Cerebral Cortex March 2009;19:497--510
Advance Access publication July 16, 2008
The Cortical Signature of Alzheimer’s
Disease: Regionally Specific Cortical
Thinning Relates to Symptom Severity in
Very Mild to Mild AD Dementia and is
Detectable in Asymptomatic Amyloid-
Bradford C. Dickerson1,2,3,4, Akram Bakkour5, David H. Salat3,6,
Eric Feczko5, Jenni Pacheco3,6, Douglas N. Greve3,6,
Fran Grodstein7, Christopher I. Wright3,4,5, Deborah Blacker2,5,
H. Diana Rosas1,2,3, Reisa A. Sperling1,2,3,4, Alireza Atri1,2, John
H. Growdon1,2, Bradley T. Hyman1,2, John C. Morris8,
Bruce Fischl3,6,9and Randy L. Buckner3,6,10
1Department of Neurology2Massachusetts Alzheimer’s Disease
Research Center3Athinoula A. Martinos Center for Biomedical
Imaging, Massachusetts General Hospital and Harvard Medical
School, Boston, MA, USA4Division of Cognitive and Behavioral
Neurology, Department of Neurology, Brigham & Women’s
Hospital, Boston, MA, USA5Department of Psychiatry
6Department of Radiology, Massachusetts General Hospital and
Harvard Medical School, Boston, MA, USA7Department of
Internal Medicine, Brigham & Women’s Hospital, Boston, MA,
USA8Department of Neurology and Alzheimer’s Disease
Research Center, Washington University School of Medicine, St
Louis, MO, USA9Computer Science and Artificial Intelligence
Laboratory, Massachusetts Institute of Technology, Cambridge,
MA, USA and10Department of Psychology and Howard Hughes
Medical Institute, Harvard University, Cambridge, MA, USA
Alzheimer’s disease (AD) is associated with neurodegeneration in
vulnerable limbic and heteromodal regions of the cerebral cortex,
detectable in vivo using magnetic resonance imaging. It is not
clear whether abnormalities of cortical anatomy in AD can be
reliably measured across different subject samples, how closely
they track symptoms, and whether they are detectable prior to
symptoms. An exploratory map of cortical thinning in mild AD
was used to define regions of interest that were applied in
a hypothesis-driven fashion to other subject samples. Results
demonstrate a reliably quantifiable in vivo signature of abnormal
cortical anatomy in AD, which parallels known regional vulner-
ability to AD neuropathology. Thinning in vulnerable cortical
regions relates to symptom severity even in the earliest stages of
clinical symptoms. Furthermore, subtle thinning is present in
asymptomatic older controls with brain amyloid binding as
detected with amyloid imaging. The reliability and clinical validity
of AD-related cortical thinning suggests potential utility as an
imaging biomarker. This ‘‘disease signature’’ approach to cortical
morphometry, in which disease effects are mapped across the
cortical mantle and then used to define ROIs for hypothesis-driven
analyses, may provide a powerful methodological framework for
studies of neuropsychiatric diseases.
Keywords: Alzheimer’s disease, cerebral cortex, magnetic resonance
imaging, medial temporal lobe, parietal cortex
The symptoms of Alzheimer’s disease (AD)—progressive
impairment in memory, executive function, visuospatial abili-
ties, language, and behavior—arise from neurodegeneration of
specific brain regions, prominently including the paralimbic
and heteromodal association areas. Initially, knowledge of brain
regions selectively vulnerable to AD was obtained from post-
mortem brain tissue (Brun and Gustafson 1976; Arnold et al.
1991; Braak and Braak 1991; Morrison and Hof 2002). In the
past 15 years, magnetic resonance imaging (MRI) has provided
insights into quantitative neuroanatomic abnormalities in living
individuals with AD as well as the progressive course of the
? 2008 The Authors
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disease. Volume loss in specific regions, such as the hippo-
campal formation (Jack et al. 1992; Killiany et al. 1993) and
entorhinal cortex (Juottonen et al. 1998; Bobinski et al. 1999;
Killiany et al. 2000; Dickerson et al. 2001), can be detected in
vivo using manual region-of-interest MRI techniques.
Manual methods are labor-intensive and typically focus on
a few a priori--defined regions, which has resulted in the
extensive study of some regions of the brain that are well
known to be affected by AD (e.g., the hippocampal formation
and entorhinal cortex) without equivalent study of the dis-
tributed network of all brain regions affected. Analysis of
differences in whole-brain volume between individuals with
early AD and controls (Fotenos et al. 2005) as well as accel-
erated whole-brain atrophy rates in AD (Fox et al. 1999;
Cardenas et al. 2003; Fotenos et al. 2005) make clear that
extensive regional changes are taking place in AD because
changes localized to the medial temporal lobe simply cannot
account for such large-scale effects, which are present even at
the earliest stages of the disease. As an extreme example,
clinically nondemented individuals (Clinical Dementia Rating
[CDR] = 0) with positive amyloid binding as measured using
positron emission tomography (PET) show reduced whole-
brain volumes relative to amyloid-free peers suggesting that
cortical atrophy may be present before clinical symptoms
appear (Fotenos et al. 2008).
These observations raise several questions that can be
investigated using MRI measures. First, of the spatially dis-
tributed cortical regions that are most prominently affected in
AD, does the relative magnitude of atrophy suggest a sequence
of involvement similar to that hypothesized from post-mortem
studies? Is the pattern of vulnerable cortical regions consistent
from one group of individuals with AD to the next? And how
early in the progression of the disease can differences in
vulnerable cortex be detected? The answers to these questions
will provide in vivo data about the brain networks affected in
AD that can complement neuropathological data as well as
identify affected cortical regions for use as biomarkers for
detection and monitoring of AD.
Insights into the distributed cortical regions that show
atrophy in AD have begun to emerge. Computational MRI data
analysis methods based on voxel-based morphometry or analy-
sis of local cortical deformations provide maps of estimated
gray matter atrophy in AD without a priori focus on specific
regions (Baron et al. 2001; Thompson et al. 2001; Frisoni et al.
2002; Good et al. 2002; Scahill et al. 2002; Karas et al. 2003;
Buckner et al. 2005). Consistent with expectations, these
studies reveal effects of AD on distributed regions of cortex
including posterior lateral temporoparietal and medial parietal
regions as well as robust effects in medial and lateral temporal
cortex. Methods have also been developed that enable the
measurement of cortical thickness across the entire cortical
mantle (Fischl and Dale 2000; MacDonald et al. 2000; Kabani
et al. 2001; Rosas et al. 2002). Initial studies of cortical
thickness demonstrate thinning in distributed association areas
again suggesting that regional atrophy can be detected across
widespread cortical regions (Lerch et al. 2005; Du et al. 2007).
One advantage of the measurement of cortical thickness is that
it provides a quantitative value that represents a physical
property of the brain that can be measured in an individual
person, whether in vivo or from post-mortem tissue (Rosas
et al. 2002).
Here we expanded upon prior work on cortical thinning in
AD in several important ways. First, although voxel-based
studies have included patients with milder forms of AD (Karas
et al. 2004; Bozzali et al. 2006; Apostolova et al. 2007; Whitwell
et al. 2008), previous studies of cortical thinning in AD have
included patients with dementia severity ranging from mild to
moderate AD, so the relative magnitude and pattern of cortical
thinning in the mildest clinical phases of AD is unclear. In the
present study we focused specifically on AD at mild and very
mild stages of the disease. Moreover, there has been little
investigation of the relationship between cortical thinning
and severity of symptoms in patients with the mildest
symptoms of AD. We explored this relationship directly.
Second, we examined AD-associated cortical thinning across
4 independent samples from multiple sites and scanners. This
allowed us to investigate the consistency of cortical thinning
across multiple data samples and also, by pooling the data
across sites, provide a highly precise large-sample estimate of
the regional magnitude of cortical thinning in AD. By
comparing data across sites this study also provides evidence
for the feasibility of such analyses for multicenter clinical
studies (e.g., the Alzheimer’s Disease Neuroimaging Initiative
[Mueller et al. 2005]).
Recent in vivo data using the amyloid-imaging tracer
[11C]Pittsburgh Compound B (PIB) (Klunk et al. 2004) indicate
that some clinically normal (asymptomatic) older individuals
harbor fibrillar amyloid deposits, consistent with a presymp-
tomatic AD state (Buckner et al. 2005; Mintun et al. 2006).
Although previous data suggest that regional deposition of
amyloid overlaps in part with areas of cortical atrophy in AD
(Buckner et al. 2005), the question of whether it is possible to
detect subtle regional cortical thinning in older individuals
with brain amyloid has never been investigated. Based on pre-
vious work in which atrophy was detected in asymptomatic
individuals prior to their conversion to very mild dementia
(Buckner et al. 2005), we hypothesized that it may be possible,
by focusing on the regions known to be affected in clinically
mild AD, to detect a subtle degree of cortical thinning in
amyloid-positive asymptomatic individuals.
Participants and Methods
Analyses proceeded in several steps that involved data from 380
participants (336 using structural MRI and 44 using amyloid-PIB PET
and structural MRI). First, in a large primary sample of participants (N =
144), we explored the entire cortical mantle to identify areas of
thinning in a relatively homogeneous sample of participants with mild
AD (N = 29) compared with nondemented older controls (OC, N =
115). This initial analysis identified a cortical signature of AD—a
spatially distributed set of specific regions with AD-related thinning.
Regions of interest (ROIs) were defined to capture the spatially
distributed pattern of cortex most affected by AD. Then, to investigate
the consistency of cortical thinning in AD, we applied these a priori
ROIs to 3 new samples of AD participants and OC (total N = 123). Each
independent sample was recruited and evaluated at a different clinical
site and scanners involved 2 different field strengths (1.5 and 3 T),
similar to multicenter studies such as clinical trials. To explore the
progression of AD, we next applied the a priori ROIs to another sample
of individuals with Incipient and very mild AD dementia (N = 69) to
determine the degree to which these regions are affected in the earliest
clinical stages of disease progression. The relationship of regional
cortical thinning to severity of symptoms was also investigated by
correlational analysis between ROI thickness and the Clinical Dementia
Rating scale Sum-of-Boxes (Morris et al. 1997), a measure of severity of
cognitive and functional impairments in daily life. A pooled analysis was
performed of all 267 mild AD patients and OC to provide a stable, highly
precise estimate of the spatial distribution and magnitude of thinning in
the cortical signature of AD. Finally, ‘‘AD-signature’’ regional thickness
was investigated in a group of OC individuals known to harbor brain
amyloid from PIB-PET scanning and compared with a group of OC
individuals without brain amyloid.
The overall data collection and analysis procedure is depicted in
a flowchart in Figure 1. Demographic and clinical data for the
participants are presented in Table 1.
The primary sample included a total of 144 participants (Sample 1a; see
Table 1 for demographic and clinical data). Data from subsets of the
participants have been published in previous studies (Buckner et al.
2004, 2005; Salat et al. 2004; Fotenos et al. 2005).
All participants in this sample were recruited from the ongoing
longitudinal study of the Washington University AD Research Center
(ADRC) using procedures approved by Washington University’s human
subjects committee. At study enrollment, participants were clinically
free of non-AD disorders that could potentially cause dementia such as
major depression, stroke, Parkinson disease, and head trauma (Berg
et al. 1998).
Trained clinicians assessed each participant for the presence and
severity of dementia based on semistructured interviews with the
participant and a knowledgeable informant (usually a spouse or adult
child) followed by a neurological examination of the participant
(Morris 1993; Morris et al. 1997). Also included in the protocol are a
health history, depression inventory, aphasia battery, and medication
inventory. The CDR staging and clinical diagnostic determinations were
made by the examining clinician. Diagnostic criteria for AD required
the gradual onset and progression of impairment in memory and in at
least one other cognitive and functional domain, comparable to
standard diagnostic criteria for probable AD (McKhann et al. 1984).
For the purposes of the present study, the resultant clinical
diagnostic categories include normal OC (CDR = 0, Mini Mental State
Examination [MMSE] 25--30, N = 115) or mild dementia of the
Alzheimer type (referred to here as AD; CDR = 1, MMSE 15--28, N =
29). In addition, we studied another sample of subjects recruited and
evaluated in the same manner who exhibited a milder level of impair-
ment (Sample 1b). Within the CDR = 0.5 category, the 2 diagnostic
groups are distinguished based on the clinical judgment of the
evaluating clinician with respect to the degree to which symptoms of
cognitive impairment impact the individual’s independent function in
daily life, as described previously: very mild AD (CDR = 0.5, MMSE 14--
30, N = 40) or incipient AD (CDR = 0.5, MMSE 24--30, N = 29) (Morris
Cortical Signature of AD
Dickerson et al.
et al. 1988, 2001; Morris 1993; Berg et al. 1998; Storandt et al. 2006).
Many of these CDR = 0.5 individuals would be classified as having mild
cognitive impairment in other settings (Morris et al. 2001; Storandt
et al. 2006).
An additional 44 participants were asymptomatic normal OC (CDR =
0, MMSE 26--30) and had both amyloid-PIB PET data available (see
below) as well as MRI data—this was Sample 1c.
Multiple (3 or 4) high-resolution structural T1-weighted magnetiza-
tion-prepared rapid gradient echo (MP--RAGE) images were acquired
on a 1.5T Siemens Vision scanner (Siemens Medical Systems, Erlingan,
Germany) with the following parameters: repetition time (TR) 9.7 ms,
echo time (TE) 4 ms, flip angle (FA) 10, inversion time (TI) 20 ms, voxel
size 1 3 1 3 1.25 mm. These data have been made openly available to
the community (http://www.oasis-brains.org/).
Additional Participant Samples
Data from 3 additional samples of nondemented OC participants and
AD patients were analyzed as part of this study. The 3 samples were
drawn from separate ongoing studies at Massachusetts General
Hospital, all of which were approved and conducted in accordance
with guidelines established by the Partners Human Research Commit-
tee. Written informed consent was obtained from each participant, and
from a caregiver for patients with AD with significant cognitive
impairment. See Table 1 for detailed demographic and clinical data on
these additional samples.
Assessments were conducted in a manner nearly identical to that
described above (details have been previously published as cited
below), with 39 participants in Sample 2 (Atri et al. 2005), 41
participants in Sample 3 (Wright, Dickerson, et al. 2007; Wright, Feczko,
et al. 2007), and 40 participants in Sample 4 (Dickerson et al. 2005;
Celone et al. 2006). The characteristics of the AD dementia participants
in these samples were as follows; see also Table 1. In Sample 2, AD
dementia participants had CDR = 0.5 (N = 10) or CDR = 1 (N = 7); mean
MMSE = 21.5 (SD = 3.9), range 12--29. In Sample 3, AD participants had
Demographic and clinical characteristics of participants
Very mild AD
115 77.2 ± 8.4 34/81
29 77.5 ± 6.5
29 78.8 ± 7.1 19/10
40 76.0 ± 6.3 18/22
35 73.7 ± 7.5
9 71.4 ± 7.5
22 78.1 ± 2.2
17 78.9 ± 3.7
29 70.3 ± 6.6 12/17
12 71.0 ± 8.9
28 74.3 ± 5.6 10/18
15 78.3 ± 6.9
29.1 ± 1.1
22.1 ± 3.5*
27.0 ± 1.6*
25.2 ± 3.8*
29.7 ± 0.3
29.3 ± 0.6
29.3 ± 0.8a
21.5 ± 3.9*a0/10/7
29.4 ± 0.9
24.6 ± 2.8*
29.6 ± 0.5
23.3 ± 4.2*
0 ± 0
5.52 ± 1.51*
1.22 ± 0.32*
3.05 ± 0.81*
0 ± 0
0 ± 0
Note: Values represent mean ± standard deviation. *P\0.001 (different from OC). BDS-IMC 5
Blessed Dementia Score Information-memory-concentration.
aMMSE scores calculated from Blessed IMC scores (Thal et al. 1986).
Figure 1. Flowchart of methodologic procedures employed in this study and specific analyses used to generate figures (Fig) and tables (Tbl). Shaded rows at bottom show the
specific subject samples (S) that were used to generate each table and figure. For example, Samples 1a and 1b were used to generate Figure 4 and Table 4 (second shaded
row). See Table 1 for details of diagnostic groups and demographic and clinical characteristics of each sample.
Cerebral Cortex March 2009, V 19 N 3 499
CDR = 0.5 (N = 2) or CDR = 1 (N = 10); mean MMSE = 24.6 (SD = 2.8),
range 20--29. In Sample 4, AD participants had CDR = 1; mean MMSE =
23.3 (SD = 4.2), range 15--30.
Samples 2 and 3 were scanned in an identical manner on 2 different
Siemens 1.5T scanners (Sample 2 on an Avanto with 12 channel Total
Imaging Matrix head coil and Sample 3 on a Sonata with 3-axis gradient
single channel head coil; Siemens Medical Systems, Erlingan, Germany).
For both samples, 2 high-resolution structural T1-weighted MP--RAGE
images were acquired with the following parameters: TR 2730 ms, TE
3.31 ms, FA 7, TI 1000 ms, voxel size 1.3 3 1 3 1 mm. Sample 4 was
scanned as follows: one high-resolution structural T1-weighted MP--
RAGE image was acquired on a 3.0T Siemens Trio scanner (Siemens
Medical Systems, Erlingan, Germany) with a 3-axis gradient head coil
with the following parameters: TR 2530 ms, TE 3.45 ms, FA 7, TI 1100
ms, voxel size 1.3 3 1 3 1 mm. For all samples, procedures for data
collection included head movement restriction using expandable foam
cushions, and automated scout and shimming procedures.
Estimation of Cortical Thickness
Methods for our surface-based analyses and estimation of cortical
thickness have been previously described in detail (Dale et al. 1999;
Fischl, Sereno, and Dale 1999; Fischl and Dale 2000; Rosas et al. 2002;
Kuperberg et al. 2003; Salat et al. 2004) and are described here only
briefly. The Freesurfer software used to perform the analyses and
visualization employed in this study, along with complete documenta-
tion, is freely available via the internet at http://surfer.nmr.mgh.harvard.
First, the multiple MP--RAGE acquisitions for each participant were
motion corrected and averaged to create a single image volume with
high contrast-to-noise (sample #4 involved a single acquisition, so this
was used for subsequent processing). The resulting averaged volume
was used to segment cerebral white matter (Dale et al. 1999) and to
estimate the location of the gray/white boundary. Topological defects
in the gray/white boundary were corrected (Fischl et al. 2001), and this
gray/white boundary was used as the starting point for a deformable
surface algorithm designed to find the pial surface with submillimeter
precision (Fischl and Dale 2000). Cortical thickness measurements
were obtained by calculating the distance between those surfaces at
each of approximately 160 000 points (per hemisphere) across the
cortical mantle (Fischl and Dale 2000). The thickness measures derived
from this technique are both valid (Rosas et al. 2002; Kuperberg et al.
2003) and reliable (Han et al. 2006; Dickerson et al. 2008).
The surface representing the gray--white border was ‘‘inflated’’
(Fischl, Sereno, and Dale 1999), differences among individuals in the
depth of gyri and sulci were normalized, and each subject’s
reconstructed brain was then morphed and registered to an average
spherical surface representation that optimally aligns sulcal and gyral
features across participants (Fischl, Sereno, and Dale 1999; Fischl,
Sereno, Tootell, et al. 1999). Thickness measures were then mapped to
the inflated surface of each participant’s reconstructed brain (Fischl,
Sereno, and Dale 1999). The data were smoothed on the surface using
an iterative nearest-neighbor averaging procedure. One hundred
iterations were applied, which is equivalent to applying a 2-dimensional
Gaussian smoothing kernel along the cortical surface with a full-width/
half-maximum of 18.4 mm. Data were then resampled for participants
into a common spherical coordinate system (Fischl, Sereno, Tootell,
et al. 1999).
Exploratory Statistical Analysis to Determine the Pattern of
Cortical Thinning in AD
Sample 1a was used to generate an exploratory map of cortical
thickness differences between nondemented OC (CDR = 0) and mild
AD (CDR = 1) participants. A statistical surface map was generated by
computing a 2-class general linear model for the effect of membership
in the AD group on cortical thickness at each point. For this
exploratory analysis, a statistical threshold of P < 0.01 was used
(uncorrected for multiple comparisons). This map reveals regions of
statistical significant cortical thinning in mild AD and was used as the
basis for definition of a priori regions that were explored in
independent data samples.
Hypothesis-Driven Statistical Analysis of Additional Samples
We next investigated the magnitude of AD-related thinning within
cortical regions identified in the exploratory analysis in 3 independent
data samples. For regions in which there was a statistical effect in
Sample 1a, an ROI label was drawn on the average cortical surface
template. These ROI boundaries followed the ‘‘AD effects’’ identified
through the exploratory analysis, not gyral or sulcal anatomic
boundaries. Figure 2 shows the statistical AD effects from the ex-
ploratory analysis, and the map in Figure 3 shows ROIs derived from
this analysis. Nine AD-signature ROIs were drawn in each hemisphere;
the effects were relatively symmetric and where differences were
present the basic size and shape characteristics of ROIs were kept
similar across hemispheres. In addition to the 9 AD-effect ROIs,
a ‘‘primary visual cortex’’ ROI label was drawn in the calcarine fissure to
serve as a control ROI. Using the spherical registration of each subject
to the template, the 10 cortical ROIs (per hemisphere) were mapped
back to individual participants. For each subject, mean cortical
thickness within each ROI was calculated by deriving an average of
all of the thickness estimates at vertices that fell within the labeled ROI.
For each subject, the resultant ROI measures of cortical thickness
were used for further statistical analysis. These ROI thickness values
were used to calculate the mean difference in the thickness of each ROI
OC, and the Cohen’s d effect sizes of AD-related thinning for each ROI.
Group comparisons were performed using analyses of variance
(ANOVAs), with a priori specified planned contrasts, to evaluate
differences between the AD and OC groups within each sample.
Analyses were repeated with age and sex as covariates to ensure that
is not correlated with head size (data not shown), so is not adjusted (i.e.,
Figure 2. The cortical signature of AD: map of cortical thinning across the
hemispheres in AD. An exploratory analysis was conducted across the entire cortical
surface to identify regional thinning in AD in Sample 1a. Surface maps of cortical
thinning were generated by assessing the influence of AD on thickness (using the
general linear model) at each vertex across the entire cortical mantle. Maps are
presented on the semi-inflated cortical surface of an average brain with dark gray
regions representing sulci and light gray regions representing gyri. Non-neocortical
regions and regions that are not part of the cortical mantle (such as the corpus
callosum and thalamus) have been excluded from the analysis. The color scale at the
bottom represents the significance of the thickness difference with yellow indicating
regions of most significant thinning in AD compared with OC. See Table 2 for
quantitative metrics of the amount of thinning in each region.
Cortical Signature of AD
Dickerson et al.
for intracranial volume). There were no hemispheric effects in these
analyses, so measures from both hemispheres were pooled to make one
measure of mean cortical thickness for each subject. Pearson correla-
tions and a multiple linear regression analysis was performed to examine
relationships between thickness ofthe 10cortical ROIsand the measure
of AD severity (the CDR Sum-of-Boxes; Morris et al. 1997). These
statistical analyses were performed using SPSS 11.0 (SPSS, Chicago, IL).
All analyses were performed with a statistical threshold for significance
of P <0.05, uncorrected for multiple comparisons.
[11C]PIB-PET Maps of Amyloid Deposition
We used [11C]PIB (Klunk et al. 2004) to image amyloid in a sample of
nondemented OC individuals (Sample 1c). Participants were imaged
using [11C]PIB on a 961 ECAT PET scanner (Siemens, Erlangen,
Germany) according to the procedures described previously (Buckner
et al. 2005; Mintun et al. 2006). PIB-PET imaging provides an in vivo
measure of human brain amyloid in plaques associated with AD (Klunk
et al. 2004; Buckner et al. 2005; Mintun et al. 2006). Individuals were
considered PIB negative if their binding potential for 4 cortical regions
(prefrontal, lateral temporal, precuneus, and gyrus rectus) was below
0.2 (Fagan et al. 2006; Mintun et al. 2006; Fotenos et al. 2008). For the
purposes of the present study, we used PIB-PET imaging to identify
a subset of 9 older individuals who were cognitively intact but harbored
significant amyloid deposition. The present classification of participants
is the same as that used by a previous study (Fotenos et al. 2008) of
Analysis of Mean Cortical Thickness
In Sample 1a, this analysis revealed an effect of AD, with the
mild AD group showing 4.5% mean cortical thinning compared
with OC (OC = 2.14 [SD = 0.08] mm, AD = 2.05 [0.11] mm;
F(1) = 26.2, P < 0.001, Cohen’s d = 1.02). Across the other
3 samples of participants, very similar effects were found. In
Sample 2, mean cortical thickness of the AD group was 5.5%
thinner than controls (OC = 2.03 [0.10] mm, AD = 1.92 [0.13]
mm; F = 11.2, P < 0.002, Cohen’s d = 1.0). In Sample 3, the AD
group’s mean cortical thickness was 6.5% thinner than controls
(OC = 2.12 [0.09] mm, AD = 2.00 [0.11] mm; F = 19.5, P <0.001,
Cohen’s d = 1.41). Finally, in Sample 4, scanned at 3.0 Tesla,
mean cortical thickness of the AD group was 6.0% thinner than
controls (OC = 2.16 [0.09] mm, AD = 2.03 [0.10] mm; F = 17.1,
P < 0.001, Cohen’s d = 1.34).
Similar analyses were also performed to investigate these
measures in the 2 subject groups with milder levels of impair-
ment (CDR = 0.5, Sample 1b). The group with very mild AD
showed effects similar to, but of a lesser magnitude than, those
of the mild AD group: 3.7% mean cortical thinning compared
with controls (very mild AD = 2.06 [0.10] mm; F = 23.6, P <
0.001, Cohen’s d = 0.87). The group with incipient AD showed
no reduction in mean cortical thickness compared with
controls (mean cortical thickness = 2.12 [0.11] mm; P = 0.32).
Regionally Specific Cortical Thinning in Mild AD:
Exploratory Analysis across the Entire Cortical Mantle
In Sample 1a, the exploratory analysis of cortical thickness
across the entire mantle revealed a set of specific regions that
Figure 3. Consistency of regional thinning in AD. ROIs (top) were generated from
exploratory analysis in subject Sample 1a (see Fig. 2) and applied to 3 new samples
of OC and AD patients (Samples 2, 3, and 4) to test the hypothesis that these regions
are thinner in AD than controls. Graphs show mean cortical thickness within each ROI
across the 4 samples, illustrating the consistency of thinning despite the differences
between the samples and MRI data acquisition (note that Sample 4 was scanned on
3.0T scanner). A primary visual cortex region was also used to illustrate minimal
effects on this region (lower right). Error bars indicate 1 standard error of the mean.
See Tables 2 and 3 for statistics. (A) Medial temporal cortex, (B) Inferior temporal
gyrus, (C) Temporal pole, (D) Angular Gyrus, (E) Superior frontal gyrus, (F) Superior
parietal lobule, (G) Supramarginal gyrus, (H) Precunes, (I) Inferior frontal sulcus, (J)
Primary visual cortex.
Cerebral Cortex March 2009, V 19 N 3 501
were thinner in AD than OC, as illustrated in Figure 2. Regions
of significant thinning were primarily located in limbic and
heteromodal association areas, including rostral medial tempo-
ral, inferior temporal, temporal pole, precuneus, inferior
parietal (supramarginal and angular gyri), superior parietal,
inferior frontal, and superior frontal cortex. There were minor
differences in the spatial location of regional thinning across
hemispheres, but generally the regions were quite consistent
bilaterally. Primary sensorimotor regions were largely spared.
Quantitative Analysis of Cortical Regions Vulnerable
We next investigated the magnitude of AD-related thinning
within each cortical region identified in the exploratory analy-
sis. Cortical ROI label locations and group mean and standard
error data are shown in Figure 3. Data for Sample 1a is shown in
the leftmost pair of bars in each graph in Figure 3. Mean
thickness, standard deviation, magnitude of group differences
(in mm), percent thinning in AD compared with controls, and
Cohen’s d effect sizes are shown in Table 2.
Thinning due to AD was most prominent (in mm) in the
rostral medial temporal cortex, with a mean magnitude of
thinning of more than 0.4 mm (14% thinning in AD compared
with OC). Other regions with more than 0.2 mm thinning in-
cluded inferior temporal, temporal pole, inferior parietal (both
angular and supramarginal gyri), and superior frontal regions,
which ranged from 8.1% to 11.6% thinner in AD than OC. The
regions with a relatively smaller magnitude of thinning (0.16--
0.19 mm, or 7--8%) included precuneus, inferior frontal, and
superior parietal regions. There was no significant thinning in
the primary visual cortex (0.03 mm [2.2%], P = 0.19).
Consistency of Regional Cortical Thinning in Mild AD:
Quantitative Analysis of Cortical Regions in 3 Separate
The consistency of regionally specific cortical thinning was
investigated in 3 additional samples of AD patients and OC
individuals. This analysis was unbiased, as it employed cortical
ROIs defined as above from Sample 1a and applied to separate
samples of participants (by mapping each cortical ROI label
from the average surface template to each individual via the
spherical average surface, as described in Methods).
The magnitude of AD-related thinning within these cortical
regions was remarkably consistent across the 3 additional sam-
ples. Figure 3 illustrates the mean thickness and standard error
within regions across all 4 samples. Table 3 provides details of
measurements from Samples 2, 3, and 4, showing magnitude of
group difference (AD vs. OC), percent thinning in AD, and
Again, across all 3 additional samples, the medial temporal
cortex showed the largest magnitude of thinning of all regions
within each sample, ranging from 0.26 to 0.55 mm thinner in
AD than OC. Temporal pole and inferior parietal regions
showed consistently large effects, whereas inferior temporal,
superior parietal, precuneus, and frontal regions were some-
what less consistent with respect to magnitude of thinning.
Primary visual cortex again showed no effects in these 3
An additional analysis was performed to investigate thickness
differences between the 4 samples. A main effect was found for
Sample 2, with mean cortical thickness biased toward slightly
thinner estimates without an interaction with diagnostic group.
Detection of Attenuated Regional Cortical Thinning in
Individuals with Milder Symptoms of AD
We next investigated a sample (Sample 1b) of individuals with
milder symptoms of AD to determine whether a lesser
magnitude of cortical thinning would be detectable within
regions known to be vulnerable to AD from the analyses above.
All of these participants had an overall CDR rating of 0.5, but
some were diagnosed with very mild AD (n = 40) and others
were diagnosed with incipient AD (n = 29). See Table 1 for
demographic and clinical data on these participants. The AD-
signature cortical ROI labels, as defined from Sample 1a, were
again applied to this sample of individuals with very mild AD or
AD-related thinning was detected within these cortical
regions in a remarkably consistent manner across the 2 milder
groups. Most of the regions demonstrated a pattern suggestive
of progressive thinning across the 4 groups, as illustrated in
Figure 4. The primary visual cortex showed no such effect. As
depicted in Table 4, statistical analysis demonstrated that the all
regions except the primary visual cortex were thinner in the
very mild AD group than OC. Inspection of the percent
thinning in very mild AD reveals a lesser degree of thinning in
all regions than in the mild AD group. The magnitude of thin-
ning in the incipient AD group is relatively small in all regions,
with most differences in regional thickness compared with OC
not reaching statistical significance (except angular and supra-
marginal gyri).The primaryvisual cortexROI shows
Quantitative metrics of thinning by region within sample #1
RegionMean thickness (mm) (SD) Group meanPercentEffect size
OCMild AD Difference
Note: Effect size 5 Cohen’s d effect size. All regions are significantly thinner in AD than OC (P\
0.01) except for primary visual, which is not statistically different between OC and AD groups.
Quantitative metrics of thinning by region within 3 additional samples of participants
Region Mean difference (mm)Percent thinning Effect size
Note: Effect size 5 Cohen’s d effect size. Regions of significant thinning in AD as compared with
OC (*P \ 0.05; **P \ 0.005; ***P \ 0.001).
Cortical Signature of AD
Dickerson et al.
a remarkable degree of reliability with respect to absolute
cortical thickness across the groups (lower right graph in Fig.
4). Figure 4 illustrates the mean thickness and standard error
within regions across the very mild AD and incipient AD
groups, with the OC and mild AD groups shown for
comparison. Table 4 provides details of measurements from
these 2 groups of participants.
Relationship of Regional Cortical Thinning to Severity of
We analyzed the relationship of the regional measures of cor-
tical thickness to severity of symptoms of cognitive impairment
within all the demented participants from Washington Univer-
sity (incipient AD, very mild AD, mild AD; N = 97). Correlational
analyses were run with the CDR Sum-of-Boxes (CDR-SB) as the
dependent measure. Although the overall CDR ratings (0.5 or 1)
of these individuals indicated that they were very mildly or
mildly demented, the CDR-SB provides a finer grading of
impairment within this spectrum, ranging in this sample of
97 participants between 0.5 and 9.0. CDR-SB was inversely
correlated with the thickness of a number of regions,
including medial temporal, inferior temporal, temporal pole,
angular gyrus, superior parietal, superior frontal, and inferior
frontal cortex (Pearson R values ranging from –0.24 through –
0.38, all P values
< 0.02). These findings indicate that
a greater level of clinical impairment is associated with
a larger magnitude of thinning within these cortical regions. A
stepwise multiple linear regression analysis was performed
with each of these regions as independent variables and
CDR-SB as the dependent variable. This model indicated that
a linear combination of medial temporal, inferior temporal,
and inferior frontal regions was the best predictor of CDR-SB
(R = 0.51, F3,93= 11.2, P < 0.001).
These correlative analyses with CDR-SB were also examined
within the diagnostic groups. The mild AD group demonstrated
trends for superior (R = –0.35, P = 0.06) and inferior frontal (R =
–0.32, P = 0.08) regions, whereas the very mild AD group
demonstrated an effect for the medial temporal cortex (R = –
0.34, P = 0.03) and a trend for the angular gyrus (R = –0.28, P =
0.08). There were no effects in the incipient AD group.
Pooled Multicenter Mapping Analysis of the Magnitude of
Cortical Thinning in Mild AD
For this analysis, a general linear model was constructed that
included all 4 mild AD and all 4 OC groups. Each participant
contributed a cortical thickness estimate mapped to the group
using spherical registration. The contrast of interest was AD
versus OC, and was weighted according to the number of
participants in each group. The parameter estimate of differ-
ence in cortical thickness between AD and OC was then used
to generate a map of the magnitude of cortical thinning in AD.
Note that this map is quantitative revealing the estimated size
(in mm) of cortical thinning. Thus, this map reflects our best
estimate of the topography and magnitude of cortical thinning
in mild AD.
Figure 5 illustrates the results of the pooled analysis, which
was undertaken to map the magnitude of thinning across
the entire cerebral cortex in Samples 1a, 2, 3, and 4 comparing
AD with OC (total N = 267). Areas of the cortex in which
the magnitude of AD-related thinning exceeds 0.15 mm are
shown, using a color scale to indicate the magnitude of
thinning. The spatial topography of regional thinning parallels
that illustrated with the statistical map of Sample 1a alone
(Fig. 2). The areas with the greatest magnitude of thinning
across this large multicenter dataset, such as medial temporal
cortex, are quite similar to those indicated by the ROI analyses
of thinning within each sample above. The congruence of the
effects detected with this pooled analysis and those detected
above using hypothesis-driven replication samples supports the
feasibility of pooled analyses of cortical thickness in multisite/
multiscanner data using the high-throughput computational
analysis system. A Supplementary Table provides the estimates
of the magnitude of thinning in AD for the entire pooled
Detection of Regional Cortical Thinning in Amyloid-
Positive Asymptomatic Older Individuals
We next investigated a sample (Sample 1c) of individuals
evaluated in the same fashion as that described above for
Sample 1a, and who were considered to be asymptomatic OC
(CDR = 0). Based on PIB-PET scans, they were dichotomized
into OC participants with (amyloid-positive, N = 9) or without
(amyloid-negative, N = 35) PIB amyloid binding. We sought to
determine whether subtle cortical thinning might be detect-
able within regions known to be vulnerable to AD from the
analyses above. See Table 1 for demographic and clinical data
on these participants. The AD-signature cortical ROI labels, as
defined from Sample 1a, were again applied to this sample of
amyloid-positive or amyloid-negative OC individuals.
Quantitative metrics of thinning by region within incipient and very mild AD participants
Region Mean thickness (mm) (SD) Percent thinning (vs. OC)Effect Size (vs. OC)
OC Incipient AD Very mild AD Incipient ADVery mild AD Incipient ADVery mild AD
Note: Superscripts indicate that the group is significantly different from OC (C), incipient AD (I), very mild AD (V), or mild AD (A) (P\0.05, uncorrected). Percent thinning is in comparison to OC group
(data presented in Table 3). Effect size is Cohen’s d.
Cerebral Cortex March 2009, V 19 N 3 503
AD-related thinning was detected within the temporal pole
(5.8% thinning, P = 0.04) and a trend was present in the
superior frontal cortex (4.6% thinning, P = 0.06) in the amyloid-
positive OC group compared with the amyloid-negative OC
group. Most other regions demonstrated a pattern suggestive of
subtle thinning (see Fig. 7), but the small sample size lacked
power for statistical demonstration of effects. Thus, the
thickness measures from all 9 ROIs were averaged to create a
single mean ‘‘AD cortical signature’’ thickness measure. A trend
toward thinning in this mean AD cortical signature measure
was present in the amyloid-positive OC group compared with
the amyloid-negative OC group (P = 0.09). This finding was
further supported by a post hoc comparison that demonstrated
thinning in the mean AD cortical signature measure of the
amyloid-positive OC group compared with the larger OC
(amyloid status unknown, N = 115) group from Sample 1a (P <
0.05). Mean thickness of the entire cortex in the amyloid-
positive group (2.17 ± 0.11 mm) did not differ from that of the
amyloid-negative group (2.13 ± 0.7 mm) nor from that of the
larger OC group from Sample 1a (all P values > 0.19). Figure 6
illustrates the AD cortical signature measure (mean and
standard error of the mean) across the amyloid-positive OC,
amyloid-negative OC, and other 4 groups from Samples 1a, 1b,
The pathology of AD typically has a predilection for limbic
allocortical and heteromodal association neocortical areas
(Brun and Gustafson 1976; Arnold et al. 1991; Braak and Braak
1991). Quantitative analysis of MRI has been used to identify, in
living AD patients, abnormalities in the normal anatomic
properties—such as volume, gray matter density, and thick-
ness—of the cerebral cortex using manual a priori ROI-based
MRI techniques (Jack et al. 1997; Juottonen et al. 1998;
Bobinski et al. 1999; Killiany et al. 2000; Dickerson et al. 2001)
and more recently using semiautomated exploratory mapping
techniques (Baron et al. 2001; Thompson et al. 2001; Good
et al. 2002; Scahill et al. 2002; Karas et al. 2003; Buckner et al.
2005; Lerch et al. 2005; Du et al. 2007; Whitwell et al. 2008). In
the present work, we pursued a novel approach combining
exploratory mapping and a priori ROI-based measurement
techniques, first by performing an exploratory analysis of
cortical thickness across the entire cortical mantle to map the
‘‘cortical signature’’ of regional thinning in mild AD and then by
using this map to generate ROIs to measure, in an a priori
fashion, the consistency of regional cortical thinning in mul-
tiple independent samples of mild AD patients and the
presence of thinning in milder forms of AD.
These additional analyses revealed a lesser magnitude of thin-
ning in patient groups with milder symptoms of AD consistent
with mild cognitive impairment (Morris et al. 2001; Storandt
et al. 2002, 2006). Even within AD patients spanning the
circumscribed spectrum of incipient, very mild, and mild AD,
the thickness of many of the critical cortical regions correlates
with the relative severity of clinical impairments. Of particular
interest, a very mild degree of cortical thinning in these regions
was detected in amyloid-positive OC (CDR = 0) individuals,
indicating that subtle anatomic change in a pattern consistent
with AD begins to occur in asymptomatic individuals who
harbor AD pathology. To provide a stable estimate of cortical
thinning in AD, Figure 5 maps a pooled analysis of the
Figure 4. Thinning in cortical ROIs in incipient and very mild AD participants. ROIs
were generated from exploratory analysis in subject Sample 1a (see Fig. 2, same
ROIs as used in Fig. 3) and applied to a new sample of Incipient and very mild AD
patients (CDR 5 0.5, Sample 1b) to test the hypothesis that these regions are thinner
in the mildest clinical stages of AD than controls. Graphs show mean cortical
thickness within each ROI across the 2 mildly impaired samples, in comparison to
controls and mildly impaired (CDR 5 1) AD patients (Sample 1a). A primary visual
cortex region was also used to illustrate minimal effects on this region (lower right).
Error bars indicate 1 standard error of the mean. See Table 3 for statistics. (A) Medial
temporal cortex, (B) Inferior temporal gyrus, (C) Temporal pole, (D) Angular Gyrus, (E)
Superior frontal gyrus, (F) Superior parietal lobule, (G) Supramarginal gyrus, (H)
Precunes, (I) Inferior frontal sulcus, (J) Primary visual cortex.
Cortical Signature of AD
Dickerson et al.
magnitude of cortical thinning in all 76 mild AD patients
compared with all 194 OC participants from the 4 samples.
Taken collectively, these observations show that this high-
throughput, semiautomated MRI data analysis procedure for
quantifying cortical thickness is feasible for pooled analysis of
multisite data, such as is typical for clinical trials or other large
multicenter studies. The method is sensitive enough to detect
subtle changes in cortical regions specifically affected by AD
prior to the onset of even the mildest symptoms.
AD-Related Regional Thinning Parallels the Topography
The spatial topography of cortical thinning in AD that we
observed in vivo in the present study is consistent with the
spatial distribution of neurodegenerative change known to
occur in the disease from post-mortem studies (Brun and
Gustafson 1976; Arnold et al. 1991; Braak and Braak 1991) and
from recent in vivo PET investigations using tracers that bind to
pathologic proteins (Klunk et al. 2004; Buckner et al. 2005;
Mintun et al. 2006; Small et al. 2006). These regions also
represent the major limbic and heteromodal cortical areas
The spatial topography of regional cortical thinning that we
identified in mild AD is consistent with previous observations
using voxel-based morphometry (Baron et al. 2001; Karas et al.
2003; Bozzali et al. 2006; Whitwell et al. 2008) and similar
techniques (Thompson et al. 2001; Scahill et al. 2002; Buckner
et al. 2005; Apostolova et al. 2007) as well as 2 previous
investigations using cortical thickness techniques (Lerch et al.
2005; Du et al. 2007). Generally, these efforts have converged
upon a similar pattern of atrophy that is present in the medial
temporal, lateral temporoparietal, and midline parietal regions,
with variable findings in frontal regions. The major contribution
of the present work relates to the demonstration of a consis-
tent, stable estimate of the localization of relatively prominent
cortical thinning in a large multicenter sample of mild AD
patients, which can be used to predict the presence of thinning
in milder and presymptomatic patient groups.
The magnitude of thinning within some regions is relatively
large given the patients’ mild level of dementia—even at early
clinical stages of the illness, several regions are 10--20% thinner
than normal. The regions with a larger degree of thinning—
medial temporal, inferior temporal, temporal pole, inferior
parietal, and posterior cingulate/precuneus—are those typically
thought to be affected earliest in the course of the disease on
the basis of the burden of pathologic accumulation (Hyman
et al. 1984; Van Hoesen et al. 1986; Arnold et al. 1991; Arriagada,
Growdon, et al. 1992; Arriagada, Marzloff, et al. 1992), neuronal
loss, and gliosis (Brun and Gustafson 1976). A number of pre-
vious studies of cortical atrophy in AD have focused on spatial
localization but have not estimated the magnitude of effects
(Baron et al. 2001; Frisoni et al. 2002; Scahill et al. 2002; Buckner
et al. 2005). Estimates of the magnitude of cortical atrophy have
demonstrated the largest effects in temporal and parietal cortex
(Karas et al. 2004; Du et al. 2007), with 15--20% thinning in
caudal lateral temporal and posterior parietal cortex (Thomp-
son et al. 2001, 2003; Lerch et al. 2005; Apostolova et al. 2007) as
well as medial temporal cortex (Lerch et al. 2005). The results
of the present study are quite consistent with these previous
studies, and contribute by showing that similar but milder
effects are present in patients with clinically milder forms of AD.
Figure 5. Magnitude of cortical thinning in AD in millimeters, derived from pooled
analysis of 4 samples of participants (Samples 1a, 2, 3, and 4). Map shows
parameter estimate of amount of thinning across cerebral cortex from general linear
model analysis of 267 participants, showing areas where cortex is at least 0.15 mm
thinner in AD group than OC group. Color scale shows magnitude of thinning from
0.15 mm (red) through 0.2 mm (yellow) in AD compared with OC.
Figure 6. Mean thickness of AD cortical signature regions is decreased in amyloid
(PIB)-positive OC (CDR 5 0), and demonstrates progressive thinning as the
symptoms of AD dementia become progressively more prominent across the
spectrum of Incipient, very mild, and mild AD dementia. Bars represent mean
thickness of the 9 cortical regions shown in Figure 2, normalized for age and
standardized to Z scores (y axis). Error bars indicate 1 standard error of the mean. The
leftmost 3 groups are all OC (CDR 5 0, MMSE 25--30), ordered by PIB status
unknown (unk) (N 5 115), PIB negative (N 5 35), and PIB positive (N 5 9). The
rightmost 3 groups are all PIB status unknown, but are progressively more impaired
with clinical symptoms ranging from incipient AD (CDR 5 0.5/CDR-SB 5 1.2, N 5
29), very mild AD (CDR 5 0.5/CDR-SB 5 3.5, N 5 40), and mild AD (CDR 5 1/CDR-
SB 5 5.5, N 5 29). Figure includes data from Samples 1a, 1b, and 1c.
Cerebral Cortex March 2009, V 19 N 3 505
MRI Measures of Regional Cortical Thinning in AD
Correlate with Severity of Symptoms of the Disease
Previous studies have shown that AD-related thinning of
particular cortical regions correlates with worse performance
on cognitive testing in patients spanning a relatively broad
spectrum of clinical impairment, including a sizable number of
moderately demented patients (Lerch et al. 2005; Du et al.
2007). In the present study, we specifically focused on the
relatively narrow clinical spectrum of incipient, very mild, and
mild AD, and investigated the relationship of regional cortical
thickness to CDR-SB. The CDR-SB is a finely graded measure
that reflects the clinician’s impression of the relative severity of
cognitive symptoms that affect memory, orientation, judgment,
and problem-solving, and daily function at home and in the
community. It is widely used in clinical research, including
trials of putative therapeutic agents. The CDR-SB is strongly
associated with cortical thickness in many of the regions
identified in this study, suggesting that progressive worsening
of cognitive impairment within the very mild to mild spectrum
of AD is associated with progressive thinning of specific
heteromodal regions of the cortex. Because the CDR-SB is
a clinical measure of impairment primarily reflecting symptom
severity in daily life, our results support the clinical validity of
regional cortical thickness measures as an imaging biomarker
of AD severity.
Although the data in this study are cross-sectional, infer-
ences can be made regarding the sequence of involvement of
the cortical regions in the course of AD. Based on the analysis
comparing the 4 groups of participants from Sample 1a and 1b,
some regions, particularly ventromedial temporal and inferior
parietal cortex, exhibit thinning even in the mildest (incipient
AD) group, suggesting very early involvement. Other regions,
particularly superior parietal and frontal cortex, do not show
appreciable thinning until symptoms are more prominent (very
mild to mild AD dementia), suggesting that they become
involved later in the course of the disease (Scahill et al. 2002;
Buckner et al. 2005). Similarly, from the within-group cor-
relational analyses, symptom severity (CDR-SB) within the very
mild AD patient group correlates with medial temporal and
inferior parietal thinning, whereas symptom severity within the
mild AD patient group correlates with thinning in frontal
regions, again suggesting temporoparietal involvement prior to
frontal involvement. These inferences are consistent with those
made from pathologic studies (Arriagada, Marzloff, et al. 1992;
Figure 7. Consistent subtle thinning appears to be present in many cortical ROIs in amyloid (PIB)-positive OC (CDR 5 0) compared with amyloid (PIB)--negative controls. ROIs
were generated from exploratory analysis in subject Sample 1a (see Fig. 2, same ROIs as used in Fig. 3) and applied to a new sample of PIBþ and PIB- controls (CDR 5 0,
Sample 1c) to test the hypothesis that these regions undergo subtle thinning in asymptomatic AD. Bars represent mean thickness of each region shown in Figure 2, normalized for
age and standardized to Z scores. Error bars indicate 1 standard error of the mean. (A) Medial temporal cortex, (B) Inferior temporal gyrus, (C) Temporal pole, (D) Angular Gyrus,
(E) Superior frontal gyrus, (F) Superior parietal lobule, (G) Supramarginal gyrus, (H) Precunes, (I) Inferior frontal sulcus.
Cortical Signature of AD
Dickerson et al.
Braak et al. 1998), but longitudinal MRI data will be required for
Detection of cortical thinning in asymptomatic amyloid-
The development of technology to image fibrillar amyloid
deposits in living individuals (Klunk et al. 2004) has led to the
confirmation of findings from post-mortem studies (Tomlinson
et al. 1968; Price et al. 1991; Bennett et al. 2006) that amyloid
(Buckner et al. 2005; Mintun et al. 2006). The topographic
distribution of amyloid in the neocortex appears to overlap in
many respects that of atrophy in AD (Buckner et al. 2005).
We demonstrate here that subtle thinning is present in some
AD cortical signature ROIs in a group of asymptomatic OC in-
dividuals who are amyloid-positive (Fig. 6). An aggregate
measure of the thickness of the AD cortical signature regions
in these asymptomatic older individuals revealed subtle thin-
ning in comparison to the large group (N = 115) of OC
individuals from Sample no. 1 whose amyloid status is un-
known. The ability to detect thinning in these cortical regions
in asymptomatic amyloid-positive individuals suggests that the
approach to regional cortical thickness measurement outlined
here may be useful as a biomarker of early disease, and it will be
of great interest to follow such individuals longitudinally with
both imaging and clinical assessments. It will also be important
to demonstrate whether this putative imaging biomarker has
reasonable sensitivity and specificity at the individual subject
Regional Cortical Thinning in Mild AD is Consistent
across 4 Patient Samples
The consistency of regional cortical thinning across the 4
samples of mild AD patients is remarkable, despite a variety of
sample- and instrument-related factors that could have con-
tributed to variability. Sample-related factors that could in-
crease variability of cortical thinning in AD include severity of
clinical impairment, which in this study is relatively similar
across the samples based on CDR and mental status test scores
(yet these clinical measures themselves are associated with a
certain level of unreliability across sites). Because diagnoses
have been made clinically, the probable inclusion of some
individuals in each sample with other pathologies in addition to
(or instead of) AD could also increase variability of cortical
thickness measures. Moreover, variability in cortical thickness
across normal participants as well as AD patients can be
influenced by age and sex (Salat et al. 2004), which do differ in
these samples and although controlled for statistically may still
have exerted subtle influence. Finally, and potentially most
importantly, MRI instrument-related factors may contribute to
variability, including scanner model, head coil, pulse sequence,
and field strength. Across the 4 samples, the scanners were all
made by the same manufacturer and employed versions of the
same sequence, but the scanner models, head coils, and
software operating systems differed, and one sample was
scanned at 3.0 Tesla, whereas the others were scanned at 1.5
Tesla. Yet the variability in cortical thickness measures across
the samples was remarkably low, as illustrated by the medial
temporal cortex, the thickness of which ranged between 2.9
and 3.0 mm in the control groups of all 4 samples (Fig. 3, upper
left graph). Variability within a single sample appears even
lower, as can be seen by examining the primary visual cortex
measure in the Washington University sample across the 4
clinical groups, which is centered almost exactly on 1.5 mm
(Fig. 4, lower right graph). There are some regions in which
variability of thinning across samples is higher, particularly
superior parietal and inferior temporal, the origins of which are
unclear but may relate to differences in the clinical character-
istics of the samples, or to heterogeneity of levels of pathology.
Further studies of the contributors to variability in cortical
thickness estimates will be useful to better understand the
potential effects of factors that did not vary in this study, such
as scanner manufacturer or sequence (Han et al. 2006;
Dickerson et al. 2008).
The consistency of AD-related cortical thinning across the
multiple subject samples strongly supports the notion that
pooling of multisite MRI data is feasible for cortical thickness
analysis (Mueller et al. 2005; Murphy et al. 2006). Further
support for this point is presented in Figure 5, which illustrates
the cortical map derived from a combined analysis of the 267
participants in all 4 mildly impaired (CDR = 1) samples. Regions
in which the thickness of the cerebral cortex of AD patients is
at least 0.15 mm thinner than OC are graded in terms of degree
of thinning. This map illustrates the spatial topography of the
effects quantified in Tables 3 and 4, showing that medial
temporal cortex has the greatest magnitude of thinning,
followed by temporal pole, inferior temporal, and inferior
parietal cortex. Because it encompasses a large number of
participants drawn from multiple samples, we believe it is the
best current estimate of the degree of regional cortical thinning
in mild AD. The map in Figure 5 depicts a spatial distribution of
thinning magnitude that is remarkably similar to the map in
Figure 2, which shows the statistical significance of the general
linear model comparing thickness in AD versus OC. Regions
may differ between the 2 maps because of variance, with some
regions with relatively prominent thinning showing lesser
statistical effects because of greater variance (e.g., posterior
cingulate). Comparison of these 2 maps again reinforces the
point that pooled analysis of multiple samples of MRI data can
be used to robustly detect disease-related effects.
Value of High-Throughput Automated MRI Data Analysis
The MRI data analysis procedure used here to quantify cortical
thickness in the 380 scans in the present study is nearly fully
automated, with manual operator involvement at a few key
processing steps for checking and minor corrections to, for
example, the skull stripping procedure. Thus, this high-
throughput data analysis system will likely lend itself well to
analyses of large data sets from clinical trials or studies such as
the ADNI. The quantitative measures of the thickness of the AD
cortical signature regions identified in this study can be derived
for individual participants and compared with a control group
to assist in diagnosis or to establish a baseline for longitudinal
An important aspect of the analytic approach used in this
study is that the ROIs were localized based on an exploratory
analysis of the ‘‘disease effect’’ of AD across the entire cortical
mantle without the use of a priori constraints tied to particular
anatomic features of the cortex. That is, the ROIs were not
delimited based on gyral crowns, sulcal fundi, or other
elements of cortical folding patterns often used to demarcate
cortical ROIs. The generation of ‘‘disease localizer’’ ROIs from
an initial exploratory analysis, followed by the use of such
localizers to test hypotheses in separate participant samples, is
Cerebral Cortex March 2009, V 19 N 3 507
analogous to the use of ‘‘functional localizers’’ in functional
neuroimaging studies. Just as functionally specific cortical re-
gions may not obey the constraints of cortical folding patterns
(Eickhoff et al. 2006), neurodegenerative diseases may selec-
tively affect subregions within larger traditional anatomic
regions (e.g., precuneus), or may traverse the gyral or sulcal
boundaries of ROIs defined using such landmarks.
Although a strength of the present study is its focus on mild
clinical stages of AD, important limitations include the lack of
longitudinal data and that the clinical diagnosis of AD is not
supported by other imaging markers or by autopsy. It will be
important to perform retrospective analyses of MRI data from
individuals who have been demonstrated by autopsy to have
definite AD with a typical pattern of pathology. It will also be of
great interest to perform multimodal in vivo studies combining
MRI measures of cortical thickness with imaging markers of
pathology (Buckner et al. 2005). It is possible that in vivo path-
ologic markers may indicate, with a high degree of specificity,
which individuals harbor AD pathology, but that MRI-derived
measures of cortical thinning may be sensitive predictors of the
emergence of clinical symptoms, but this hypothesis will
require focused investigation.
Possible Biological Contributors to Cortical Thinning
Studies of post-mortem tissue have shown that thickness is
reduced in regions of the cerebral cortex that are affected
pathologically in AD (Gomez-Isla et al. 1996; Regeur 2000).
Although a few investigations have demonstrated that MRI-
derived hippocampal volume correlates with neurofibrillary
tangle burden in AD patients (Gosche et al. 2002; Jack et al.
2002; Silbert et al. 2003; Csernansky et al. 2004), the histologic
determinants of cortical thinning are unknown. Some regions
with prominent thinning identified in the present study are
primarily affected by neurofibrillary tangles early in the course
of the disease and to a much lesser degree by plaques (e.g.,
medial temporal cortex), whereas others carry a heavy burden
of both major pathologic markers of AD (e.g., temporal pole
and rostral inferior temporal gyrus) (Brun and Gustafson 1976;
Arnold et al. 1991; Braak and Braak 1991; Arriagada, Marzloff,
et al. 1992). It is notable that regions in which amyloid
deposition tends to be prominent from PIB imaging data
(prefrontal, gyrus rectus, precuneus, lateral temporal) are not
areas in which prominent thinning is found. Although cortical
thinning may be an indicator of the burden of neurofibrillary
tangles, neuritic plaques, or other pathology, it is likely a more
global indicator of the disruption of the healthy anatomic
configuration of the cortical mantle. This may be a sign of the
loss of neuronal, glial, or other important cellular components
such as neuropil volume, which reflects synaptic numbers and
extent of dendritic branching, both of which are markedly
reduced early in the course of AD (Coleman and Flood 1987;
DeKosky and Scheff 1990; Scheff et al. 1990; DeKosky et al.
1996; Coleman et al. 2004) and relate to degree of cognitive
impairment (Terry et al. 1991). Higher-resolution MRI data
(Schleicher et al. 2005) will probably be required to test
hypotheses (Arnold et al. 1991) about laminar-specific patterns
of abnormalities in AD and related disorders.
materialcan be foundat: http://www.cercor.
National Institute on Aging grants (K23-AG22509, P50-
AG05134, P50-AG05681, and P01-AG03991, R01-AG29411,
R21-AG29840); National Institute of Neurological Disorders
and Stroke grants (R01-NS042861, National Center for Research
Resources P41-RR14075, U24-RR021382); the Alzheimer’s
Association; Howard Hughes Medical Institute; and the Mental
Illness and Neuroscience Discovery Institute.
We thank the faculty and staff of the Washington University ADRC, the
Massachusetts ADRC, and the Memory Disorders Unit of Brigham and
Women’s Hospital. We thank the staff at the Martinos Center for
Biomedical Imaging, particularly Mary Foley, Larry White, and Jill Clark,
for their technical expertise. We express special appreciation to
the participants in this study and their families for their valuable
contributions, without which this research would not have been
possible. Conflict of Interest: None declared.
Address correspondence to Brad Dickerson, MD, MGH Gerontology
Research Unit, 149 13th St, Suite 2691, Charlestown, MA 02129, USA.
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