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8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 18
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-
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
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
8152019 Hippocampus ALS MRI
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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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821078
8152019 Hippocampus ALS MRI
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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
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1079
8152019 Hippocampus ALS MRI
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(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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821080
8152019 Hippocampus ALS MRI
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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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H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821082
8152019 Hippocampus ALS MRI
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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-
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
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
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 48
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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821078
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 58
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
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1079
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 68
(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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821080
8152019 Hippocampus ALS MRI
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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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Foerster BR Welsh RC Feldman EL 2013 25 Years of neuroimaging in amyo-trophic lateral sclerosis Nat Rev Neurol 9 513e524
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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
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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
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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
Van der Werf YD Witter MP Uylings HB Jolles J 2000 Neuropsychology of infarctions in the thalamus a review Neuropsychologia 38 613e627
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
Zarei M Patenaude B Damoiseaux J Morgese C Smith S Matthews PMBarkhof F Rombouts SA Sanz-Arigita E Jenkinson M 2010 Combining
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821082
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 38
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
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
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
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 48
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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821078
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 58
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
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1079
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 68
(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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821080
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 78
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
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
Fischl B Salat DH van der Kouwe AJ Makris N Segonne F Quinn BTDale AM 2004 Sequence-independent segmentation of magnetic resonanceimages NeuroImage 23 (Suppl 1) S69eS84
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1081
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 88
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
Van der Werf YD Witter MP Uylings HB Jolles J 2000 Neuropsychology of infarctions in the thalamus a review Neuropsychologia 38 613e627
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
Zarei M Patenaude B Damoiseaux J Morgese C Smith S Matthews PMBarkhof F Rombouts SA Sanz-Arigita E Jenkinson M 2010 Combining
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821082
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 48
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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821078
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 58
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
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1079
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 68
(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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821080
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 78
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
References
Agosta F Gorno-Tempini ML Pagani E Sala S Caputo D Perini MBartolomei I Fruguglietti ME Filippi M 2009 Longitudinal assessment of grey matter contraction in amyotrophic lateral sclerosis a tensor basedmorphometry study Amyotroph Lateral Scler 10 168e174
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
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
Fischl B Salat DH van der Kouwe AJ Makris N Segonne F Quinn BTDale AM 2004 Sequence-independent segmentation of magnetic resonanceimages NeuroImage 23 (Suppl 1) S69eS84
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1081
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 88
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
Van der Werf YD Witter MP Uylings HB Jolles J 2000 Neuropsychology of infarctions in the thalamus a review Neuropsychologia 38 613e627
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
Zarei M Patenaude B Damoiseaux J Morgese C Smith S Matthews PMBarkhof F Rombouts SA Sanz-Arigita E Jenkinson M 2010 Combining
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821082
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 58
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
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1079
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 68
(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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821080
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 78
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
References
Agosta F Gorno-Tempini ML Pagani E Sala S Caputo D Perini MBartolomei I Fruguglietti ME Filippi M 2009 Longitudinal assessment of grey matter contraction in amyotrophic lateral sclerosis a tensor basedmorphometry study Amyotroph Lateral Scler 10 168e174
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
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
Fischl B Salat DH van der Kouwe AJ Makris N Segonne F Quinn BTDale AM 2004 Sequence-independent segmentation of magnetic resonanceimages NeuroImage 23 (Suppl 1) S69eS84
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1081
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 88
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
Van der Werf YD Witter MP Uylings HB Jolles J 2000 Neuropsychology of infarctions in the thalamus a review Neuropsychologia 38 613e627
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
Zarei M Patenaude B Damoiseaux J Morgese C Smith S Matthews PMBarkhof F Rombouts SA Sanz-Arigita E Jenkinson M 2010 Combining
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821082
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 68
(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)
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821080
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 78
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
References
Agosta F Gorno-Tempini ML Pagani E Sala S Caputo D Perini MBartolomei I Fruguglietti ME Filippi M 2009 Longitudinal assessment of grey matter contraction in amyotrophic lateral sclerosis a tensor basedmorphometry study Amyotroph Lateral Scler 10 168e174
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
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
Fischl B Salat DH van der Kouwe AJ Makris N Segonne F Quinn BTDale AM 2004 Sequence-independent segmentation of magnetic resonanceimages NeuroImage 23 (Suppl 1) S69eS84
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1081
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 88
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
Van der Werf YD Witter MP Uylings HB Jolles J 2000 Neuropsychology of infarctions in the thalamus a review Neuropsychologia 38 613e627
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
Zarei M Patenaude B Damoiseaux J Morgese C Smith S Matthews PMBarkhof F Rombouts SA Sanz-Arigita E Jenkinson M 2010 Combining
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821082
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 78
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
References
Agosta F Gorno-Tempini ML Pagani E Sala S Caputo D Perini MBartolomei I Fruguglietti ME Filippi M 2009 Longitudinal assessment of grey matter contraction in amyotrophic lateral sclerosis a tensor basedmorphometry study Amyotroph Lateral Scler 10 168e174
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
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
Fischl B Salat DH van der Kouwe AJ Makris N Segonne F Quinn BTDale AM 2004 Sequence-independent segmentation of magnetic resonanceimages NeuroImage 23 (Suppl 1) S69eS84
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e1082 1081
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 88
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
Van der Werf YD Witter MP Uylings HB Jolles J 2000 Neuropsychology of infarctions in the thalamus a review Neuropsychologia 38 613e627
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
Zarei M Patenaude B Damoiseaux J Morgese C Smith S Matthews PMBarkhof F Rombouts SA Sanz-Arigita E Jenkinson M 2010 Combining
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821082
8152019 Hippocampus ALS MRI
httpslidepdfcomreaderfullhippocampus-als-mri 88
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
Van der Werf YD Witter MP Uylings HB Jolles J 2000 Neuropsychology of infarctions in the thalamus a review Neuropsychologia 38 613e627
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
Zarei M Patenaude B Damoiseaux J Morgese C Smith S Matthews PMBarkhof F Rombouts SA Sanz-Arigita E Jenkinson M 2010 Combining
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
H-J Westeneng et al Neurobiology of Aging 36 (2015) 1075e10821082