Traumatic brain injury (TBI) is a major cause of death and disability worldwide, with 235 000 hospitalizations reported each year in the United States alone.1 A common consequence of TBI is cerebral atrophy, which progresses over months and possibly years after injury.2-10 The predominant view is that posttraumatic atrophy is a consequence of direct injury to the neuron body, or soma, which subsequently undergoes cytotoxic or apoptotic cell death.11 However, it is now evident that significant loss of cerebral volume occurs even in those without focal lesions, suggesting that atrophy may result from diffuse traumatic axonal injury (TAI) with secondary wallerian degeneration and delayed neuronal cell death rather than direct damage to neuronal cell bodies.9 Because axons and soma differ substantially in cellular and molecular features such as expression of ion channels, cytoskeletal proteins, and bioenergetics, it is likely that future neuroprotective therapies will need to be separately tailored toward axonal or somatic injury.
Few studies have examined the spatial distribution of atrophy after TBI, and it remains unclear if volume loss is diffuse or regionally selective.10,12-14 Recent postmortem histopathological data suggest that TAI results in greater loss of pyramidal neurons from the prefrontal cortex than nondiffuse mechanisms of TBI.15 However, to our knowledge, no studies have assessed regional volume changes in vivo in patients with predominantly TAI. There are several challenges to quantifying the distribution of posttraumatic atrophy, including intersubject anatomic variation and focal trauma that often coexists with diffuse lesions leading to regional shape distortion and complications with image registration and tissue segmentation.
Despite this, several quantitative magnetic resonance imaging (MRI) techniques have been applied to TBI. Region of interest analysis involves manually tracing readily identifiable structures based on a priori designation of tissue boundaries3 and is limited in its ability to quantify less discrete neuroanatomic regions. To overcome this, methods have been developed that analyze brain tissue on a voxelwise or whole-brain approach, such as voxel-based morphometry5,8,14,16 and tensor-based morphometry,10,13 noting atrophy after TBI in several prominent white matter tracts and subcortical gray matter regions. However, voxelwise approaches have several limitations, including low sensitivity for cortical atrophy and inadequacies in delineating gray matter from white. Moreover, few studies have longitudinally assessed atrophy after trauma,6,10,14,17,18 and only 3 have examined regional variations in volume loss.10,14,18 Most existing longitudinal data rely on initial MRI scans that were performed several months after injury, and to our knowledge, no study has assessed the progression of atrophy beginning acutely (within 1 week) after injury.
Recently, several automated approaches have been developed that allow for improved quantification of brain tissue. The FreeSurfer image analysis suite (http://surfer.nmr.mgh.harvard.edu) allows for automated parcellation of cortical and subcortical gray and white matter. Unlike the aforementioned voxelwise approaches, FreeSurfer allows for delineation of specific atlas-derived brain regions and improved quantification of cortical surfaces because of subvoxel positioning and geometry-based intersubject registration resulting in enhanced matching of homologous cortical regions. It has been validated in epilepsy,19 dementia,20 Alzheimer disease,21 major depressive disorder,22 and pediatric TBI12 among others. To our knowledge, this is the first application of FreeSurfer morphometry to adult TBI.
The primary goal of this investigation was to quantify cerebral atrophy in patients with TAI using global and regional metrics, thereby determining if certain brain regions are selectively vulnerable to atrophy after trauma. We also aimed to assess the relationship between atrophy and functional outcome.
This study was approved by the institutional review board at the University of Texas Southwestern Medical Center in Dallas. From September 2005 to October 2008, 31 patients with TBI were recruited. Initial MRI (scan A) was obtained at a median of 1 day (range, 0.5-9 days) postinjury. Follow-up MRI (scan B) was performed at a median of 7.9 months (range, 6-14 months). Five patients had substantial motion artifact on either scan A or B, and 1 patient did not return for follow-up. This resulted in 25 patients with complete data (Table 1). Twenty-two controls without a history of TBI or neurological disorder and selected to match the TBI group with respect to age and sex were scanned once. Demographic information for patients and controls is displayed in Table 2.
Imaging acquisition and analysis
Three-dimensional T1-weighted structural MPRAGE images were acquired on a GE Signa Excite 3-T MRI scanner (General Electric Healthcare, Milwaukee, Wisconsin) using fast spoiled gradient-recalled acquisition in the steady state sequences (256 × 92 matrix size, 240-mm field of view, 130 slices, 1.3-mm slice thickness, no gap, 2.4-millisecond echo time, 25° flip angle, 2 excitations, 6-minute acquisition time). Image files were transferred to a Macintosh workstation for analysis with FreeSurfer image analysis suite (version 4.5.0; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts), which has been described in detail in prior publications.23-26
In brief, FreeSurfer analysis includes averaging of multiple volumetric T1-weighted images, removal of nonbrain tissue, conversion to Talairach coordinates, automated segmentation of subcortical white and deep gray matter structures, tessellation of the gray-white matter junction, surface deformation along intensity gradients for optimal placement of gray-white and gray–cerebrospinal fluid borders, and cortical parcellation with submillimeter precision into units based on gyral and sulcal structure. These procedures result in high-resolution quantification of thickness, surface area, and volume over the entire brain, in addition to delineating atlas-derived subcortical and cortical brain regions.
Functional outcome was assessed at the time of follow-up MRI using the Glasgow Outcome Scale–Extended (GOSE). The GOSE provides an objective measure of recovery after TBI and is an ordinal scale from 1 to 8 with higher scores reflecting better outcomes. All follow-up interviews were conducted by 1 of 3 study coordinators with specific training and experience in interviewing patients with TBI, and interviews were conducted face to face. Outcome assessors were not involved in morphometric analysis and were blinded to neuroimaging results. Interrater reliability was assessed by auditing 20% of scoring sheets every 3 months, with greater than 99% reproducibility.
Volumetric differences between scans A and B were tested using repeated-measures analysis of covariance with correction for intracranial volume. Differences in volume between controls and patients were tested using analysis of covariance with an intracranial volume covariate. Cortical structures were reconstructed and voxelwise volume changes between scans A and B were computed with FreeSurfer's general linear model for paired analysis using a 10-mm full-width half-maximum gaussian kernel. A false discovery rate of 0.05 was used for all analyses to account for effects of multiple comparisons. To determine candidate regions with prognostic value, correlations between atrophy rates and GOSE scores were calculated using Spearman correlation coefficients and a screening false discovery rate threshold of 0.10. Structures surviving the correlation analysis screen were entered into ordinal regression models for calculation of odds ratios of posttraumatic disability using volume change between scans A and B as the predictor variable and GOSE score, trichotomized into severe disability (GOSE score 3-4), moderate disability (GOSE score 5-6), and good recovery (GOSE score 7-8), as the dependent variable. All statistical analyses were performed with SPSS (version 11.5; SPSS Inc, Chicago, Illinois).
Morphometric analyses were conducted by 3 independent raters (M.A.W., T.Y., and A.C.), and interrater reliability was determined by having each rater analyze 20 brains for determination of intraclass correlation coefficients using 2-way analysis of variance with mixed effects. Regions having an intraclass correlation coefficient less than 0.850 or a single-rater coefficient of variation greater than 20% in controls, with the exception of the ventricles, were excluded from region-based analyses. The voxel-based analysis did not exclude any brain regions.
The mean intraclass correlation coefficient for interrater reliability was 0.964 (median, 0.978; range, 0.855-0.999). Four cortical regions, the left and right temporal and frontal poles, and four subcortical structures, the left and right globus pallidum and accumbens area, had a coefficient of variation greater than 20% in controls and were excluded from regional analysis. However, these regions were considered in the voxel-based analysis.
All global measures of brain volume indicated loss of volume between scans A and B, with significant decreases in 9 of 12 measures (Table 3). Whole-brain parenchymal volume (WBPV) decreased by a mean of 4.5% (95% confidence interval, 2.7%-6.3%) and whole white matter volume, by 5.8% (95% confidence interval, 3.2%-8.4%). There was substantial enlargement of all 4 ventricles and an increase in total cerebrospinal fluid volume.
Thirteen of 22 subcortical structures underwent atrophy after injury (Table 4), with the highest rates occurring bilaterally in the amygdala, which underwent mean volume loss of nearly 15%. Substantial atrophy was also seen in the thalamus, hippocampus, and putamen, but not in the caudate or cerebellum. The corpus callosum was particularly vulnerable to volume loss.
Of the 62 cortical regions analyzed by structural boundaries, atrophy was found in 13 (Table 5). Volume differences analyzed per brain voxel revealed substantial atrophy extending bilaterally into numerous regions including the superior frontal and rostral middle frontal cortex, superior and inferior parietal cortex, paracentral lobule, pars orbitalis, pericalcarine cortex, precuneus, cuneus, lingual cortex, and postcentral and supramarginal gyri (Figure). Loss of brain volume was most prominent in the precuneus, paracentral lobules, and parietal cortex.
Control group comparisons
In global comparisons between controls and initial scans, the lateral ventricles were significantly larger in the control group (Table 3). In subcortical and cortical analyses, there were no significant differences between controls and patients with acute injury (Table 4 and Table 5).
Atrophy and functional outcome
Three global brain volume metrics and 14 subcortical and cortical regions survived a correlation analysis screen of atrophy rates and outcome. Odds ratios for disability with 10% volume loss were calculated for each (Table 6). The WBPV and whole gray matter volume loss demonstrated prognostic value, as did atrophy in several brain regions. The probability of having disability (GOSE score <7) or severe disability (GOSE score <5) at follow-up was assessed for changes in WBPV (Table 7). With no change in WBPV, the risk for disability was 10%, but this risk increased to 37% with 5% atrophy and 76% with 10% atrophy.
We prospectively and longitudinally assessed regional and global changes in gray and white matter volumes in patients with TAI scanned acutely and again several months after injury, while also investigating the relationship between atrophy and functional outcome. The distribution of atrophy was essentially symmetric. Substantial atrophy was observed in the cerebral cortex, subcortical structures, and white matter. Loss of WBPV was predictive of poor outcome, as was atrophy in several brain regions. To our knowledge, this represents the first application of FreeSurfer morphometry in a longitudinal investigation of adult TBI.
Our findings of significant decreases in global brain volume after traumatic insult are consistent with previous studies that have noted mean global atrophy rates ranging from 1.4% to 7.8% between time of initial (range, 1-61 weeks) and follow-up (range, 6-30 months) MRI.6,10,17,18 While the loss of WBPV in our study (mean, 4.5%) is similar to previously reported values, the rate of atrophy in our study and the recent study by Xu and colleagues18 (mean, 7.8%) is greater than that seen in previous studies that delayed longer to establish baseline MRI. By obtaining the initial MRI earlier in this study (median, 1 day), it is likely that we increased our ability to detect atrophy in the acute and early subacute posttraumatic period. As noted previously, it is probable that the rate and distribution of atrophy are dependent on time after injury,10 and higher atrophy rates may occur during the acute/early subacute period than during the late subacute/chronic period. It is also possible that acutely after injury, brain edema could exaggerate longitudinal decreases in brain volume. However, since we did not find group differences between acute scans and scans from age- and sex-matched controls, any possible effect of acute edema is likely to be small. In addition, differences in global atrophy rates may be related to the automated methods used for morphometric analysis, which may result in minor variations in calculation of WBPV.27 Finally, it is probable that severely injured patients may undergo higher rates of atrophy than those with milder injuries, contributing to discrepancies between studies. In our study, the majority of patients had severe TBI (Glasgow Coma Scale score, 3-8) and only 3 patients had mild TBI (Glasgow Coma Scale score, 13-15). Mean global atrophy rates for the severe and mild groups were 5.7% and 2.5%, respectively. However, given the small sample size of the mild group, meaningful conclusions are unable to be drawn.
Our study examined patients whose predominant injury mechanism was TAI, excluding those with focal lesions more than 10 mL and those requiring cranial surgery. Even in the absence of focal trauma, there was substantial loss of brain volume, supporting the hypothesis that a primary mechanism of posttraumatic atrophy is diffuse white matter damage with secondary wallerian degeneration and eventual neuronal cell death. A previous study from our group examined the relationship between acute measures of white matter integrity and global atrophy in patients with TAI, finding that acute axonal lesions (within 1 month of injury) measured by fluid attenuation inversion recovery imaging were strongly predictive of atrophy at 6 months.9 A recent study of patients with severe TBI, not limited to those with TAI, found the most substantial decreases in brain volume in regions susceptible to the consequences of TAI.10 However, since conventional neuroimaging techniques, including computed tomography and structural MRI, have low sensitivity for TAI, it is likely that patients with focal hematomas also had significant diffuse axonal injuries, potentially explaining the similarities between our findings and previous work.6,10,17 To improve posttraumatic outcomes, it will be essential to advance clinical detection and diagnosis of TAI.
Posttraumatic atrophy was not uniformly diffuse. Among subcortical structures, the highest rates of atrophy were noted bilaterally in the amygdala, hippocampus, thalamus, and putamen. Atrophy in the thalamus and putamen have been observed in several previous TBI studies.13,14,28 Loss of volume in the amygdala and hippocampus may contribute to various behavioral and cognitive difficulties that commonly affect head-injured patients such as lability of mood, heightened irritability, and difficulties with memory and learning.
In cortical analysis, a variety of regions experienced marked atrophy, with the most dramatic volume loss occurring in the parietal lobes, superior frontal lobes, precuneus, and paracentral lobules. A recent longitudinal study found decreased volume in the supplementary motor area and precentral and postcentral gyri,14 while another found atrophy only in small portions of the frontal cortex.10 The apparent disparity in degree of cortical atrophy in our study vs previous studies is likely due to intersubject variability in cortical sulci and gyri that make volumetric analysis of the cortex exceptionally difficult with traditional voxelwise approaches. The application of FreeSurfer morphometry to this study improves the ability to delineate and quantify the cerebral cortex at the subvoxel level, resulting in increased sensitivity for cortical volume loss. In addition, previous studies have not excluded patients with focal lesions that may further obscure cortical morphometry. Although extensive, cortical atrophy was not diffuse, and several regions, including the entorhinal cortex, parahippocampal gyrus, and fusiform gyrus, were resilient to atrophy. Because it is our hypothesis that posttraumatic volume loss occurs primarily as a consequence of axonal injury, differences in regional atrophy rates are likely to be related to discrepancies in degree of compromise to efferent and afferent fibers. Alternatively, these regional differences in atrophy may be related to inherent differences in gene and ion channel expression in distinct cortical regions. Larger studies with increased follow-up times will be needed to improve the detection and quantification of regional volume changes after TAI.
Regionally selective cortical and subcortical atrophy has been studied extensively in Alzheimer disease, and many of the areas that are particularly susceptible to atrophy in Alzheimer disease are also vulnerable after TAI. For example, in addition to hippocampal volume loss, patients with Alzheimer disease have high rates of atrophy in the amygdala,29-31 precuneus, parietal and frontal cortices,32-34 and corpus callosum.35-38 While interesting, the relationship is far from perfect. However, it is plausible that regional similarities in atrophy between TAI and Alzheimer disease may contribute to posttraumatic deficits in certain cognitive domains such as learning and memory. Also, many brain regions vulnerable to atrophy in our study and in Alzheimer disease are involved in the default network.34 These findings may relate to common molecular mechanisms shared between Alzheimer disease and TBI-related neurodegeneration.
As expected, loss of WBPV was predictive of disability at time of patient follow-up, with a nearly 30-fold increase in disability risk in patients with 10% atrophy. In addition, volume loss in several candidate brain regions displayed prognostic value for outcome, suggesting that regional morphometry may hold value as a biomarker for recovery after trauma. We hypothesize that the effect of atrophy on global outcome is a summation of the effects of regional atrophy on particular cognitive domains that contribute to functional recovery and reintegration. While interesting, our analysis involved only a small number of patients and was underpowered to fully investigate these relationships. To better understand the influence of regional volume changes on patient outcomes, it will be necessary to assess atrophy-outcome relationships for a greater number of brain regions in a larger number of patients with more precise metrics of functional recovery after brain trauma such as neuropsychological battery tests.
There are several limitations to our study. We assessed longitudinal changes in brain volumes between the acute and late subacute periods. Because the brain may swell acutely after injury, it is possible that the clearing of brain edema may contribute to observed losses of brain volume. However, in cross-sectional comparisons between scans of controls and patients during the acute period, there were no significant differences in cortical or subcortical brain volumes. The only significant difference between groups was volume of the lateral ventricles, which were larger in controls, suggesting that there may be diffuse swelling after injury. However, because ventricular enlargement is at best an indirect measurement of atrophy, it is much less sensitive than direct measurement of changes in structural volumes.13 Prior studies have also noted transient edema within days of injury, but as in our study, brain volume increases were not statistically different from healthy controls.18,39 Therefore, it is unlikely that brain edema played a substantial role in observed decreases in brain volume. This study was designed to enroll subjects with TAI as their primary injury mechanism. However, because the diagnosis of TAI relies on pathologic confirmation, it was only possible to select subjects using the best available clinical and imaging evidence. In addition, our study contained only a modest sample size, and to further understand atrophy after TAI, it will be necessary to enroll a larger number of patients. Moreover, follow-up MRI scans were not performed on controls, which would have permitted more robust comparisons between independent groups. Controls and patients were matched based on sex and age but not on years of education. This resulted in a control group with a significantly higher education level, which could potentially confound between-group comparisons. Finally, this longitudinal study used 2 time points for quantitative MRI and only assessed atrophy that occurred between the acute and late subacute periods. To more fully understand the time course and regional distribution of posttraumatic atrophy, it will be necessary to obtain additional serial MRI scans at shorter intervals and over a longer study period.
This prospective evaluation of longitudinal changes in brain volumes after TAI offers new information on the spatial distribution of posttraumatic cerebral atrophy. Our findings indicate that atrophy is not uniformly diffuse, but rather has substantial selectivity for various subcortical and cortical regions including the amygdala, hippocampus, thalamus, precuneus, and parietal and frontal cortices. Atrophy in several brain regions may also be predictive of long-term functional recovery. Future studies will be needed to determine the impact of regional atrophy on particular neuropsychological outcomes. Finally, it will be necessary to integrate regional volumetric data with measurements of axonal integrity to assess the true relationship between acute white matter injury and chronic volume loss in corresponding gray matter.
Correspondence: Ramon Diaz-Arrastia, MD, PhD, Department of Neurology, University of Texas Southwestern Medical Center at Dallas, 5323 Harry Hines Blvd, Dallas, TX 75390-9036 (firstname.lastname@example.org).
Accepted for Publication: May 3, 2010.
Published Online: July 12, 2010. doi:10.1001/archneurol.2010.149
Author Contributions: All authors had full access to the data in the study and take full responsibility for the data integrity, data analysis, and interpretation of results. Study concept and design: Warner, Youn, Marquez de la Plata, Moore, McColl, Devous, and Diaz-Arrastia. Acquisition of data: Warner, Youn, Davis, Chandra, Moore, Harper, Madden, McColl, Devous, and Diaz-Arrastia. Analysis and interpretation of data: Warner, Davis, Marquez de la Plata, Spence, Devous, King, and Diaz-Arrastia. Drafting of the manuscript: Warner and Devous. Critical revision of the manuscript for important intellectual content: Warner, Youn, Davis, Chandra, Marquez de la Plata, Moore, Harper, Madden, Spence, McColl, Devous, King, and Diaz-Arrastia. Statistical analysis: Warner, Spence, and Devous. Obtained funding: Warner, Youn, Devous, and Diaz-Arrastia. Administrative, technical, and material support: Chandra, Marquez de la Plata, Moore, Harper, Madden, McColl, King, and Diaz-Arrastia. Study supervision: Warner, Davis, Marquez de la Plata, Devous, and Diaz-Arrastia.
Financial Disclosure: None reported.
Funding/Support: This study was supported by a Clinical Research Fellowship through the Doris Duke Charitable Foundation (Mr Warner and Dr Youn), grants R01 HD48179 and U01 HD42652 from the National Institutes of Health National Institute of Child Health and Human Development (Dr Diaz-Arrastia), and grant H133 A020526 from the US Department of Education (Dr Diaz-Arrastia).
Additional Contributions: Evelyn Babcock, PhD, provided technical support with image acquisition and quality control.
K Traumatic Brain Injury in the United States: Emergency Department Visits, Hospitalizations, and Deaths. >Atlanta, GA National Center for Injury Prevention and Control2006;
et al. Hippocampal head atrophy after traumatic brain injury. Neuropsychologia
1956- 1961PubMedGoogle ScholarCrossref
EA Day-of-injury computerized tomography, rehabilitation status, and development of cerebral atrophy in persons with traumatic brain injury. Am J Phys Med Rehabil
793- 806PubMedGoogle ScholarCrossref
SC Traumatic brain injury and grey matter concentration: a preliminary voxel based morphometry study. J Neurol Neurosurg Psychiatry
984- 988PubMedGoogle ScholarCrossref
et al. Brain atrophy in mild or moderate traumatic brain injury: a longitudinal quantitative analysis. AJNR Am J Neuroradiol
1509- 1515PubMedGoogle Scholar
et al. Gross morphology and morphometric sequelae in the hippocampus, fornix, and corpus callosum of patients with severe non-missile traumatic brain injury without macroscopically detectable lesions: a T1 weighted MRI study. J Neurol Neurosurg Psychiatry
1314- 1322PubMedGoogle ScholarCrossref
et al. Changes in white matter in long-term survivors of severe non-missile traumatic brain injury: a computational analysis of magnetic resonance images. J Neurotrauma
76- 82PubMedGoogle ScholarCrossref
KMarquez de la Plata
et al. Cerebral atrophy after traumatic white matter injury: correlation with acute neuroimaging and outcome. J Neurotrauma
1433- 1440PubMedGoogle ScholarCrossref
et al. Long-term global and regional brain volume changes following severe traumatic brain injury: a longitudinal study with clinical correlates. Neuroimage
1- 8PubMedGoogle ScholarCrossref
DI Update of neuropathology and neurological recovery after traumatic brain injury. J Head Trauma Rehabil
76- 94PubMedGoogle ScholarCrossref
HS Diffuse changes in cortical thickness in pediatric moderate-to-severe traumatic brain injury. J Neurotrauma
1343- 1345PubMedGoogle ScholarCrossref
et al. Structural consequences of diffuse traumatic brain injury: a large deformation tensor-based morphometry study. Neuroimage
1014- 1026PubMedGoogle ScholarCrossref
et al. Longitudinal changes in patients with traumatic brain injury assessed with diffusion-tensor and volumetric imaging. Neuroimage
503- 514PubMedGoogle ScholarCrossref
DI Stereology of cerebral cortex after traumatic brain injury matched to the Glasgow outcome score. Brain
139- 160PubMedGoogle ScholarCrossref
BJ Cognitive sequelae of head injury: involvement of basal forebrain and associated structures. Brain
189- 200PubMedGoogle ScholarCrossref
et al. Longitudinal changes in global brain volume between 79 and 409 days after traumatic brain injury: relationship with duration of coma. J Neurotrauma
766- 771PubMedGoogle ScholarCrossref
et al. Early nonischemic oxidative metabolic dysfunction leads to chronic brain atrophy in traumatic brain injury. J Cereb Blood Flow Metab
883- 894PubMedGoogle ScholarCrossref
et al. Subcortical and cerebellar atrophy in mesial temporal lobe epilepsy revealed by automatic segmentation. Epilepsy Res
130- 138PubMedGoogle ScholarCrossref
PJ Comparative reliability of total intracranial volume estimation methods and the influence of atrophy in a longitudinal semantic dementia cohort. J Neuroimaging
37- 46PubMedGoogle ScholarCrossref
et al. the Alzheimer's Disease Neuroimaging Initiative, Subregional neuroanatomical change as a biomarker for Alzheimer's disease. Proc Natl Acad Sci U S A
20954- 20959PubMedGoogle ScholarCrossref
KW Validation of hippocampal volumes measured using a manual method and two automated methods (FreeSurfer and IBASPM) in chronic major depressive disorder. Neuroradiology
569- 581PubMedGoogle ScholarCrossref
MI Cortical surface-based analysis, I: segmentation and surface reconstruction. Neuroimage
179- 194PubMedGoogle ScholarCrossref
AM Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A
11050- 11055PubMedGoogle ScholarCrossref
AM Cortical surface-based analysis, II: inflation, flattening, and a surface-based coordinate system. Neuroimage
195- 207PubMedGoogle ScholarCrossref
et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron
341- 355PubMedGoogle ScholarCrossref
et al. Diffusion tensor imaging during recovery from severe traumatic brain injury and relation to clinical outcome: a longitudinal study. Brain
559- 572PubMedGoogle ScholarCrossref
et al. Comprehensive dissection of the medial temporal lobe in AD: measurement of hippocampus, amygdala, entorhinal, perirhinal and parahippocampal cortices using MRI. J Neurol
794- 800PubMedGoogle ScholarCrossref
et al. Different atrophic patterns in early- and late-onset Alzheimer's disease and evaluation of clinical utility of a method of regional z-score analysis using voxel-based morphometry. Dement Geriatr Cogn Disord
175- 186PubMedGoogle ScholarCrossref
et al. Volumetry of amygdala and hippocampus and memory performance in Alzheimer's disease. Psychiatry Res
251- 261PubMedGoogle ScholarCrossref
et al. Apolipoprotein E epsilon4 is associated with disease-specific effects on brain atrophy in Alzheimer's disease and frontotemporal dementia. Proc Natl Acad Sci U S A
2018- 2022PubMedGoogle ScholarCrossref
NC Mapping the evolution of regional atrophy in Alzheimer's disease: unbiased analysis of fluid-registered serial MRI. Proc Natl Acad Sci U S A
4703- 4707PubMedGoogle ScholarCrossref
et al. Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci
7709- 7717PubMedGoogle ScholarCrossref
et al. Progression of corpus callosum atrophy in Alzheimer disease. Arch Neurol
243- 248PubMedGoogle ScholarCrossref
et al. Regional pattern of hippocampus and corpus callosum atrophy in Alzheimer's disease in relation to dementia severity: evidence for early neocortical degeneration. Neurobiol Aging
85- 94PubMedGoogle ScholarCrossref
et al. Regionally specific atrophy of the corpus callosum in AD, MCI and cognitive complaints. Neurobiol Aging
1613- 1617PubMedGoogle ScholarCrossref
et al. Comparison of the pattern of atrophy of the corpus callosum in frontotemporal dementia, progressive supranuclear palsy, and Alzheimer's disease. J Neurol Neurosurg Psychiatry
623- 629PubMedGoogle ScholarCrossref
et al. MR-based brain and cerebrospinal fluid measurement after traumatic brain injury: correlation with neuropsychological outcome. AJNR Am J Neuroradiol
1- 10PubMedGoogle Scholar