hippocampus als mri

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Subcortical structures in amyotrophic lateral sclerosis

Henk-Jan Westeneng a Esther Verstraete a Reneacutee Walhout a Ruben Schmidt a Jeroen Hendrikse b Jan H Veldink a Martijn P van den Heuvel c1Leonard H van den Berg a1

a Department of Neurology Brain Center Rudolf Magnus University Medical Center Utrecht Utrecht The Netherlandsb Department of Radiology Brain Center Rudolf Magnus University Medical Center Utrecht Utrecht The Netherlandsc Department of Psychiatry Brain Center Rudolf Magnus University Medical Center Utrecht Utrecht The Netherlands

a r t i c l e i n f o

Article history

Received 12 June 2014

Received in revised form 14 August 2014

Accepted 1 September 2014

Available online 6 September 2014

Keywords

Amyotrophic lateral sclerosis

Magnetic resonance imaging

Longitudinal

Basal ganglia

Hippocampal sub1047297elds

a b s t r a c t

The aim of this study was to assess the involvement of deep gray matter hippocampal sub1047297elds and

ventricular changes in patients with amyotrophic lateral sclerosis (ALS) A total of 112 ALS patients and

60 healthy subjects participated High-resolution T1-weighted images were acquired using a 3T MRI

scanner Thirty-nine patients underwent a follow-up scan Volumetric and shape analyses of subcortical

structures were performed measures were correlated with clinical parameters and longitudinal changes

were assessed At baseline reduced hippocampal volumes (left p frac14 0007 right p frac14 0011) and larger

inferior lateral ventricles (left p frac14 0013 right p frac14 0041) were found in patients compared to healthy

controls Longitudinal analyses demonstrated a signi1047297cant decrease in volume of the right cornu

ammonis 23 and 4dentate gyrus and left presubiculum ( p frac14 0002 p frac14 0045 p lt 0001) and a sig-

ni1047297cant increase in the ventricular volume in the lateral (left p lt 0001 right p lt 0001) 3rd ( p lt 0001)

and 4th ( p frac14 0001) ventricles Larger ventricles were associated with a lower ALSFRS-R score ( p frac14 0021)

In conclusion ALS patients show signs of neurodegeneration of subcortical structures and ventricular

enlargement Subcortical involvement is progressive and correlates with clinical parameters highlighting

its role in the neurodegenerative process in ALS 2015 Elsevier Inc All rights reserved

1 Introduction

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative dis-

ease characterized by progressive upper and lower motor neuron

degeneration (Kiernan et al 2011) Although progressive motor

neuron degeneration is the hallmark feature of ALS widespread

extramotor brain involvement can be found as well ( Agosta et al

2007 Verstraete et al 2014) It has been shown that ALS affects a

subnetwork in the brain including white matter connections with

subcortical structures such as the thalamus caudate nucleus pu-

tamen globus pallidus and hippocampus (Verstraete et al 2014)

These 1047297ndings may suggest involvement of these structures in the

underlying neurodegenerative process in ALS

Magnetic resonance imaging (MRI) is a noninvasive sensitive

method allowing in vivo study of volume changes of structures

within the brain Most neuroimaging studies have focused on the

cortical surface and white matter changes aiming to capture

upper motor neuron degeneration (Foerster et al 2013 Turner

et al 2012) Postmortem studies have however shown promi-

nent involvement of subcortical structures in ALS (Brettschneider

et al 2013 Geser et al 2008 Takeda et al 2009 ) In addition

studies using positron emission tomographyecomputed tomog-

raphy (PET-CT) single-photon emission computed tomography

(SPECT) magnetic resonance spectroscopy and diffusion tensor

imaging have also shown involvement of deep gray matter (DGM

thalamus caudatus putamen pallidum hippocampus amygdala

accumbens) but morphometric changes have been reported

sporadically (Sach et al 2004 Turner et al 2004 Verstraete

et al 2014) Currently there is only 1 cross-sectional study that

has reported a more detailed morphometric analysis of the DGM

in ALS (Bede et al 2013) This cross-sectional study in 39 ALS

patients showed reduced volumes of the left caudate left hip-

pocampus and right accumbens in ALS underscoring the rele-

vance of the subcortical structures in the disease process

Although in the classical conception the hippocampus is a

structure of the cortex (3-layered cortex not neocortex) one may

also refer to it as a subcortical structure because it is located under

the cortex

Corresponding author at Department of Neurology G03228 University Med-

ical Center Utrecht PO Box 85500 3508 GA Utrecht The Netherlands Tel thorn3188

7557939 fax thorn31 30 2542100

E-mail address LHvandenBergumcutrechtnl (LH van den Berg)1 Authors contributed equally

Contents lists available at ScienceDirect

Neurobiology of Aging

j o u r n a l h o m e p a g e w w w e l s e v i e r c o m l o ca t e n e u a g i n g

0197-4580$ e see front matter 2015 Elsevier Inc All rights reserved

httpdxdoiorg101016jneurobiolaging201409002

Neurobiology of Aging 36 (2015) 1075e1082



Longitudinal analyses are important for the understanding of

patterns of disease progression and might result in the discovery of

a more speci1047297c marker that can be used to monitor disease pro-

gression in ALS Longitudinal neuroimaging studies may be an

important tool to assess cerebral neurodegeneration in detail in a

noninvasive way For example hippocampal atrophy has been re-

ported in ALS but also in other neurological and psychiatric diseases

(Bede et al 2013 Thompson et al 2004) Longitudinal analyses in

combination with a more detailed analysis of the hippocampus(hippocampal sub1047297eld segmentations) might shed more light on

when the hippocampus becomes involved and which sub1047297elds in

particular may be affected

We therefore studied volumes of ventricles and DGM (including

hippocampal sub1047297elds) cross-sectionally and longitudinally in a

large group of patients with ALS and correlated our 1047297ndings with

clinical characteristics

2 Methods

21 Participants

All 172 participating subjects were recruited from the outpatient

clinic for motor neuron diseases of the University Medical CenterUtrecht in The Netherlands Patients were classi1047297ed as having

de1047297nite probable or possible ALS using the revised El Escorial

criteria after excluding other conditions (Brooks et al 2000) Sub-

jects with a history of brain injury epilepsy psychiatric illness

other neurodegenerative disease (including frontotemporal lobe

dementia) or structural brain disease were excluded The median

time between the 1047297rst and second MRI scan was 55 months

Written informed consent was obtained from all participants in

accordance with the Declaration of Helsinki

22 Clinical parameters

Clinical characteristics including handedness disease duration

and survival were recorded Functional status was evaluated usingthe revised ALS Functional Rating Scale (ALSFRS-R) (Cedarbaum

et al 1999) The disease progression rate was calculated using the

formula (48 ALSFRS-R score)disease duration (in months) Dis-

ease duration was evaluated from symptom onset

23 Data acquisition

A 3T Philips Achieve Medical Scanner was used to acquire a

high-resolution T1-weighted image Acquisition parameters were

as follows 3-dimensional fast 1047297eld echo (FFE) using parallel im-

aging TRTE frac14 1046 ms 1047298ip angel 8 slice orientation sagittal

075 075 08 mm (045 mm3) voxel size 1047297eld of view (FOV) frac14

160 240 240 mm (9216 dm3) and reconstruction matrix frac14

200 320 320 covering the whole brain Acquisition time was11 minutes The high-resolution MRI scans for scienti1047297c research

were combined with a standard MRI examination and these scans

were reviewed by an experienced neuroradiologist In the case of

structural abnormalities made scans were excluded

24 Data processing

Two groups of analyses were performed cross-sectional and

longitudinal Both analyses focused on volumes of ventricles DGM

and hippocampal sub1047297elds

For the cross-sectional analysis subcortical volumes were

automatically segmented and measured by FreeSurfer version 51

(Fischl et al 2002 2004) In addition hippocampal sub1047297elds were

automatically segmented and measured using a FreeSurfer

subroutine (Van Leemput et al 2009) In this article we have

focused on cornu ammonis 1 (CA1) CA23 CA4dentate gyrus (CA4

DG) subiculum and presubiculum Fimbria and hippocampal

1047297ssure were disregarded because these are the smallest sub1047297elds

and segmentation is less reliable (Van Leemput et al 2009)

To detect subtle regional volumechanges of DGM we performed

a shape analysis of DGM (thalamus putamen caudate nucleus

nucleus accumbens and hippocampus) previously reported to be

altered in ALS (Agosta et al 2009 Bede et al 2013 Chang et al2005 Thivard et al 2007) The shape of the above-mentioned

DGM (except the hippocampus the sub1047297elds of which were stud-

ied) was analyzed using the FSLs FIRST module version 500

(Patenaude et al 2011) This vertex-based shape analysis was cor-

rected for multiple testing using permutation tests with 10000

permutations of cluster mass

The longitudinal analysis was performed using FreeSurfer which

creates an unbiased within-subject template space and image using

robust inverse consistent registration (Reuter and Fischl 2011

Reuter et al 2010) Several processing steps such as skull strip-

ping Talairach transforms atlas registration as well as spherical

surface maps and parcellations are then initialized using common

information from the within-subject template This analysis method

has been validated and shown to signi1047297cantly increase reliability andstatistical power (Reuter et al 2012)

25 Statistical analysis

251 Cross-sectional analyses

ManneWhitney U and Fisher exact tests were used to compare

demographic and clinical data Cross-sectional volume differences

were compared between ALS and healthy controls using an analysis

of covariance (ANCOVA) All of these analyses were adjusted for age

and gender Because of possible non-normality we applied per-

mutation tests with 10000 permutations according to participant

groups

252 Relationship between imaging and clinical characteristicsThe relationship between cross-sectional clinical data and

volumes in ALS patients was assessed using a combination of an

ANCOVA and principal component analysis (PCA) PCA is a

method that is used to describe a large group of variables by a

smaller group of principal components (PCs) each consisting of a

number of interrelated variables Of all subcortical structures (n frac14

20) 3 PCs were retained (Supplementary Fig 1) These PCs were

linearly regressed using clinical data (using ANCOVA) to assess the

relationship between clinical data and volumes (represented by

PCs) thereby adjusting for age and gender This method was used

because it takes advantage of the underlying correlation of

different subcortical structures (eg the ventricles are actually

part of 1 system see also Supplementary Fig 1) and increase both

power and robustness by grouping variables that share commonfeatures (in PCs) reducing the number of comparisons and

minimizing possible effects of multicollinearity The relationship

between the PCs of the subcortical structures and survival was

studied using univariate and multivariate Cox proportional haz-

ards models Known independent predictors of survival (age at

onset and bulbar onset) were included in the multivariate anal-

ysis Gender was not statistically signi1047297cantly associated with

survival and was therefore excluded from the multivariate sur-

vival analysis

253 Longitudinal analyses

A linear mixed-effects model (LME) was used to assess the rate

of change of subcortical volumes in ALS patients over time while

accounting for random between-subject variation (Bernal-Rusiel

H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821076



et al 2012) Age and gender were included as covariates in this

analysis

Alltestswere 2-tailedand p-valueslt005 were considered to be

statistically signi1047297cant A false discovery rate (FDR) correction formultiple testing was performed Data was reported as mean

standard error of volume in mm3 (unless otherwise speci1047297ed)

Statistical analyses were performed using the software program R

(httpcranr-projectorg )

3 Results

31 Clinical characteristics

A total of 112 ALS patients and 60 healthy controls were enrolled in

this study (Table 1) Patients and controls were well matched for age

( p frac14 0414) gender ( p frac14 1000) and handedness ( p frac14 0648) The

median ALSFRS-R score was relatively high (41) because of the rela-

tively short median disease duration (142 months Supplementary

Fig 3 for distribution of the disease duration) Seven (63) ALS pa-

tients carried the C9orf72 repeat expansion and 77 (688) ALS pa-

tients died Although there was a trend for longer disease duration in

familial ALS patients (median [range] 2116 [5e75]) compared to

sporadic patients (1314 [4e59]) this was not statistically signi1047297cant

( p frac14 0057)

32 Cross-sectional analysis

The outcomes of the volumetric analysis of the DGM ventricles

and hippocampal sub1047297elds are shown in Table 2 Intracranial vol-

umes in ALS patients and healthy subjects were similar ( p frac14 0672)

The cross-sectional analysis revealed that patients with ALS

compared to healthy controls had the following 1) signi1047297cantly

lower hippocampal volumes (left 195 71 mm3 p frac14 0007

right173 67mm3 p frac14 0011) 2) larger inferior lateral ventricles

(left 18676 mm3 pfrac14 0013 right 114 56mm3 pfrac14 0041) and

3) a smaller left presubiculum (29 11 mm3 p frac14 0009) Trends

for volume differences were found for the right presubiculum ( p frac14

0052) and for the subiculum (left p frac14 0091 right p frac14 0062) The

volume of CA1 was similar in patients and healthy controls We

additionally studied the relationship between age and hippocampalvolume as shown in Supplementary Fig 2 This 1047297gure shows that

the hippocampal volume is smaller in ALS patients compared with

healthy subjects irrespective of age

In addition the shape of the thalamus putamen and caudate

nucleus and nucleus accumbens was analyzed As shown in Fig 1 1

cluster of regional volume change was found in both thalami (left

p frac14 0008 right pfrac140026) Based on anatomical knowledge this

cluster would appear to be located at the point where the intra-

medullary lamina (IML) enters and exits the thalamus (Zarei et al

2010) The shape analysis of the putamen caudate nucleus and

nucleus accumbens did not reveal differences between ALS patients

and healthy controls Comparison of sporadic versus familial ALS

patients did not reveal any statistically signi1047297cant differences

Table 1

Demographic and clinical characteristics of study subjectsa

ALS patients Healthy

controls

Baseline

(n frac14 112)

Follow-up

(n frac14 39)

Baseline

(n frac14 60)

Age 604 (24e78) 599 (24e78)b 604 (29e76)

Gender (malefemale) 8626 309 4614

Handedness (leftright)c 1886 532 744ALSFRS-R score 41 (29e48) 36 (25e46)

Site of onset ()

Bulbar 24 (21) 3 (8)

Cervical 55 (49) 24 (62)

Lumbosacral 33 (30) 12 (31)

Disease progression rate

(points decreasemonth)d05 (026)e 06 (05 to 3)f

El Escorial criteria ()

De1047297nite 13 (12) 4 (10)b

Probable 48 (43) 19 (49)b

Probable laboratory

supported

35 (31) 10 (26)b

Possible 16 (14) 6 (15)b

Disease duration (months) 142 (4e75) 185 (10e82)

Type (sporadicfamilial ALS) 1057 372

C9orf repeat expansion 7112 539

Died 77112 2339 060

Key ALSFRS-R revised ALS Functional Rating Scalea Values are in median (range) unless otherwise speci1047297edb At baselinec Missing data for ALS patients (n frac14 8) follow-up ALS patients (n frac14 2) healthy

controls (n frac14 9)d Points decrease are points decrease on the ALSFRS-R scoree Disease progression rate for baseline was calculated using the formula (48

ALSFRS-R score)disease duration (in months)f Disease progression rate for follow-up was calculated using the formula

(ALSFRS-R score on baselineeALSFRS-R score on follow-up)time since baseline MRI

(in months)

Table 2

Age- and gender-adjusted subcortical volume differences in study subjects a

Healthy controls ALS patients Difference p Valueb

Left

Thalamus 6621 83 6475 61 146 103 0159

Caudatus 3673 54 3642 39 32 67 0636

Putamen 5562 67 5497 49 65 83 0435

Pallidum 1678 26 1655 19 23 32 0468

H ippocampus 3892 58 3697 42 195 71 0 007

Amygdala 1615 31 1572 23 43 39 0274

Accumbens 577 15 545 11 32 19 0091

Right

Thalamus 6474 83 6304 60 170 102 0098

Caudatus 3730 55 3645 40 85 69 0216Putamen 5326 70 5325 51 2 87 0984

Pallidum 1575 21 1528 16 47 26 0078

H ippocampus 4034 54 3861 40 173 67 0 011

Amygdala 1831 35 1816 25 16 43 0719

Accumbens 688 13 678 10 10 16 0561

Ventricles

Left lateral 13337 1036 14766 757 1429 1284 0273

Left inferior lateral 556 61 742 45 186 76 0013

Right lateral 11502 8 17 1 29 51 598 1449 1014 0155

Right inferior lateral 501 45 615 33 114 56 0041

Third 1481 74 1617 54 136 92 0144

Fourth 1986 90 2162 66 176 1 11 0 117


Left

CA1 335 5 331 4 4 6 0509

CA23 972 16 944 12 28 20 0162

CA4DG 549 9 535 7 14 11 0209

P resubiculum 491 9 462 6 29 11 0009

Subiculum 646 11 624 8 23 13 0091

Right

CA1 346 5 341 3 5 6 0417

CA23 1027 15 1012 11 15 18 0409

CA4DG 572 8 562 6 10 10 0329

P resubiculum 473 9 452 6 21 11 0052

Subiculum 643 10 618 8 24 13 0062

Hippocampal atrophy is present on both sides and enlarged inferior lateral ventri-

cles Atrophy of the left presubiculum was statistically signi1047297cant on the right side

there was a tendency to atrophy in ALS patients ( p frac14 0052) Values are in mean

standard error

Key ALS ALS patients CA cornu ammonis CO healthy controls DG dentate gyrus

p lt 005

p lt 001a Volumes are reported in mm3b

p Values were completely randomly permutated 10000 times

H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1077



33 Relationship with clinical characteristics

Principal component analysis is a method that allows different

variables to be grouped into a smaller number of representative

variables (Supplementary Fig1) As shown in this1047297gure the 1047297rst PC

represents the basal ganglia and accumbens areas on both sides

the second PC represents the ventricles and the third PC represents

the limbic structures of the DGM (both hippocampi and amyg-

dalae) The results of the regression of these PCs with clinical

characteristics are listed in Table 3 In summary larger ventricles

were signi1047297cantly associated with a lower ALSFRS-R score (106

047 p frac14 0026) In addition smaller basal ganglia smaller limbic

structures and larger ventricles were associated with a shortersurvival (basal ganglia hazard ratio [HR] frac14 144 [95 con1047297dence

interval 113e182) p frac14 0003 ventricles HR frac14 128 [103e159] p frac14 0029 limbic structures HR frac14 131 [108e160] p frac14 0007)

With adjustment for bulbar onset effects remained statistically

signi1047297cant for basal ganglia and limbic structures but with addi-

tional adjustment for age at onset components did not remain

statistically signi1047297cant

34 Longitudinal analysis

This analysis showed progressive enlargement of the lateral

ventricles (left 10908 2233 p lt 0001 right 9647 2089 p lt

0001) the right inferior lateral ventricle (601 246 p frac14 0014)

and the third and fourth ventricles (third 697

182 p lt

0001

fourth 1055 318 p frac14 0001) in ALS patients DGM volume did

not change signi1047297cantly during follow-up in ALS patients Figure 2

and Supplementary Table 1 summarize the results of the longitu-

dinal analysis of subcortical structures They also show that volume

decrease of the hippocampal sub1047297elds was progressive in the left

presubiculum (228 63 mm3 p lt 0001) the right CA23 (227

75 p frac14 0002) and CA4DG (87 44 p frac14 0045) Effects of

volume increase of the lateral ventricles did reach FDR correction

for multiple testing (q frac14 005) other comparisons did not

4 Discussion

ALS patients show a pattern of subcortical involvement charac-terized by hippocampal and thalamic atrophy as well as ventricular

enlargement Hippocampal involvement is most severe and pro-

gressive in the left presubiculum and this is accompanied by

enlarged temporal ventricles During follow-up we also observed

shrinkage in the right CA23 and CA4DG as well as enlarging ven-

tricles (both lateral right inferior lateral third and fourth ventricles)

indicating cerebral disease progression Although the thalamus vol-

ume was not signi1047297cantly different in patients compared to controls

shape analysis was suggestive of atrophy of the thalamic intra-

medullary lamina (IML) that interacts with frontostriatal circuits

(Zarei et al 2010) With respect to clinical measures we found that

larger ventricular volume at baseline correlated with lower ALSFRS-R

scores Considering the differences found between ALS patients and

healthy subjects and the associations with clinical measurements it

Fig 1 Thalamic shape Comparison of thalamic shape of ALS patients with healthy subjects The orange areas indicate affected aspects These areas correspond closely to the

intramedullary laminae of the thalamus (For interpretation of the references to color in this Figure the reader is referred to the web version of this article)




is likely that subcortical structures play a role in the neurodegener-

ative process of ALS In addition shorter survival was related to

smaller basal ganglia and limbic structures and larger ventricles but

multivariate analyses showed that age at onset was associated morestrongly with survival than the above-mentioned PCs

Only 1 study reported a detailed cross-sectional analysis of the

deep gray matter in 39 ALS patients (Bede et al 2013) Hippo-

campal atrophy at baseline was comparable in these studies sug-

gesting a role of the hippocampus in the neurodegenerative process

and clinical phenotype of ALS patients The shape analysis of the

thalami was largely comparable in this study and in our examina-

tion (Bede et al 2013) In our study in 112 ALS patients however a

change in thalamic shape was not observed to be accompanied by

volume changes of the entire thalamus Neither shape nor

morphometric analysis showed (regional) atrophy of other DGM

whereas the above-mentioned study did report atrophy of the

caudate nucleus accumbens area and putamen A possible expla-

nation for this difference is the shorter disease duration in ourstudy (14 vs 26 months) A subgroup analysis (n frac14 26) was per-

formed (mean disease duration standard deviation 243

104 months) to further elucidate this difference With respect to

the DGM the right hippocampus ( p frac14 0028) showed a signi1047297cant

difference in this speci1047297c subgroup This comparison is however

hampered because of the relatively small sample size and different

distribution of the data and because other demographic charac-

teristics such as ALSFRS-R score and disease progression were not

available for comparison Although our longitudinal analysis

showed a tendency for the putamen caudate nucleus and right

accumbens area to decrease in volume these decreases did not

reach statistical signi1047297cance (Fig 2) This 1047297rst longitudinal analysis

of subcortical structures also showed progressive ventricular

enlargement and decreasing volumes of some hippocampal sub-1047297elds indicating progressive neurodegeneration Hippocampal

sub1047297elds have not previously been studied in vivo but the 1047297nding

of hippocampal sub1047297eld degeneration is supported by post mortem

histological research (Takeda et al 2009 Zu et al 2013) and the

present study shows that it can also be detected in vivo at a rela-

tively early stage of the disease

Ventricular enlargement at baseline was restricted to the tem-

poral parts of the ventricular system (in line with hippocampal

atrophy) and progressed during follow-up to signi1047297cant enlarge-

ment of both lateral ventricles and third and fourth ventricles

These results suggest that neurodegeneration in the temporal lobe

is an early characteristic of ALS and is present before progressive

neurodegeneration becomes visible in ventricular enlargement in

the rest of the brain Ventricular enlargement is a common feature

of neurodegenerative diseases but has not previously been studied

in ALS (Thompson et al 2004) This study showed that larger

ventricular volume in ALS is also correlated with a lower functional

motor score (ALSFRS-R) and shorter survival In addition smallerbasal ganglia and smaller limbic structures at baseline were asso-

ciated with shorter survival Multivariate survival analyses how-

ever showed age at onset to be associated more strongly with

survival than the PCs of basal ganglia ventricles and limbic struc-

tures The association between age of onset and survival was not

studied further because this has been studied in detail before (Chio

et al 2009) Analysis of individual brain structures (rather than

PCs) in larger cohorts might provide more insight into the rela-

tionship between individual structures and survival

Although hippocampal atrophy is a nonspeci1047297c feature of

various brain disorders the pattern of hippocampal sub1047297eld

degeneration might be more speci1047297c for different diseases and

might be related to the cognitive pro1047297le of ALS patients (Frisoni

et al 2008 Lindberg et al 2012) For example it is suggestedthat the presubiculum is involved in processing spatial information

which is in line with the de1047297cits on spatial working memory tasks

observed in ALS patients (Hammer et al 2011 Jarrard et al 2004)

With respect to the other hippocampal sub1047297elds it is important to

note that no volume change of the CA1 was observed at baseline or

during follow-up which is in accordance with clinical observations

Clinically involvement of the CA1 causes severe amnesia known

from diseases such as Alzheimerrsquos disease and transient global

amnesia (Bartsch et al 2006) Although memory impairment is

reported to be present in ALS severe amnesia is atypical for ALS in

the early stages Histopathological studies have reported involve-

ment of the CA1 but this might develop later in the disease and is

not always accompanied by neuronal cell loss thereby possibly

explaining why no atrophy of the CA1 was found (Brettschneideret al 2013 Takeda et al 2009) Detailed interpretation of the

clinical signi1047297cance of these 1047297ndings requires studies that combine

extensive cognitive measurements and neuroimaging data and

these are currently scarce

The pattern of regional atrophy of the thalamus described here is

similar to the results of a recent study (Bede et al 2013) Although

not described as the thalamic IML by Bede et al based on the

anatomy of the thalamus these clusters correspond to the thalamic

IML Additional atrophy of the anterior and anterodorsal nucleus

might contribute to this change but cannot explain the entire

pattern (Zarei et al 2010) This change was quite subtle as it did not

signi1047297cantly affect the whole thalamic volume but it might be

clinically signi1047297cant because of its in1047298uence on frontal cognitive

functions and for example because it correlates with verbal1047298

uency

Table 3

Correlations between subcortical structures and clinical parameters in study subjects

PC1 (basal ganglia) mean SE p value PC2 (ventricles) mean SE p value PC3 (limbic structures) mean SE p value

Progression rate (univariate)a004 004 0316 006 004 0145 003 004 0524

Progression rate (multivariate)ab 001 006 0814 009 005 0060 001 005 0783

ALSFRS-R (univariate) 085 043 0049 071 043 0100 040 043 0351

ALSFRS-R (multivariate)b 073 055 0185 106 047 0026 017 050 0736

Survival (univariate)c 144 (113e182) 0003 128 (103e159) 0029 131 (108e160) 0007

Survival (multivariate)cd 112 (085e148) 0410 103 (079e133) 0844 105 (081e135) 0719

At baselinehigher ventricular volumeis associated with lower ALSFRS-R scoreSurvivalis shorter in patients with smaller basal ganglia largerventricularvolume andsmaller

limbic structures (see also Fig 2)

Key ALSFRS-R revised ALS Functional Rating Scale PC1 principal component 1 (representing basal ganglia) PC2 principal component 2 (representing ventricles) PC3

principal component 3 (representing both hippocampi and amygdalas)

p lt 005

p lt 001a Progression rate frac14 (48 ALSFRS-R score)disease duration (in months)b Covariates were age and genderc Values are hazard ratio (95 con1047297dence interval)d Covariates were age at onset and bulbar onset




(Van der Werf et al 2000 Zarei et al 2010) Surprisingly no shape

alteration was observed in the nucleus connected with the motor

cortex the ventral lateral nucleus

Although a relatively large number of patients and controls were

studied in detail several limitations of this study should be taken

into account First no follow-up of healthy controls was performed

Normal aging has however been extensively studied and shows

that DGM volume usually decreases by less than 05 and ventricle

size increases by less than 3 in 6 months in healthy subjects (Fjell

et al 2009) It is therefore highly unlikely that the volume changes

in this study are due to normal aging (eg interior lateral ventricles

of ALS patients increased to 130e140 the size of normal subjects

in 6 months) (Fjell et al 2009) Second males were somewhat

overrepresented in this study based on what is known from

Fig 2 Longitudinal analysis of subcortical structures The x-axis shows the number of the magnetic resonance imaging (MRI) scan (1 frac14 1047297rst scan 2 frac14 second scan) The y-axisshows the volumes normalized to healthy subjects meaning that 100 was the mean subcortical volume of healthy subjects at baseline This 1047297gure shows signi1047297cantly smaller

volumes of both hippocampi and signi1047297cantly larger volumes of both inferior lateral ventricles in ALS patients at baseline After a follow-up of 55 months (on average) the volumes

of the right CA23 and CA4DG decreased signi1047297cantly In addition volumes of nearly all ventricles increased signi1047297cantly during follow-up The colors in the graphs correspond to

the colors in the pictures of subcortical structures and hippocampal sub1047297elds Error bars indicate standard errors Abbreviations CA cornu ammonis DG dentate gyrus Sub

subiculum Presub presubiculum p lt 005 p lt 001 p lt 0001 (For interpretation of the references to color in this Figure the reader is referred to the web version of this

article)




population-based studies but gender was well matched between

ALS patients and healthy subjects (Huisman et al 2011) Third

more detailed neuropsychological examination and correlation

with for example hippocampal atrophy would have been inter-

esting (Bede et al 2013) With respect to the outcomes of the

hippocampal sub1047297eld analysis assessment of spatial working

memory function would have been of interest Larger studies

combining neuropsychological and histopathological data with

structural and functional MRI data are therefore of great impor-tance The NeuroImaging Society in ALS (NISALS) might provide an

opportunity to realize this (Turner et al 2011)

5 Conclusions

The present study shows that ALS patients have reduced hip-

pocampal volumes at an early stage of the disease the area most

affected being the presubiculum This combined with ventricular

enlargement found to be progressive during follow-up was asso-

ciated with survival and ALSFRS-R Furthermore thalamic degen-

eration was found to be most probably located in the IML In

conclusion subcortical involvement is progressive and correlates

with clinical parameters in ALS underscoring its role in the path-

ophysiology of ALS

Disclosure statement

Henk-Jan Westeneng has nothing to disclose

Esther Verstraete has nothing to disclose

Reneacutee Walhout has nothing to disclose

Jeroen Hendrikse has nothing to disclose

Jan H Veldink has nothing to disclose

Martijn P van den Heuvel has nothing to disclose

Leonard H van den Berg reports grants from Netherlands ALS

Foundation grants from Prinses Beatrix Spierfonds grants from

Netherlands Organisation for Health Research and Development (Vici

scheme) grants from European Communityrsquos Health Seventh

Framework Programme (FP72007e

2013) (grant agreement no259867) during the conduct of the study personal fees from Baxter

for Scienti1047297c Advisory Board and Travel Grant and personal fees from

Scienti1047297c Advisory Board BiogenIdec outside the submitted work

Acknowledgements

This work was supported by the Netherlands ALS Foundation

Prinses Beatrix Fonds Netherlands Organization for Health

Research and Development (Vici scheme to LHvdB) the Neder-

landse Organisatie voor Wetenschappelijk Onderzoek under the

frame of E-RARE-2 the ERA-Net for Research on Rare Diseases and

the European Communityrsquos Health Seventh Framework Programme

(FP72007e2013) under grant agreement (259867)

Appendix A Supplementary data

Supplementary data associated with this article can be found

in the online version at httpdxdoiorg101016jneurobiolaging

201409002

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Agosta F Pagani E Rocca MA Caputo D Perini M Salvi F Prelle A Filippi M2007 Voxel-based morphometry study of brain volumetry and diffusivity in

amyotrophic lateral sclerosis patients with mild disability Hum Brain Mapp28 1430e1438

Bartsch T Alfke K Stingele R Rohr A Freitag-Wolf S Jansen O Deuschl G2006 Selective affection of hippocampal CA-1 neurons in patients with tran-sient global amnesia without long-term sequelae Brain 129 2874e2884

Bede P Elamin M Byrne S McLaughlin RL Kenna K Vajda A Pender NBradley DG Hardiman O 2013 Basal ganglia involvement in amyotrophiclateral sclerosis Neurology 81 2107e2115

Bernal-Rusiel JL Greve DN Reuter M Fischl B Sabuncu MR for AlzheimerrsquosDisease Neuroimaging I 2012 Statistical analysis of longitudinal neuroimage

data with linear mixed effects models NeuroImage 66C 249e

260Brettschneider J Del Tredici K Toledo JB Robinson JL Irwin DJ Grossman M

Suh E Van Deerlin VM Wood EM Baek Y Kwong L Lee EB Elman LMcCluskey L Fang L Feldengut S Ludolph AC Lee VM Braak HTrojanowski JQ 2013 Stages of pTDP-43 pathology in amyotrophic lateralsclerosis Ann Neurol 74 20e38

Brooks BR Miller RG Swash M Munsat TL World Federation of NeurologyResearch Group on Motor Neuron D 2000 El Escorial revisited revised criteriafor the diagnosis of amyotrophic lateral sclerosis Amyotroph Lateral SclerOther Mot Neuron Disord 1 293e299

Cedarbaum JM Stambler N Malta E Fuller C Hilt D Thurmond BNakanishi A 1999 The ALSFRS-R a revised ALS Functional Rating Scale thatincorporates assessments of respiratory function BDNF ALS Study Group (PhaseIII) J Neurol Sci 169 13e21

Chang JL Lomen-Hoerth C Murphy J Henry RG Kramer JH Miller BLGorno-Tempini ML 2005 A voxel-based morphometry study of patterns of brain atrophy in ALS and ALSFTLD Neurology 65 75e80

Chio A Logroscino G Hardiman O Swingler R Mitchell D Beghi ETraynor BG Eurals C 2009 Prognostic factors in ALS a critical review

Amyotroph Lateral Scler 10 310e

323Fischl B Salat DH Busa E Albert M Dieterich M Haselgrove C van der

Kouwe A Killiany R Kennedy D Klaveness S Montillo A Makris NRosen B Dale AM 2002 Whole brain segmentation automated labeling of neuroanatomical structures in the human brain Neuron 33 341e355

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Fjell AM Walhovd KB Fennema-Notestine C McEvoy LK Hagler DJHolland D Brewer JB Dale AM 2009 One-year brain atrophy evident inhealthy aging J Neurosci 29 15223e15231

Foerster BR Welsh RC Feldman EL 2013 25 Years of neuroimaging in amyo-trophic lateral sclerosis Nat Rev Neurol 9 513e524

Frisoni GB Ganzola R Canu E Rub U Pizzini FB Alessandrini F Zoccatelli GBeltramello A Caltagirone C Thompson PM 2008 Mapping local hippo-campal changes in Alzheimerrsquos disease and normal ageing with MRI at 3 TeslaBrain 131 3266e3276

Geser F Brandmeir NJ Kwong LK Martinez-Lage M Elman L McCluskey L

Xie SX Lee VM Trojanowski JQ 2008 Evidence of multisystem disorder inwhole-brain map of pathological TDP-43 in amyotrophic lateral sclerosis ArchNeurol 65 636e641

Hammer A Vielhaber S Rodriguez-Fornells A Mohammadi B Munte TF 2011A neurophysiological analysis of working memory in amyotrophic lateral scle-rosis Brain Res 1421 90e99

Huisman MH de Jong SW van Doormaal PT Weinreich SS Schelhaas HJ vander Kooi AJ de Visser M Veldink JH van den Berg LH 2011 Populationbased epidemiology of amyotrophic lateral sclerosis using capture-recapturemethodology J Neurol Neurosurg Psychiatry 82 1165e1170

Jarrard LE Davidson TL Bowring B 2004 Functional differentiation within themedial temporal lobe in the rat Hippocampus 14 434e449

Kiernan MC Vucic S Cheah BC Turner MR Eisen A Hardiman O Burrell JRZoing MC 2011 Amyotrophic lateral sclerosis Lancet 377 942e955

Lindberg O Walterfang M Looi JC Malykhin N Ostberg P Zandbelt BStyner M Paniagua B Velakoulis D Orndahl E Wahlund LO 2012 Hip-pocampal shape analysis in Alzheimerrsquos disease and frontotemporal lobardegeneration subtypes J Alzheimerrsquos Dis 30 355e365

Patenaude B Smith SM Kennedy DN Jenkinson M 2011 A Bayesian model of

shape and appearance for subcortical brain segmentation NeuroImage 56907e922

Reuter M Fischl B 2011 Avoiding asymmetry-induced bias in longitudinal imageprocessing NeuroImage 57 19e21

Reuter M Rosas HD Fischl B 2010 Highly accurate inverse consistent regis-tration a robust approach NeuroImage 53 1181e1196

Reuter M Schmansky NJ Rosas HD Fischl B 2012 Within-subject templateestimation for unbiased longitudinal image analysis NeuroImage 611402e1418

Sach M Winkler G Glauche V Liepert J Heimbach B Koch MA Buchel CWeiller C 2004 Diffusion tensor MRI of early upper motor neuron involve-ment in amyotrophic lateral sclerosis Brain 127 340e350

Takeda T Uchihara T Arai N Mizutani T Iwata M 2009 Progression of hip-pocampal degeneration in amyotrophic lateral sclerosis with or withoutmemory impairment distinction from Alzheimer disease Acta Neuropathol117 35e44

Thivard L Pradat PF Lehericy S Lacomblez L Dormont D Chiras J Benali HMeininger V 2007 Diffusion tensor imaging and voxel based morphometry




study in amyotrophic lateral sclerosis relationships with motor disability J Neurol Neurosurg Psychiatry 78 889e892

Thompson PM Hayashi KM De Zubicaray GI Janke AL Rose SE Semple JHong MS Herman DH Gravano D Doddrell DM Toga AW 2004 Map-ping hippocampal and ventricular change in Alzheimer disease NeuroImage 221754e1766

Turner MR Agosta F Bede P Govind V Lule D Verstraete E 2012 Neuro-imaging in amyotrophic lateral sclerosis Biomarkers Med 6 319e337

Turner MR Cagnin A Turkheimer FE Miller CC Shaw CE Brooks DJLeigh PN Banati RB 2004 Evidence of widespread cerebral microglial acti-

vation in amyotrophic lateral sclerosis an [11C](R)-PK11195 positron emissiontomography study Neurobiol Dis 15 601e609

Turner MR Grosskreutz J Kassubek J Abrahams S Agosta F Benatar MFilippi M Goldstein LH van den Heuvel M Kalra S Lule DMohammadi B First Neuroimaging Symposium in ALS 2011 Towards aneuroimaging biomarker for amyotrophic lateral sclerosis Lancet Neurol 10400e403

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Van Leemput K Bakkour A Benner T Wiggins G Wald LL Augustinack JDickerson BC Golland P Fischl B 2009 Automated segmentation of hippo-campal sub1047297elds from ultra-high resolution in vivo MRI Hippocampus 19 549e557

Verstraete E Veldink JH van den Berg LH van den Heuvel MP 2014 Structuralbrain network imaging shows expanding disconnection of the motor system inamyotrophic lateral sclerosis Hum Brain Mapp 35 1351e1361

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shape and connectivity analysis an MRI study of thalamic degeneration inAlzheimerrsquos disease NeuroImage 49 1e8

Zu T Liu Y Banez-Coronel M Reid T Pletnikova O Lewis J Miller TMHarms MB Falchook AE Subramony SH Ostrow LW Rothstein JDTroncoso JC Ranum LP 2013 RAN proteins and RNA foci from antisensetranscripts in C9ORF72 ALS and frontotemporal dementia Proc Natl Acad SciUSA 110 E4968eE4977




Longitudinal analyses are important for the understanding of

patterns of disease progression and might result in the discovery of

a more speci1047297c marker that can be used to monitor disease pro-

gression in ALS Longitudinal neuroimaging studies may be an

important tool to assess cerebral neurodegeneration in detail in a

noninvasive way For example hippocampal atrophy has been re-

ported in ALS but also in other neurological and psychiatric diseases

(Bede et al 2013 Thompson et al 2004) Longitudinal analyses in

combination with a more detailed analysis of the hippocampus(hippocampal sub1047297eld segmentations) might shed more light on

when the hippocampus becomes involved and which sub1047297elds in

particular may be affected

We therefore studied volumes of ventricles and DGM (including

hippocampal sub1047297elds) cross-sectionally and longitudinally in a

large group of patients with ALS and correlated our 1047297ndings with

clinical characteristics

2 Methods

21 Participants

All 172 participating subjects were recruited from the outpatient

clinic for motor neuron diseases of the University Medical CenterUtrecht in The Netherlands Patients were classi1047297ed as having

de1047297nite probable or possible ALS using the revised El Escorial

criteria after excluding other conditions (Brooks et al 2000) Sub-

jects with a history of brain injury epilepsy psychiatric illness

other neurodegenerative disease (including frontotemporal lobe

dementia) or structural brain disease were excluded The median

time between the 1047297rst and second MRI scan was 55 months

Written informed consent was obtained from all participants in

accordance with the Declaration of Helsinki

22 Clinical parameters

Clinical characteristics including handedness disease duration

and survival were recorded Functional status was evaluated usingthe revised ALS Functional Rating Scale (ALSFRS-R) (Cedarbaum

et al 1999) The disease progression rate was calculated using the

formula (48 ALSFRS-R score)disease duration (in months) Dis-

ease duration was evaluated from symptom onset

23 Data acquisition

A 3T Philips Achieve Medical Scanner was used to acquire a

high-resolution T1-weighted image Acquisition parameters were

as follows 3-dimensional fast 1047297eld echo (FFE) using parallel im-

aging TRTE frac14 1046 ms 1047298ip angel 8 slice orientation sagittal

075 075 08 mm (045 mm3) voxel size 1047297eld of view (FOV) frac14

160 240 240 mm (9216 dm3) and reconstruction matrix frac14

200 320 320 covering the whole brain Acquisition time was11 minutes The high-resolution MRI scans for scienti1047297c research

were combined with a standard MRI examination and these scans

were reviewed by an experienced neuroradiologist In the case of

structural abnormalities made scans were excluded

24 Data processing

Two groups of analyses were performed cross-sectional and

longitudinal Both analyses focused on volumes of ventricles DGM

and hippocampal sub1047297elds

For the cross-sectional analysis subcortical volumes were

automatically segmented and measured by FreeSurfer version 51

(Fischl et al 2002 2004) In addition hippocampal sub1047297elds were

automatically segmented and measured using a FreeSurfer

subroutine (Van Leemput et al 2009) In this article we have

focused on cornu ammonis 1 (CA1) CA23 CA4dentate gyrus (CA4

DG) subiculum and presubiculum Fimbria and hippocampal

1047297ssure were disregarded because these are the smallest sub1047297elds

and segmentation is less reliable (Van Leemput et al 2009)

To detect subtle regional volumechanges of DGM we performed

a shape analysis of DGM (thalamus putamen caudate nucleus

nucleus accumbens and hippocampus) previously reported to be

altered in ALS (Agosta et al 2009 Bede et al 2013 Chang et al2005 Thivard et al 2007) The shape of the above-mentioned

DGM (except the hippocampus the sub1047297elds of which were stud-

ied) was analyzed using the FSLs FIRST module version 500

(Patenaude et al 2011) This vertex-based shape analysis was cor-

rected for multiple testing using permutation tests with 10000

permutations of cluster mass

The longitudinal analysis was performed using FreeSurfer which

creates an unbiased within-subject template space and image using

robust inverse consistent registration (Reuter and Fischl 2011

Reuter et al 2010) Several processing steps such as skull strip-

ping Talairach transforms atlas registration as well as spherical

surface maps and parcellations are then initialized using common

information from the within-subject template This analysis method

has been validated and shown to signi1047297cantly increase reliability andstatistical power (Reuter et al 2012)

25 Statistical analysis

251 Cross-sectional analyses

ManneWhitney U and Fisher exact tests were used to compare

demographic and clinical data Cross-sectional volume differences

were compared between ALS and healthy controls using an analysis

of covariance (ANCOVA) All of these analyses were adjusted for age

and gender Because of possible non-normality we applied per-

mutation tests with 10000 permutations according to participant

groups

252 Relationship between imaging and clinical characteristicsThe relationship between cross-sectional clinical data and

volumes in ALS patients was assessed using a combination of an

ANCOVA and principal component analysis (PCA) PCA is a

method that is used to describe a large group of variables by a

smaller group of principal components (PCs) each consisting of a

number of interrelated variables Of all subcortical structures (n frac14

20) 3 PCs were retained (Supplementary Fig 1) These PCs were

linearly regressed using clinical data (using ANCOVA) to assess the

relationship between clinical data and volumes (represented by

PCs) thereby adjusting for age and gender This method was used

because it takes advantage of the underlying correlation of

different subcortical structures (eg the ventricles are actually

part of 1 system see also Supplementary Fig 1) and increase both

power and robustness by grouping variables that share commonfeatures (in PCs) reducing the number of comparisons and

minimizing possible effects of multicollinearity The relationship

between the PCs of the subcortical structures and survival was

studied using univariate and multivariate Cox proportional haz-

ards models Known independent predictors of survival (age at

onset and bulbar onset) were included in the multivariate anal-

ysis Gender was not statistically signi1047297cantly associated with

survival and was therefore excluded from the multivariate sur-

vival analysis

253 Longitudinal analyses

A linear mixed-effects model (LME) was used to assess the rate

of change of subcortical volumes in ALS patients over time while

accounting for random between-subject variation (Bernal-Rusiel





analysis






3 Results












( p frac14 0057)



























Table 1



controls

Baseline

(n frac14 112)

Follow-up

(n frac14 39)

Baseline

(n frac14 60)

Age 604 (24e78) 599 (24e78)b 604 (29e76)



Site of onset ()

Bulbar 24 (21) 3 (8)

Cervical 55 (49) 24 (62)





De1047297nite 13 (12) 4 (10)b

Probable 48 (43) 19 (49)b

Probable laboratory

supported

35 (31) 10 (26)b

Possible 16 (14) 6 (15)b




Died 77112 2339 060





(in months)

Table 2



Left

Thalamus 6621 83 6475 61 146 103 0159

Caudatus 3673 54 3642 39 32 67 0636

Putamen 5562 67 5497 49 65 83 0435

Pallidum 1678 26 1655 19 23 32 0468

H ippocampus 3892 58 3697 42 195 71 0 007

Amygdala 1615 31 1572 23 43 39 0274

Accumbens 577 15 545 11 32 19 0091

Right

Thalamus 6474 83 6304 60 170 102 0098


Pallidum 1575 21 1528 16 47 26 0078

H ippocampus 4034 54 3861 40 173 67 0 011

Amygdala 1831 35 1816 25 16 43 0719

Accumbens 688 13 678 10 10 16 0561

Ventricles

Left lateral 13337 1036 14766 757 1429 1284 0273


Right lateral 11502 8 17 1 29 51 598 1449 1014 0155


Third 1481 74 1617 54 136 92 0144

Fourth 1986 90 2162 66 176 1 11 0 117


Left

CA1 335 5 331 4 4 6 0509

CA23 972 16 944 12 28 20 0162

CA4DG 549 9 535 7 14 11 0209

P resubiculum 491 9 462 6 29 11 0009

Subiculum 646 11 624 8 23 13 0091

Right

CA1 346 5 341 3 5 6 0417

CA23 1027 15 1012 11 15 18 0409

CA4DG 572 8 562 6 10 10 0329

P resubiculum 473 9 452 6 21 11 0052

Subiculum 643 10 618 8 24 13 0062




standard error


p lt 005




























182 p lt

0001










4 Discussion










































































































uency

Table 3













p lt 005
























article)














5 Conclusions









ophysiology of ALS
















Acknowledgements











201409002

References























































analysis






3 Results












( p frac14 0057)



























Table 1



controls

Baseline

(n frac14 112)

Follow-up

(n frac14 39)

Baseline

(n frac14 60)

Age 604 (24e78) 599 (24e78)b 604 (29e76)



Site of onset ()

Bulbar 24 (21) 3 (8)

Cervical 55 (49) 24 (62)





De1047297nite 13 (12) 4 (10)b

Probable 48 (43) 19 (49)b

Probable laboratory

supported

35 (31) 10 (26)b

Possible 16 (14) 6 (15)b




Died 77112 2339 060





(in months)

Table 2



Left

Thalamus 6621 83 6475 61 146 103 0159

Caudatus 3673 54 3642 39 32 67 0636

Putamen 5562 67 5497 49 65 83 0435

Pallidum 1678 26 1655 19 23 32 0468

H ippocampus 3892 58 3697 42 195 71 0 007

Amygdala 1615 31 1572 23 43 39 0274

Accumbens 577 15 545 11 32 19 0091

Right

Thalamus 6474 83 6304 60 170 102 0098


Pallidum 1575 21 1528 16 47 26 0078

H ippocampus 4034 54 3861 40 173 67 0 011

Amygdala 1831 35 1816 25 16 43 0719

Accumbens 688 13 678 10 10 16 0561

Ventricles

Left lateral 13337 1036 14766 757 1429 1284 0273


Right lateral 11502 8 17 1 29 51 598 1449 1014 0155


Third 1481 74 1617 54 136 92 0144

Fourth 1986 90 2162 66 176 1 11 0 117


Left

CA1 335 5 331 4 4 6 0509

CA23 972 16 944 12 28 20 0162

CA4DG 549 9 535 7 14 11 0209

P resubiculum 491 9 462 6 29 11 0009

Subiculum 646 11 624 8 23 13 0091

Right

CA1 346 5 341 3 5 6 0417

CA23 1027 15 1012 11 15 18 0409

CA4DG 572 8 562 6 10 10 0329

P resubiculum 473 9 452 6 21 11 0052

Subiculum 643 10 618 8 24 13 0062




standard error


p lt 005




























182 p lt

0001










4 Discussion










































































































uency

Table 3













p lt 005
























article)














5 Conclusions









ophysiology of ALS
















Acknowledgements











201409002

References












































































182 p lt

0001










4 Discussion










































































































uency

Table 3













p lt 005
























article)














5 Conclusions









ophysiology of ALS
















Acknowledgements











201409002

References












































































































































uency

Table 3













p lt 005
























article)














5 Conclusions









ophysiology of ALS
















Acknowledgements











201409002

References









































































article)














5 Conclusions









ophysiology of ALS
















Acknowledgements











201409002

References
































































5 Conclusions









ophysiology of ALS
















Acknowledgements











201409002

References




















































hippocampus als mri

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