quantification of carotid plaque volume measurements

8/7/2019 QUANTIFICATION OF CAROTID PLAQUE VOLUME MEASUREMENTS

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doi:10.1016/j.ultrasmedbio.2005.02.011

Original Contribution

QUANTIFICATION OF CAROTID PLAQUE VOLUME MEASUREMENTS

USING 3D ULTRASOUND IMAGING

ANTHONY LANDRY,* J. DAVID SPENCE,* and AARON FENSTER**Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; and Stroke Prevention and

Atherosclerosis Research Centre, Robarts Research Institute, London, Ontario, Canada

(Received 27 July 2004; revised 8 February 2005; in final form 17 February 2005)

AbstractAn accurate and reliable technique used to quantify carotid plaque volume has practical importancein research and patient management. In this study, we develop and investigate a theoretical description of carotidplaque volume measurements made using three-dimensional (3D) ultrasound (US) images and compare it withexperimental results. Multiple observers measured 48 3D US patient images of carotid plaque (13.2 to 544.0 mm 3)by manual planimetry. Coefficients of variation in the measurement of plaque volume were found to decreasewith increasing plaque size for both inter- (90.8 to 3.9%) and intraobserver (70.2 to 3.1%) measurements. Plaquevolume measurement variability was found to increase with interslice distance (ISD), while the relative mea-surement accuracy remained constant for ISDs between 1.0 and 3.0 mm and then decreased. Root-mean-square(RMS) difference between our theoretical description of plaque volume measurement variance and the experi-mental results was 5.7%. Thus, our results support the clinical utility of measuring carotid plaque volume bymanual planimetry noninvasively using 3D US. 2005 World Federation for Ultrasound in Medicine &Biology.

Key Words: 3D ultrasonography, Carotid disease, Plaque volume, Serial manual planimetry, Plaque progression.

INTRODUCTION

Measurement of carotid atherosclerosis burden and pro-

gression is an important tool for research and manage-

ment of patients at risk for stroke. Since many patients

receive nonsurgical treatment, investigations involving

quantification of plaque regression and progression are

expanding (Liapis et al. 2002; Norris et al. 1986;

Schminke et al. 2000; Serena 1999). Measurements of

plaque volume have the potential to be more sensitive to

change than measurements of plaque area (Spence et al.

2002), intima-media thickness (Ebrahim et al. 1999;

Markus et al. 1997; OLeary et al. 1997, Salonen et al.

1993) and carotid stenosis severity, because carotid

plaque progression is not limited to changes in one ortwo directions. Therefore, the quantification of plaque

volume may provide beneficial information to improve

stroke risk management.

Accurate and reproducible measurement techniques

are required to monitor carotid plaque changes. Recent

improvements in ultrasound (US) technology that hold

promise for plaque assessment are compound imaging(Jespersen et al. 1998), which improves the definition of

the plaque surface, and 3-D (3D) US techniques, which

improve visualization and quantification of pathology

(Cardinal 2000; Fenster et al. 2001). 3D US also has the

potential to allow quantitative monitoring of plaque vol-

ume changes, which can provide accurate and reliable

information about plaque response to therapy (Delcker et

al. 1995; Griewing et al. 1997; Hackam et al. 2000;

Liapis et al. 2002; Norris et al. 1986; Schminke et al.

2000; Serena 1999; Steinke 1989).

Previous studies have demonstrated the efficacy of

employing 3D US techniques to measure carotid plaquevolume in vivo and in vitro. Griewing et al. (1997)

measured carotid plaque volumes in a range spanning 53

to 685 mm3. The aggregate intra- and interobserver vari-

abilities in the measurement of plaque volume reported

by Griewing et al. (1997) were 4.16% and 5.87%, re-

spectively (r 0.96; r 0.89). In a series of papers,

Delcker et al. (1994a, 1994b, 1995, 1998) measured

carotid plaque volumes using 3D US and obtained sim-

ilar results for the aggregate intraobserver and interob-

server variabilities in the measurement of plaque volume.

Address correspondence to: Aaron Fenster, Ph.D., Imaging Re-search Laboratories, Robarts Research Institute, P.O. Box 5015, 100Perth Drive, London, Ontario, N6A 5K8, Canada. E-mail:[email protected]

Ultrasound in Med. & Biol., Vol. 31, No. 6, pp. 751762, 2005Copyright 2005 World Federation for Ultrasound in Medicine & Biology

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Furthermore, Palombo et al. (1998) measured carotid

plaque volume ranging from 7 to 450 mm3 and obtained

reliability coefficients close to 1 in this in vivo intraob-

server and interobserver study.

In our previous work, we used 3D US to investigate

the accuracy and variability in the measurement of

plaque volume in vitro by manual planimetry (using testphantoms) as a function of plaque volume (volume

range: 68.2 mm3 to 285.5 mm3) and also developed a

theoretical description to predict plaque volume mea-

surement variability using the measurement technique

(Landry and Fenster 2002). The mean accuracy in plaque

volume measurement was 3.1% 0.9%. Variability in

plaque volume measurement was calculated to be 4.0%

1.0% and 5.1% 1.4% for intra- and interobserver

measurements, respectively. RMS difference between

experimentally and theoretically determined values of

plaque volume fractional variance was 9%.

More recently, we have reported on the observervariability in the measurement of carotid plaque volume

in 40 patients (volume range: 37.43 to 604.1 mm3) and

reported on the variability in the measurement of plaque

volume introduced from repeat 3D US scans (Landry et

al. 2004). Intraobserver and interobserver measurement

reliabilities were 94% and 93.2%, respectively. Plaque

volume measurement variability was found to decrease

with increasing plaque volume (range: 27.1% to 2.2%).

Repeat 3D US scan measurements were not different

from single scan measurements (p 0.867).

In addition to the measurement of plaque volume,

3D US studies have already been undertaken to monitor

the progression and regression of plaque. Hennerici et al.

(1991) performed prospective 3D US examinations of

four flat and 17 soft carotid plaques during an average of

17 months in seven patients with heterozygous hyper-

cholesterolemia during heparin-induced extracorpeal

low-density lipoprotein elimination on precipitation from

plasma. By means of a quantitative 3D US analysis,

Hennerici et al. (1991) measured significant plaque vol-

ume reduction in all 34 subjects, along with a marked

reduction of total and low-density lipoprotein cholesterol

and fibrinogen serum levels. Furthermore, Schminke et

al. (2000) sought to establish an in vivo method for

visualizing structural changes in the carotid plaques in aprospective study involving 32 patients. After a mean of

18.9 months, carotid artery plaque progression had oc-

curred in 15% of carotid artery plaques, with plaque

volume increasing by 59% in these cases, while plaque

volume remained constant in 85% of cases.

Developments of more accurate and reliable meth-

ods to measure plaque volume may improve the capa-

bility of 3D US for use in serial monitoring of patient

response to therapy. In this paper, we extend our previ-

ous theoretical analysis of plaque volume measurement

variability using test phantoms (Landry and Fenster

2002) to an analysis of actual plaques in which the

choice of the interslice thickness contributes significantly

to the total measurement variance. Thus, here we de-

velop and investigate a more complete theoretical de-

scription of plaque volume measurement variability and

analyze the parameters that contribute to the total vari-ance. Using this theoretical description, we explore the

measurement of plaque volume in patients with plaque

volumes ranging from 13.2 to 544.0 mm3 in 48 patient

images acquired by 3D US. Specifically, we investigate

the contribution of observer-defined parameters (plaque

contour variance, initial and final slice location variance

and interslice distance) on the total plaque volume mea-

surement variance. A quantitative theoretical description

of plaque volume measurements is important to under-

stand the nature of the plaque volume measurement

technique. A mathematical analysis of the individual

factors (e.g., operator, image specific, measurement pro-tocol) and the relative contribution of each factor to the

overall measurement variability will provide information

related to the limitations of the technique and guide

improvements.

MATERIALS AND METHODS

Measurement variability of plaque volume

In this section, we derive an expression for the

coefficient of variation (CV) (standard deviation divided

by the mean) for plaque volume measurements made by

manual planimetry using 3D US images.

The volume of a sliced solid can be measured by

multiplying the interslice distance (ISD), a, by the aver-

age cross-sectional area of two sequential slices, k and k

1, where 0 k ka and ka is the total number of slices

in the measurement as constrained by the length of the

solid and the ISD selected. Thus, the incremental volume

of the solid for two sequential slices is given by:

Vka

2AkAk1. (1)

Therefore, the total volume of the sliced solid is

given by:

Va

2 k0

ka1

AkAk1. (2)

where Ak is the area of the kth slice. Assuming that the

measurement of areas in each cross-sectional slice of the

plaques are uncorrelated, the variance of the entire vol-

ume is the sum of the variances in each incremental

volume, such that:

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V2

a2

4 k0

ka1

Ak2 Ak12 (3)

where where Ak is the standard deviation in the area of

the kth slice. Using eqn 18 from Appendix 1, we substi-

tute an expression for the standard deviation in the area

of each slice to obtain:

V2

a2Ac

4 k0

ka1

r,k2 Nb,k2

nk

r,k12 Nb,k12

nk1.(4)

where r,k is the standard deviation in determining the

plaque boundary, Ac is the area of a pixel, nk is thenumber of radial sectors of the kth slice and Nb,k is the

number of border pixels of the kth slice. In our previous

work (Landry and Fenster 2002), we have shown that the

number of radial sectors of the kth slice, nk, and the

standard deviation in determining the plaque boundary of

the kth slice, r,k, are independent of the slice being

investigated. Therefore, eqn 4 may be simplified to:

V2

a2r2Ac

4n k0

ka1

Nb,k2 Nb,k12 (5)

Equation 5 does not take into account the variancein the starting location of the initial slice. It assumes that,

for a repeated measurement of a given plaque volume,

the starting location will be the same. In practice, of

course, this is not the case. The variance in the volume

associated with the starting location of the initial slice,

Vinitial2 , is given by:

Vinitial2

Vz

2

z2Az

2z2. (6)

where Az is the area of the slices as a function of the axial

position along the vessel axis and Z2 is the variance in

the starting location of the initial slice. Therefore, the

variance of the entire plaque volume is given by eqn 7a,

a combination of variances associated with the starting

location (eqn 7b) and measurement of the body of the

plaque volume (eqn 7c):

V2Vinitial

2Vbody

2 (7a)

Vinitial2

Az2z

2 (7b)

Vbody2

a2r

2Ac

4n k0

ka1

Nb,k2 Nb,k12 (7c)

Thus, the coefficient of variance (CV), the standard

deviation divided by the mean, of the plaque volume is

given by:

V

V

Az2z2a2r2Ac4n k0

ka1

Nb,k2 Nb,k12V

(8)

Table 1 is a summary of the parameters in eqn 8. In

subsequent paragraphs of this section, we describe the

methods used to determine the values of these parame-

ters.

Effect of interslice distance

Selection of the ISD, a, will affect the measurement

variability and the plaque volume measured. Using eqn

8, we can determine the effect of ISD on measurement

variability. To investigate the effect of ISD on plaque

volume measurements made with different ISDs, a1 and

a2, we calculate their relative volumes:

Fig. 1. Schematic of longitudinal cross-section of an ideal-ized plaque geometry theoretically to determine the effects ofinterslice distance on plaque volume measurement accuracy

and variability.

Table 1. Parameter summary for eqn 8 used to describe thetheoretical coefficient of variance (CV) for plaque volumemeasurements by manual planimetry using 3D US images

Parameter symbol Description Units

Bodya Inter-slice distance (ISD) mm

Ac Pixel area mm2

r2 Contour boundary variance mm2

Nb(k) Number of border pixels of the kth

contour boundaryn/a

ka Number of boundary contours n/ank Number of radial sectors of the k

thslice

Initial slicez

2 Initial contour location variance mmA(z) Initial contour area mm2

Carotid plaque volume by 3D US A. LANDRY et al. 753


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Va1

Va2

a1k0

ka1

AkAk11

a2k0

ka1

AkAk12

(9)

The relationship between the ISD, a and the mean

number of slices measured for multiple plaque volume

measurements, ka, has been calculated in Appendix 2

using Figure 1.

Subject data

The 3D US carotid plaque images used in the study

were obtained from patients referred to the Premature

Atherosclerosis Clinic and the Stroke Prevention Clinic

at the University Campus of the London Health Sciences

Center, London, Ontario, Canada. Five 3D US scans

were performed of both the left and right carotid arteriesfor each of 48 patients (26 male, 22 female, age 75.2

7.1). Patients were referred to either clinic because of

vascular disease not explained by usual risk factors (e.g.,

age, obesity), a strong family history of vascular disease,

a stroke or transient ischemic attack, or because of

asymptomatic carotid stenosis.

Image acquisition, reconstruction and display

A computer-controlled mechanical 3D US scanning

system was employed for data acquisition (Life Imaging

Systems Inc., London, Ontario, Canada) (Cardinal 2000;

Fenster et al. 2001). To produce 3D US images, the

ultrasound transducer (L12-5, 50 mm, Philips, Bothell,

WA, USA) was translated by the computer-controlled

motor driven mechanism along the neck of a patient for

13 s over an approximate distance of 4.0 cm. While the

transducer was translated, sequential 2D images were

acquired from the US machine (ATL HDI 5000, Philips,

Bothell, WA, USA) with a spatial interval 0.25 mm and

constant transducer angle ( 20). The 3D US images

were immediately reconstructed into a Cartesian data

cube and displayed to verify image quality (Fenster et al.

2001). Figure 2 shows 3D US carotid plaque images

typical of those used in the study.

Plaque selection

The four to five 3D US images obtained from each of

the 48 patients were reviewed and the best 3D US image for

each patient was selected for analysis, providing a total of

48 3D US images. The selection was based on the presence

of image artifacts, shadowing, contrast etc., but no patients

were excluded. Plaques were identified based on visible

changes in vessel surface morphology where the local

thickening of the intimal layer exceeded 1.0 mm (Landry

2004). Plaque geometry, composition, distribution and ar-

terial location (left or right carotid) were not factors con-

sidered for inclusion in this study.

Determination of plaque volume

To determine plaque volume, the 3D US images of

plaque were measured by manual planimetry, a method

Fig. 2. 3D US carotid plaque images. 3D US images are viewedusing a multiplanar reformatting approach. (a) Has been slicedto reveal the plaque in a transverse view; (b) In a longitudinalview; (c) In a coronal view.



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that has been investigated in vitro (Landry and Fenster

2002) and in vivo (Delcker et al. 1994a, 199b; Landry et

al. 2004). Each 3D image was sliced transverse to the

vessel axis, from one edge of the plaque to the other,

using a predetermined ISD. In each cross-sectional im-

age, the plaques contour was traced using a mouse-

driven cross-haired cursor using software developed inour laboratory. As contours were manually outlined, the

visualization software calculated contour area automati-

cally. To calculate the incremental volume, sequential

contour areas were averaged and multiplied by the ISD

(eqn 1). Summation of incremental volumes provided a

measure of carotid plaque volume (eqn 2). After mea-

suring a complete plaque volume, observers viewed the

3D US image in multiple orientations to verify that the

set of measured plaque boundaries matched the entire

plaque volume. Otherwise, the measurement process was

repeated. For a typical plaque having seven to 30 slices,

the entire measurement process required 5 to 8 min.Figure 3 is a sequence of 3D US images that shows the

process of volume determination by manual planimetry.

Measurement protocol

To quantify observer variability in the measurement

of plaque volume, five observers were trained to identify

carotid plaque and to measure plaque volume using 3D

US images. After the observers had been trained, two

studies were performed (Table 2). In the first study, five

observers measured the volume of 48 plaques (range:

13.2 mm3 to 544.0 mm3) five times each in four sessions

using an ISD of 1.0 mm (multiple observer study). We

used an ISD of 1.0 mm for plaque measurement, since

we have shown in our previous work (Landry and Fen-

ster 2002), that the identification of plaque features in the

scanning direction (direction of measurement) had an

associated variability of approximately 1.0 mm. In the

second study, a single observer measured the volume of

five plaques five times each using nine ISDs ranging

from 1.0 to 5.0 mm in 0.5 mm increments (single ob-

server study). The range of plaque volumes measured in

the single observer study (range: 42.2 mm3 to 544.0

mm3) was chosen to span the entire range of volumes

investigated in the multiple observer study for compari-

son. For both studies, the measurement sessions wereconducted under the same conditions, with sessions

scheduled two weeks apart to avoid bias.

Plaque contour variance, r2

To determine the variance in the detection of the

plaque boundary contour of a cross-sectional slice, r2,

we followed a procedure described by Mao et al. (2000)

and Ladak et al. (2000) (Fig. 4). The manually-outlined

contours for each plaque cross-section were superim-

posed and divided into 360 sections, using the center of

gravity of the first contour as the center of the radial

lines. For each of the 360 angles, we measured the

distance to each contour from the center and then calcu-

lated the local variance of the contours in the radial

direction. The mean contour variance was calculated by

averaging the 360 local variances. The contour variances

for each slice of a particular plaque were averaged to

determine the mean variance for the plaque. Both inter-

Fig. 3. 3D US carotid plaque images showing the process ofvolume determination by manual planimtery. (a) 3D US imageof carotid plaque; (b) Manual outlining of a plaques cross-

sectional area; (c) Successive plaque contours shown in alongitudinal view.



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observer and intraobserver mean plaque contour vari-

ances were determined for each plaque in this manner.

Initial and final slice variance, z2

Five observers viewed each of the 48 plaques in

multiple orientations and then measured the initial and

final slice locations. Since the final slice location is

dependent on the ISD, each observer recorded both the

location where they observed the plaque end and the final

slice location as constrained by the ISD selected. Both

the initial and final slice location variances were deter-

mined using the interobserver and intraobserver meanmeasurements for each plaque.

Number of radial sectors, nkThe number of radial sectors, nk, for a contour area

of a measured plaque was determined using the number

of manually-placed points of the particular contour. The

mean number of radial sectors for a particular plaque was

obtained by averaging the number of radial sectors for

each contour.

Number of border pixels, Nb,kThe mean number of border pixels, Nb,k, f o r a

contour area of a measured plaque was determined bymeasuring the perimeter of each plaque slice contour and

dividing by the width of a pixel. The mean number of

border pixels for a particular plaque was obtained by

averaging the number of border pixels for each contour.

Interslice distance, a

We determined the mean offset location, x, (final

slice location mean relative to the final slice location

mean for identification of the plaque edge without the

constraint of an ISD) and the standard deviation in the

location of the final slice, , for each ISD used to

measure plaque volume in the single observer study. Wethen compared our experimental results with a theoreti-

cal description of plaque volume measurement CV (eqn

8) and relative measurement accuracy (eqn 9) by calcu-

lating the RMS difference between theoretical and ex-

perimental results.

RESULTS

Plaque contour variance, r2

Figure 5 shows the standard deviation in the detec-

tion of the plaque boundary, r, as a function of plaque

volume. r ranged from 0.16 to 0.44 mm (mean 0.27

mm) and 0.19 to 0.31 mm (mean 0.25 mm) for

interobserver and intraobserver measurements of plaque

volume, respectively. Linear regression analysis shows

that, regardless of the plaque volume measured, the stan-

dard deviation in the detection of the plaque boundary is

scattered equally about the mean for both interobserver

(r 0.27 mm; r 0.20) and intraobserver (r 0.25

mm; r 0.01) measurements. Therefore, we used the

mean standard deviation in the detection of the plaque

boundary of all 48 plaques measured in our calculations

to determine the theoretical CV.

Fig. 4. Determination of plaque contour variance, r2. (a) Five

contours of a plaque measured in the multiple observer study;(b) Five contours of a plaque measured in the single observerstudy.

Table 2. Summary of the two plaque volume measurement protocols

Plaque volume study Volume range (mm3) Plaques Observers Measurements plaque Interslice distance (mm) Measurements

Multiple observer study 13.2544.0 40 5 5 1.0 1000

Single observer study 42.2544.0 5 1 5/ISD1.0, 1.5, 2.0, 2.5, . . . ,

5.0 225



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Initial and final slice location variance, z2

Figure 6 shows the frequency distributions of the

initial (Fig 6a) and final (Fig. 6b) slice locations about

the mean of all 48 plaque volumes measured in the

multiple observer study. The resulting frequency distri-

butions resemble a Gaussian curve. The standard devia-

tion in the detection of the initial slice location, z,i,

ranged from 0.98 to 1.41 mm (mean 1.24 mm) and

0.88 to 1.29 mm (mean 1.18 mm) for interobserver

and intraobserver measurements of plaque volume, re-

spectively. The standard deviation in the detection of the

final slice location when the observer was not con-

strained by an ISD, z,f, ranged from 0.96 to 1.46 mm

(mean 1.27 mm) and 0.95 to 1.36 mm (mean 1.23

mm) for interobserver and intraobserver measurements

of plaque volume, respectively. Figure 7 shows the stan-

dard deviation in the detection of the initial slice location

as a function of plaque volume. Linear regression anal-

ysis shows that, regardless of the plaque volume mea-

sured, the standard deviation in the location of the initial

slice is scattered equally about the mean for both inter-

observer (z,i 1.22 mm; r 0.55) and intraobserver

(z,i 1.19 mm; r 0.42) measurements. Therefore, we

used the mean standard deviation in the location of the

initial slice of all 48 plaques measured in our calculations

to determine the theoretical CV.

Plaque volume measurement variability

The theoretical CVs (eqn 8) were determined usingthe measurement parameters determined for each plaque

and the global parameter means (e.g., interobserver, r

0.27 mm, z,i 1.24 mm) were used for parameters that

were determined to be plaque-independent.

Figure 8 shows the experimental and theoretical

CVs as a function of plaque volume for the 48 plaques

measured in the multiple observer study for both inter-

observer (Fig. 8a) and intraobserver (Fig. 8b) measure-

ments of plaque volume. For both interobserver and

intraobserver measurements of plaque volume, CV de-

Fig. 5. Standard deviation in the detection of the plaque bound-ary contours, r, as a function of plaque volume for interob-server (diamond) and intraobserver (triangle) measurements ofplaque volume. r does not correlate with plaque volume forinterobserver (r 0.16) or intraobserver (r 0.21)

measurements.

0

10

20

30

40

50

-5 -4 -3 -2 -1 0 1 2 3 4 5

Distance From Mean (mm)

Frequency

Intra-Observer

Inter-Observer

a)

0

10

20

30

40

50

60

70

-5 -4 -3 -2 -1 0 1 2 3 4 5

Distance From Mean (mm)

Frequen

cy

Intra-Observer

Inter-Observer

b)

Fig. 6. Frequency distributions of: (a) Initial slice locations; and(b) Final slice locations about the mean for measurements made

when the observer is not constrained by the ISD.

Fig. 7. Standard deviation in the detection of the initial slicelocation, z, as a function of plaque volume for interobserver(diamond) and intraobserver (triangle) measurements of plaquevolume. z does not correlate with mean plaque volume forinterobserver (r 0.63) or intraobserver (r 0.56)

measurements.



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creases with increasing plaque size, with the interob-

server results decreasing less than the intraobserver CV

values. Figure 8a shows the interobserver CVs as a

function of mean plaque volume (diamond). The exper-

imental values for the interobserver CVs range from 90.8

to 3.9% for plaque volumes of 13.2 to 544.0 mm3,

respectively. Figure 8a also shows the theoretically-de-

termined interobserver CV (eqn 8) as a function of

plaque volume (solid line). Root-mean-square (RMS)

difference between experimental and theoretical results

was 4.2%. Similarly, Fig. 8b shows the intraobserver CVas a function of mean plaque volume (diamond). The

experimental values for the interobserver CVs range

from 70.2 to 3.1% for plaque volumes of 13.2 to 544.0

mm3, respectively. RMS difference between experimen-

tal and theoretical results was 5.7%.

Figure 9 shows the relative contribution of the vari-

ance in the detection of the plaque body (diamond) (eqn

7c) and the variance in the detection of the initial slice

location (triangle) (eqn 7b) to the CV in the measurement

of plaque volume (eqn 8). The relative contribution to the

total variance from the detection of the plaque body

ranges from 0.4 to 27.0%. Therefore, the relative contri-

bution to the total variance from the initial slice location

ranges from 99.6 to 73.1%. The variance in the detection

of the initial slice location dominates the total variance in

the measurement of plaque volume, for all of the plaques

investigated.

Effect of interslice distance

Table 3 shows the standard deviation and the meanoffset in the final slice location for the range of ISDs used

to measure plaque volume in the single observer study.

The standard deviation in the final slice location ranged

from 0.9 to 2.6 mm for ISDs of 1.0 to 5.0 mm, respec-

tively. Mean measurement offset values, x (eqn 10),

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500

Volume (mm3)

CV(%)

a)

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500

Volume (mm3)

CV(%

)

b)

Fig. 8. Interobserver experimental (diamond) and theoretical(solid line) coefficients of variance (CV) in the measurement ofplaque volume as a function of mean plaque volume. The error

bars represent one standard deviation.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 100 200 300 400 500

Volume (mm3)

RelativeContribution

toTotalMeasurement

Var

iance

Fig. 9. The contribution of the variance in the initial slicelocation and the variance in the plaque boundary relative to thetotal plaque volume measurement variance. The variance in themeasurement of plaque volume is dominated by the initial slice

location variance.

Table 3. Standard deviation, z, and mean offset, x, of thefinal contour location for the five plaques measured in the

single observer study using interslice distances (ISD) of 1.0to 5.0 mm. The offset, x, is the position of the mean final

slice location for an ISD relative to the mean final slice

location determine without the constraint of an ISD

a(mm)

z(mm)

x(mm)

1.0 0.9 0.11.5 1.3 0.12.0 1.3 0.22.5 1.3 0.13.0 1.5 0.33.5 1.6 2.14.0 1.6 2.24.5 1.9 3.55.0 2.6 5.1



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ranged from 0.02 to 5.1 mm for ISDs of 1.0 to 5.0 mm,

respectively (positive offset values indicate a measure-

ment position greater than the mean; negative offset

values indicate a measurement position less than the

mean).

Figure 10 shows the mean plaque volume (relative

to the mean value for ISD

1.0 mm from the multipleobserver study) (diamond) and the CV (square) as a

function of ISD for the plaque volumes investigated in

the single observer study. The relative mean plaque

volume ranges from 0.99 to 0.83 for ISDs from 1.0 mm

to 5.0 mm, respectively. Relative mean plaque volume

was approximately constant up to an ISD of 3.0 mm and

then reduced to 0.83 for an ISD of 5.0 mm. CV increased

with increasing plaque volume and ranged from 9.2 to

13.5% for ISDs of 1.0 to 5.0 mm, respectively. Figure 10

also shows the theoretical values for the CV (dotted line)

and the relative mean plaque volume (solid line), as

determined using eqn 8 and eqn 9 respectively. RMSdifference between experimental and theoretical mea-

surements of CV was 5.7%.

DISCUSSION

The large range of plaque volumes measured in this

study allows a comparison of our results with literature

data. In a series of papers, Delcker et al. (1994a, 1994b,

1995, 1999) measured carotid plaque volume in the 2 to

200 mm3 range. (Palombo et al. (1998) measured carotid

plaque volumes ranging from 7 to 450 mm3. Our study

differs from these previous studies, that use 3D US to

measure plaque volume, in that their papers report on the

mean variability over the entire range investigated, while

we have explored the variability in the measurement of

plaque volume as a function of plaque volume. Figure 8

shows that, as the volume of plaque increases, the CV in

the measurement of plaque volume decreases. Thus,

analysis of plaque volume measurement variability and

comparisons between studies should consider the plaque

volume being measured. Furthermore, we have devel-

oped a theoretical description of plaque volume measure-

ment variability to compare with our experimental re-

sults. This analysis allowed us to investigate areas of

improvement in the technique.The relationship between the CV in the measure-

ment of plaque volume as a function of plaque volume

has particular importance in the monitoring of disease

progression or regression. From Figure 8, we can deter-

mine the minimum percentage change in plaque volume

that must be observed to conclude with statistical confi-

dence (95%) that a plaque has undergone volumetric

change. For example, a plaque measured to have a vol-

ume of 200 mm3 in an initial measurement must undergo

a minimum volumetric change of approximately 28%

V

z2 SEM; z

1.96,

0.05, SEM

stan-dard error in measurement) to conclude in a follow-up

measurement, made by the same observer, that the

plaque has actually changed volume and that differences

in the measured volume are not a result of observer

variability.

Figure 9 shows that the variance in the total plaque

volume measurement is dominated by the variance in the

initial slice location. Therefore, methods to improve the

measurement technique should focus on reducing the

variance associated with the identification of the plaque

edges (i.e., the initial and final slice location). Strategies

to improve initial slice location variance might involve

viewing the plaque along the vessel axis (longitudinal),

isolating the initial and final slices of the plaque without

an ISD constraint and then subdividing the plaque length

into equal segments. Another strategy might involve

measuring the plaque volume contained within a speci-

fied distance from the bifurcation.

The mean plaque contour variance, r2, is depen-

dent on a number of factors. Foremost, r2 will vary

depending on the image quality of the reconstructed 3D

US images. Image artifacts such as dropouts and shad-

owing, which are present due to attenuation, increase the

variability in the measurement of plaque contours and

may obstruct the view of the plaque altogether. Addi-tionally, the geometry, echogenicity and abnormalities of

each plaque will influence the variability in the detection

of the plaque contour. We have determined that, for the

plaques investigated in this study, the plaque contour

variability was not dependent on plaque volume. This

result is consistent with our previous work (Landry and

Fenster, 2002), in which we determined the mean stan-

dard deviation in the slice boundary detection to be 0.15

mm for plaque phantoms of a similar range in volume.

Therefore, in our theoretical analysis, we assumed that

Fig. 10. Relative mean plaque volume as a function of ISD forthe five plaques measured in the single observer study. Exper-imental (diamond) and theoretical (solid line) plaque volumemeasurement coefficients of variance (CV) as a function of

ISD.



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the plaque contour variability is a global measurement

parameter, since individual plaque contour variability did

not vary from plaque to plaque.

Image quality, the resolution of the 3D image in the

3D scanning direction, the distribution of plaque within

the vessel and our definition of plaque (intimal thicken-

ing 1.0 mm) are all factors that will contribute to theinitial and final slice location variance, z

2. Without the

constraint of an ISD, initial and final slice locations yield

comparable standard deviations. Furthermore, we have

determined that the variance in the initial and final slice

locations is not dependent on plaque volume. Therefore,

in our theoretical analysis, we assumed that the plaque

initial slice location variability is a global measurement

parameter, since individual initial slice location variabil-

ity did not vary from plaque to plaque.

The final slice location variance is subject to con-

straint depending on the ISD chosen for the plaque

volume measurement and the length of the plaque inves-tigated. Figure 10 shows that the relative mean volume

remains relatively constant up to 3.0 mm and then re-

duces to 0.83 for an ISD of 5.0 mm. Figure 10 also shows

that, regardless of the ISD used, the variability of the

final slice location increases with ISD. The decrease in

the relative plaque volume measured can be explained by

Table 3, which shows that the mean offset remains close

to 0 for ISDs less than 3.0 mm and then increases for

ISDs greater than 3.0 mm. Thus, our measurement tech-

nique systematically underestimates plaque volume for

ISDs greater than 3.0 mm, since the final edge of the

plaque is not included as an additional incrementalplaque volume.

Regardless of the plaque volume investigated, de-

creasing the ISD would have the effect of decreasing the

measurement variability. Decreasing the ISD, however,

would result in a more tedious and time-consuming mea-

surement process. Furthermore, the standard deviation in

the detection of the initial slice was approximately 1.0

mm for both interobserver and intraobserver measure-

ments of plaque volume. Thus, the inability of the ob-

servers to distinguish plaque features less than 1.0 mm in

the 3D scanning direction promotes the use of an ISD

equal to the inherent observer variability in the directionof measurement. The measurement process could be

simplified, however, by implementing algorithms for au-

tomated or semiautomated segmentation of plaque vol-

ume (Zahalka and Fenster, 2001).

In our previous in vitro work, we have shown that

repeat 3D US acquisitions do not increase the variability

in the measurement of plaque volume for scans of equal

image quality (Landry et al. 2004). While every effort

was made to select the best 3D US images from each

patient, patient respiration, swallowing and cardiac mo-

tion during image acquisition did reduce the quality

some of the images available for analysis.

Every effort was made to maintain a consistent

measurement protocol among observers. However, there

may have been variability introduced by the identifica-

tion of the plaque itself. We defined plaque as a measur-

able change in the vessel surface morphology where theintimal thickening exceeds 1.0 mm. This definition

proved to be useful but did not overcome all of the

plaque identification problems encountered. In some

cases, it was difficult to determine the extent of the

plaque in the vessel wall. Plaque identification at the

carotid bifurcation and in areas of poor image resolution

or in shadow also created some difficulty in plaque

identification. While the observers in this study were

trained to follow the same measurement techniques, dif-

ferences in plaque outlining strategies were still ob-

served.

SUMMARY

Multiple observers measured 48 3D US patient im-

ages of carotid plaque (13.2 to 544.0 mm3) by manual

planimetry. Coefficients of variation in the measurement

of plaque volume were found to decrease with increasing

plaque size for both inter- (90.8 to 3.9%) and intraob-

server (70.2 to 3.1%) measurements. Plaque volume

measurement variability was found to increase with in-

terslice distance, while the relative measurement accu-

racy remained constant for interslice distances between

1.0 and 3.0 mm and then decreased. We have developeda theoretical description of plaque volume measurements

that describes manual planimetric measurement of ca-

rotid plaque volume. Correlation with significant mea-

surement parameters suggests that the measurement

technique is a viable tool to measure carotid plaque

volume noninvasively using 3D US.

AcknowledgmentsThe authors wish to thank Craig Ainsworth andChris Blake for their work on the technical aspects of this project. Thiswork has been supported by the Canadian Institutes for Health Re-search, The Ontario R&D Challenge Fund and The Natural Sciencesand Engineering Research Council of Canada. The third author holds aCanada Research Chair and acknowledges The Canada Research Chair

Program.

REFERENCES

Cardinal HN, Gill JD, Fenster A. Analysis of geometrical distortion andstatistical variance in length, area and volume in a linearly scanned3D ultrasound image. IEEE Trans Med Imaging 2000;19:63251.

Delcker A, Diener HC. 3D Ultrasound Measurement of AtheroscleroticPlaque Volume in Carotid Arteries. Bildebung 1994;61(2):116121.

Delcker A, Diener HC. Quantification of atherosclerotic plaque incarotid arteries by three-dimensional ultrasound. Br. J. Radiol. 199467(799):672678.



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APPENDIX 2

To determine the relationship between the ISD, a, and the aver-age length of the plaque measured, za, for multiple plaque measure-ments we consider the variability in the detection of the plaque end.Figure 1 is a schematic diagram of the longitudinal cross-section ofplaque having idealized geometry. In our previous work (Landry andFenster 2002) and also in the current paper (Fig. 6), we have shown thatthe frequency distribution of the final slice location, P(z), about themean final slice location, zf, for identification of the plaque end withoutthe constraint of an ISD resembled a Gaussian distribution. Therefore,we assume that the probability that an observer will make a measure-ment beyond a slice location, z, that will turn out to be the last orsecond last slice follows the probability distribution given by (assketched in Fig. 1):

P(z)1

2e(zzf)2

22;zfzezzfze

0 ;zfzez

(20)

where is the standard deviation about the mean slice location, zf, foridentification of the plaque end without the constraint of an ISD and z

is a position such that when P(z) threshold, the observer will decide

that no plaque is seen in the image. For simplicity, we assume that this

threshold 0.05. Thus, for repeated measurements, the slice that is thefinal slice or the next to final slice is given by z

zf 1.65 (i.e.,

P(z) 0.05). From position z, there are two possibilities for the

location of the final slice position. If z a zf z (beyond theplaque end), the probability that an observer will identify plaque at alocation z a, P(z a) is zero. Therefore, the location of the finalslice measurement is za z. If zf z z a zf z (within theplaque end), the probability that an observer will identify plaque at a

location z

a, P(z

a), is given by eqn 20. Thus, the mean locationof the final slice measurement, za, for a given ISD, a, is approximatedby the sum of probability that final slice location is at z and theprobability that the final slice location is at z a:

zaz1 P(z a) z aP(z a) (21a)

zaz aP(za). (21b)

The relationship between the ISD, a and the mean number ofslices used for multiple measurements of the same plaque, ka (see eqn1) is then given by the largest integer less than za/a.

ka int(zaa) int(za)Pzaz

(1Pza)

a . (22)


quantification of carotid plaque volume measurements

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