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Progression of Corpus Callosum Atrophy in Alzheimer Disease
Stefan J. Teipel, MD;
Wolfram Bayer, MD;
Gene E. Alexander, PhD;
York Zebuhr, MD;
Diane Teichberg;
Luka Kulic, MD;
Marc B. Schapiro, MD;
Hans-Jürgen Möller, MD;
Stanley I. Rapoport, MD;
Harald Hampel, MD
Arch Neurol. 2002;59:243-248.
ABSTRACT
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Background Atrophy of the corpus callosum in the absence of primary white matter
degeneration reflects loss of intracortical projecting neocortical pyramidal
neurons in Alzheimer disease (AD).
Objectives To determine individual rates of atrophy progression of the corpus callosum
in patients with AD and to correlate rates of atrophy progression with clinical
disease severity and subcortical disease.
Methods Magnetic resonance imaging–derived measurements of corpus callosum
size were studied longitudinally in 21 patients clinically diagnosed as having
AD (mean observation time, 17.0 ± 8.5 months) and 10 age- and sex-matched
healthy controls (mean observation time, 24.1 ± 6.8 months).
Results Corpus callosum size was significantly reduced in AD patients at baseline.
Annual rates of atrophy of total corpus callosum, splenium, and rostrum were
significantly larger in AD patients (-7.7%, -12.1%, and -7.3%,
respectively) than in controls (-0.9%, -1.5%, and 0.6%, respectively).
Rates of atrophy of the corpus callosum splenium were correlated with progression
of dementia severity in AD patients ( = 0.52, P<.02).
The load of subcortical lesions at baseline (P<.05)
predicted rate of anterior corpus callosum atrophy in healthy controls. Rates
of atrophy of corpus callosum areas were independent of white matter hyperintensity
load in patients with AD.
Conclusions Measurement of corpus callosum size allows in vivo mapping of neocortical
neurodegeneration in AD over a wide range of clinical dementia severities
and may be used as a surrogate marker for evaluation of drug efficacy.
INTRODUCTION
THE FIBERS of the corpus callosum arise predominantly from large pyramidal
neurons in layers III and V of association neocortex.1-2
These neurons form a subset of the intracortical projecting pyramidal neurons
that have been shown in neuropathologic studies on postmortem brain specimens
to be early and specifically affected by Alzheimer disease (AD) pathological
characteristics.3-4 Consistent
with the dropout of the callosally projecting neurons, several studies5-12
reported significant atrophy of the corpus callosum in AD. We recently described
a regional pattern of corpus callosum atrophy in AD that was independent of
primary white matter degeneration and was related to clinical stages of disease.13-14 Atrophy of specific areas of the
corpus callosum is correlated with the pattern of cortical metabolic decline
as measured by positron emission tomography.12, 15
On this basis, we propose region-specific corpus callosum atrophy as an indirect
marker for the loss of intracortical projecting neurons.
In the present study, we used structural magnetic resonance imaging
(MRI) to investigate the longitudinal course of regional corpus callosum atrophy
in 21 AD patients compared with 10 healthy, age- and sex-matched control subjects.
We investigated whether progression of corpus callosum atrophy was related
to progression of clinical disease severity in individual patients. In addition,
we assessed whether the load of subcortical lesions at baseline would predict
rates of atrophy progression in AD or healthy aging. To our knowledge, this
is the first study to show progression of corpus callosum atrophy in AD and
healthy aging.
PATIENTS AND METHODS
PATIENT SELECTION
We studied at baseline 27 patients (mean ± SD age, 69.2 ±
9.3 years; 13 women and 14 men) with the clinical diagnosis of probable AD
according to the National Institute of Neurological and Communicative Disorders
and Stroke and the Alzheimer's Disease and Related Disorders Associations
criteria.16 For comparison, 28 healthy volunteers
(68.2 ± 8.5 years; 15 women and 13 men) were selected. Groups were
matched for age and sex.
With the exception of 8 AD patients and 1 healthy control subject, all
subjects had been included in previously published cross-sectional studies
on corpus callosum atrophy in AD.13-15
Cognitive impairment in the AD patients was assessed using the Mini-Mental
State Examination (MMSE).17 Mean ± SD
disease duration was 6.4 ± 3.0 years in the AD patients, with an average
age of onset of 62.8 ± 8.3 years. Subgroups of 21 AD patients and 10
controls were studied longitudinally with MRI. Two patients had severe (MMSE
score <10), 10 patients had moderate (MMSE score  10 but <20), and
9 patients had mild (MMSE 20) dementia. Six patients from the cross-sectional
group had not been included in the longitudinal analysis. Three patients were
too severely impaired to undergo MRI at follow-up; 1 of these patients died
2 years after MRI and was confirmed to have AD by autopsy. Two patients were
followed up with a different MRI sequence. One patient who was moderately
impaired at baseline did not return for follow-up. The cross-sectional group
and the longitudinal subgroup of AD patients were not different in sex distribution
or age (P = .9), but the MMSE score was marginally
different between groups with higher values in the longitudinal subgroup (P = .09). Fourteen AD patients and all 10 control subjects
were studied twice with MRI; 6 AD patients underwent 3 MRI scans; and 1 AD
patient underwent 4 MRI scans. The AD patients were followed up between 5.1
and 31.3 months (mean ± SD, 17.0 ± 8.5 months), and the healthy
controls were followed up between 11.9 and 31.7 months (24.1 ± 6.8
months). Mean observation time was significantly shorter in the AD group compared
with controls (t29 = -2.3, P<.03). Two MRI scans from 2 AD patients were discarded
because of unsatisfactory image quality because of movement artifacts. In
both cases, the scans were the first in a series of 3 MRI scans. Clinical
and demographic data for the longitudinal group are presented in Table 1.
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Table 1. Clinical and Demographic Data at Baseline for the Longitudinal
Group
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Significant medical comorbidity in the AD patients and controls was
excluded by history, physical and neurologic examination, psychiatric evaluation,
chest x-ray examination, electrocardiogram, electroencephalogram, brain MRI,
and laboratory tests (complete blood cell count; erythrocyte sedimentation
rate; electrolytes, glucose, blood urea nitrogen, creatinine, liver-associated
enzymes, cholesterol, high-density lipoprotein, triglycerides, antinuclear
antibodies, and rheumatoid factor measurement; VDRL test; human immunodeficiency
virus test; serum B12 and folate measurement; thyroid function
tests; and urine analysis). All subjects were free from clinical risk factors
of cerebrovascular disease such as hypertension and diabetes. All patients
were free of specific antidementive treatment. All subjects or the holders
of their durable power of attorney signed consent forms to undergo MRI and
neuropsychological assessment for clinical investigation and research. The
protocol was approved by the National Institute of Neurological Disease and
Stroke's Institutional Review Board.
MAGNETIC RESONANCE IMAGING
An axially oriented double-echo sequence (slice thickness, 6 mm; repetition
time/echo time, 2000/80 and 2000/20, respectively) and a sagittally oriented
T1-weighted volumetric sequence (slice thickness, 2 mm; in-plane resolution,
1 x 1 mm; repetition time/echo time, 20/6; flip angel, 45°) were
obtained using a 0.5-T magnetic resonance tomograph (Picker Instruments, Cleveland,
Ohio).
DATA PREPROCESSING
Volumetric data were manually aligned to the interhemispheric plane.
To adjust the individual scans for differences in global intensity, background
intensity of each scan was determined as the mean pixel intensity of a 15
x 15-mm2 region of interest averaged over all slices. The
region of interest always was placed in the upper left corner of the field
of view. Intensity values of all scans were then scaled to have the same mean
background intensity.
Preprocessing and subsequent measurements were done using ANALYZE software
(Biomedical Imaging Resource, Mayo Foundation, Rochester, Minn) on an SGI
workstation (Silicon Graphics, Palo Alto, Calif). All measurements were performed
by one investigator (W.B.) who was masked to clinical information. Scans were
analyzed in randomized order with the investigator blinded to a subject's
identity.
CORPUS CALLOSUM AREA MEASUREMENTS
The areas of the corpus callosum and of 5 callosal subregions were measured
in the midsagittal slice of the 3-dimensional MRI, as described elsewhere.13 Briefly, the total callosal area was obtained by
manually tracing the outer edge of the corpus callosum on the midsagittal
slice. Subsequently, areas of 5 callosal subregions were defined. Subregions
were labeled C1 to C5 in rostral-occipital direction, with region C1 covering
the callosal rostrum and genu; regions C2, C3, and C4, the anterior, middle,
and posterior truncus, respectively; and region C5, the callosal isthmus and
splenium. The number of pixels within each region was summed and multiplied
by pixel size to obtain absolute values (in square millimeters) for the measured
areas.
The intraclass correlation coefficient for interrater reliability (determined
from 10 scans measured by 2 independent researchers [S.J.T. and W.B.]) ranged
from 0.98 for total corpus callosum area and subregions C1 and C2 to 0.95
for region C3. The relative error of measurement for total corpus callosum
areas was 2.7% ± 1.3%, ranging from 3.0% ± 1.6% for subregion
C5 and 5.7% ± 2.7% for subregion C3. The intraclass correlation coefficient
for intrarater reliability (determined from 10 scans measured twice by the
same researcher, blinded to scan identity [W.B.]) was 0.98 for total callosal
area with a relative error of measurement of 1.8% ± 1.5%.
MEASUREMENT OF TOTAL INTRACRANIAL VOLUME
Total intracranial volume was manually traced on the 3-dimensional MRI
at the inner edge of the dura. Each pixel represents a volume element (voxel)
of the size 1 x 1 mm in the sagittal plane and 1.5 mm in the right-left
axis. All voxels belonging to the traced regions of interest were summed over
all slices to obtain a measure of intracranial volume.
GRADING OF WHITE MATTER HYPERINTENSITIES
The extent of white matter hyperintensities (WMH) was assessed in the
axial T2-weighted MRI sequence according to a previously reported rating scale.18 We obtained scores for WMH in the frontal, parietal,
occipital, and temporal lobes. Scores for parietal, occipital, and temporal
lobes were summed to obtain WMH for posterior brain, as previously described.14 The intraclass correlation coefficient for interrater
reliability (2 independent researchers rating 10 randomly selected MRI scans)
was 0.65 for total WMH, 0.65 for frontal WMH, and 0.62 for posterior WMH load.
STATISTICAL ANALYSIS
The primary end point of the analyses was the annual percent change
in corpus callosum areas for each individual subject. In the case of more
than 2 observations, the individual annual rates of change were determined
as the slope of the linear regression of time of follow-up (in months) on
corpus callosum areas. In the case of only 2 observations, individual rates
of atrophy were determined as the areas of corpus callosum on image 2 -
image 1 divided by the duration between both images (in months). Individual
rates of change were then divided by region size at baseline and multiplied
by 12 months to obtain percent rates of change per year.
A group-by-subregion interaction for individual percent rates of change
was assessed by repeated-measures analysis of variance with diagnosis as between-subjects
factor and the percent rate of change of the 5 corpus callosum subregions
as within-subject factor. A significant overall effect was followed up by
pairwise single-effect analyses using the Student t
test.
Using a stepwise linear multiple regression model, within the AD and
the control groups, individual percent rates of change were predicted by age
at baseline, sex, anterior and posterior WMH load, length of observation time,
and, in the AD group, rate of point loss in MMSE score. In the first step,
all variables were forced into the equation to assess the amount of variance
explained by the selected model. Variables were then stepwise removed from
the model when the amount of explained variance, which was contributed to
the model, was below a threshold of F = 2.71 (corresponding to P = .10).
Differences in mean total and regional corpus callosum cross-sectional
areas between AD patients and controls were assessed using the t test. The level of significance was determined at P<.05. Analyses were performed using the Statistical Package for
the Social Sciences, release 9.0.1 (SPSS Inc, Chicago, Ill).
RESULTS
CROSS-SECTIONAL ANALYSES
There was a statistically significant difference between AD patients
and healthy controls in total corpus callosum area (P<.002)
at baseline, with smaller area in the AD patients. Reduction of corpus callosum
area was predominant in subregions C1 (rostrum and genu) and C5 (isthmus and
splenium) (P<.02 and P<.001,
respectively), whereas subregions C2 to C4, representing corpus callosum truncus,
remained relatively spared. Statistical significance of results remained unchanged,
when areas were normalized to intracranial volume (area/intracranial volume)
to correct for differences in head size. Absolute values and percentage of
differences between group for corpus callosum sizes are given in Table 2.
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Table 2. Cross-sectional Atrophy of Corpus Callosum*
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In the AD group, MMSE score and age explained a significant amount of
the variance of total corpus callosum area (ß = 0.38 and -0.41,
respectively; P<.05). Intracranial volume, anterior
and posterior WMH load, and sex did not contribute explanatory power to the
model.
In the healthy control group, total cranial volume explained a significant
amount of variance of total corpus callosum area (ß = 0.72, P<.001). Anterior and posterior WMH load, age, and sex did not contribute
explanatory power to the model.
LONGITUDINAL ANALYSES
There was a significant difference in percent rates of change of areas
over time for total corpus callosum. There was a significant effect of diagnosis
on corpus callosum subregion (P<.005). In the
single-effect analyses, percent rates of change of callosal subregions C1
(rostrum, genu), C2 (genu, anterior truncus), and C5 (isthmus, splenium) were
significantly different between AD patients and controls. Mean percent rates
of change for total corpus callosum were -7.7% per year in AD patients
and -0.9% in healthy control subjects (Table 3). Because mean observation times were different between
AD patients and healthy controls, we repeated the analyses with a subgroup
of 16 AD patients who were matched in observation time to the healthy controls
(P = .16). There was a significant difference between
percent rates of atrophy of total corpus callosum and callosal subregions
C1 and C5 between AD patients and healthy controls (P<.05).
The difference for region C2 was not significant (P
= .83).
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Table 3. Atrophy Progression of Corpus Callosum*
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The individual trajectories of atrophy progression are illustrated in Figure 1. In the AD group, annual point loss
in MMSE score was correlated significantly with percent reduction of corpus
callosum area C5, both within the full regression model (ß = 0.446, P<.03), controlling for age, sex, observation time,
and WMH load, and in the single-effect analysis ( = 0.52, P<.02) (Figure 2). No
other area reduction of the corpus callosum was related to point loss in MMSE
score. There was no correlation between percent rate of atrophy of total corpus
callosum or any corpus callosum subregion with age, sex, time of observation,
or load of frontal or posterior WMH.
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Figure 1. Trajectories of corpus callosum
atrophy in 21 patients with Alzheimer disease (A) and 10 healthy, elderly
control subjects (B). MRI indicates magnetic resonance imaging.
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Figure 2. Correlation between the atrophy
rate of corpus callosum subregion C5 and Mini-Mental State Examination (MMSE)
score difference in 21 patients with Alzheimer disease.
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In the control group, percent rate of atrophy of anterior corpus callosum
area C2 was correlated significantly with anterior WMH load (ß = -0.90, P<.05) and sex (ß = 0.85, P<.05),
with greater rates of area reduction in women. There was no correlation with
posterior WMH load, age, or time of observation. There also was no correlation
between percent rate of atrophy of other corpus callosum areas and WMH load
at baseline.
COMMENT
In the present study, we investigated the longitudinal progression of
corpus callosum atrophy in AD and healthy aging. Based on previous evidence
from cross-sectional studies, we expected greater atrophy progression in AD
patients than in healthy subjects. We further expected that in AD patients
who were free of clinical risk factors for cerebrovascular disease, atrophy
progression of corpus callosum would be independent of the extent of subcortical
lesions.
We found an overall reduction of corpus callosum area by roughly 7.7%
per year in AD patients compared with 0.9% per year in healthy controls. The
rate of atrophy was significantly greater in AD patients compared with controls
in rostrum and splenium of the corpus callosum, regions that were the most
severely affected during cross-sectional comparisons. The truncus remained
relatively preserved in the cross-sectional and the longitudinal analyses.
In the healthy control subjects, the extent of frontal lobe WMH predicted
the rate of area reduction of the anterior corpus callosum. Because WMH are
commonly regarded as measures of primary subcortical disease,19
this association suggests that age-related atrophy of the anterior corpus
callosum in healthy subjects results from primary subcortical lesions to fiber
tracts crossing the frontal lobe white matter. This finding agrees with neuropathologic
evidence for predominant frontal lobe involvement of cerebral white matter
in cerebrovascular disease.20 This further
agrees with a significant correlation between frontal lobe WMH load and anterior
corpus callosum atrophy in healthy, elderly subjects in a cross-sectional
study.14 This interpretation, however, needs
further confirmation in an independent sample because the group of healthy
subjects was small in our study and the range of subcortical lesions was low.
In contrast, in the AD patients, longitudinal progression of regional
corpus callosum atrophy mainly results from loss of callosally projecting
cortical neurons. Neuron loss as the main cause of atrophy then would mask
any additional effect from primary lesions to the callosally projecting fibers
in subcortical white matter. This notion is first supported by the lack of
difference in the extent of WMH between AD patients and healthy controls.
In addition, rate of atrophy progression in AD patients was independent from
the extent of WMH. It also agrees with previous findings of statistically
significant correlations between regional cortical hypometabolism as a measure
of cortical neuronal integrity and regional corpus callosum atrophy independent
of WMH load in AD patients.12, 15
It has been estimated from postmortem studies that about 30% of intracortical
association neurons are lost in layers III and V of neocortex in AD patients.21 Corpus callosum fibers arise from a subset of these
neurons.1-2 Neocortical neuron
loss, as shown in neuropathologic studies and reflected by cortical metabolic
decline, is most pronounced in the temporal and parietal association areas21-22 that send interhemispheric projections
through corpus callosum isthmus and splenium (corresponding to region C5).23-25 Less neuron loss
is seen in frontal association cortex projecting through the rostrum (corresponding
to region C1). Primary sensory motor areas that project through the corpus
callosum truncus are least affected.
The significant correlation between progression of splenium atrophy
and the progression of clinical disease severity as measured by the MMSE in
the AD patients is in agreement with the outlined fiber topography, since
loss of functional integrity in the parietal and temporal association areas
that project through corpus callosum splenium is closely related to disease
severity.26 Decline in MMSE score explained
about 27% of variance between individual trajectories of atrophy in splenium
in the AD patients. This suggests that a considerable part of the variance
in our longitudinal measures reflects clinically meaningful differences in
the course of the disease. It is likely that variability in repeated measurements
contributed to the high variability in longitudinal measures of corpus callosum
subregions. It may also in part account for the positive rates of change found
in area C3 in AD patients and in area C2 in controls. In addition, the variability
in observation time may contribute to variability in rates of change because
shorter length of observation time may lead to less accurate assessment of
the rate of change, particularly when rates of change are not linear over
all stages of disease.
In summary, we investigated the longitudinal rate of corpus callosum
atrophy in AD patients compared with healthy age-matched controls. Rates of
atrophy progression were significantly greater in AD patients compared with
controls. Progression of clinical disease severity was correlated with progression
of atrophy of the corpus callosum. Atrophy of the corpus callosum, independently
of primary white matter degeneration, reflects loss of intracortical projecting
pyramidal neurons in the neocortex. Therefore, we propose longitudinal corpus
callosum measurement as a surrogate marker of progressive neocortical neuronal
degeneration in AD27 if the results of this
first longitudinal study can be confirmed in an independent sample. Measurement
of corpus callosum areas in vivo may help to map efficacy of pharmacologic
intervention on the progression of morphologic changes in AD patients free
of cerebrovascular disease.
AUTHOR INFORMATION
Accepted for publication September 12, 2001.
Author contributions: Study concept and design (Drs Teipel, Alexander, Schapiro, Rapoport, and Hampel);
acquisition of data (Drs Teipel, Bayer, Alexander, Zebuhr,
and Kulic and Ms Teichberg); analysis and interpretation of data (Drs Teipel, Alexander, Möller, Rapoport, and Hampel);
drafting of the manuscript (Drs Teipel, Bayer, and Hampel
and Ms Teichberg); critical revision of the manuscript for important
intellectual content (Drs Bayer, Alexander, Zebuhr, Kulic,
Schapiro, Möller, Rapoport, and Hampel and Ms Teichberg); statistical
expertise (Drs Teipel, Alexander, Möller, and Hampel); obtained funding (Drs Teipel and Hampel);
administrative, technical, and material support (Drs Bayer,
Zebuhr, Rapoport, Kulic, and Schapiro and Ms Teichberg); study supervision (Drs Möller, Rapoport, and Hampel).
This study was supported in part by a grant from Eisai (Frankfurt) and
Pfizer (Karlsruhe) (Drs Hampel and Teipel), and by a grant from the Medical
Faculty of the Ludwig-Maximilian University, Munich (Dr Teipel), Germany.
Portions of this article originate from the doctoral thesis of Dr Bayer
(Ludwig-Maximilian University, Munich, Germany; in preparation).
We thank A. W. L. Bokde, PhD, Department of Psychiatry, Ludwig-Maximilian
University, for helpful discussion.
Corresponding author and reprints: Stefan J. Teipel, MD, and Harald
Hampel, MD, Dementia and Neuroimaging Section, Department of Psychiatry, Ludwig-Maximilian
University, Nussbaumstr 7, 80336 Munich, Germany (e-mail: stt{at}psy.med.uni-muenchen.de).
From the Dementia and Neuroimaging Section, Department of Psychiatry,
Ludwig-Maximilian University, Munich, Germany (Drs Teipel, Bayer, Zebuhr,
Kulic, Möller, and Hampel); Arizona Alzheimer's Research Center and Department
of Psychology, Arizona State University, Tempe (Dr Alexander); Brain Physiology
and Metabolism Section, National Institute on Aging, National Institutes of
Health, Bethesda, Md (Ms Teichberg and Dr Rapoport); and Department of Pediatric
Neurology, Children Hospital Medical Center, Cincinnati, Ohio (Dr Schapiro).
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Frontal Lobe Volume, Function, and {beta}-Amyloid Pathology in a Canine Model of Aging
Tapp et al.
J. Neurosci. 2004;24:8205-8213.
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Differential Vulnerability of Anterior White Matter in Nondemented Aging with Minimal Acceleration in Dementia of the Alzheimer Type: Evidence from Diffusion Tensor Imaging
Head et al.
Cereb Cortex 2004;14:410-423.
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Higher atrophy rate of entorhinal cortex than hippocampus in AD
Du et al.
Neurology 2004;62:422-427.
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Relation of Corpus Callosum and Hippocampal Size to Age in Nondemented Adults With Down's Syndrome
Teipel et al.
Am. J. Psychiatry 2003;160:1870-1878.
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Atrophy rates of entorhinal cortex in AD and normal aging
Du et al.
Neurology 2003;60:481-486.
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Dentate gyrus volume is reduced before onset of plaque formation in PDAPP mice: A magnetic resonance microscopy and stereologic analysis
Redwine et al.
Proc. Natl. Acad. Sci. USA 2003;100:1381-1386.
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