons with hemophilia experience reoccurring hemarthrosis, which eventually leads

to pannus formation, resulting in the loss of cartilage [Nieuwenhuizen et al., 2014;

Melchiorre et al., 2017]. Cartilage degeneration is characterized by the disorientation

of water molecules and collagen fibers, which can be inferred using MRI through T2

mapping [Amirabadi et al., 2015]. We believe that T2 mapping of the cartilage can

provide some insight to understand early hemophilic arthropathy in children and


adolescents. A recent longitudinal study using blood-induced arthropathic rabbits

showed a reduction of cartilage, based on reduction of T2 relaxation times over a

ten week period [Amirabadi et al., 2015]. We hypothesize that children and adoles-

cents with hemophilia will have lower ankle/knee cartilage T2 relaxation times in

comparison to healthy individuals, as a result of cartilage degeneration.


1.3.2 Study #2 Characterization of T2 Mapping in Healthy

Children and Adolescents

Purpose and Aims:

A non-invasive method to infer changes in healthy human cartilage has involved

the use of T2 mapping. However protocols for T2 mapping of healthy human carti-

lage may differ for different cross-sectional clinical investigations, resulting in poor

generalizability. Hence there is a need for a T2 mapping protocol which can be used

as a reference standard to evaluate changes in healthy human cartilage.

This cross-sectional study is composed of two parts. Firstly, to evaluate the T2

relaxation times of ankle cartilage in healthy male children and adolescent under

altered MRI protocols (i.e. protocol 1, 2, and 3). Secondly, to understand the asso-

ciation of age, body mass index (BMI), and cartilage T2 relaxation times for healthy

individuals.

Hypothesis:

We believe no significant differences will result in T2 relaxation times of the an-

kle cartilage in healthy male children and adolescents under different MRI protocols.

By having similar results in mean cartilage T2 relaxation times under altered image

protocols, a high degree of generalizability for future studies can be concluded. Fur-

thermore, it is known that children who are overweight or obese have an increased

chance of injuring their ankle [Zonfrillo et al., 2008]. As a result we hypothesize that

an increase in BMI may be associated with a decline of cartilage T2 relaxation times.

Chapter 2

Study #1

T2 Mapping of Children and Ado-lescents with Hemophilic Arthropa-thy

37

Chapter 2. Study #1 38

2.1 Background

One of the clinical symptoms persons with hemophilia face is recurrent episodes of

hemarthrosis [Gringeri et al., 2014]. The term hemophilic arthropathy can be defined

as a condition that is characterized by repetitive long-term episodes of hemarthro-

sis, which over time can result in damage to the joint [Carcao, 2012]. Overall due

to the nature of this disease, symptoms of hemophilic arthropathy mimic those of

osteoarthritis (i.e. a degenerative disease) [Bolton-Maggs & Pasi, 2003; Lobet et

al., 2014]. Hemarthrosis results in iron-mediated synovitis. Researchers believe

that repetitive hemarthrosis leads to iron release from hemoglobin, which induces

a chronic inflammatory process mediated by cytokines, leading to progressive syn-

ovial pannus growth. Whereas some investigators believe that pannus is responsible

for cartilage damage, others believe that cytokines can have a direct deleterious effect

on cartilage over time [Nieuwenhuizen et al., 2014; Melchiorre et al., 2017; Feldman

et al., 2018].

In order to diagnose hemophilic arthropathy, radiography has remained the gold

standard tool for more than a century [Doria, 2010]. However radiography is only

able to diagnose late arthropathy changes, as a result it is an inadequate tool to

identify early cartilage damage [Doria, 2010]. MRI is preferred over other techniques

to understand early stages of hemophilic arthropathy, due to its high soft tissue con-

trast resolution, thus making it possible to infer early damage to the cartilage [Doria,

2010]. Spatial resolution is primarily defined by the size of the imaging voxels, given

as a matrix which denotes the number of frequency encoding steps by the number

of phase encoding steps. On the other hand, contrast resolution is the different in-

tensities present in an image [Lin & Alessio, 2009]. The spatial resolution of MRI

in general is not high compared to other imaging modalities such as computerized

tomography (CT), MRI has a superb contrast resolution.

Clinicians often use scoring systems as a tool to measure the individual’s severity

of a certain disease. Though there does not exist a MRI based score using T2 mapping

to evaluate hemophilic arthropathy, but anatomical IPSG MRI based scoring system

was constructed to measure disease severity at various time points. The protocol


for anatomic imaging that enables the application of the IPSG MRI scoring system

includes coronal spin-echo T1-weighted sequences (TR/TE, 517/12; slice thickness,

3 mm; matrix, 256×192 pixels) [Doria et al., 2015], so that longitudinal changes

in disease severity can be identified to support decisions on treatment management

[Lundin et al., 2012]. T2 mapping holds great promise for assessing early notable

changes in the ankle and knee cartilage for persons with hemophilic arthropathy.

Recent studies have understood changes in the ankle and knee cartilage using T2

mapping in adults who are healthy [Mamisch et al., 2010; Watanabe et al., 2007;

Waldenmeier et al., 2018] and in adults who have osteoarthritis [Yu et al., 2015]. T2

mapping has also been used to understand cartilage variability in adults after long

durations of physical activity [Mosher et al., 2010; Chen et al., 2017] and on children

with arthropathy and/or juvenile idiopathic arthritis [Kim et al., 2010; Karmazyn

et al., 2012]. A recent pilot-longitudinal study used T2 mapping to infer cartilage

degeneration in blood-induced arthropathic rabbits [Amirabadi et al., 2015]. This

study found T2 relaxation times of cartilage in nine blood-induced arthropathic rab-

bits rabbits over a ten week period (baseline MRI-T2 at weeks 1, 5, 10) [Amirabadi et

al., 2015]. During this ten week period the authors document a significant decrease

in T2 relaxation times of cartilage in blood-induced arthropathic rabbits from the

first week to the tenth, implying cartilage degeneration [Amirabadi et al., 2015].

Others have proposed that MRI-T2 mapping of cartilage can reveal early arthro-

pathic changes even before clinical symptoms become apparent [Keshava et al., 2015].

However to our knowledge there exists no study to understand cartilage degeneration

in children and adolescents with hemophilia using T2 mapping. This cross-sectional

clinical investigation seeks understand T2 relaxation times of ankle/knee cartilage in

children and adolescents with hemophilia.


2.2 Methods

2.2.1 Study Population

A cross-sectional, single center study was conducted at The Hospital for Sick Children

(SickKids), with written informed consent obtained from the parents or guardians

of all hemophilic patients and healthy individuals. A total of twenty-eight male

hemophilic patients aged 7-16 years (median age; 11.5 years) were recruited from

the hematology clinic at SickKids in the year 2013/2014. Seventeen out of the nine-

teen patients had severe hemophilia A (89.5%) while the other two had moderate

hemophilia A (10.5%). All hemophilic patients had a mother who was a carrier of

the F8 gene, except for one patient who developed hemophilia in during his late

childhood. Based on the anatomical IPSG scale, each hemophilic patient was given

a sub-total osteochondral and soft tissue score.

To have a comparable reference standard of ankle/knee cartilage T2 relaxation

times in hemophilic patients, we also recruited twenty-three male healthy subjects

aged 5-17 years (median age; 15 years). Healthy subjects were recruited in 2013/2014

from public schools falling in the Toronto District School Board. The exclusion cri-

teria for these healthy subjects included any prior disorders, arthropathy, surgery, or

history of fractures in the lower extremity (i.e. from the hip to toes).

2.2.2 MRI - T2 Mapping Protocols

Hemophilic patients and healthy subjects underwent a similar protocol of MRI-T2

(see Table 2). The nine parameters listed in the table below were used to classify

the images as T2 maps. Two-dimensional Ssagittal lateral and medial positions were

scanned applied once (containing 33 slices in the protocol) using a 3.0 T magnet

(Siemens PrismaFIT VE11C) at SickKids. T2 relaxation times for the ankle (tibia-

talus) and knee (femur-tibia) cartilage were calculated using the standard spin echo

method. The cartilage T2 relaxation times for the ankle were computed for the

following four regions: lateral center, lateral edge, medial center, and medial edge

(Figure 7). The cartilage T2 relaxation times for the knee were computed for the


following four regions: lateral weight bearing (WB), lateral non-weight bearing (Non-

WB), medial WB, and medial Non-WB.

Table 2 MRI-T2 mapping protocol using a 3.0 T magnet

Persons with Hemophilia Healthy Subjects

Matrix Size 384 × 384 384 × 384Resolution (mm) 0.5 × 0.5 0.5 × 0.5Slice thickness (mm) 3.0 3.0Field of view (mm) 200 200Repetition times (ms) 1000 1000Echo time (ms) 9.9, 19.8, 29.7 9.6, 19.2, 28.8Bandwidth (Hz/pixel) 296 296Average scan time (min) ∼ 3.5 ∼ 3.5

2.2.3 Statistical Analysis

The data analysis of this study incorporates both regression coefficients (i.e. trends)

and association of T2 relaxation times for ankle and knee cartilage with respect to

hemophilic and healthy age. All data analysis was conducted using the software

Matlab version R2017b. The Pearson’s correlation coefficient was used to determine

the association between age, cartilage T2 relaxation times, and IPSG MRI scores.

Linear regression was used to compute trends of ankle/knee cartilage T2 relaxation

time (dependant variable) with age and IPSG MRI scores (independent variables)

for both hemophilia and healthy individuals [Paternoster et al., 1998]. Statistical

significance was considered to be P≤0.05 using the Student’s t-test. At each region,

to compare the trends between hemophilic and healthy groups we used the analysis

of variance (ANOVA) test.


Figure 7 MRI of a nine year old hemophilic boy’s ankle (top) and knee (bottom).The center (yellow) and edge (blue) regions where used and averaged to obtain acartilage T2 relaxation time.


2.3 Results

2.3.1 T2 Relaxation Times in Persons with Hemophilia

The data for hemophilic ankle and knee cartilage T2 relaxation times as well as

the data for healthy ankle and knee cartilage T2 relaxation times are presented in

boxplots in Figure 8. In order to compare cartilage T2 relaxation times between

hemophilic and healthy individuals, ankle and knee data were aggregated. For per-

sons with hemophilia the mean ± SD T2 relaxation times were 40.1 ± 7.5 ms, 33.1

± 6.9 ms, 41.3 ± 5.6 ms, 38.9 ± 9.8 ms, corresponding to the regions of lateral

WB, lateral Non-WB, medial WB, and medial Non-WB, respectively. For healthy

individuals the mean ± SD T2 relaxation times were 51.9 ± 5.6 ms, 48.2 ± 5.7 ms,

53.1 ± 11.2 ms, 47.7 ± 7.1 ms, corresponding to the regions of lateral WB, lateral

Non-WB, medial WB, and medial Non-WB, respectively. Cartilage T2 relaxation

times were higher in healthy individuals than persons with hemophilia. As a result

cartilage T2 relaxation times were found to have a statistically significant difference

between the hemophilic and healthy group for all four regions (ankle and knee data

aggregated).


20

30

40

50

60

70

80

T2

Rel

axat

ion

Tim

e (m

s)

Lateral Non-WB* Lateral WB* Medial Non-WB* Medial WB*

Hemophilia Healthy

Figure 8 Aggregated data for ankle and knee cartilage T2 relaxation times.Hemophilia (n = 28) and healthy (n = 23) ankle and knee cartilage T2 relaxationtimes were aggregated together for each of the four selected regions. An asterisk(*) has been used in the boxplot labels to denote statistically significant (P ≤ 0.05)differences between hemophilia and healthy mean cartilage T2 relaxation times.


20

30

40

50

60

70

80T

2 R

elax

atio

n T

ime

(ms)

Lateral Edge* Lateral Center* Medial Edge Medial Center*

Haemophilia Healthy

20

30

40

50

60

70

80

T2

Rel

axat

ion

Tim

e (m

s)

Lateral Non-WB* Lateral WB Medial Non-WB* Medial WB

Haemophilia Healthy

Figure 9 Separate ankle and knee cartilage T2 relaxation time data. Hemophilia(n = 19) and healthy (n = 16) ankle T2 relaxation times for the four selected regions(top). Hemophilia (n = 9) and healthy (n = 7) knee cartilage T2 relaxation timesfor the four selected regions (bottom). An asterisk (*) has been used in the boxplotlabels to denote statistically significant (P ≤ 0.05) differences between hemophiliaand healthy mean cartilage T2 relaxation times.


Upon analyzing cartilage T2 relaxation times for hemophilic ankle and knee sep-

arately as well as healthy ankle and knees separately (Figure 9), we found different

results in comparison to the aggregated data described above. For ankle data, sta-

tistically significant differences in mean T2 relaxation times were found between

hemophilic and healthy groups for all regions, except medial edge. For knee data,

statistically significant differences in mean cartilage T2 relaxation times were found

between hemophilic and healthy groups for lateral and medial Non-WB.

The data for hemophilic and healthy ankle cartilage T2 relaxation times were

plotted against age, presented in Figure 10. The data for hemophilic and healthy knee

cartilage T2 relaxation times were plotted against age, presented in Figure 11. We

found statistically significant strong negative correlations in all four regions between

age and T2 relaxation times for hemophilic and healthy ankle and knee cartilage.

We also found negative trends in all four regions upon regressing T2 relaxation times

on age for hemophilic and healthy ankle and knee cartilage. These trends have been

summarized in Tables 3-5, where we note that hemophilia and healthy groups have a

similar magnitude in the trend. Statistically significant differences upon comparing

the trends for each region of the ankle and knee in both groups were found.


4 6 8 10 12 14 16 1820

30

40

50

60

70

80

4 6 8 10 12 14 16 1820

30

40

50

60

70

80

4 6 8 10 12 14 16 1820

30

40

50

60

70

80

4 6 8 10 12 14 16 1820

30

40

50

60

70

80

A

B

C

D

Figure 10 A-D) Association between age and ankle cartilage T2 relaxation timesfor each selected region. Hemophilia (red; n = 19) and healthy (blue; n = 16) havebeen distinguished with different colours, along with their least squares regressionline of best fit. T2 relaxation times of the ankle cartilage were computed based onthe following regions, A) lateral center, B) medial center, C) lateral edge, D) medialedge.


4 6 8 10 12 14 16 1820

30

40

50

60

70

80

4 6 8 10 12 14 16 1820

30

40

50

60

70

80

4 6 8 10 12 14 16 1820

30

40

50

60

70

80

4 6 8 10 12 14 16 1820

30

40

50

60

70

80

A

B

C

D

Figure 11 A-D) Association between age and knee cartilage T2 relaxation times foreach selected region. Hemophilia (orange; n = 9) and healthy (purple; n = 7) havebeen distinguished with different colours, along with their least squares regressionline of best fit. T2 relaxation times of the knee cartilage were computed based onthe following regions, A) lateral center, B) medial center, C) lateral edge, D) medialedge.


Tab

le3

Com

bin

edan

kle

and

knee

cart

ilag

eT

2re

laxat

ion

tim

edat

afo

rhem

ophilia

and

hea

lthy

sub

ject

s.

Hem

ophil

ia(n

=28

)H

ealt

hy

(n=

23)

Mea

n±

SD

(95%

CI)

Tre

nd

(P-v

alue)

ms/

yr

Mea

n±

SD

(95%

CI)

Tre

nd

(P-v

alue)

ms/

yr

Age

(yrs

)11

.7±

3.0

(10.

5-12

.9)

-13

.7±

3.2

(12.

3-15

.1)

-L

ater

alW

B(m

s)41

.0±

7.6

(38.

1-43

.9)

-1.1

4(0

.01)

*51

.6±

5.1

(49.

4-53

.8)

-1.2

9(<

0.00

1)*

Lat

eral

Non

-WB

(ms)

38.2

±5.

7(3

6.0-

40.4

)-0

.72

(0.0

4)*

48.2

±5.

8(4

5.7-

50.7

)-0

.88

(0.0

2)*

Med

ial

WB

(ms)

41.0

±6.

1(3

8.7-

43.4

)-1

.27

(0.0

01)*

54.0

±9.

8(4

9.8-

58.3

)-2

.01

(<0.

001)

*M

edia

lN

on-W

B(m

s)43

.1±

5.2

(41.

1-45

.1)

-1.1

8(<

0.00

1)*

47.4

±6.

5(4

4.6-

50.2

)-0

.53

(0.2

2)*

den

ote

svalu

es

stati

stic

all

ysi

gn

ifica

nt

atP

≤0.05.

Tab

le4

Ankle

(tib

ia-t

alus)

cart

ilag

eT

2re

laxat

ion

tim

esfo

rhem

ophilia

and

hea

lthy

sub

ject

s.

Hem

ophil

ia(n

=19

)H

ealt

hy

(n=

16)

Mea

n±

SD

(95%

CI)

Tre

nd

(P-v

alue)

ms/

yr

Mea

n±

SD

(95%

CI)

Tre

nd

(P-v

alue)

ms/

yr

Age

(yrs

)11

.3±

2.4

(10.

1-12

.5)

-12

.9±

3.5

(11.

1-14

.8)

-L

ater

alC

ente

r(m

s)38

.4±

6.4

(35.

3-41

.5)

-1.7

3(0

.002

)*52

.0±

6.0

(48.

8-55

.2)

-1.4

1(<

0.00

1)*

Lat

eral

Edge

(ms)

36.6

±5.

5(3

3.7-

39.1

)-1

.26

(0.0

1)*

46.3

±5.

9(4

3.2-

49.5

)-1

.39

(<0.

001)

*M

edia

lC

ente

r(m

s)41

.3±

6.1

(38.

4-44

.3)

-1.6

7(0

.002

)*59

.4±

6.0

(56.

2-62

.6)

-1.3

3(<

0.00

1)*

Med

ial

Edge

(ms)

44.6

±4.

8(4

2.3-

47.0

)-1

.39

(<0.

001)

*44

.3±

5.2

(41.

5-47

.1)

-1.2

3(<

0.00

1)*

*den

ote

svalu

es

stati

stic

all

ysi

gn

ifica

nt

atP

≤0.05.

Table

5K

nee

(fem

ur-

tibia

)ca

rtilag

eT

2re

laxat

ion

tim

esfo

rhem

ophilia

and

hea

lthy

sub

ject

s.

Hem

ophil

ia(n

=9)

Healt

hy

(n=

7)M

ean±

SD

(95%

CI)

Tre

nd

(P-v

alue)

ms/

yr

Mea

n±

SD

(95%

CI)

Tre

nd

(P-v

alue)

ms/

yr

Age

(yrs

)12

.6±

4.1

(9.4

-15.

7)-

15.3

±1.

9(1

3.5-

17.0

)-

Lat

eral

WB

(ms)

46.6

±7.

0(4

1.2-

52.0

)-1

.21

(0.0

3)*

50.6

±2.

0(4

8.8-

52.5

)-0

.81

(0.0

4)*

Lat

eral

Non

-WB

(ms)

42.1

±3.

9(3

9.1-

45.2

)-0

.68

(0.0

4)*

52.5

±3.

3(5

0.4-

54.6

)-0

.90

(0.0

5)*

Med

ial

WB

(ms)

40.4

±6.

5(3

5.4-

45.4

)-0

.99

(0.0

7)41

.7±

2.5

(39.

4-44

.0)

-0.9

1(0

.09)

Med

ial

Non

-WB

(ms)

39.8

±4.

7(3

6.2-

43.4

)-0

.82

(0.0

3)*

54.4

±1.

8(5

2.7-

56.0

)-0

.52

(0.2

)*

den

ote

svalu

es

stati

stic

all

ysi

gn

ifica

nt

atP

≤0.05.


2.3.2 Association of IPSG MRI Scores with T2 Relaxation

Times

The total IPSG MRI score (17 points) is comprised of soft tissue (9 points) and

osteochondral (8 points) components. For ankles, the mean ± SD soft tissue, os-

teochondral, and total IPSG MRI scores were 2.4 ± 2.1, 0.7 ± 1.7, and 3.1 ± 2.3,

respectively. For knees, the mean ± SD soft tissue, osteochondral, and total IPSG

MRI scores were 3.6 ± 1.8, 2.3 ± 2.9, and 5.9 ± 3.9, respectively. In general, the

knees resulted in higher soft tissue, osteochondral, and total IPSG MRI scores than

ankles.

The age of persons with hemophilia was correlated with soft tissue and osteochon-

dral scores for ankles and knees separately, shown in Figure 12. The age of persons

with hemophilia was also correlated with the total IPSG MRI scores for ankles and

knees separately, shown in Figure 13. For the ankle and knee, the correlation between

age and soft tissue score, age and osteochondral score, as well as age and total IPSG

was conducted. For the ankle, the correlation between age and the total IPSG score

was found to be weak, whereas for the knee this was found to be strong. Further-

more, the data of the ankle and knee cartilage T2 relaxation times for persons with

hemophilia were plotted against total IPSG MRI scores shown in Figures 14 and 15,

respectively. In general weak correlations were found between ankle/knee cartilage

T2 relaxation times and total IPSG MRI scores. We also found weak trends in all

four regions upon regressing ankle and knee cartilage T2 relaxation times on total

IPSG, soft tissue, and osteochondral scores, which have been summarized in Tables

6 and 7.


4 6 8 10 12 14 16 180

2

4

6

8

10

12

4 6 8 10 12 14 16 180

2

4

6

8

10

12

Figure 12 Association between age, IPSG soft tissue (red) and osteochondral(blue) scores (n = 19) for ankles with hemophilia (top). Association betweenage, IPSG soft tissue (red) and osteochondral (blue) scores (n = 9) for knees withhemophilia (bottom). The least squares regression line of best fit has also beenshown.


4 6 8 10 12 14 16 180

2

4

6

8

10

12

4 6 8 10 12 14 16 180

2

4

6

8

10

12

Figure 13 Association between age and total IPSG MRI scores for hemophilicankles (top) and knees (bottom).


0 2 4 6 8 10 1220

30

40

50

60

70

80

0 2 4 6 8 10 1220

30

40

50

60

70

80

0 2 4 6 8 10 1220

30

40

50

60

70

80

0 2 4 6 8 10 1220

30

40

50

60

70

80

A

B

C

D

Figure 14 A-D) Association between total IPSG MRI scores and ankle cartilageT2 relaxation times for each selected region (n = 19). T2 relaxation times of theankle cartilage were computed based on the following regions, A) lateral center, B)medial center, C) lateral edge, D) medial edge.


0 2 4 6 8 10 1220

30

40

50

60

70

80

0 2 4 6 8 10 1220

30

40

50

60

70

80

0 2 4 6 8 10 1220

30

40

50

60

70

80

0 2 4 6 8 10 1220

30

40

50

60

70

80

A

B

C

D

Figure 15 A-D) Association between total IPSG MRI scores and knee cartilageT2 relaxation times for each selected region (n = 9). T2 relaxation times of the kneecartilage were computed based on the following regions, A) lateral center, B) medialcenter, C) lateral edge, D) medial edge.


Table 6 Trends (P-value) of hemophilic ankle data regressed with IPSG MRIscores.

Hemophilia (n = 19)Total IPSG Score Soft Tissue Score Osteochondral Score

Age (yrs) -0.10 (0.7) score/yrs -0.09 (0.7) score/yrs -0.01 (0.9) score/yrsLateral Center (ms) 0.01 (0.9) ms/score 0.37 (0.6) ms/score -0.49 (0.6) ms/scoreLateral Edge (ms) 0.73 (0.2) ms/score 0.73 (0.2) ms/score 0.29 (0.7) ms/score

Medial Center (ms) -0.39 (0.5) ms/score -0.21 (0.7) ms/score -0.41 (0.6) ms/scoreMedial Edge (ms) 0.17 (0.7) ms/score 0.08 (0.9) ms/score 0.21 (0.7) ms/score

* denotes values statistically significant at P ≤ 0.05.

Table 7 Trends (P-value) of hemophilic knee data regressed with IPSG MRI scores.

Hemophilia (n = 9)Total IPSG Score Soft Tissue Score Osteochondral Score

Age (yrs) 0.70 (0.02)* score/yrs 0.21 (0.2) score/yrs 0.49 (0.04)* score/yrsLateral WB (ms) -0.70 (0.3) ms/score -0.07 (0.9) ms/score -1.26 (0.1) ms/score

Lateral Non-WB (ms) -0.70 (0.04)* ms/score -1.55 (0.03)* ms/score -0.68 (0.2) ms/scoreMedial WB (ms) -0.24 (0.7) ms/score -0.74 (0.6) ms/score -0.16 (0.9) ms/score

Medial Non-WB (ms) -0.21 (0.6) ms/score -0.04 (0.9) ms/score -0.37 (0.5) ms/score* denotes values statistically significant at P ≤ 0.05.

2.3.3 Linear Regression Models for T2 Relaxation Times

We also assessed the estimated mean ankle/knee cartilage T2 relaxation times at the

four regions of interest (Figure 7) in a linear regression model by incorporating age,

soft tissue, osteochondral, and total IPSG MRI scores as covariates in the model.

The results in the linear models has been summarized in Tables 8-10. Age was found

to have a statistically significant regression coefficient for all regions in the ankle

and knee. These linear regression models suggests that with every one year increase

in the age for persons with hemophilia it results in an estimated mean ankle/knee

cartilage T2 relaxation time decline of 1.5 ms, while holding total IPSG MRI scores

constant. Regression coefficients for soft tissue, osteochondral, and total IPSG MRI


scores were not found to be statistically significant.

In the linear regression models shown below, T2 is the estimated mean cartilage

T2 relaxation time for a hemophilic ankle/knee at the four regions of interest, A is

the age of the hemophilic patient, I is the total IPSG MRI score, S is the soft tissue

score, and O is the osteochondral score given to persons with hemophilia.

Table 8 Regression models using hemophilic ankle/knee age and total IPSG MRIscores.

Ankles Knees

Lateral Center/WB T2 = 58.7 − 1.7∗A− 0.17I T2 = 63.4 − 1.6∗A + 0.48ILateral Edge/Non-WB T2 = 48.1 − 1.2∗A + 0.6I T2 = 49.5 − 0.4A− 0.39I

Medial Center/WB T2 = 62.6 − 1.7∗A− 0.6I T2 = 56.2 − 1.8∗A + 1.1IMedial Edge/Non-WB T2 = 60.2 − 1.4∗A + 0.02I T2 = 52.7 − 1.4∗A + 0.89I* denotes coefficients statistically significant at P ≤ 0.05.

Table 9 Regression models using hemophilic ankle/knee age and soft tissue scores.

Ankles Knees

Lateral Center/WB T2 = 57.4 − 1.7∗A + 0.16S T2 = 60.5 − 1.6∗A + 1.6∗SLateral Edge/Non-WB T2 = 48.6 − 1.2∗A + 0.59S T2 = 51.6 − 0.4A− 1.1∗S

Medial Center/WB T2 = 61.7 − 1.7∗A− 0.42S T2 = 52.6 − 1.1∗A + 0.43SMedial Edge/Non-WB T2 = 60.7 − 1.4∗A− 0.09S T2 = 49.1 − 1.1∗A + 1.1∗S* denotes coefficients statistically significant at P ≤ 0.05.

Table 10 Regression models using hemophilic ankle/knee age and osteochondralscores.

Ankles Knees

Lateral Center/WB T2 = 58.4 − 1.7A− 0.53O T2 = 61.4 − 1.2A− 0.13OLateral Edge/Non-WB T2 = 50.4 − 1.2A + 0.27O T2 = 50.5 − 0.6A− 0.04O

Medial Center/WB T2 = 60.6 − 1.7A− 0.44O T2 = 59.1 − 1.8A + 1.6OMedial Edge/Non-WB T2 = 60.2 − 1.4A + 0.18O T2 = 53.4 − 1.2A + 0.84O* denotes coefficients statistically significant at P ≤ 0.05.


2.4 Discussion & Limitations

Due to its detection of water and underlying collagen structure in the cartilage, MRI

through T2 mapping is believed to hold great promise for assessing early notable

changes in the cartilage [Maier et al., 2003]. This clinical cross-sectional investiga-

tion was undertaken to primarily understand if T2 mapping can be used as a valid

tool to evaluate children and adolescents with hemophilic arthropathy. From our

results we note a statistically significant difference in mean cartilage T2 relaxation

times between hemophilic and healthy groups for the ankle. Majority of patients for

this study had severe hemophilia, thus it is known that severe hemophilic arthropa-

thy primarily impacts the ankles through cartilage T2 relaxation [Leslie & Catherine,

2007]. Young individuals with severe hemophilia face majority of the joint bleeds in

the ankle, leading to prominent ankle arthropathy [Kuijlaars et al., 2017].

Although low cartilage T2 relaxation times inferred severe hemophilic arthropa-

thy, however arthropathy was not noted through the IPSG MRI scores. In fact, for

the ankle our results found a weak correlation between age and IPSG MRI scores.

The lack of correlation found between age and IPSG MRI scores may be due to

the fact that the IPSG scoring system has known limitations in its incapability to

differentiate severe joint damage and arthropathy in the ankle [Hong et al., 2016].

Furthermore, our findings suggest that age plays an important role to understand

the decline of ankle and knee cartilage T2 relaxation times for both hemophilia and

healthy groups. We believe the decline in ankle and knee cartilage T2 relaxation

times for persons with hemophilia may infer early cartilage degeneration. As for

healthy individuals, the decline in ankle and knee cartilage T2 relaxation times may

be due to the thinning of cartilage and reduction of water content around the joints

during skeletal maturation, as the physes starts to close [Kim et al., 2014; Shiraj et

al., 2014]. Our results are consistent with another study on healthy male and female

children and adolescents, which established a sequential decrease in patellar carti-

lage T2 relaxation times with respect to increasing chronologic age [Kim et al., 2014].


Persons with severe hemophilia can experience their first joint bleed in an ankle

or knee joint as early into their second year of birth [Carcao, 2012; Coppola & Fran-

chini, 2013]. In Canada, nearly all persons with severe hemophilia start prophylaxis

between one to two years of age and the bleeding frequency is evaluated by clini-

cal follow-up every three months [Coppola & Franchini, 2013]. While prophylaxis

helps decrease the frequency and severity of bleeds in persons with hemophilia, it

does not prevent all bleeds [Simpson & Valentino, 2012; Feldman et al., 2018]. Over

time, small bleeding events could result in early cartilage degeneration through iron-

mediated synovitis [Nieuwenhuizen et al., 2014]. Nevertheless this study suggests

that cartilage T2 relaxation times of the ankle and knee may help to understand

early hemophilic arthropathy in children and adolescents with hemophilia. A longi-

tudinal study is needed to verify this study and cartilage degeneration in children

and adolescents with severe hemophilic arthropathy.

One of the limitations to our study includes the absence of socioeconomic and

lifestyle data available for the studied hemophilic and healthy children and adoles-

cents. Although in Canada, the cost of prophylaxis is covered by the provincial

government, however socioeconomic status plays an important role in children and

adolescents day-to-day lifestyle activities. Various global studies on socioeconomic

and children’s general health outcomes have been conducted, noting that lower so-

cioeconomic status of parents results in poor health outcomes for children [Stringhini

et al., 2017; Baumann et al., 2018], and hemophilia is no exception. In addition,

children of families with lower socioeconomic status lack the nutrition through their

daily diet resulting in an under development of the human skeleton and possibly the

cartilage [Prentice et al., 2006]. Secondly, due to the lack of data, the level of physi-

cal activity among hemophilic and healthy individuals was not considered. Vigorous

physical activity for a duration of an hour in children and adolescents with hemophilia

was transiently associated with a moderate increase in risk of bleeding and trauma

[Broderick et al., 2012]. Prolonged bleeding and trauma to the joints could influence

early cartilage degeneration. Future studies should incorporate clinical, social, and

possible environmental factors into the assessment of joint outcomes by imaging to

fully understand early cartilage degeneration in children and adolescents with severe

hemophilia.

Chapter 3

Study #2

Characterization of T2 Mapping inHealthy Children and Adolescents

59


3.1 Background

Human cartilage is an intricate tissue, which withstands numerous dynamic loads

and injuries on a day-to-day basis and helps reduce localized stress concentrations

in the underlying bone [Ronken et al., 2012]. There are mainly three types of car-

tilage throughout the body, each characterized by their dispersion of chondrocytes.

The hyaline cartilage in the ankle has average variations in thickness of ∼2-4 mm,

primarily depending on an individual’s age [Fox et al., 2009; Shepherd & Seedhom,

1999]. The thickness of cartilage decreases over an individual’s life time due to a

decrease in proteoglycan content [Roughley et al., 1980].

As children age into their adolescent years, they experience a growth in their

skeletal frame, which includes increased osteogenic and chondrocyte cells [Herring,

2008]. One of the principal mechanisms that takes place during skeletal maturation in

late childhood is the elongation and lengthening of bone and the concomitant reduc-

tion in epiphyseal cartilage [Herring, 2008]. After skeletal maturation and cessation

of bone growth, the cartilage, and its composition, stabilizes [Asanbaeva et al., 2008].

It is widely accepted that in healthy individuals the greatest amount of load is

exerted on the ankle, specifically the tibia-talus joint [Cher et al., 2016]. For obese

children and adolescents who have a high body mass index (BMI), the likelihood of

injury to the ankle increases [Zonfrillo et al., 2008].

MRI is an excellent imaging tool to detect soft tissue anatomy [Maier et al.,

2003; Thapa et al., 2012]. Among MRI techniques, T2 mapping holds great promise

for assessment of early notable changes in the cartilage [Maier et al., 2003] due its

ability of detection of water in cartilage and underlying collagen [Welsch et al., 2014].

There have been numerous studies conducted on understanding the association

between age and T2 relaxation times, particularly in the cartilage of healthy knees

[Kim et al., 2014; Ding et al., 2005; Baum et al., 2013; Joseph et al., 2015]. Most

previous studies have focused on differences of T2 relaxation times of tibia-talus car-

tilage with respect to anatomical and topographic variations in the ankle [Lim et


al., 2016], as well as the effects of exercise on cartilage strain [Cher et al., 2016].

However to our knowledge there has been no study conducted to understand the as-

sociation of age, BMI, and cartilage T2 relaxation times in ankles of healthy children

and adolescents under different MRI protocols. That is, does altering image spatial

resolutions of MRI result in a substantial difference of cartilage T2 relaxation times

in the ankle for healthy individuals? Understanding cartilage T2 relaxation maps in

healthy individuals under different MRI protocols (i.e. which can be performed in

any type of MRI scanner) should improve generalizability of results of future studies

using this technique and should enable wider utilization of this technique if results

of larger series confirm the results of our pilot study. Overall this study assesses the

feasibility of using a given protocol l for generalizability in future clinical studies on

T2 mapping.


3.2 Methods

3.2.1 Study Population

This cross-sectional research was conducted as a clinical investigation, where before

commencing this study, a research ethics board approval was obtained from Sick-

Kids. Eleven healthy subjects were recruited from public schools within the Toronto

District School Board region between September 2017 and April 2018. The healthy

subjects were children and adolescents aged 8-17 years old (median age of 14 years)

with a BMI range of 15.5-25.6 kg/m2 (median of 19.3 kg/m2) whose parents provided

informed consent for participation towards this study. According to the individual’s

BMI, three individuals were noted to be underweight (<18.5 kg/m2) and one individ-

ual was overweight (≥ 25−<30 kg/m2). These individuals fulfilled the criteria of no

change in regular lifestyle made prior to study participation. The exclusion criteria

included a history of any connective tissue disorder or inflammatory arthritis, prior

ankle surgery, or any history of a fracture (i.e. in the lower leg or foot).

3.2.2 MRI - T2 Mapping Protocols

These healthy subjects underwent MRI-T2 examinations of sagittal lateral and me-

dial positions with a 3.0 T magnet (Siemens PrismaFIT VE11C) at SickKids using

a 15-Channel Ankle Coil, under three MRI protocols to understand if the mean car-

tilage T2 relaxation time is statistically similar under different spatial resolutions.

Protocol 1 was developed in-house and protocols 2 and 3 were built-in as a package

from the manufacturer’s scanner. We hypothesized that if the mean cartilage T2

relaxation time was statistically similar under different protocols, protocol 1 could

be used in scanners that did not have specific T2 mapping programs in the core

settings available for use. This situation would be useful in optimizing scan time

and standardizing protocols in future clinical studies. Table 11 shows parameters

adjusted of each protocol. Although the matrix size and resolution is fairly similar

between the three protocols, however for protocol 1 the field of view and bandwidth

were relatively lower in comparison to protocol 2 and 3 (high resolution). Protocol 1

uses a constant TR/TE developed where the time interval between TR and TE was

kept constant of 500 ms [Sussman et al., 2010]. Thus protocol 1 (TE = 13, 19, 28


ms; TR = 513, 519, 528 ms), protocol 2 (TE = 9.6, 19.2, 28.8 ms; TR = 1000 ms),

and protocol 3 (TE = 11.1, 22.2, 33.3 ms; TR = 1690 ms) (Table 11). Hence for

example a lower bandwidth sample data at a slower rate along with a smaller field

of view leads to a quicker scan time in comparison to protocol 2 and 3. All eleven

subjects underwent the three MRI-T2 protocols.


Table 11 MRI parameters for healthy pediatric ankle scan at 3.0 T

Protocol 1 Protocol 2 Protocol 3 (High resolution)

Matrix Size 384 × 384 384 × 384 384 × 384Resolution (mm) 0.4 × 0.4 0.5 × 0.5 0.4 × 0.4Slice thickness (mm) 3.0 3.0 1.0Field of view (mm) 150 200 150Repetition times (ms) 513, 519, 528 1000 1690Echo time (ms) 13, 19, 28 9.6, 19.2, 28.8 11.1, 22.2, 33.3Bandwidth (Hz/pixel) 130 296 296Flip angle (degrees) 90 180 180Average scan time (min) ∼ 3 ∼ 3.5 ∼ 6

Figure 16 The ankle (tibia-talus) is depicted of an eight year old boy, using T2protocol 2. The image shows the center (orange) and edge (green) regions where T2relaxation times of the cartilage were computed.


3.2.3 Data and Statistical Analysis

Cartilage T2 relaxation times for the ankle were computed using the standard spin

echo method for what we choose to call center and edge regions of the ankle. Three

echo times were used to calculate the T2 relaxation time for lateral as well as medial

center and edge regions, comprised of both of the tibia and talus cartilage and only

the talus, respectively (Figure 16). For the purpose of conducting associations, the

Pearson’s correlation coefficient was used. The magnitude of trends were determined

from the coefficients using linear regression. To obtain the reliability of cartilage

T2 relaxation times taken under different protocols the Bland-Altman method was

applied. A P value of ≤0.05 was deemed to be statistically significant. All data and

statistical analysis was performed in combination of Stata 14 and MATLAB R2017b.


3.3 Results

Figure 17 illustrates MRI conducted for the lateral aspect of the ankle using all

three protocols. Specifically, figures 17a,d,e show the results using protocol 1. Fig-

ures 17b,e,h show the results using protocol 2. Figures 17c,f,i show the results using a

high resolution protocol. Figures 18 illustrates MRI conducted for the medial aspect

of the ankle using all three protocols. Specifically, Figures 18a,d,e show the results

using protocol 1. Figures 18b,e,h show the results using protocol 2. Figures 18c,f,i

show the results using a high resolution protocol.

In Figures 17 and 18, cartilage T2 relaxation times for lateral and medial aspects

of the ankle were plotted against age of healthy males. Regardless of the protocol

and region of the ankle, all correlation coefficients between age and cartilage T2

relaxation times were found to be strongly negative, ranging from -0.91 (P <0.001)

to -0.67 (P = 0.03). This suggests that an increase in age explains ∼45-85% of the

variance in the decline of cartilage T2 relaxation times for the ankle. Figures 19-21

show good reliability of cartilage T2 relaxation time measurements under the three

different protocol, using the Bland-Altman method. Mean cartilage T2 relaxation

times between each protocol were similar in magnitude, ranging from 40.1-63.2 ms,

and as a result were not found to be statistically different amongst each other. The

mean cartilage T2 relaxation times were found to be higher for center ankle regions

in comparison to edge.


a)

d)

b) c)

e) f)

g) h) i)

Figure 17 MRI of lateral aspect of the ankle for a 16 year old healthy male. d-f)Association of age to cartilage T2 relaxation times for lateral center aspect of theankle under protocol 1, 2, and 3, respectively. g-i) Association of age to cartilageT2 relaxation times for lateral edge aspect of the ankle under protocol 1, 2, and 3,respectively. All associations shown here were found to be statistically significant(P ≤ 0.05).


a)

d)

b) c)

e) f)

g) h) i)

Figure 18 MRI of medial aspect of the ankle for a 16 year old healthy male. d-f)Association of age to cartilage T2 relaxation times for medial center aspect of theankle under protocol 1, 2, and 3, respectively. g-i) Association of age to cartilageT2 relaxation times for medial edge aspect of the ankle under protocol 1, 2, and 3,respectively. All associations shown here were found to be statistically significant(P ≤ 0.05).


20 30 40 50 60 70 8020

30

40

50

60

70

80

20 30 40 50 60 70 80-25

-20

-15

-10

-5

0

5

10

15

20

25

Figure 19 Association of healthy ankle cartilage T2 relaxation times for the fourankle regions obtained from protocol 1 and 2 (left), and the Bland-Altman plotshowing the difference in means between the two protocols (right). On the rightpanel, the blue line represents the mean difference between the protocols, whereasthe red lines represent 2σ.


20 30 40 50 60 70 8020

30

40

50

60

70

80

20 30 40 50 60 70 80-25

-20

-15

-10

-5

0

5

10

15

20

25

Figure 20 AAssociation of healthy ankle cartilage T2 relaxation times for thefour ankle regions obtained from protocol 1 and high resolution protocol (left), andthe Bland-Altman plot showing the difference in means between the two protocols(right). On the right panel, the blue line represents the mean difference between theprotocols, whereas the red lines represent 2σ.


20 30 40 50 60 70 8020

30

40

50

60

70

80

20 30 40 50 60 70 80-25

-20

-15

-10

-5

0

5

10

15

20

25

Figure 21 Association of healthy ankle cartilage T2 relaxation times for the fourankle regions obtained from protocol 2 and high resolution protocol (left), and theBland-Altman plot showing the difference in means between the two protocols (right).On the right panel, the blue line represents the mean difference between the protocols,whereas the red lines represent 2σ.


Association of age to their BMI (n = 11) was found to be weak to be moderate

(r = 0.43, P = 0.2), with a trend value was 0.41 kg/m2/year (P = 0.18), in this

particular cohort of healthy male children and adolescents. The mean ± SD (95%

CI) height and weight was noted to be 156.5 ± 17.1 (145.1-168.0) cm and 49.2 ±13.6 (40.1-58.4) kg, respectively. The correlation between BMI and cartilage T2 re-

laxation times for lateral (Figure 22) and medial (Figure 23) aspects of the ankle

were found to be weakly negative, suggesting that variation in healthy BMI has an

influence of <10% on the variability of cartilage T2 relaxation times.

Using linear regression, the regression coefficients (i.e. trends) of cartilage T2

relaxation times with respect to age and BMI were found for each protocol, sum-

marized in Tables 12-14. Trends of cartilage T2 relaxation times with age for each

protocol range from -2.08 ms/year (P = 0.006) to -0.80 ms/year (P <0.01). Trends

of cartilage T2 relaxation times with age between all three protocols were quantita-

tively compared at each region of interest, and no statistically significant difference

was found.

We also assessed the estimated mean of ankle cartilage T2 relaxation times by

incorporating age and BMI at the four regions of interest in linear regression mod-

els, summarized in Tables 15-17. Age was found to have a statistically significant

regression coefficient for all regions in the ankle. These linear regression models sug-

gests that every one year increase in a healthy individual’s age yields an estimated

mean decline in cartilage T2 relaxation time ∼2 ms, while holding BMI constant.

Regression coefficients for BMI were not found to be statistically significant.


a) d)

b) e)

c) f)

Figure 22 Association of healthy individual’s BMI to lateral center and edge aspectof the ankle cartilage T2 relaxation times under protocol 1 (a,d); under protocol 2(b,e); and under high resolution (c,f).


a) d)

b) e)

c) f)

Figure 23 Association of healthy individual’s BMI to medial center and edge as-pect of the ankle cartilage T2 relaxation times under protocol 1 (a,d); under protocol2 (b,e); and under high resolution (c,f).


Table 12 Data summary of healthy ankle MRI protocol 1

Protocol 1 (n = 11)Mean ± SD (95% CI) Trend (P-value)

Age (yrs) 12.9 ± 3.5 (10.6-15.2) -BMI (kg/m2) 19.7 ± 3.0 (17.5-21.9) 0.41 (0.2) kg/m2/year

Lateral Center (ms) 52.6 ± 8.1 (47.2-58.0) -1.93 (0.001)* ms/yearLateral Edge (ms) 50.7 ± 7.5 (45.6-55.7) -1.7 (0.004)* ms/year

Medial Center (ms) 56.8 ± 6.9 (52.1-61.4) -1.82 (<0.001)* ms/yearMedial Edge (ms) 45.2 ± 7.6 (40.2-50.3) -1.86 (<0.001)*


Table 13 Data summary of healthy ankle MRI protocol 2

Protocol 2 (n = 11)Mean ± SD (95% CI) Trend (P-value)


Lateral Center (ms) 49.7 ± 7.3 (44.8-54.6) -1.89 (<0.001)* ms/yearLateral Edge (ms) 45.9 ± 8.2 (40.0-51.0) -1.76 (0.009)* ms/year

Medial Center (ms) 63.2 ± 9.9 (56.6-69.9) -1.88 (0.03)* ms/yearMedial Edge (ms) 40.9 ± 7.2 (36.1-45.8) -1.69 (0.002)*


Table 14 Data summary of healthy ankle MRI high resolution

High Resolution (n = 11)Mean ± SD (95% CI) Trend (P-value)


Lateral Center (ms) 49.8 ± 9.0 (43.8-55.8) -1.99 (0.006)* ms/yearLateral Edge (ms) 35.9 ± 4.3 (32.9-38.8) -1.13 (<0.001)* ms/year

Medial Center (ms) 60.0 ± 9.5 (53.7-66.4) -2.08 (0.006)* ms/yearMedial Edge (ms) 40.0 ± 3.5 (37.7-42.4) -0.80 (0.003)*



Table 15 Regression models using protocol 1

Protocol 1

Lateral Center T2 = 69.5 − 2.2∗A+ 0.56BLateral Edge T2 = 65.1 − 1.9∗A+ 0.52B

Medial Center T2 = 77.3 − 1.9∗A+ 0.2BMedial Edge T2 = 62.8 − 2.0∗A+ 0.45B

* denotes coefficients statistically significant at P ≤ 0.05. A:Age; B:BMI

Table 16 Regression models using protocol 2

Protocol 2

Lateral Center T2 = 65.6 − 2.1∗A+ 0.58BLateral Edge T2 = 57.1 − 2.1∗A+ 0.76B

Medial Center T2 = 68.4 − 2.4∗A+ 1.32∗BMedial Edge T2 = 59.6 − 1.8∗A+ 0.22B

* denotes coefficients statistically significant at P ≤ 0.05. A:Age; B:BMI

Table 17 Regression models using high resolution

High Resolution

Lateral Center T2 = 59.1 − 2.45∗A+ 1.13∗BLateral Edge T2 = 47.6 − 1.2∗A+ 0.2B

Medial Center T2 = 81.0 − 2.25∗A+ 0.41BMedial Edge T2 = 49.5 − 0.82A+ 0.06B* denotes coefficients statistically significant at P ≤ 0.05. A:Age; B:BMI


3.3.1 Discussion & Limitations

This pilot study documents cartilage T2 relaxation times in ankles of healthy chil-

dren and adolescents under three altered MRI protocols. The mean cartilage T2

relaxation times were found to be higher for center in comparison to edge region of

the ankle. This could be due to the difference in cartilage thickness, where center

of the ankle is known to have a thicker cartilage than the ankle edge [Eckstein et

al., 2006]. The thickness of cartilage is determined by the amount of extracellular

matrix present through water content, which can influence cartilage T2 relaxation

times [Mosher et al., 2010]. In general, healthy children and adolescents have thicker

tibia-talus cartilage than adults, hence thickness of cartilage is known to decrease

with increasing age in males [Welsch et al., 2014; Spannow et al., 2010]. Although

there is paucity of information on cartilage T2 mapping for male children in the lit-

erature, the magnitude range of cartilage T2 relaxation times reported in this study

are consistent with other clinical investigations on healthy youth (18-25 years) [Cha

et al., 2015; Lim et al., 2016].

Our main finding suggests that age plays an important role to understand car-

tilage T2 relaxation times of ankles in healthy males. We document a decline in

cartilage T2 relaxation times of the ankle under three different MRI protocols to

achieve a reference standard and generalizability for future clinical studies using T2

mapping. One of our three MRI protocols used a high spatial image resolution,

where we decreased the slice thickness, which may have affected the signal-to-noise

ratio of the image, however this was necessary to obtain an accurate computation of

cartilage T2 relaxation times [Watanabe et al., 2007]. At a high image resolution the

ankle edge regions (specifically of the talus) are noted to have increased noise, often

leading to inconsistent results [Shapiro & Gold, 2012]. In this study, we did not find

a statistically significant change in the mean tibia-talus cartilage T2 relaxation times

transitioning between the three protocols. This is important for two reasons. Firstly,

we believe that due to the low signal-to-noise ratio the high resolution protocol ex-

hibits, the tibia-talus cartilage was difficult to clearly distinguish from the tibia and

talus bones. Secondly, the use of a high resolution protocol increases the individual

scan time, which becomes a problem when scanning children, given their inability


of staying still for long durations. Hence, future studies evaluating musculoskeletal

disorders by imaging in children, we expect similar T2 maps to be obtained regard-

less of the protocol used, even if a specific T2 mapping sequence is not available as

a built-in tool for the scanner’s set of programs available for use to help optimize

scanning time. At the same time still obtain the desired results for cartilage T2

relaxation times of the ankle.

Furthermore we also found that the BMI of healthy individuals are weakly associ-

ated with cartilage T2 relaxation times. Recent research has shown that individuals

who have a BMI of ≥ 25−<30 kg/m2 (i.e. overweight) are strongly associated with

MRI-detected knee cartilage damage [Keng et al., 2017]. Specifically the authors

note that overweight individuals are three times likely to damage their cartilage, in

comparison to those individuals with a normal BMI [Keng et al., 2017]. While we

did not find a similar strength in correlation between BMI and cartilage T2 relax-

ation times in comparison to previous studies, however we also note that 64% of our

population cohort had a normal BMI, as a result we believe a larger sample size is

needed to clearly document this association.

The primary limitation of this research lies in its small sample size since this

work was undertaken as a pilot study. In addition, no information was obtained

concerning the amount of physical activity individual achieved on a day-to-day ba-

sis. Past research has noted that individuals who are involved in rigorous physical

activity demonstrated a 6-20% reduction in cartilage volume, altering their tibia-

talus cartilage T2 relaxation time [Welsch et al., 2014; Nag et al., 2004]. Some of

the image slices under the high resolution protocol were distorted, since a few indi-

viduals slightly moved their ankle during the scan, which may have caused slightly

inaccurate computations for cartilage T2 relaxation times conducted under the high

resolution protocol.

Chapter 4

Conclusions and Future Directions

79

Chapter 4. Conclusions and Future Directions 80

4.1 Study #1 - T2 Mapping of Children and Ado-

lescents with Hemophilic Arthropathy

Despite efforts of clinical research for hemophilia, evaluating internal cartilage de-

rangement has been difficult. This first study was conducted as a cross-sectional

clinical investigation to understand early cartilage degeneration in hemophilic chil-

dren and adolescents. In Canada, nearly all persons with severe hemophilia are on

prophylaxis, usually initiated before their second year of birth [Carcao et al., 2012].

For persons with hemophilia the initiation of prophylaxis at an early age can prolong

severe arthropathy and cartilage degeneration [Carcao, 2012]. While prophylaxis

helps decrease the frequency and severity of bleeds in persons with hemophilia, it

does not prevent all bleeds [Simpson & Valentino, 2012; Feldman et al., 2018]. Over

time, small bleeding events could result in early cartilage degeneration through iron-

mediated synovitis [Nieuwenhuizen et al., 2014].

To our knowledge this is the first cross-sectional study that documents the use

of T2 mapping to understand early hemophilic arthropathy in children and adoles-

cents. The primary finding of this study suggests that age plays an important role

to understand the decline of T2 relaxation times in ankle and knee cartilage for male

children and adolescents with hemophilia A. We believe that as persons with severe

hemophilia age, the thickness of their cartilage decreases, due to the loss of water

content in the ankle and knee over time, noted through a decline of cartilage T2

relaxation times.

Using the IPSG MRI scores, we found weak correlations with cartilage T2 relax-

ation times for the ankle and knee. Past research noted that the IPSG MRI scoring

system has known limitations in its incapability to differentiate severe joint damage

and arthropathy in the ankle [Hong et al., 2016]. Also, IPSG MRI scores are based

on an anatomical MRI scoring system, and do not have a MRI based T2 mapping

component., thus we suggest that IPSG MRI scores should not be used to understand

changes to the cartilage. In a manuscript (Appendix A) the evaluative purpose of

the IPSG anatomical scale and its respective development and validation processes

were discussed. We also critically appraise the validity, reliability and responsiveness


of using the IPSG scale for evaluation of hemophilic arthropathy in different clinical

and research settings, and whenever applicable, compare these clinimetric properties

of the IPSG scale with those of its precursors, the compatible additive and progres-

sive MRI scales.

Although this is a proposed association from a cross-sectional study, future longi-

tudinal studies are needed to verify this association. Persons with hemophilia in this

study were scanned during 2013/2014, hence it has now been five years. A future

study should involve rescanning these children and adolescents with the same MRI

protocol and compute their cartilage T2 relaxation times again. This can provide in-

sights on the rate at which cartilage follows children and adolescents with hemophilia

after a five year period.

While our study incorporated majority of persons with severe hemophilia A, how-

ever the degree of severity is not the same in developed versus developing nations.

For example, these persons with hemophilia are part of the Canadian Prophylaxis

Study, hence to obtain a larger sample size of severe hemophilia A patients and to

understand the full onset of hemophilic arthropathy in children and adolescent with

high rates of hemarthrosis, a longitudinal study in a developing nation would be ideal.

At the same time, future studies should look to construct a MRI scoring system

based on T2 mapping. Overall there exists numerous other factors that can impact

children and adolescents with severe hemophilia. As mentioned in Chapter 1, factors

such as patient’s genetics, bleeding history, socioeconomic status, and levels of phys-

ical activity can all have an effect, either directly or indirectly on the cartilage. Over

time, combining clinical, social, and environmental information about the patient can

be incorporated into a prediction model to fully understand hemophilic arthropathy

and possibly early cartilage degeneration. This will allow clinicians to understand

the unfavourable outcomes of persons with hemophilia, monitoring disease progres-

sion, and treatment selection. Therefore only by incorporating multiple factors we

will be able to understand early cartilage degeneration in children and adolescents

with hemophilic arthropathy and possibly other types of pediatric arthropathies.


4.2 Study #2 - Characterization of T2 Mapping

in Healthy Children and Adolescents

One of the challenges when imaging children is their impatience and lack of resistance

to stay still for long durations. For conducting T2 mapping on healthy children and

adolescents, there is a need to achieve generalizability and reduce scan time. In this

cross-sectional study, the cartilage T2 relaxation times of ankles in healthy males

were documented using three different MRI protocols. We also characterize and un-

derstand the association between age and cartilage T2 relaxation times.

There were a few main findings from this study. Our primary finding results in a

negative association between age and cartilage T2 relaxation time, suggesting that

age plays a statistically significant role in understanding the loss of water, implying

early cartilage degeneration. Furthermore, we recommend clinicians to use the con-

stant TE/TR MRI protocol to help reduce scan time for children, and still obtain

suitable results for cartilage T2 relaxation times in the ankle.

Also, other aspects part of the social determinants of health can influence early

cartilage degeneration in healthy children and adolescents, such as social and envi-

ronmental factors, which could be considered in future studies.

Chapter 5

References

Aledort LM, Aster RH, Bidwell E, Maycock W, Cash J, Davey M, Greenwalt T,Hollan S, Masure R, Nevanlinna H, Shapiro M. International Forum: Can a national allvoluntary blood transfusion service by adequate blood component therapy cover actual andfuture needs of AHF? Vox Sang 1976;31:296-320.

Arnold WD, Hilgartner MW. Hemophilic arthropathy: Current concepts of pathogen-esis and management. Journal of Bone and Joint Surgery 1977;59,287-305.

Asanbaeva A, Tam J, Schumacher BL, Klisch SM, Masuda K, Sah RL. Articular carti-lage tensile integrity: modulation by matrix depletion is maturation-dependent. Archivesof Biochemistry and Biophysics 2008;474:175-182.

Auerswald G, Dolan G, Duffy A, Hermans C, Jimenez-Yuste V, Ljung R, Morfini M,Lambert T, Salek SZ. Pain and pain management in haemophilia. Blood Coagulation andFibrinolysis 2016;27(8):845-854.

Bansal GJ. Digital radiography. A comparison with modern conventional imaging.Postgraduate Medical Journal 2006;82(969):425-428.

Baum T, Joseph GB, Karampinos DC, Jungmann PM, Link TM, Bauer JS. Cartilageand meniscal T2 relaxation time as non-invasive biomarker for knee osteoarthritis and car-tilage repair procedures. Osteoarthritis and Cartilage 2013;21:1474-1484.

Baumann S, Majeed H, Majeed H. A socioeconomic lens on understanding early child-hood linear growth faltering. Lancet Global Health 2018;6(3):e253.

Beeson PB. Jaundice occurring one to four months after transfusion of blood or plasma.JAMA 1943;121:1332-1334.

83

Chapter 5. References 84

Berger A. How does it work?: Magnetic resonance imaging. British Medical Journal2002;324(7328):35.

Berntorp E. History of prophylaxis. Haemophilia 2013;19:163-165.

Berntorp E, Shapiro AD. Modern haemophilia care. Lancet 2012;379(9824):1447-1456.

Bhatnagar N, Hall GW. Major bleeding disorders: diagnosis, classification, manage-ment and recent developments in haemophilia. Archives of Disease in Childhood 2018;103:509-513.

Biggs R, Douglas AS, Macfarlane RG, Dacie JV, Pitney WR, Merskey C, O’Brien Jr.Christmas disease: A condition previously mistaken for haemophilia. British Medical Jour-nal 1952;2(4799):1378-1382.

Blanchette VS, Manco-Johnson M, Santagostino E, Ljung R. Optimizing factor prophy-laxis for the haemophilia population: where do we stand? Haemophilia 2004;10(4):97-104.

Blankenship CS. To manage costs of hemophilia, patients need more than clotting fac-tor. Biotechnology Healthcare 2008;5(4):37-40.

Bolton-Maggs PH, Pasi KJ. Haemophilias A and B. Lancet 2003;361(9371):1801-1809.

Bowen DJ. Haemophilia A and haemophilia B: molecular insights. Molecular Pathol-ogy 2002;55(1):1-18.

Bovenschen N, Rijken DC, Havekes LM, Van Vlijmen BJ, Mertens K. The B domain ofcoagulation factor VIII interacts with the asialoglycoprotein receptor. Journal of Throm-bosis and Haemostasis 2005;3(6):1257-1265.

Broderick CR, Herbert RD, Latimer J, Barnes C, Curtin JA, Mathieu E, MonagleP, Brown SA. Association between physical activity and risk of bleeding in children withhemophilia. JAMA 2012;308(14):1452-1459.

Carcao MD. The diagnosis and management of congenital hemophilia. Seminars inThrombosis and Hemostasis 2012;38(7):727-734.

CDC (U.S. Centers for Disease Control and Prevention). 2018. CDC WONDERdatabase: Compressed mortality file, underlying cause of death. Accessed December 2018.http://wonder.cdc.gov/mortSQL.html.

Cha JG, Yi JS, Han JK, Lee YK. Comparison of quantitative cartilage T2 measure-


ments and qualitative MR imaging between professional ballet dancers and healthy volun-teers. Radiology 2015;276:199-206.

Chen D, Shen J, Zhao W, Wang T, Han L, Hamilton JL, Im HJ. Osteoarthritis: towarda comprehensive understanding of pathological mechanism. Bone Research 2017;5:16044.

Cher WL, Utturkar GM, Spritzer CE, Nunley JA, DeFrate LE, Collins AT. An analysisof changes in in-vivo cartilage thickness of the healthy ankle following dynamic activity.Journal of Biomechanics 2016;49(13):3026-3030.

Coppola A, Franchini M. Target of prophylaxis in severe haemophilia: more than factorlevels. Blood Transfusion 2013;11(3):327-329.

De Kleijn P, Odent T, Berntorp E, Hilliard P, Pasta G, Srivastava A, Iliescu A, Mo-hanty S. Differences between developed and developing countries in paediatric care inhaemophilia. Haemophilia 2012;18:94-100.

Ding C, Cicuttini F, Scott F, Cooley H, Jones G. Association between age and kneestructural change: a cross sectional MRI based study. Annals of the Rheumatic Diseases2005;64:549-555.

Doria AS. State-of-the-art imaging techniques for the evaluation of haemophilic arthropa-thy: present and future. Haemophilia 2010;16:107-114.

Eckstein F, Hudelmaier M, Putz R. The effects of exercise on human articular cartilage.Journal of Anatomy 2006;208(4):491-512.

Eldar-Lissai A, Hou Q, Krishnan S. The changing costs of caring for hemophilia pa-tients in the US: insurers’ and patients’ perspectives. Blood 2014;124:199.

Espinosa M, Gottlieb BS. Juvenile idiopathic arthritis. Pediatrics in Review 2012;33(7):303-313.

Feldman BM, Pai M, Rivard GE, Israels S, Poon M-C, Demers C, et al. Tailoredprophylaxis in severe hemophilia A: interim results from the first 5 years of the Cana-dian Hemophilia Primary Prophylaxis Study. Journal of Thrombosis and Haemostasis2006;4:1228-1236.

Feldman BM, Rivard GE, Babyn P, Wu JK, Steele M, Poon MC, Card RT, Israels SJ,Laferriere N, Gill K, Chan AK. Tailored frequency-escalated primary prophylaxis for severehaemophilia A: results of the 16-year Canadian Hemophilia Prophylaxis Study longitudinalcohort. Lancet Haematology 2018;5(6):e252-260.


Fijnvandraat K, Cnossen MH, Leebeek FW, Peters M. Diagnosis and management ofhaemophilia. British Medical Journal 2012;344(2707):1-5.

Foppen W, van der Schaaf IC, Beek FJ, Verkooijen HM, Fischer K. Scoring haemophilicarthropathy on X-rays: improving inter-and intra-observer reliability and agreement usinga consensus atlas. European Radiology 2016;26(6):1963-1970.

Fox AJ, Bedi A, Rodeo SA. The basic science of articular cartilage. Sports Health2009;1(6):461-468.

Franchini M, Favaloro EJ, Lippi G. Mild hemophilia A. Journal of Thrombosis andHaemostasis 2010;8(3):421-432.

Franchini M, Frattini F, Crestani S, Sissa C, Bonfanti C. Treatment of hemophilia B:focus on recombinant factor IX. Biologics 2013;7:33-38.

Franz T, Hasler EM, Hagg R, Weiler C, Jakob RP, Mainil-Varlet P. In situ compres-sive stiffness, biochemical composition, and structural integrity of articular cartilage of thehuman knee joint. Osteoarthritis and Cartilage 2001;9(6):582-592.

Gitschier J, Wood WI, Goralka TM, Wion KL, Chen EY, Eaton DH, Vehar GA, CaponDJ, Lawn RM. Characterization of the human factor VIII gene. Nature 1984;312(5992):326-330.

Goel R, Chappidi MR, Patel EU, Ness PM, Cushing MM, Frank SM, Tobian AA.Trends in red blood cell, plasma, and platelet transfusions in the United States, 1993-2014.JAMA 2018;319(8):825-827.

Gringeri A, Ewenstein B, Reininger A. The burden of bleeding in haemophilia: is onebleed too many? Haemophilia 2014;20(4):459-463.

Gunderman RB. Essential radiology. Clinical presentation, pathophysiology, imaging.2nd Edition, 2006.

Hay J. Account of a remarkable haemorrhagic disposition, existing in many individualsof the same family. New England Journal of Medicine and Surgery 1813;2(3):221-5.

Heemstra HE, Zwaan T, Hemels M, Feldman BM, Blanchette V, Kern M, EinarsonTR. Cost of severe haemophilia in Toronto. Haemophilia 2005;11(3):254-260.

Herring JA. Pediatric Orthopaedics. Saunders/Elsevier; 2008.

Hofstraat SH, Falla AM, Duffell EF, Hahne SJ, Amato-Gauci AJ, Veldhuijzen IK,


Tavoschi L. Current prevalence of chronic hepatitis B and C virus infection in the generalpopulation, blood donors and pregnant women in the EU/EEA: a systematic review. Epi-demiology and Infection 2017;145(14):2873-2885.

Hong W, Raunig D, Lundin B. SPINART study: validation of the extended mag-netic resonance imaging scale for evaluation of joint status in adult patients with severehaemophilia A using baseline data. Haemophilia 2016;22(6):e519-526.

Huang JN, Koerper MA. Factor V deficiency: a concise review. Haemophilia 2008;14(6):1164-1169.

Ingram GI. The history of haemophilia. Journal of Clinical Pathology 1976;29(6):469-479.

Joseph GB, McCulloch CE, Nevitt MC, Heilmeier U, Nardo L, Lynch JA, et al. Areference database of cartilage 3 Tesla MRI T2 values in knees without diagnostic evidenceof cartilage degeneration: Data from the osteoarthritis initiative. Osteoarthritis and Car-tilage 2015;23:897-905.

Jung BA, Weigel M. Spin echo magnetic resonance imaging. Journal of Magnetic Res-onance Imaging 2013;37(4):805-817.

Katti G, Ara SA, Shireen A. Magnetic resonance imaging (MRI)-A review. Interna-tional Journal of Dental Clinics 2011;3(1):65-70.

Keng A, Sayre EC, Guermazi A, Nicolaou S, Esdaile JM, Thorne A, et al. Associa-tion of body mass index with knee cartilage damage in an asymptomatic population-basedstudy. BMC Musculoskeletal Disorders 2017;18.

Kim HK, Shiraj S, Anton CG, Horn PS, Dardzinski BJ. Age and sex dependency ofcartilage T2 relaxation time mapping in MRI of children and adolescents. American Jour-nal of Roentgenology 2014;202(3):626-632.

Kotecha, M., Klatt, D., Magin, R.L. Monitoring cartilage tissue engineering using mag-netic resonance spectroscopy, imaging, and elastography. Tissue Engineering 2013;19:470-484.

Lee CA. The best of times, the worst of times: a story of haemophilia. Clinical Medicine2009;9(5):453-458.

Lenting PJ, van Mourik JA, Mertens K. The life cycle of coagulation factor VIII inview of its structure and function. Blood 1998;92(11):3983-3996.


Leslie R, Catherine M. Modern management of haemophilic arthropathy. British Jour-nal of Haematology 2007;136(6):777-787.

Lim Y, Cha JG, Yi J, Kang SJ, Lee YK, Lee SJ, et al. Topographical and sex variationsin the T2 relaxation times of articular cartilage in the ankle joints of healthy young adultsusing 3.0T MRI. Journal of Magnetic Resonance Imaging 2016;43:455-462.

Lin E, Alessio A. What are the basic concepts of temporal, contrast, and spatial reso-lution in cardiac CT? Journal of Cardiovascular Computed Tomography 2009;3(6):403-408.

Lobet S, Hermans C, Lambert C. Optimal management of hemophilic arthropathy andhematomas. Journal of Blood Medicine 2014;5:207-218.

Lundin B, Babyn P, Doria AS, et al. Compatible scales for progressive and additiveMRI assessments of haemophilic arthropathy. Haemophilia 2005;11:109-115.

Lundin B, Manco-Johnson ML, Ignas DM, Moineddin R, Blanchette VS, Dunn AL,et al. An MRI scale for assessment of haemophilic arthropathy from the InternationalProphylaxis Study Group. Haemophilia 2012;18:962-970.

Maartens G, Celum C, Lewin SR. HIV infection: epidemiology, pathogenesis, treat-ment, and prevention. Lancet 2014;384(9939):258-271.

Maier CF, Tan SG, Hariharan H, Potter HG. T2 quantitation of articular cartilage at1.5 T. Journal of Magnetic Resonance Imaging 2003;17:358-364.

Majeed H, Moore GW. Impact of multidecadal climate variability on United Kingdomrickets rates. Nature-Scientific Reports 2017;7(1):15764.

Melchiorre D, Manetti M, Matucci-Cerinic M. Pathophysiology of hemophilic arthropa-thy. Journal of Clinical Medicine 2017;6(7):63.

Manco-Johnson MJ, Abshire TC, Shapiro AD, Riske B, Hacker MR, Kilcoyne R, In-gram JD, Manco-Johnson ML, Funk S, Jacobson L, Valentino LA. Prophylaxis versusepisodic treatment to prevent joint disease in boys with severe hemophilia. New EnglandJournal of Medicine 2007;357(6):535-544.

Matino D, Teitel J, Page D, Keepanasseril A, Iorio A, Walker I. The haemophilia cer-tification system in Canada. Blood Transfusion 2014;12(3):e531-541.

Matzat SJ, van Tiel J, Gold GE, Oei EH. Quantitative MRI techniques of cartilagecomposition. Quantitative Imaging in Medicine and Surgery 2013;3(3):162-174.


Moreno-Otero R. Abulcasis, the father of modern surgery. Medical Archives. 2013;67(2):151.

Mosher TJ, Liu Y, Torok CM. Functional cartilage MRI T2 mapping: Evaluating theeffect of age and training on knee cartilage response to running. Osteoarthritis and Carti-lage 2010;18(3):358-364.

Nag D, Liney GP, Gillespie P, Sherman KP. Quantification of T(2) relaxation changesin articular cartilage with in situ mechanical loading of the knee. Journal of MagneticResonance Imaging 2004;19(3):317-322.

Nathwani AC, Reiss UM, Tuddenham EG, Rosales C, Chowdary P, McIntosh J, DellaPeruta M, Lheriteau E, Patel N, Raj D, Riddell A. Long-term safety and efficacy of factorIX gene therapy in hemophilia B. New England Journal of Medicine 2014;371(21):1994-2004.

Nassa M, Anand P, Jain A, Chhabra A, Jaiswal A, Malhotra U, Rani V. Analysis ofhuman collagen sequences. Bioinformation 2012;8(1):26-33.

Ng WH, Chu WC, Shing MK, Lam WW, Chik KW, Li CK, Li CK, Ling SC. Roleof imaging in management of hemophilic patients. American Journal of Roentgenology2005;184(5):1619-1623.

Nieuwenhuizen L, Roosendaal G, Mastbergen SC, Coeleveld K, Biesma DH, Lafeber FP,Schutgens RE. Deferasirox limits cartilage damage following haemarthrosis in haemophilicmice. Thrombosis and Haemostasis 2014;112(5):1044-1050.

O’Hara J, Hughes D, Camp C, Burke T, Carroll L, Diego DA. The cost of severehaemophilia in Europe: the CHESS study. Orphanet Journal of Rare Diseases 2017;12(1):106.

Oldenburg J. Optimal treatment strategies for hemophilia: achievements and limita-tions of current prophylactic regimens. Blood 2015;125:2038-2044.

Panych LP, Madore B. The physics of MRI safety. Journal of Magnetic ResonanceImaging 2018;47(1):28-43.

Pettersson H, Ahlberg A, Nilsson IM. A radiologic classification of hemophilic arthropa-thy. Clinical Orthopaedics and Related Research 1980;149:153-159.

Plug I, Mauser-Bunschoten EP, Brcker-Vriends AH, van Amstel HK, van der Bom JG,van Diemen-Homan JE, Willemse J, Rosendaal FR. Bleeding in carriers of hemophilia.Blood 2006;108(1):52-56.

Pradsgaard Do, Spannow AH, Heuck C, Herlin T. Decreased cartilage thickness in juve-


nile idiopathic arthritis assessed by ultrasonography. Journal of Rheumatology 2013;40(9):1596-1603.

Prentice A, Schoenmakers I, Laskey MA, de Bono S, Ginty F, Goldberg GR. Sympo-sium on ‘Nutrition and health in children and adolescents’ Session 1: Nutrition in growthand development Nutrition and bone growth and development. Proceedings of the Nutri-tion Society 2006;65(4):348-360.

Rocha P, Carvalho M, Lopes M, Araujo F. Costs and utilization of treatment in pa-tients with hemophilia. BMC Health Services Research 2015;15(1):484.

Ronken S, Arnold MP, Garca HA, Jeger A, Daniels AU, Wirz D. A comparison ofhealthy human and swine articular cartilage dynamic indentation mechanics. Biomechan-ics and Modeling in Mechanobiology 2012;11(5):631-639.

Rosen HR. Chronic hepatitis C infection. New England Journal of Medicine 2011;364(25):2429-2438.

Ross C. A comparison of osteoarthritis and rheumatoid arthritis: diagnosis and treat-ment. Nurse Practitioner 1997;22(9):20-23.

Roughley PJ, White RJ. Age-related changes in the structure of the proteoglycan sub-units from human articular cartilage. Journal of Biological Chemistry 1980;255(1):217-224.

Schmaier A.H., Lazarus, H.M. (2011). Concise guide to hematology. Sussex, UK: Wiley.

Schramm W. The history of haemophilia-a short review. Thrombosis Research 2014;134:S4-9.

Shepherd D, Seedhom B. Thickness of human articular cartilage in joints of the lowerlimb. Annals of the Rheumatic Diseases 1999;58(1):27-34.

Shapiro LM, Gold GE. MRI of weight-bearing and movement. Osteoarthritis and Car-tilage 2012;20(2):69-78.

Simpson ML, Valentino LA. Management of joint bleeding in hemophilia. Expert Re-view of Hematology 2012;5(4):459-468.

Spannow AH, Pfeiffer-Jensen M, Andersen NT, Herlin T, Stenbg E. Ultrasonographicmeasurements of joint cartilage thickness in healthy children: age- and sex-related stan-dard reference values. Journal of Rheumatology 2010;37(12):2595-2601.

Stonebraker JS, BoltonMaggs PH, Michael Soucie J, Walker I, Brooker M. A study


of variations in the reported haemophilia A prevalence around the world. Haemophilia2010;16(1):20-32.

Stonebraker JS, BoltonMaggs PH, Michael Soucie J, Walker I, Brooker M. A studyof variations in the reported haemophilia B prevalence around the world. Haemophilia2011;18(3):e91-94.

Stringhini S, Carmeli C, Jokela M, Avendao M, Muennig P, Guida F, Ricceri F, d’ErricoA, Barros H, Bochud M, Chadeau-Hyam M. Socioeconomic status and the 25 x 25 riskfactors as determinants of premature mortality: a multicohort study and meta-analysis of1.7 million men and women. Lancet 2017;389(10075):1229-1237.

Sussman MS, Vidarsson L, Pauly JM, Cheng H-LM. A technique for rapid single-echospin-echo T2 mapping. Magnetic Resonance in Medicine 2010;64(2):536-545.

Thapa MM, Iyer RS, Khanna PC, Chew FS. MRI of Pediatric Patients: Part 1, Normaland abnormal cartilage. American Journal of Roentgenology 2012;198:W450-455.

Twilt M, Pradsgaard D, Spannow AH, Horlyck A, Heuck C, Herlin T. Joint cartilagethickness and automated determination of bone age and bone health in juvenile idiopathicarthritis. Pediatric Rheumatology 2017;15(1):63.

Bloodinduced joint disease: the pathophysiology of hemophilic arthropathy. Journal ofThrombosis and Haemostasis 2010;8(9):1895-1902.

Watanabe A, Boesch C, Siebenrock K, Obata T, Anderson SE. T2 mapping of hiparticular cartilage in healthy volunteers at 3T: a study of topographic variation. Journalof Magnetic Resonance Imaging 2007;26(1):165-171.

Welsch GH, Hennig FF, Krinner S, Trattnig S. T2 and T2* Mapping. Current Radiol-ogy Reports 2014;2:60.

WHF. Report on the annual global survey. World Federation of Hemophilia, 2017.

Xia Y. Magic-angle effect in magnetic resonance imaging of articular cartilage: a re-view. Investigative Radiology 2000;35(10):602-621.

Zonfrillo MR, Seiden JA, House EM, Shapiro ED, Dubrow R, Baker MD, et al. Theassociation of overweight and ankle injuries in children. Ambulatory Pediatrics Association2008;8:66-69.

Chapter 6

Appendix A: Critical AppraisalManuscript

Critical Appraisal of the International Prophylaxis Study Group Mag-

netic Resonance Image Scale for Evaluating Hemophilic Arthropathy

Abstract

The International Prophylaxis Study Group (IPSG) MRI scale has the goal of be-

ing an accurate instrument to measure MRI-based disease severity at various time

points, so that longitudinal changes in disease severity can be identified to support

decisions on treatment management. We discuss in this paper the evaluative purpose

of the IPSG MRI scale and its respective development and validation processes. We

also critically appraise the validity, reliability and responsiveness of using the IPSG

MRI scale for evaluation of hemophilic arthropathy in different clinical and research

settings, and whenever applicable, compare these clinimetric properties of the IPSG

MRI scale with those of its precursors, the compatible additive and progressive MRI

scales.

Introduction

Bleeding into joint spaces (i.e. hemarthrosis) is a common symptom of persons

with hemophilia. Repeated hemarthrosis leads to joint degradation and hemophilic

arthropathy (HA). The goal of treating patients with hemophilia with prophylaxis

92

Chapter 6. Appendix A: Critical Appraisal Manuscript 93

through factor replacement therapy is to decrease the frequency of joint bleeds and

ultimately limit end organ damage. It has demonstrated its effectiveness in obser-

vational and randomized controlled trials [1-3]. However, in longitudinal studies,

validated and responsive clinical indices are needed to monitor patient disease status

and treatment effectiveness. Hence, a measure of early-stage HA is needed to guide

decisions in hemophilia treatment options.

The decision to start, alter, or terminate prophylactic factor replacement ther-

apy relies on a variety of measurements, including physical assessment of the joints,

pharmacokinetics parameters, as well as diagnostic imaging techniques, such as mag-

netic resonance imaging (MRI). MRI remains the most accurate available diagnostic

standard for assessing early-stage arthropathies [4-7], hence the outcome measures in

this context concern mostly with MRI assessment for assessment of disease severity

in hemophilic joints.

Since 2002, an imaging expert group within the International Prophylaxis Study

Group (IPSG) has overseen the iterative development of a single MRI scale [6,7]

combining the item definitions and measurement criteria from two previous scales,

the Denver [8] and European [9] MRI scales. Whereas the Denver MRI scoring sys-

tem [8] is a progressive scale, with the most severe item score determining the overall

domain score, the European MRI scale is additive, producing a combined score from

individual scores of multiple items [9]. Initially these two MRI systems were modified

into the “compatible additive and progressive IPSG MRI scale” [10]. In the devel-

opment of the compatible MRI scales [10] the IPSG committee had first achieved

consensus on the definition of the constructs, specifying its scope to MRI-based HA.

The item generation and selection of items were therefore optimized to efficiently

and completely capture of significant constructs. The compatible indices were then

modified and merged into a single IPSG scale which additively scored ordinal and

categorical-level items separated into soft tissue and osteochondral domains, respec-

tively. After a detailed process of development and testing, the latest version of the

IPSG scale was published in 2012 [7] (Appendix B), tailored for scoring early MRI

findings of HA.


The IPSG MRI scale is intended to measure MRI-based disease severity at vari-

ous time points, so that longitudinal changes in disease severity can be identified to

support decisions on treatment management. Therefore, among the three primary

purposes for outcome measures as per Kirschner and Guyatt’s [11] definition, which

are evaluative, discriminative and predictive, we will discuss in this paper the evalu-

ative purpose of the IPSG MRI scale and its respective development and validation

processes. Now that previous clinical trials [12-14] and surveys [15,16] have applied

to the IPSG MRI scale and assessed its cross-sectional value it becomes crucial that

the purposes of the IPSG MRI scale for assessment of both cross-sectional and longi-

tudinal changes of HA be discussed. In this paper we critically appraise the validity,

reliability and responsiveness of using the IPSG MRI scale for evaluation of HA in

different clinical and research settings, and whenever applicable, compare with the

compatible additive and progressive MRI scales which were its precursors.

Face Validity

Face validity is an initial qualitative assessment of whether the instrument is suit-

able and effective in measuring the construct it purports to measure. The IPSG

scale has items organized in two domains; soft tissue and osteochondral. Segregating

the soft tissue items from osteochondral items better reflects the pathophysiology of

HA, as these two types of changes may follow different natural histories. The soft

tissue items, especially joint effusion and synovial hypertrophy are often reversible,

whereas the osteochondral domain items generally follow a degenerative path [4].

The two groups of items also respond differently to treatments, hence differenti-

ating the domains allows more specific response estimates in assessing treatment

effectiveness. One advantage is seen with scoring the item “Effusion/hemarthrosis”

separately from “Hemosiderin”. As more blood leaks into the joint spaces turning

into additional amounts of hemosiderin over time, the IPSG and compatible progres-

sive MRI scales would be able to give higher scores for the progression of disease

severity (from 1 to 2, 1 to 3 or 2 to 3), whereas with the compatible additive MRI

scale only presence or absence of hemosiderin would be recorded.

It should also be noted that for identifying treatment effects, scoring the items

separately in an additive fashion is better suited to the evaluative measurement pur-


pose. The maximum score in the IPSG (i.e. 17 score per joint) corresponds to

changes to a joint that represent all stages of pathology, which characterizes a joint

with the high level of active disease (i.e. hemarthrosis, synovial hypertrophy) in

addition to previously existing joint destruction (i.e. large amount of hemosiderin

deposition, extensive surface erosions, subchondral cysts and cartilage degradation).

In a joint with established osteochondral damage, the previous progressive scale score

would not respond to presence of new active disease features. Although the previous

compatible additive scale has a maximum total score of 20, items related to active

disease features are de-emphasized (4/20 total score) compared to the IPSG MRI

scale (9/17 total). In practice however, these theoretical advantages may be min-

imal. A recent cross-sectional study found that all three MRI scales were able to

show difference in ankle and knee joints’ outcomes between administration of factor

prophylaxis and on-demand treatment in groups of patients with hemophilia aged

12 to 35 years at the time of group assignment (data reported, but not shown in the

paper) [17].

The composition of the IPSG MRI scale is consistent with the understanding that

joint degeneration generally follows a linear progression, starting from hemarthrosis

leading to hemosiderin deposition in the joint, and from smaller to larger bone ero-

sions and/or subchondral cysts progressively involving a larger extent of the articular

surface, as it occurs with joint cartilage loss [18]. According to the IPSG MRI scale,

the process of degeneration of soft tissue and osteochondral tissues is independent.

Theoretically, the scoring allows one patient joint to demonstrate only osteochondral

findings at a given joint, without associated soft tissue changes, or show only soft tis-

sue changes without associated osteochondral changes. Nevertheless, these scenarios

are rare, since hemosiderin deposition indicating previous hemarthrosis typically is

present when osteochondral changes are apparent.

The grade scaling for the soft tissue items of the IPSG MRI scale is based on

ordinal-level grading, whereas the osteochondral items are scored additively for all

binary criteria achieved for each item. For example, if one joint demonstrates diffuse

partial cartilage loss and focal full-thickness cartilage loss in less than half of the joint

surface in at least one bone it receives 3 scores in total for the cartilage degradation


item: 1 score for the “full-thickness loss in at least some area” criterion, 1 score for

“any loss of joint cartilage height” and 1 score for “loss of half or more of the total

volume of joint cartilage in at least one bone”. Nevertheless, there are important

formal issues in the specification of some ordinally graded items. Unlike other items

in the osteochondral domain, subchondral cysts can receive its upper-tier grade (e.g.

subchondral cysts in at least two bones, or cystic changes involving a third or more

of the articular surface in at least one bone) simply by being present in multiple

bones, regardless of how small the cyst is in each bone. Furthermore, this upper-tier

grade of subchondral cysts combines two different types of measurement criteria,

one concerning the number of bones involved (which is not used in any of the other

items of the scale) and one concerning the horizontal extent of involvement of cystic

changes. Consequently, a joint that presents with cystic changes involving a third

of more of the articular surface in one bone receives the same score as another joint

that presents with subchondral cysts in less than one third of the articular surface

in two bones (Fig. 25). A ceiling effect problem arises when both these criteria

are met, for example, if a patient’s joint progresses from presenting a small (<1/3)

extent of involvement of the articular cartilage in two bones to a larger (≥1/3) ex-

tent of involvement of the articular cartilage over time, the IPSG MRI scale cannot

respond to this change. However one could argue that this ceiling effect would not

alter medical management of this joint.

Similar ceiling effect also exists for surface erosions (Fig. 26) and cartilage degra-

dation (Fig. 27), in which the number of bones affected is not reflected in the

score scaling. For example, it may be possible to encounter a joint which shows full

thickness cartilage loss or erosive changes with <50% of involvement of the artic-

ular surface in multiple bones. This joint would receive the same score as another

joint with similar changes observed in only one bone, since there is no clause “one

or more bones” in the grading definition of these two items and therefore, the scale

does not allow differentiation of these two cases. Furthermore, a joint that presents

with <50% involvement in multiple bones would receive a lower score than another

joint that presented with ≥50% involvement in two bones of a given joint. The cur-

rent grading criteria is hence limited to clinical and research scenarios in which all


Figure 24 Unique subitem of the IPSG MRI scale on upper-tier grade for presenceof subchondral cysts in two bones. Two patients: (a) Coronal gradient-recalled echo(GRE) MR image of the right ankle of a 15-year-old boy with hemophilia type Ashows subchondral cysts in ≥1/3 of the articular surface of the dome of the talus(arrows). (b) Sagittal fat saturated T2-weighted image of the left ankle of a 17 year-old boy with hemophilia type A shows subchondral cysts in the articular surfaces ofthe lower end of the tibia and the dome of the talus (arrows). A joint that presentswith cystic changes involving ≥1/3 of the articular surface in one bone receives thesame score as another joint that presents with subchondral cysts in less than onethird of the articular surface in two bones.

bones in the joint degrade at simultaneous rates, which may not always occur. To

complicate the matter, changes in different bones of the joint may have different lev-

els of importance, which could require further “weighting” specification in the future.

The recently published extended MRI (eMRI) scale [19], which is based on the

IPSG MRI scale, improves upon these ceiling effects inherent in the IPSG MRI scale

by splitting the combined criteria of subchondral cysts, and grading all the osteo-

chondral items in each of the three pre-specified bones in the target joints. The


Figure 25 Ceiling effect of the IPSG MR scale for scoring bone erosions. Twopatients: (a) Coronal high resolution water-excitation gradient-recalled echo (GRE)MR image of the left ankle of a 17 year-old boy with hemophilia A. Bone erosions(arrows) are noted in distal tibia and dome of the talus representing any surfaceerosions (score of 1). (b) Coronal GRE MR image of the right ankle of a 10 year-oldboy with hemophilia type A shows bone erosions in the dome of the talus only whichalso represent any surface erosion (score of 1). Bone erosions in one bone score thesame as bone erosions in multiple bones in IPSG MR scale.

eMRI scale includes 45 total scores for each of up to 6 joints (bilateral elbows, knees,

and ankles) for assessment of late stage joint changes in adults with hemophilia A,

and has started its validation process in the SPINART study. This eMRI scale con-

tains the same 6 items as the IPSG MRI scale. Its major difference is the inclusion

of higher number of osteochondral grades, specifically one extra grade for subchon-

dral cysts, and 3 extra for cartilage degeneration. Compared with the IPSG MRI

scale the eMRI scale has superior face validity at the cost of additional osteochondral

grading criteria, which increases the duration for interpretation of MRI examinations.


Figure 26 Ceiling effect of the IPSG MR scale for scoring cartilage degradation.(a) Sagittal gradient-recalled echo MR image of the right ankle of a 16 year-old boywith hemophilia type A shows full-thickness cartilage loss over the dome of the talus(arrow). (b) Sagittal fat saturated T2- weighted MR image of the right ankle of a13 year-old boy with hemophilia type A shows full-thickness cartilage loss (arrows)anteriorly over in distal tibia and the dome of the talus. Both cases score the sameas per the IPSG MR scale.

Clarity and Ease of Use

The use of image interpretation guidelines is improved by clear, unambiguous defini-

tions and accompanying imaging atlases to represent the various definitions, grades,

and measurement criteria. The IPSG MRI scale is considered easier to use and less

complicated than the original compatible MRI scale by experienced musculoskeletal

radiologists. The compatible indices contained many subdivisions for the osteochon-

dral items (Appendix B). Nevertheless, an imaging atlas for HA which is currently

in final stages of review, would be helpful to standardize the understanding and use


of the grading criteria.

The cutoffs of the soft tissue items of the IPSG MRI scale have a subjective

interpretation without the utilization of an atlas. Further, it can also be especially

difficult to assess the loss of volume in cartilage degradation, as required for one

of the four grades achievable for this item. Although the ≥50% volume loss grade

is intended to capture non-focal pattern of cartilage loss, it may be subjective to

estimate differences between ≥50% volume loss grade is in at least one bone which

yields 1 score if present and full-thickness loss grade cartilage in at least one bone

which also yields 1 score if present. For use in adolescent boys with typically thinner

cartilage [20] it may also be challenging to discriminate less than and ≥50% volume

loss (Fig. 28).

Content Validity

Content validity is the assessment of whether the outcome measure captures all facets

of the intended construct [21]. Important content validity issues were addressed from

the original compatible scoring systems. Effusion/hemarthrosis and the hemosiderin

items were included in the new IPSG scale but was not present in the previous

additive scale (Appendix B). Given the fact that hemarthrosis is considered the

ethiopathogenic factor responsible for joint degeneration in HA it makes sense to

grade it over time in the evaluation of joints of patients with hemophilia. Within

the soft tissue domain of the IPSG MRI scale, both hemarthrosis and hemosiderin

are given equal weight as synovial hypertrophy. Note should be made, however, that

upon presence of moderate to large amounts of hemosiderin deposition in the joint

hemosiderin deposition may obscure visualization of synovial hypertrophy (Fig. 29),

this reducing the content validity of the IPSG MRI scale for the synovial hypertrophy

item.

Most of the items (except hemarthrosis and hemosiderin), but especially joint

effusion [13], are not specific to hemophilic change, but also occur in other forms

of arthritis or arthropathies. However, since these items are the commonly known


Figure 27 Difficulties for discriminate between loss of half or more (≥50%) of totalcartilage volume and full-thickness cartilage loss in a 15 year old boy with severehemophilia A and a history of 61 previous bleeds into the right ankle. Sagittal fatsaturated T2-weighted MR image of the patient’s right tibiotalar joint demonstratesa central area of total loss of cartilage on the talar dome [small arrow] which receivesa score of 3 for cartilage degradation according to the IPSG MRI scale. The scoreof 3 represents 1 score for “any loss of joint cartilage height”, 1 score for “loss of≥50%” of the total volume of joint cartilage in at least one bone and 1 score for the“full-thickness loss in at least some area” criterion.

consequences of the hemophilia-specific changes in patients with hemophilia, these

items were considered valid components of the disease definition by the time of the

conception of the IPSG MRI scale. Patients that have the relevant comorbidities

involving their joints would need to be identified and excluded in clinical or research

scenarios where hemophilia-specific treatments are assessed, since these other comor-

bidities can confound and underestimate treatment effect. Furthermore, by giving

the hemophilia-specific effusion/hemarthrosis item a greater weight within the soft

tissue domain in comparison to the additive compatible scale (which would give a


Figure 28 Reduction of content validity of the IPSG synovial hypertrophy item dueto gradient echo susceptibility artifacts in a 13 year-old boy with severe hemophiliaA and a history of 16 previous bleeds into the right ankle. Ultrasound images ofthe patient’s right ankle joint, posterior recess (a, b), with corresponding sagittalproton-density (c) and MERGE gradient-recalled echo (d) MRI images demonstratesynovial hypertrophy [small arrows in a, b, c]. Blooming artifact from hemosiderindeposit; (d) concealed the hypertrophied synovium hemosiderin deposit.

maximum score of 1 for hemosiderin if present in the joint), the IPSG MRI scale

provides greater content (and face) validity for the intended construct.

Item Weighing

The IPSG MRI scale is considered a formative scale, in which the construct being

measured is defined or caused by its indicator items, not vice versa, as in what are


called reflective scales [21]. Item weighing in the IPSG MRI scoring system is im-

plied by the number of grades or scores each item contains. It is important to test

the appropriateness of the current weighing structure, at least at the face validity

level. Potentially it could be tested in a group consensus setting by assessing the

scale score-derived rank ordering of a set of patient vignettes that show a variety

of combinations of items, spanning both spectra of scores. Another important issue

relevant to formative scales is item (indicator) collinearity (or inter-item dependence)

[21], which still remains to be investigated for the IPSG scale. When some items

of a given scale are correlated to a great extent, not only does it indicate potential

overweighing of the scored feature, but also impairs the use of multiple regression

methods for identifying the relative weights of items.

Construct Validity

Construct validity is defined as the degree to which the scores from an outcome mea-

sure are consistent with hypotheses based on the assumption that the instrument

validly measures its intended construct [22]. It requires that testable hypotheses

are generated based on the scale’s expected convergence or divergence with other

outcome measures, or the change in its scores across groups expected or known to

be different. As the IPSG MRI scale is a formative measure limited in its scope to

MRI-observable definition of HA disease severity, its relationship with other clinical

outcome measures cannot serve as a basis for its validation Nevertheless, it is still

useful to test how closely the MRI-based HA severity as defined by the IPSG scale

relates to other formative and reflective measures of HA.

A previous study that tested the construct validity of the IPSG MRI scale showed

that the number of lifetime joint bleeds correlated poorly to substantially with MRI

measures [7]. This is likely due to the excellent sensitivity of MRI in detecting early

stage blood degradation products compared to other imaging modalities such as X-

ray (Fig. 30). Additionally, patients may under report hemarthroses, particularly

episodes of micro bleeding. Furthermore, other clinical measures are inadequate for

fully assessing the anatomic changes. While ultrasound is also able to differentiate

synovium from joint effusion, allowing it to detect early changes, its limited tissue

penetrance allows only the visualization of the periphery of joints, which is greatly


detrimental in large joints. Secondly, the technique is highly dependent on the tech-

nical skills of the operator [23]. Whereas moderate to substantial correlations were

noted between X-rays (Pettersson scores) and the osteochondral domain of the IPSG

MRI system (Fig. 30), poor correlations were noted between X-ray scores (which do

not assess soft tissues) and the soft tissue domain of the IPSG scale [7]. It must be

noted that although both soft tissue changes and loss of cartilage can be primary

causes of joint pain and immobility, cartilage cannot be directly visualized on X-rays

by means of narrowing of joint spaces, which decreases the strength of correlations

between X-ray and MRI scores [4].


Figure 29 Construct validity between plain X-ray Pettersson and IPSG MRI scoresfor severe osteochondral changes in a 15 year-old boy with hemophilia A (a, b).Anterior-posterior and lateral X-ray views of the right ankle reveal a Petterssonscore of 8 (c,d). Coronal and sagittal gradient-recalled echo MR images of sameankle of the same patient receives an IPSG MR score of 6 for osteochondral changes.The strong correlation between scores of X-rays and MRI images of the same joint ofthe same patients points out to good construct validity between the two constructsaccording to pre-specified hypotheses.


Influence of Imaging Methods on Scale Reliability

There are non-exclusive sources of variability in imaging-based outcome measures.

Variations in MR imaging parameters can produce substantial variabilities in the

images acquired, especially relative to the narrow grading cutoffs of the IPSG MRI

scale. The hemosiderin item, for example, is more sensitive to small variations in

the TE parameter (echo time, measured in milliseconds) compared to other types

of tissues. This is due to the presence of paramagnetic iron particles contained

within hemosiderin causing susceptibility artifacts in MR images, distorting the im-

age around hemosiderin deposits [24]. Consequently, in MRI scans obtained for

clinical purposes, where the parameters are changed to optimize scanning time and

image quality, there may be variability in the assessment of hemosiderin which be-

comes clinically relevant if changes over time are assessed in the same patients.

Motion artifacts can reduce image quality, adding further measurement variation

between the construct and the scale score. Recommendations on standard image

acquisition parameters that best visualize the items in the scoring system and can

be adjusted to different MRI manufacturer’s aim to minimize variations of data ac-

quisition protocols.

Inter- and Intra-Reader Reliability

Reader interpretation of the scoring system definitions and cutoffs when reviewing

images is a source of measurement error that is typically assessed by asking multiple

readers to assess the same set of images independently of each other, and comparing

the inter-reader agreement. In the primary IPSG scale study [7], the inter-reader re-

liability exercise was conducted with four readers, following a tutorial reading session

to standardize the use of the scale. Although an MRI atlas depicting the various lev-

els of joint changes and grading specifications was available to aid the image reading

it provided information on the Denver MRI scale [8]. Four raters independently rated

the 61 joints from children aged 4-18 years using the IPSG and compatible scales, and

one of them also rated the X-rays of 48 of these joints in a separate setting blinded

to MRIs. The results showed high inter-reader reliability in the IPSG scoring system.

Intra-reader reliability is also an important indicator of the measurement relia-

bility, influenced by various factors related to the instrument comprehensibility and


response shift in the reader. For the IPSG scale, this type of reliability was not tested,

assuming it would be at least equal or higher than inter-reader reliability. The inter-

reader reliability is generally a conservative proxy for intra-reader reliability since if

the reader cannot recall their initial assessment of the image and has absolutely no

degree of consistency in their use of the scale - both of which are unlikely then two

measurements made by the same reader is no different from two measurements done

by different independent readers.

Previous studies on the compatible MRI scales showed high inter and intra-reader

reliability [10,25]. The osteochondral domain of the IPSG scale shows similarly high

reliabilities with the previous additive scale, as both contain mostly similar items.

For the soft tissue domain however, it is difficult to make comparisons and use the

old reliability coefficients as evidence, as the scale composition is dissimilar to both

the previous progressive and additive scales. In the IPSG scale, however, many of

the osteochondral item-levels were collapsed, which should further increase reliabil-

ity, though this is difficult to observe as both scales showed high reliability in Lundin

et al’s study sample [7]. It is important to note that reliability coefficients are also

dependent on the variability in the sample’s disease score distribution [26]. The left

skewed score distribution seen in this study sample (i.e., 53/244 readings received

0/17 score), together with the resulting floor effect, may have overestimated the re-

liability coefficients samples.

Responsiveness Study

Responsiveness is the ability to measure change over time when change is expected

[22] and is used for evaluating the patient’s disease progress or treatment effective-

ness over time. However, longitudinal studies assessing the responsiveness of the new

IPSG MRI scale or its predecessors are yet to be conducted [27].

A prior short-term longitudinal study evaluated 2-year interval changes in joints

of boys with hemophilia on tailored prophylaxis compared with those on standard

prophylaxis in a single-center pilot trial using three-generation MRI scoring system:

IPSG, Compatible and Denver MRI scales [28]. In this study, both the IPSG and the

P-compatible and Denver scales were able to identify both increase and reduction


of synovial scores. Further, the IPSG scale showed superior sensitivity to change

as compared to the other MRI scales concerning interval synovial and hemosiderin

deposition progression which were not depicted by the other MRI scales. Although

more detailed osteochondral information can be obtained from the Compatible A-

scale than with the IPSG MRI scale enabling assessment of minimal interval changes

the first scale is more time consuming for imaging interpretation than the IPSG MRI

scale and lacks content validity for joint effusion/hemarthrosis and hemosiderin items

which limits its use in clinical practice.

Testing the responsiveness of a measure is done by testing the direction and mag-

nitude of its concordance with expected trends in a criterion measure or with other

comparator measures. In longitudinal change data, the construct is measured twice-

once at baseline and then again at follow-up. Therefore, the measurement error in

change data is almost double the measurement error of cross sectional data, save for

some within-patient correlation of error.

In a single study, it is only possible to conclude that either the outcome measure

can detect longitudinal change or the treatment can produce longitudinal change, not

both [29]. If the study shows a null effect for the treatment based on a priori effect

size thresholds, it is impossible to know whether the treatment was ineffective, or if

the scale is not responsive, or both. Conversely, even when a significant treatment

effect is observed using the outcome measure, the measure may still be underesti-

mating or overestimating the change. It will be important to use multiple clinical

measures as external comparative measures to the MRI scale in order to determine

the relative responsiveness of the MRI scale, and not just base the responsiveness on

arbitrary effect size thresholds.

Responsiveness is commonly measured by statistics such as the effect size (ES)

and the standardized response mean (SRM), both of which are ratios of mean change

over some form of measurement variability in the sample. Nevertheless, these metrics

were not used in a previous longitudinal study [28] that evaluated the responsiveness

of the IPSG MRI scale. In the absence of a reference standard comparator to corre-

late changes in the measure under study, assessment of responsiveness can be against


other acceptable concurrent measures administered on the same interval and sam-

ple. Potential comparator measures or indicators in measuring HA include lifetime

number of hemarthrosis events, ultrasound and X-ray findings. Since these other

comparators either measure slightly different constructs or are technically limited

compared to MRI for measuring the same constructs, some discordance is expected.

Generalizability and Translatability

The IPSG MRI scale and its predecessors were designed to be applicable for a variety

of anatomical joints frequently affected by HA, including knees, ankles, and elbows,

hence they contain items that are common to most large joints and could be used to

assess other arthropathies that affect large joints (e.g. juvenile idiopathic arthritis,

except the hemosiderin item would be excluded).

Chan et al.’s systematic review concluded a weak level of evidence that the use

of MRI-directed factor replacement showed better outcomes than on-demand factor

replacement, illustrating the potential clinical impact of MRI [27]. Similarly, impact

analysis studies may be conducted in the future to see if IPSG MRI scale-directed

therapies improve clinical outcomes.

Conclusions

The IPSG MRI scale [7] is a formative scale that provides a consensus- developed

definition of what constitutes MRI-derived HA disease severity and how to mea-

sure it, which conforms to current understanding of disease pathophysiology. It

has shown evidence for equivalency in reliability to previous scales it was derived

from, but with better sensibility. Additionally a limited longitudinal study found

the IPSG MRI scale was able to identify interval increase and reduction of synovial

scores as well as synovial and hemosiderin deposition progression The clinical uptake

of this instrument could be facilitated by efforts to refine the relative weighting of

the indicator items to better reflect their importance in defining the construct, and

studies on the scale responsiveness. Methodological limitations of this scale include

challenges for readers to segmentate thin cartilages of older children and adolescents

into three categories (100% thickness, or reduced at ≥50% or <50%), the use of two

subitems altogether within the single upper-tier grade item of subchondral cysts and


the discrepancy of assessing at least two bones in the subchondral cyst upper-tier

grade item, when all other items of the scale assess at least one bone. Finally, it

would be necessary in the future to assess the scale interpretability, by testing and

refining its capacity to detect the minimum clinically important difference, once such

a difference is defined. Re-visiting the aforementioned limitations of the IPSG MRI

scale according to specific clinimetric properties would improve the diagnostic per-

formance of the scale and would make it a stronger reference standard against which

other measures could be compared in future clinical trials.

Chapter 7

Appendix B: IPSG MRI scale

In this scale, items are measured by radiologists trained in musculoskeletal imaging,

using the clinical Picture Archiving and Communication System (PACS) worksta-

tion, by visually assessing for the presence and/or severity of the items according to

the definitions and grading criteria presented in this table.

111

Chapter 7. Appendix B: IPSG MRI scale 112

Correspondence of items in the IPSG scale with its predecessor scale, the “com-

patible additive and progressive MRI scales”. Yellow arrows: soft tissue changes, red

arrows: osteochondral changes.


Appendix References

[1] Blanchette VS, Manco-Johnson M, Santagostino E, Ljung R. Optimizing factor prophy-laxis for the haemophilia population: where do we stand? Haemophilia 2004;10:97-104.

[2] Feldman BM, Pai M, Rivard GE, Israels S, Poon M-C, Demers C, et al. Tailored pro-phylaxis in severe hemophilia A: Interim results from the first 5 years of the CanadianHemophilia Primary Prophylaxis Study. J Thromb Haemost 2006;4:1228-1236.

[3] Manco-Johnson MJ, Abshire TC, Shapiro AD, Riske B, Hacker MR, Kilcoyne R, etal. Prophylaxis versus episodic treatment to prevent joint disease in boys with severehemophilia. N Engl J Med 2007;357:535-544.

[4] Kilcoyne RF, Lundin B, Pettersson H. Evolution of the imaging tests in hemophiliawith emphasis on radiography and magnetic resonance imaging. Acta Radiol Stockh Swed1987 2006;47:287-296.

[5] Pergantou H, Matsinos G, Papadopoulos A, Platokouki H, Aronis S. Comparative studyof validity of clinical, X-ray and magnetic resonance imaging scores in evaluation and man-agement of haemophilic arthropathy in children. Haemophilia 2006;12:241-247.

[6] Feldman BM, Funk S, Lundin B, Doria AS, Ljung R, Blanchette V. Musculoskeletalmeasurement tools from the International Prophylaxis Study Group (IPSG). Haemophilia2008;14:162-169.

[7] Lundin B, Manco-Johnson ML, Ignas DM, Moineddin R, Blanchette VS, Dunn AL, etal. An MRI scale for assessment of haemophilic arthropathy from the International Pro-phylaxis Study Group. Haemophilia 2012;18:962-970.

[8] Nuss R, Kilcoyne RF, Geraghty S, Shroyer ALW, Rosky JW, Mawhinney S, et al. MRIfindings in haemophilic joints treated with radiosynoviorthesis with development of an MRIscale of joint damage. Haemophilia 2000;6:162-169.

[9] Lundin B, Pettersson H, Ljung R. A new magnetic resonance imaging scoring methodfor assessment of haemophilic arthropathy. Haemophilia 2004;10:383-389.

[10] Lundin B, Babyn P, Doria AS, Kilcoyne R, Ljung R, Miller S, et al. Compatible scalesfor progressive and additive MRI assessments of haemophilic arthropathy. Haemophilia2005;11:109-115.

[11] Kirshner B, Guyatt G. A methodological framework for assessing health indices.1985;38:27-36.


[12] Brunel T, Lobet S, Deschamps K, Hermans C, Peerlinck K, Vandesande J, et al. Relia-bility and clinical features associated with the IPSG MRI tibiotalar and subtalar joint scoresin children, adolescents and young adults with haemophilia. Haemophilia 2018;24:141-148.

[13] Doria AS, Keshava SN, Mohanta A, Jarrin J, Blanchette V, Srivastava A, et al. Diag-nostic Accuracy of Ultrasound for Assessment of Hemophilic Arthropathy: MRI Correla-tion. Am J Roentgenol 2015;204:336-347.

[14] Foppen W, van der Schaaf IC, Witkamp TD, Fischer K. Is joint effusion on MRI spe-cific for haemophilia? Haemophilia 2014;20:582-586.

[15] Carcao MD, Avila L, Leissinger C, Blanchette VS, Aledort L, the Factor UtilizationExpert Working Group of the International Prophylaxis Study Group (IPSG) and Partic-ipating Survey Investigators. An International Prophylaxis Study Group (IPSG) surveyof prophylaxis in inhibitor positive children/adults with severe haemophilia. Haemophilia2017;23:e444-447.

[16] Carcao MD, Avila L, Leissinger C, Blanchette VS, Aledort L, the Factor UtilizationExpert Working Group of the International Prophylaxis Study Group (IPSG) and partici-pating Survey Investigators. An International Prophylaxis Study Group (IPSG) survey ofprophylaxis in adults with severe haemophilia. Haemophilia 2017;23:e447-450.

[17] Oldenburg J, Zimmermann R, Katsarou O, Theodossiades G, Zanon E, Niemann B,et al. Controlled, cross-sectional MRI evaluation of joint status in severe haemophilia Apatients treated with prophylaxis vs on demand. Haemophilia 2015;21:171-179.

[18] Roosendaal G, Lafeber FP. Pathogenesis of haemophilic arthropathy. Haemophilia2006;12:117-121.

[19] Hong W, Raunig D, Lundin B. SPINART study: validation of the extended mag-netic resonance imaging scale for evaluation of joint status in adult patients with severehaemophilia A using baseline data. Haemophilia 2016;22:e519-526.

[20] Keshava SN, Gibikote SV, Mohanta A, Poonnoose P, Rayner T, Hilliard P, et al. Ultra-sound and magnetic resonance imaging of healthy paediatric ankles and knees: a baselinefor comparison with haemophilic joints. Haemophilia 2015;21:e210-222.

[21] Diamantopoulos A, Winklhofer HM. Index construction with formative indicators: analternative to scale development. J Mark Res 2001;38:269-277.

[22] Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. TheCOSMIN study reached international consensus on taxonomy, terminology, and definitions


of measurement properties for health-related patient-reported outcomes. J Clin Epidemiol2010;63:737-745.

[23] Doria AS. State-of-the-art imaging techniques for the evaluation of haemophilic arthropa-thy: present and future. Haemophilia 2010;16:107-114.

[24] Port JD, Pomper MG. Quantification and minimization of magnetic susceptibility ar-tifacts on GRE images. J Comput Assist Tomogr 2000;24:958-964.

[25] Doria AS, Babyn PS, Lundin B, Kilcoyne RF, Miller S, Rivard GE, et al. Reliabilityand construct validity of the compatible MRI scoring system for evaluation of haemophilicknees and ankles of haemophilic children. Expert MRI working group of the internationalprophylaxis study group. Haemophilia 2006;12:503-513.

[26] Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice.Pearson/Prentice Hall; 2009.

[27] Chan MW, Leckie A, Xavier F, Uleryk E, Tadros S, Blanchette V, et al. A system-atic review of MR imaging as a tool for evaluating haemophilic arthropathy in children.Haemophilia 2013;19:e324-334.

[28] Zhang N, Carcao M, Hilliard P, Babyn PS, Man C, Stain AM, et al. Two-Year Inter-val Imaging Changes on Joint Outcomes of Hemophilic Boys on Secondary Prophylaxis.Proceedings of World Federation of Hemophilia Congress Paris, France; 2012.

[29] Angst F. The new COSMIN guidelines confront traditional concepts of responsiveness.

BMC Med Res Methodol 2011;11:1-6.

understanding early hemophilic arthropathy in children and...

Documents