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Figure 1.
Coronal sections moving from anterior to posterior showing the pattern of the T statistic of spatially consistent contractions related to frontotemporal dementia diagnosis. Color scales are marked with significance levels. BF indicates Bonferroni over brain voxels; PT, permutation testing; and UC, uncorrected.

Coronal sections moving from anterior to posterior showing the pattern of the T statistic of spatially consistent contractions related to frontotemporal dementia diagnosis. Color scales are marked with significance levels. BF indicates Bonferroni over brain voxels; PT, permutation testing; and UC, uncorrected.

Figure 2.
The T statistic map is overlaid on the spatially normalized average magnetic resonance image (N = 44). The red contour encompasses the contraction voxels that were contained in the large cluster that included regions of the frontal and temporal lobes, subcortical structures, and brainstem. FTD indicates frontotemporal dementia; CN, cognitively normal.

The T statistic map is overlaid on the spatially normalized average magnetic resonance image (N = 44). The red contour encompasses the contraction voxels that were contained in the large cluster that included regions of the frontal and temporal lobes, subcortical structures, and brainstem. FTD indicates frontotemporal dementia; CN, cognitively normal.

Table. 
Region of Interest Volumes Expressed as a Percentage of Intracranial Volume
Region of Interest Volumes Expressed as a Percentage of Intracranial Volume
1.
Broe  MHodges  JRSchofield  EShepherd  CEKril  JJHalliday  GM Staging disease severity in pathologically confirmed cases of frontotemporal dementia. Neurology 2003;601005- 1011
PubMedArticle
2.
Boccardi  MLaakso  MPBresciani  L  et al.  The MRI pattern of frontal and temporal brain atrophy in fronto-temporal dementia. Neurobiol Aging 2003;2495- 103
PubMedArticle
3.
Kaufer  DIMiller  BLItti  L  et al.  Midline cerebral morphometry distinguishes frontotemporal dementia and Alzheimer's disease. Neurology 1997;48978- 985
PubMedArticle
4.
Frisoni  GBLaakso  MPBeltramello  A  et al.  Hippocampal and entorhinal cortex atrophy in frontotemporal dementia and Alzheimer's disease. Neurology 1999;5291- 100
PubMedArticle
5.
Ashburner  JFriston  KJ Voxel-based morphometry—the methods. Neuroimage 2000;11805- 821
PubMedArticle
6.
Rosen  HJGorno-Tempini  MLGoldman  WP  et al.  Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology 2002;58198- 208
PubMedArticle
7.
Studholme  CCardenas  VBlumenfeld  R  et al.  Deformation tensor morphometry of semantic dementia with quantitative validation. Neuroimage 2004;211387- 1398
PubMedArticle
8.
Neary  DSnowden  JSGustafson  L  et al.  Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 1998;511546- 1554
PubMedArticle
9.
Brooks  BR El Escorial World Federation of Neurology criteria for the diagnosis of amyotrophic lateral scleroris. J Neurol Sci 1994;124(suppl)96- 107Article
10.
Studholme  CNovotny  EZubal  IGDuncan  JS Estimating tissue deformation between functional images induced by intracranial electrode implantation using anatomical MRI. Neuroimage 2001;13561- 576
PubMedArticle
11.
Studholme  CCardenas  VMaudsley  AWeiner  M An intensity consistent filtering approach to the analysis of deformation tensor derived maps of brain shape. Neuroimage 2003;191638- 1649
PubMedArticle
12.
Nichols  TEHolmes  AP Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 2002;151- 25
PubMedArticle
13.
Glantz  S Primer of Biostatistics. 4th ed. New York, NY: McGraw-Hill; 1981
14.
Worsley  KJLiao  CHAston  J  et al.  A general statistical analysis for fMRI data. Neuroimage 2002;151- 15
PubMedArticle
15.
Bloomer  CWLangleben  DDMeyerhoff  DJ Magnetic resonance detects brainstem changes in chronic, active heavy drinkers. Psychiatry Res 2004;132209- 218
PubMedArticle
16.
Boxer  ALTrojanowski  JQLee  VY-MMiller  MJ Frontotemporal lobar degeneration.  In: Beal  MF, Lang  AE, Ludolph  AC, eds. Neurodegenerative Diseases: Neurobiology, Pathogenesis and Therapeutics. Cambridge, England: Cambridge University Press; 2005
17.
Mann  DMSouth  PW The topographic distribution of brain atrophy in frontal lobe dementia. Acta Neuropathol (Berl) 1993;85334- 340
PubMed
18.
Dickson  DW Neuropathology of Pick's disease. Neurology 2001;56(suppl 4)S16- S20
PubMedArticle
19.
Litvan  IHauw  JJBartko  JJ  et al.  Validity and reliability of the preliminary NINDS neuropathologic criteria for progressive supranuclear palsy and related disorders. J Neuropathol Exp Neurol 1996;5597- 105
PubMedArticle
20.
Verny  MJellinger  KAHauw  JJBancher  CLitvan  IAgid  Y Progressive supranuclear palsy: a clinicopathological study of 21 cases. Acta Neuropathol (Berl) 1996;91427- 431
PubMedArticle
21.
Boxer  ALGeschwind  MDBelfor  N  et al.  Patterns of brain atrophy that differentiate corticobasal degeneration syndrome from progressive supranuclear palsy. Arch Neurol 2006;6381- 86
PubMedArticle
22.
Rippon  GABoeve  BFParisi  JE  et al.  Late-onset frontotemporal dementia associated with progressive supranuclear palsy/argyrophilic grain disease/Alzheimer's disease pathology. Neurocase 2005;11204- 211
PubMedArticle
23.
Paviour  DCLees  AJJosephs  KA  et al.  Frontotemporal lobar degeneration with ubiquitin-only-immunoreactive neuronal changes: broadening the clinical picture to include progressive supranuclear palsy. Brain 2004;1272441- 2451
PubMedArticle
24.
Meyniel  CRivaud-Pechoux  SDamier  PGaymard  B Saccade impairments in patients with fronto-temporal dementia. J Neurol Neurosurg Psychiatry 2005;761581- 1584
PubMedArticle
25.
Rankin  KPKramer  JHMychack  PMiller  BL Double dissociation of social functioning in frontotemporal dementia. Neurology 2003;60266- 271
PubMedArticle
26.
Liddell  BJBrown  KJKemp  AH  et al.  A direct brainstem-amygdala-cortical ‘alarm' system for subliminal signals of fear. Neuroimage 2005;24235- 243
PubMedArticle
27.
Knopman  DSMastri  ARFrey  WH  IISung  JHRustan  T Dementia lacking distinctive histologic features: a common non-Alzheimer degenerative dementia. Neurology 1990;40251- 256
PubMedArticle
28.
Josephs  KAPetersen  RCKnopman  DS  et al.  Clinicopathologic analysis of frontotemporal and corticobasal degenerations and PSP. Neurology 2006;6641- 48
PubMedArticle
Original Contribution
June 2007

Deformation-Based Morphometry Reveals Brain Atrophy in Frontotemporal Dementia

Author Affiliations

Author Affiliations: Magnetic Resonance Unit, San Francisco Veterans Affairs Medical Center (Drs Cardenas, Chao, Weiner, and Studholme), and Departments of Radiology (Drs Cardenas, Chao, Weiner, and Studholme) and Psychiatry (Dr Chao) and the Memory and Aging Center, Department of Neurology (Drs Boxer, Gorno-Tempini, and Miller), University of California, San Francisco.

Arch Neurol. 2007;64(6):873-877. doi:10.1001/archneur.64.6.873
Abstract

Objective  To compare deformation-based maps of local anatomical size between subjects with frontotemporal dementia (FTD) and healthy subjects to identify regions of the brain involved in FTD.

Design  Structural magnetic resonance images were obtained from 22 subjects with FTD and 22 cognitively normal, age-matched controls. We applied deformation-based morphometry and compared anatomy between groups using an analysis of covariance model that included a categorical variable denoting group membership and covaried for head size.

Setting  University of California, San Francisco, Memory and Aging Center, and the San Francisco Veterans Affairs Medical Center.

Patients  Twenty-two subjects with FTD and 22 cognitively normal, age-matched controls.

Interventions  Neurological, neuropsychological, and functional evaluations and magnetic resonance imaging.

Main Outcome Measure  Deformation maps of local anatomical size.

Results  Patients with FTD showed extensive, significant atrophy of the frontal lobes, affecting both gray matter and white matter. Atrophy of similar magnitude but less significance was observed in the anterior temporal lobes. The subcortical and midbrain regions, particularly the thalamus, pons, and superior and inferior colliculi, showed strongly significant atrophy of smaller magnitude.

Conclusions  We confirmed frontal and anterior temporal gray matter atrophy in FTD. The observed white matter loss, thalamic involvement, and midbrain atrophy are consistent with pathological findings in late-stage FTD. Dysfunction of ventral-frontal-brainstem circuitry may underlie some of the unique clinical features of FTD.

Frontotemporal dementia (FTD) is a clinical subtype of frontotemporal lobar degeneration defined by deficits in social and personal conduct. Postmortem studies have suggested that brain atrophy in FTD begins in the frontal lobe, extending into the anterior temporal lobes, basal ganglia, and the thalamus. White matter (WM), including the corpus callosum, is prominently affected.1

In vivo magnetic resonance imaging (MRI) structural analyses have compared patients with FTD with controls using conventional measures of gray matter (GM), WM, or cerebrospinal fluid volumes obtained from computer segmentation and volumes of manually delineated regions of interest, such as the hippocampus. Using such measurements, atrophy of the frontal and temporal lobes2 and corpus callosum3 has been demonstrated in FTD. Hippocampal atrophy is present in FTD as compared with controls, but it is not as severe as in Alzheimer disease.4

Unlike region of interest methods, voxelwise structural image analysis assesses anatomical variation without prior hypotheses about the location and extent of the anatomical variation. Early techniques, such as voxel-based morphometry,5 provided regional indications of GM loss in the frontal and temporal regions.6 Because voxel-based morphometry relies on the automated segmentation of images into GM, WM, and cerebrospinal fluid, regions of abnormal WM (prevalent in older populations) may be incorrectly classified as GM by automatic segmentation. In addition, automatic segmentation of subcortical structures can be problematic because of the mixing of GM and WM in these structures. For these reasons, voxel-based morphometry is suboptimal for investigating WM loss or determining subcortical involvement in FTD.

Improvements in image alignment allow purely deformation-based morphometry (DBM) to be used to provide more direct quantitative maps of anatomical variation.7 By avoiding the need for image segmentation and using robust registration methods, DBM may be more suitable for investigating anatomical variation of WM and subcortical structures.

In this study, our goal was to compare deformation-based maps of local anatomical size between subjects with FTD and healthy subjects to identify regions of the brain involved in FTD. We hypothesized that subjects with FTD would show atrophy in frontal and temporal GM and WM and subcortical structures, including the basal ganglia and thalamus.

METHODS
PARTICIPANTS

All subjects underwent neurological, neuropsychological, and functional evaluations at the University of California, San Francisco, Memory and Aging Center. Cognitively normal (CN) controls (mean ± SD age, 63 ± 7 years; n = 22; 7 women) had cognitive test scores within the normal age and education-adjusted range. All subjects with FTD (mean ± SD age, 63 ± 6 years; n = 22; 7 women; mean ± SD 6.6 ± 3.7 years since disease onset) met Neary8 criteria for FTD. In addition, 5 subjects with FTD also met El Escorial criteria9 for possible or probable amyotrophic lateral sclerosis. Diagnoses were blinded to neuroimaging results to avoid confounding future neuroimaging analyses.6 Pathological verification of diagnosis was obtained in 5 subjects (2, Pick disease; 2, FTD-ubiquitin; 1, FTD–motor neuron disease). The Clinical Dementia Rating (CDR) scaled and sum of boxes scores were 0 for both measures for CN controls and mean ± SD 1.12 ± 0.69 (scaled) and 6.7 ± 3.8 (sum) for the FTD group. The mean ± SD Mini-Mental State Examination score for the FTD group was 23.1 ± 7.0 and for the CN controls, 29.3 ± 2.2. The study received institutional review board approval and all participants gave informed consent before the study.

MAGNETIC RESONANCE IMAGING

The MRI data were acquired at the San Francisco Veterans Affairs Medical Center on a clinical 1.5-T MRI scanner (Vision; Siemens Medical Systems, Iselin, NJ). Coronal T1-weighted images were acquired using a magnetization-prepared rapid-acquisition gradient-echo sequence (repetition time, 9 milliseconds; inversion time, 300 milliseconds; echo time, 4 milliseconds; 1 × 1 mm2 in-plane resolution; 1.5-mm slabs); images were acquired orthogonal to the long axis of the hippocampus.

FULLY AUTOMATED DBM

A B-Spline free-form deformation algorithm driven by normalized mutual information10 was used to register individual scans to a 72-year-old female reference atlas, chosen to retain the finest anatomical structures for accurate registration.7 The Jacobian determinant of this transformation at each point, giving the pattern of volume change required to force the individual anatomy to conform to the reference, was mapped and smoothed using an intensity-consistent filtering approach.11 These voxel maps of relative local anatomical size of each individual were then analyzed using statistical parametric mapping. Using a general linear model, we compared the FTD and CN groups with a categorical variable coding group membership and head size (defined as the average Jacobian determinant within the intracranial vault delineated on the reference anatomy) included as a covariate, as shown in the equation, where |J(x)| is the Jacobian evaluated at voxel x, and a(x), b(x), and the intercept c(x) are estimated at each voxel. Because statistics were computed independently at each voxel, we calculated the corrected P<.05 peak threshold using permutation testing,12 where we permuted the group membership 1000 times and recalculated the voxel statistics to build the null distribution, and also the method of Bonferroni13 (using all voxels within the average brain). We used fMRIstat14 to identify in FTD clusters of contracting or expanding voxels, where both magnitude (all voxels within the cluster must be significant at P<.001 uncorrected) and spatial extent (larger clusters are less likely to be false positives) were jointly used to assess corrected significance.

RESULTS
DEFORMATION-BASED MORPHOMETRY

Figure 1 shows regions where patients with FTD demonstrate brain volume reductions compared with CN controls. Regions where patients with FTD show significant (P<.01 uncorrected, or T =2.70) atrophy are overlaid on the average spatially normalized MRI. The threshold at P = .05 corrected for multiple comparisons using permutation testing is T = 5.0 and the corrected threshold using the method of Bonferroni is T = 6.62; these 2 thresholds are marked on the Figure 1 color bar (as PT P=.05 and BF [Bonferroni over brain voxels] P=.05, respectively). Figure 1 reveals many voxels where patients with FTD show significant atrophy relative to CN controls even after correction for multiple comparisons, including a large region of the pons and midbrain, the right superior and inferior colliculus, thalamus, left superior frontal GM, anterior frontal WM, and a ventromedial frontal WM region. At lower significance, patients with FTD showed extensive atrophy of frontal and anterior temporal WM and GM.

Cluster analysis using fMRIstat revealed a single connected cluster of contraction in patients with FTD vs CN controls encompassing all the regions mentioned earlier. Figure 2 shows the T statistic map overlaid on the average spatially normalized MRI, where voxels belonging to this significant cluster of contraction are outlined in red. Negative T values that indicate atrophy in patients with FTD compared with CN controls are in green and blue; positive T values that indicate expansion in patients with FTD relative to CN controls (all located within cerebrospinal fluid) are in yellow and red.

To estimate the magnitude of atrophy in patients with FTD, the brainstem (including midbrain), thalamus, and ventromedial frontal lobe were defined anatomically on the average image, and we then averaged the estimates a(x) from the equation at all statistically significant voxels x (t > 5) within each region of interest. We found that tissue volume was reduced by 10% in the brainstem region in patients with FTD compared with CN controls, by 26% in the thalamic region, and by 34% in the ventromedial frontal region. Although no single voxel in the temporal lobes reached significance after correction for multiple comparisons, the regions of the temporal lobes were part of the significant cluster of contraction. To determine whether the relatively small T statistics in the anterior temporal lobe were due to a small volume difference between groups or due to variability within groups, we averaged the estimates a(x) from the equation at all voxels x in the anterior temporal lobe that belonged to the significant cluster of contraction. This showed that tissue volume was reduced by 35% in the anterior temporal region in patients with FTD compared with CN controls, as large a reduction as observed in the frontal lobes.

To validate DBM, we calculated region of interest measures on 22 consecutive subjects (11 with FTD and 11 CN controls), measuring frontal and temporal lobe volumes and brainstem volume (midbrain, pons, and medulla) on a single midsagittal slice.15 Volumes were then normalized to account for global head size differences and expressed as a percentage of intracranial volume, as shown in the Table. Similar to DBM, we found significant volume differences between patients with FTD and CN controls within the frontal lobe and brainstem and no significant difference within the temporal lobe. The magnitude of the reduction within the frontal and temporal lobes was smaller, probably because these regions of interest included the entire frontal or temporal lobe, whereas our DBM estimates were within only significant subregions.

COMMENT

We used DBM to examine brain structure differences between patients with FTD and CN controls. The major findings of this study are (1) patients with FTD showed significant atrophy in the frontal lobes, affecting both WM and GM, (2) significant atrophy was observed within the thalamus and adjacent WM in FTD, (3) the brainstem, including the midbrain and pontine tegmentum as well as the superior and inferior colliculi, showed significant tissue volume reduction in FTD, and (4) regions of the anterior temporal lobes were atrophied in FTD.

The frontal and anterior temporal GM atrophy observed in FTD is consistent with previous postmortem and voxel-based morphometry studies. The frontal and temporal volumes were comparably reduced, although the reduction in the temporal lobes was not as significant. A quantitative validation7 showed excellent agreement between our deformation-derived (reference image was the same 72-year-old subject as in this study) and manually delineated temporal volumes, so it is unlikely that this lower significance in the temporal lobe arises because of poor alignment. Instead, we believe that some patients with FTD have much smaller temporal lobes than CN individuals but that in others the FTD disease does not involve or has not progressed to the stage where the temporal lobes are greatly affected. Such an inconsistent spatial pattern within the FTD group would explain the lowered significance of atrophy in the anterior temporal region, and this interpretation is highly consistent with the considerable variability in clinical and neuroimaging features observed in FTD.16 Consistent with other reports, we did not observe any significant atrophy in parietal or occipital lobes in the patients with FTD.

In addition to frontal and temporal GM tissue loss, we observed frontal WM and thalamic atrophy in patients with FTD compared with CN controls. Thalamic volume loss of up to 37% has previously been described in neuropathological studies of FTD.17 In a proposed scheme for staging pathological disease severity in FTD, WM and thalamic atrophy are thought to occur at later stages, only after the frontal and temporal lobes are severely affected,1 roughly corresponding to CDR scores of 3 to 5. Our data suggest that these changes are measurable in patients with FTD at earlier stages of disease (mean ± SD CDR score 1.2 ± 0.68). Our study also may have had greater sensitivity to these changes because of a more homogeneous clinical sample (all had FTD) and a smaller interval between CDR and brain atrophy measurement, as well as the more quantitative nature of the DBM analysis over visual atrophy measurements.

Although midbrain atrophy has not previously been emphasized in imaging studies in FTD, FTD-related pathological features are frequently found in the substantia nigra and other brainstem structures,18 and this finding supports the known clinical overlap between FTD and progressive supranuclear palsy (PSP). Neuroimaging and pathological features of PSP show atrophy in the midbrain, basal ganglia, and other structures.1921 Cases of clinically diagnosed FTD have been found to have PSP pathological features at autopsy,22 and clinically diagnosed PSP cases have been described with FTD-ubiquitin pathological features involving the midbrain.23 Recent evidence suggests that patients with FTD have measurable saccade abnormalities, which may in part reflect damage to the superior colliculus and/or WM tracts that connect it to the frontal lobes and basal ganglia,24 consistent with our results. Midbrain and thalamic pathological features may underlie some of the deficits in social function and emotion perception identified in FTD25 since integrity of this region is likely to be necessary for function of a midbrain-thalamus-amygdala pathway implicated in emotion perception.26 Finally, there is an extensive literature on midbrain involvement in FTD at a pathology level. For example, in the original study by Knopman et al27 on dementia lacking distinctive histological features, the authors noted that 79% of these patients had pathological features in the midbrain. In previous voxel-based morphometry work from our center, we also found atrophy in the midbrain, and DBM is a better technique for delineating these changes.

These cases were defined on the basis of their clinical features and only a small number have been autopsy confirmed. Because FTD is a pathologically heterogeneous disorder,28 it will be of particular interest to confirm these results in histopathologically diagnosed FTD and to assess whether subcortical and brainstem atrophy is associated with specific biochemical FTD phenotypes, such as tau protein inclusions, which might further strengthen the link between FTD and PSP.

Taken together, our findings suggest that dysfunction of a frontal-subcortical-brainstem circuit may underlie some of the unique clinical features of FTD and that DBM measures of volume may be useful for exploring these brain-behavior relationships.

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Article Information

Correspondence: Valerie A. Cardenas, PhD, University of California, San Francisco, Department of Veterans Affairs Medical Center, 4150 Clement St, 114M, San Francisco, CA 94121 (valerie.cardenas-nicolson@ucsf.edu).

Accepted for Publication: September 5, 2006.

Author Contributions: All authors had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Cardenas, Boxer, Chao, Gorno-Tempini, and Weiner. Acquisition of data: Gorno-Tempini. Analysis and interpretation of data: Cardenas, Boxer, Chao, Gorno-Tempini, Miller, Weiner, and Studholme. Drafting of the manuscript: Cardenas and Boxer. Critical revision of the manuscript for important intellectual content: Cardenas, Boxer, Chao, Gorno-Tempini, Miller, Weiner, and Studholme. Statistical analysis: Cardenas and Gorno-Tempini. Obtained funding: Miller, Weiner, and Studholme. Administrative, technical, and material support: Cardenas, Boxer, Chao, Weiner, and Studholme. Study supervision: Boxer, Chao, Gorno-Tempini, Weiner, and Studholme.

Financial Disclosure: None reported.

Funding/Support: This work was supported in part by National Institutes of Health grants P01 AG19724, R01 AG10897, and R01 MH65392.

Acknowledgment: We would like to acknowledge Diana Truran, BA, and Erin Clevenger, BA, for magnetic resonance imaging, image quality control, and data organization, and Joanna Hellmuth, BS, for database assistance.

References
1.
Broe  MHodges  JRSchofield  EShepherd  CEKril  JJHalliday  GM Staging disease severity in pathologically confirmed cases of frontotemporal dementia. Neurology 2003;601005- 1011
PubMedArticle
2.
Boccardi  MLaakso  MPBresciani  L  et al.  The MRI pattern of frontal and temporal brain atrophy in fronto-temporal dementia. Neurobiol Aging 2003;2495- 103
PubMedArticle
3.
Kaufer  DIMiller  BLItti  L  et al.  Midline cerebral morphometry distinguishes frontotemporal dementia and Alzheimer's disease. Neurology 1997;48978- 985
PubMedArticle
4.
Frisoni  GBLaakso  MPBeltramello  A  et al.  Hippocampal and entorhinal cortex atrophy in frontotemporal dementia and Alzheimer's disease. Neurology 1999;5291- 100
PubMedArticle
5.
Ashburner  JFriston  KJ Voxel-based morphometry—the methods. Neuroimage 2000;11805- 821
PubMedArticle
6.
Rosen  HJGorno-Tempini  MLGoldman  WP  et al.  Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology 2002;58198- 208
PubMedArticle
7.
Studholme  CCardenas  VBlumenfeld  R  et al.  Deformation tensor morphometry of semantic dementia with quantitative validation. Neuroimage 2004;211387- 1398
PubMedArticle
8.
Neary  DSnowden  JSGustafson  L  et al.  Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 1998;511546- 1554
PubMedArticle
9.
Brooks  BR El Escorial World Federation of Neurology criteria for the diagnosis of amyotrophic lateral scleroris. J Neurol Sci 1994;124(suppl)96- 107Article
10.
Studholme  CNovotny  EZubal  IGDuncan  JS Estimating tissue deformation between functional images induced by intracranial electrode implantation using anatomical MRI. Neuroimage 2001;13561- 576
PubMedArticle
11.
Studholme  CCardenas  VMaudsley  AWeiner  M An intensity consistent filtering approach to the analysis of deformation tensor derived maps of brain shape. Neuroimage 2003;191638- 1649
PubMedArticle
12.
Nichols  TEHolmes  AP Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 2002;151- 25
PubMedArticle
13.
Glantz  S Primer of Biostatistics. 4th ed. New York, NY: McGraw-Hill; 1981
14.
Worsley  KJLiao  CHAston  J  et al.  A general statistical analysis for fMRI data. Neuroimage 2002;151- 15
PubMedArticle
15.
Bloomer  CWLangleben  DDMeyerhoff  DJ Magnetic resonance detects brainstem changes in chronic, active heavy drinkers. Psychiatry Res 2004;132209- 218
PubMedArticle
16.
Boxer  ALTrojanowski  JQLee  VY-MMiller  MJ Frontotemporal lobar degeneration.  In: Beal  MF, Lang  AE, Ludolph  AC, eds. Neurodegenerative Diseases: Neurobiology, Pathogenesis and Therapeutics. Cambridge, England: Cambridge University Press; 2005
17.
Mann  DMSouth  PW The topographic distribution of brain atrophy in frontal lobe dementia. Acta Neuropathol (Berl) 1993;85334- 340
PubMed
18.
Dickson  DW Neuropathology of Pick's disease. Neurology 2001;56(suppl 4)S16- S20
PubMedArticle
19.
Litvan  IHauw  JJBartko  JJ  et al.  Validity and reliability of the preliminary NINDS neuropathologic criteria for progressive supranuclear palsy and related disorders. J Neuropathol Exp Neurol 1996;5597- 105
PubMedArticle
20.
Verny  MJellinger  KAHauw  JJBancher  CLitvan  IAgid  Y Progressive supranuclear palsy: a clinicopathological study of 21 cases. Acta Neuropathol (Berl) 1996;91427- 431
PubMedArticle
21.
Boxer  ALGeschwind  MDBelfor  N  et al.  Patterns of brain atrophy that differentiate corticobasal degeneration syndrome from progressive supranuclear palsy. Arch Neurol 2006;6381- 86
PubMedArticle
22.
Rippon  GABoeve  BFParisi  JE  et al.  Late-onset frontotemporal dementia associated with progressive supranuclear palsy/argyrophilic grain disease/Alzheimer's disease pathology. Neurocase 2005;11204- 211
PubMedArticle
23.
Paviour  DCLees  AJJosephs  KA  et al.  Frontotemporal lobar degeneration with ubiquitin-only-immunoreactive neuronal changes: broadening the clinical picture to include progressive supranuclear palsy. Brain 2004;1272441- 2451
PubMedArticle
24.
Meyniel  CRivaud-Pechoux  SDamier  PGaymard  B Saccade impairments in patients with fronto-temporal dementia. J Neurol Neurosurg Psychiatry 2005;761581- 1584
PubMedArticle
25.
Rankin  KPKramer  JHMychack  PMiller  BL Double dissociation of social functioning in frontotemporal dementia. Neurology 2003;60266- 271
PubMedArticle
26.
Liddell  BJBrown  KJKemp  AH  et al.  A direct brainstem-amygdala-cortical ‘alarm' system for subliminal signals of fear. Neuroimage 2005;24235- 243
PubMedArticle
27.
Knopman  DSMastri  ARFrey  WH  IISung  JHRustan  T Dementia lacking distinctive histologic features: a common non-Alzheimer degenerative dementia. Neurology 1990;40251- 256
PubMedArticle
28.
Josephs  KAPetersen  RCKnopman  DS  et al.  Clinicopathologic analysis of frontotemporal and corticobasal degenerations and PSP. Neurology 2006;6641- 48
PubMedArticle
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