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ABSTRACT: Physical activity (PA) has been hypothesized to spare gray matter volume in late adulthood, but longitudinal data testing an association has been lacking. Here we tested whether PA would be associated with greater gray matter volume after a 9-year follow-up, a threshold could be identified for the amount of walking necessary to spare gray matter volume, and greater gray matter volume associated with PA would be associated with a reduced risk for cognitive impairment 13 years after the PA evaluation.
In 299 adults (mean age 78 years) from the Cardiovascular Health Cognition Study, we examined the association between gray matter volume, PA, and cognitive impairment. Physical activity was quantified as the number of blocks walked over 1 week. High-resolution brain scans were acquired 9 years after the PA assessment on cognitively normal adults. White matter hyperintensities, ventricular grade, and other health variables at baseline were used as covariates. Clinical adjudication for cognitive impairment occurred 13 years after baseline.
Walking amounts ranged from 0 to 300 blocks (mean 56.3; SD 69.7). Greater PA predicted greater volumes of frontal, occipital, entorhinal, and hippocampal regions 9 years later. Walking 72 blocks was necessary to detect increased gray matter volume but walking more than 72 blocks did not spare additional volume. Greater gray matter volume with PA reduced the risk for cognitive impairment 2-fold.
Greater amounts of walking are associated with greater gray matter volume, which is in turn associated with a reduced risk of cognitive impairment.
Neurology 10/2010; 75(16):1415-22. · 8.31 Impact Factor
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C A Raji,
C Lee,
O L Lopez,
J Tsay,
J F Boardman,
E D Schwartz,
W S Bartynski,
H M Hefzy,
H M Gach,
W Dai, J T Becker
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ABSTRACT: MR imaging of the brain has significant potential in the early detection of neurodegenerative disorders such as AD. The purpose of this work was to determine if perfusion MR imaging can be used to separate AD from normal cognition in individual subjects. We investigated the diagnostic utility of perfusion MR imaging for early detection of AD compared with structural imaging.
Data were analyzed from 32 participants in the institutional review board-approved CHS-CS: 19 cognitively healthy individuals and 13 with clinically adjudicated AD. All subjects underwent structural T1-weighted SGPR and CASL MR imaging. Four readers with varying experience separately rated each CASL and SPGR scan finding as normal or abnormal on the basis of standardized qualitative diagnostic criteria for observed perfusion abnormalities on CASL or volume loss on SPGR and rated the confidence in their evaluation.
Inter-rater reliability was superior in CASL (kappa = 0.7 in experienced readers) compared with SPGR (kappa = 0.17). CASL MR imaging had the highest sensitivity (85%) and accuracy (70%). Frontal lobe CASL findings increased sensitivity to 88% and accuracy to 79%. Fifty-seven percent of false-positive readings with CASL were in controls with cognitive decline or instability within 5 years. Three of the 4 readers revealed a statistically significant relationship between confidence and correct classification when using CASL.
Readers were able to separate individuals with mild AD from those with normal cognition with high sensitivity by using CASL but not volumetric MR imaging. This initial experience suggests that CASL MR imaging may be a useful technique for detecting AD.
American Journal of Neuroradiology 05/2010; 31(5):847-55. · 2.93 Impact Factor
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ABSTRACT: The purpose of this study was to evaluate the relationship between cognitive performance, risk factors for cardiovascular and cerebrovascular disease (CVD), and HIV infection in the era of highly active antiretroviral therapy.
We evaluated the cognitive functions of men enrolled in the cardiovascular disease substudy of the Multicenter AIDS Cohort Study who were aged > or =40 years, with no self-reported history of heart disease or cerebrovascular disease. Results from comprehensive neuropsychological evaluations were used to construct composite scores of psychomotor speed and memory performance. Subclinical CVD was assessed by measuring coronary artery calcium and carotid artery intima-media thickness (IMT), as well as laboratory measures, including total cholesterol, fasting glucose, glycosylated hemoglobin, glomerular filtration rate (estimated), and standardized blood pressure and heart rate measures.
After accounting for education, depression, and race, carotid IMT and glomerular filtration rate were significantly associated with psychomotor speed, whereas IMT was associated with memory test performance. HIV serostatus was not significantly associated with poorer cognitive test performance. However, among the HIV-infected individuals, the presence of detectable HIV RNA in plasma was linked to lower memory performance.
These findings suggest that HIV infection may not be the most important predictor of cognitive performance among older gay and bisexual men in the post-highly active antiretroviral therapy era, at least among those with access to medical care and to appropriate medications. Medical factors associated with normal aging are significantly associated with performance on neuropsychological tests, and good clinical management of these factors both in HIV-infected individuals and those at risk for infection may have beneficial effects in the short term and could reduce the risk of subsequent cognitive decline.
Neurology 10/2009; 73(16):1292-9. · 8.31 Impact Factor
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ABSTRACT: Lack of clear understanding remains on the overlapping atrophy patterns of aging and early Alzheimer disease (AD) pathology in gray matter (GM) of the brain in vivo.
To evaluate the independent and overlapping patterns of GM atrophy in normal aging and AD.
A total of 169 cognitively normal subjects and 33 persons with probable AD enrolled in the longitudinal Cardiovascular Health Study-Cognition Study underwent 3-dimensional volumetric MRI scans. Controls remained cognitively normal for at least 5 years after their MRI scans and the probable AD subjects were relatively early in their clinical course with an average modified Mini-Mental State Examination score of 76/100. The scans were analyzed using voxel-based morphometry adjusting for total intracranial volume, gender, education, and race.
With older age, GM volume was lower in the sensorimotor and heteromodal association areas in frontal, temporal, occipital, and parietal lobes, as well as in the cerebellum (false discovery rate p = 0.05). Additional atrophy was observed in the posterior hippocampus, thalamus, and middle cingulate gyrus. By contrast, atrophy was seen in subjects with AD in the anterior hippocampal/parahippocampal regions and the precuneus. Normal aging and AD overlapped in the hippocampal body and the entorhinal cortex.
Brain atrophy with aging was observed in supratentorial and infratentorial areas, as well in primary motor, sensory, and heteromodal association regions. Age and Alzheimer disease exert independent gray matter atrophy patterns but these effects overlapped substantially in the hippocampus and entorhinal cortex.
Neurology 10/2009; 73(22):1899-905. · 8.31 Impact Factor
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ABSTRACT: We propose a quantified asymmetry based method for age estimation. Our method uses machine learning to discover automatically the most discriminative asymmetry feature set from different brain regions and image scales. Applying this regression model on a Tl MR brain image set of 246 healthy individuals (121 females; 125 males, 66 plusmn 7.5 years old), we achieve a mean absolute error of 5.4 years and a mean signed error of -0.2 years for age estimation on unseen MR images using the stringent leave-15%-out cross validation. Our results show significant changes in asymmetry with aging in the following regions: the posterior horns of the lateral ventricles, the amygdala, the ventral putamen with a nearby region of the anterior inferior caudate nucleus, the basal fore- brain, hyppocampus and parahyppocampal regions. We confirm the validity of the age estimation model using permutation test on 30 replicas of the original dataset with randomly permuted ages (with p-value < 0.001). Furthermore, we apply this model to a separate set of MR images containing normal, Alzheimer's disease (AD) and mild cognitive impairment (MCI) subjects. Our results reflect the relative severity of brain pathology between the three subject groups: mean signed age estimation error is 0.6 years for normal controls, 2.2 years for MCI patients, and 4.7 years for AD patients.
Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on; 06/2008
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ABSTRACT: To examine the association between incident Alzheimer disease (AD), and plasma A beta 1-40 and A beta 1-42 levels in normal and mild cognitive impairment (MCI) subjects in a subgroup of participants of the Cardiovascular Health Study Cognition Study.
We determined the plasma A beta 1-40 and A beta 1-42 levels of 274 nondemented subjects (232 normals and 42 with MCI) in 1998-1999 and repeated the measurements in 2002-2003. The mean age of the subjects at baseline was 79.3 +/- 3.6 years. We examined the association between A beta levels and incident AD over the ensuing 4.5 years, controlling for age, cystatin C level (marker of glomerular function), apolipoprotein E-4 allele, Modified-Mini-Mental State Examination scores, and MRI-identified infarcts.
In an unadjusted prospective model in normal subjects, both A beta 1-40 and A beta 1-42 levels in 1998-1999 were associated with incident AD (n = 55) in 2002-2003 (longitudinal analysis). In the fully adjusted multivariate model, neither A beta 1-42 nor A beta 1-40 nor their ratio was associated with incident AD. However, adjustment had a very small effect on point estimates for A beta 1-42, from an odds ratio (OR) of 1.61 (p = 0.007) in the unadjusted model to an OR of 1.46 (p = 0.08) in the fully adjusted model. In 2002-2003 (cross-sectional analysis), only the unadjusted models showed that both peptides were associated with AD.
Plasma A beta levels are affected by age and by systemic and CNS vascular risk factors. After controlling for these conditions, A beta-40 and A beta 1-42 are weak predictors of conversion to Alzheimer disease (AD) in normal subjects and are only weakly associated with AD in cross-sectional analysis. Consequently, plasma levels of A beta do not seem to be useful biomarkers for AD.
Neurology 06/2008; 70(19):1664-71. · 8.31 Impact Factor
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N Lepore,
C Brun,
Y Y Chou,
M C Chiang,
R A Dutton,
K M Hayashi,
E Luders,
O L Lopez,
H J Aizenstein,
A W Toga, J T Becker,
P M Thompson
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ABSTRACT: This paper investigates the performance of a new multivariate method for tensor-based morphometry (TBM). Statistics on Riemannian manifolds are developed that exploit the full information in deformation tensor fields. In TBM, multiple brain images are warped to a common neuroanatomical template via 3-D nonlinear registration; the resulting deformation fields are analyzed statistically to identify group differences in anatomy. Rather than study the Jacobian determinant (volume expansion factor) of these deformations, as is common, we retain the full deformation tensors and apply a manifold version of Hotelling's $T(2) test to them, in a Log-Euclidean domain. In 2-D and 3-D magnetic resonance imaging (MRI) data from 26 HIV/AIDS patients and 14 matched healthy subjects, we compared multivariate tensor analysis versus univariate tests of simpler tensor-derived indices: the Jacobian determinant, the trace, geodesic anisotropy, and eigenvalues of the deformation tensor, and the angle of rotation of its eigenvectors. We detected consistent, but more extensive patterns of structural abnormalities, with multivariate tests on the full tensor manifold. Their improved power was established by analyzing cumulative p-value plots using false discovery rate (FDR) methods, appropriately controlling for false positives. This increased detection sensitivity may empower drug trials and large-scale studies of disease that use tensor-based morphometry.
IEEE Transactions on Medical Imaging 02/2008; 27(1):129-41. · 3.64 Impact Factor
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M A Cole,
J B Margolick,
C Cox,
X Li,
O A Selnes,
E M Martin, J T Becker,
H A Aronow,
B Cohen,
N Sacktor,
E N Miller
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ABSTRACT: Recent case reports have suggested that some asymptomatic HIV-infected individuals can develop CNS disturbances despite intact immunologic functioning and long-term suppression of plasma HIV concentrations to undetectable levels. This possibility has not yet been systematically studied longitudinally.
Using longitudinal data from the Multicenter AIDS Cohort Study, we investigated neuropsychological performance in long-term asymptomatic HIV-infected men who have sex with men. Performance over a 5-year period on the Symbol Digit Modalities test and the Trail Making Tests were compared in three HIV-positive asymptomatic groups [defined as 1) highly active antiretroviral therapy (HAART) treated with undetectable viral loads (n = 83), 2) AIDS-free for more than 15 years without HAART (n = 29), and 3) absence of clinical AIDS or CD4(+) lymphocyte count below 200 cells/muL at the beginning and end of the study period (n = 233)] and in HIV-negative controls (n = 237). Data were analyzed using linear mixed models and proportional odds logistic regression modeling with generalized estimating equations.
There was no evidence of performance differences or performance declines over the 5-year period of study in any of the three long-term asymptomatic groups as compared with the HIV-negative group in the Symbol Digit Modalities test or the Trail Making Tests. Performance decrements were, however, observed with increasing age in each of the tests administered, demonstrating that performance declines could be detected by these methods.
Regardless of how long-term asymptomatic status was defined immunologically or virologically, neuropsychological test performances remained stable. These findings suggest that psychomotor speed is preserved over many years in HIV-infected individuals with controlled HIV viremia.
Neurology 01/2008; 69(24):2213-20. · 8.31 Impact Factor
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ABSTRACT: While it is clear that HIV-1 can cause CNS dysfunction, current approaches to classification and diagnosis of this dysfunction rely on syndromic definitions or measures of abnormality on neuropsychological testing in the background context of HIV-1 infection. These definitions have been variably applied, offer only limited sensitivity or specificity, and do not easily distinguish active from static brain injury. Supplanting or augmenting these approaches with objective biologic measurements related to underlying disease processes would provide a major advance in classification, diagnosis, epidemiology, and treatment assessment. Two major avenues are now actively pursued to this end: 1) analysis of soluble molecular markers in CSF and, to a lesser degree, in blood, and 2) neuroimaging markers using anatomic, metabolic, and functional measurements. This review considers the rationale and prospects of these approaches.
Neurology 11/2007; 69(18):1781-8. · 8.31 Impact Factor
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A Antinori,
G Arendt, J T Becker,
B J Brew,
D A Byrd,
M Cherner,
D B Clifford,
P Cinque,
L G Epstein,
K Goodkin, [......],
K Marder,
C M Marra,
J C McArthur,
M Nunn,
R W Price,
L Pulliam,
K R Robertson,
N Sacktor,
V Valcour,
V E Wojna
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ABSTRACT: In 1991, the AIDS Task Force of the American Academy of Neurology published nomenclature and research case definitions to guide the diagnosis of neurologic manifestations of HIV-1 infection. Now, 16 years later, the National Institute of Mental Health and the National Institute of Neurological Diseases and Stroke have charged a working group to critically review the adequacy and utility of these definitional criteria and to identify aspects that require updating. This report represents a majority view, and unanimity was not reached on all points. It reviews our collective experience with HIV-associated neurocognitive disorders (HAND), particularly since the advent of highly active antiretroviral treatment, and their definitional criteria; discusses the impact of comorbidities; and suggests inclusion of the term asymptomatic neurocognitive impairment to categorize individuals with subclinical impairment. An algorithm is proposed to assist in standardized diagnostic classification of HAND.
Neurology 11/2007; 69(18):1789-99. · 8.31 Impact Factor
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Owen T Carmichael,
L H Kuller,
O L Lopez,
P M Thompson,
R A Dutton,
A Lu,
S E Lee,
J Y Lee,
H J Aizenstein,
C C Meltzer,
Y Liu,
A W Toga, J T Becker
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ABSTRACT: Interactions between prevalent late-life medical conditions and expansion of the cerebral ventricles are not well understood. Thirty elderly subjects received three magnetic resonance (MR) scans each, in 1997-1999, 2002-2004, and 2003-2005. A linear expansion model of MR-measured lateral ventricle volume was estimated for each subject by fitting a line to a plot of their 1997-1999 and 2002-2004 volumes as a function of time. Acceleration in ventricular expansion was defined as the deviation between the 2003-2005 volumes measured from MR and the 2003-2005 volumes predicted by the linear expansion model. Ventricular acceleration was analyzed in a multivariate model with age, race, history of heart disease, diabetes, and hypertension as fixed effects. Ventricular acceleration was significantly higher in non-whites, diabetics, and those without heart disease (p<0.05). Ventricular acceleration was higher in subjects with a history of hypertension, but the difference was not statistically significant (p=0.08). Acceleration of ventricular expansion in the elderly may be related to demographic and cardiovascular factors.
Neurobiology of aging 09/2007; 28(9):1316-21. · 5.94 Impact Factor
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ABSTRACT: Maps of local tissue compression or expansion are often computed by comparing magnetic resonance imaging (MRI) scans using nonlinear image registration. The resulting changes are commonly analyzed using tensor-based morphometry to make inferences about anatomical differences, often based on the Jacobian map, which estimates local tissue gain or loss. Here, we provide rigorous mathematical analyses of the Jacobian maps, and use them to motivate a new numerical method to construct unbiased nonlinear image registration. First, we argue that logarithmic transformation is crucial for analyzing Jacobian values representing morphometric differences. We then examine the statistical distributions of log-Jacobian maps by defining the Kullback-Leibler (KL) distance on material density functions arising in continuum-mechanical models. With this framework, unbiased image registration can be constructed by quantifying the symmetric KL-distance between the identity map and the resulting deformation. Implementation details, addressing the proposed unbiased registration as well as the minimization of symmetric image matching functionals, are then discussed and shown to be applicable to other registration methods, such as inverse consistent registration. In the results section, we test the proposed framework, as well as present an illustrative application mapping detailed 3-D brain changes in sequential magnetic resonance imaging scans of a patient diagnosed with semantic dementia. Using permutation tests, we show that the symmetrization of image registration statistically reduces skewness in the log-Jacobian map.
IEEE Transactions on Medical Imaging 07/2007; · 3.64 Impact Factor
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ABSTRACT: In the past decade, information theory has been studied extensively in medical imaging. In particular, maximization of mutual information has been shown to yield good results in multi-modal image registration. In this paper, we apply information theory to quantifying the magnitude of deformations. We examine the statistical distributions of Jacobian maps in the logarithmic space, and develop a new framework for constructing image registration methods. The proposed framework yields both theoretically and intuitively correct deformation maps, and is compatible with large-deformation models. In the results section, we tested the proposed method using a pair of serial MRI images. We compared our results to those computed using the viscous fluid registration method, and demonstrated that the proposed method is advantageous when recovering voxel-wise local tissue change
Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on; 05/2007
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ABSTRACT: We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.
Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on; 05/2007
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ABSTRACT: We propose a computational framework for learning predictive image features as "biomarkers" for Alzheimer's disease discrimination using high-resolution magnetic resonance (MR) brain images. We focus on the exploration of a very large (>500 million) feature space derived extensively from the deformation and tensor fields. In such a huge space, our computational tool supports an automatic search for discriminative feature subspaces and the corresponding anatomical regions in human brains, which can be used to discriminate previously unseen, individual structural MR images from Alzheimer' disease (AD) and normal control (CTL) subjects. Our aggressive leave-ten-out cross-validations on 40 subjects demonstrate higher than 90% sensitivity and specificity. In addition, we demonstrate intriguing anatomical locations as automatically discovered "biomarkers" and the spatial distributions of 20 mild cognitive impairment (MCI) subjects in the discriminative feature space automatically learned for AD and CTL separations. Our results illustrate a truly complementary effort of human and computers for early diagnosis of AD from MR images.
Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on; 05/2007
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ABSTRACT: Conscious recall of past events which have specific temporal and spatial contexts, termed episodic memory, is mediated by a system of interrelated brain regions. In Alzheimer's disease (AD) this system breaks down, resulting in an inability to recall events from the immediate past. Studies of normal human auditory-verbal short-term memory suggest that the brain system underlying these processes has distinct components, and the present study utilized the methods of functional brain mapping to determine the nature and extent of the breakdown that occurs in AD. Using subtraction techniques of PET-acquired images of regional cerebral blood flow we demonstrate that AD patients show a compensatory hyperactivation of various regions of cerebral cortex normally involved in these tasks, as well as activation of cortical areas not activated by normal elderly subjects. These results provide clear evidence of functional plasticity in the AD patient's brain even if those changes do not result in normal memory function.
Annals of the New York Academy of Sciences 12/2006; 777(1):239 - 242. · 3.15 Impact Factor
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ABSTRACT: To determine the relationship between major depression and the presence of Lewy bodies (LBs) in patients with Alzheimer disease (AD).
The authors examined the presence of major depression in 267 pathologically diagnosed AD cases with Mini-Mental State Examination (MMSE) scores >9. LBs were identified in 142 (53%) patients using alpha-synuclein immunohistochemistry. Subjects were classified according to the Consensus Guidelines for the Clinical and Pathologic Diagnosis of Dementia with LB: 1 to 2 (n = 21), 3 to 6 (n = 26), and 7 to 10 (n = 69). Twenty-six patients had LB only in the amygdala. All cases with LB scores 7 to 10 (or cortical) had amygdala LBs. The association between LBs and major depression was examined with logistic regression analyses, controlled for age at study entry, education level, MMSE scores, antidepressant use, follow-up time, and the presence of cerebrovascular disease.
Major depression was present in 11 (9%) AD alone cases, and in 25 (18%) of the AD + LBs cases; amygdala: 8 (31%), scores 1 to 2: 1 (5%), scores 3 to 6: 3 (11.5%), and scores 7 to 10: 13 (14%). Major depression was associated with LBs, in general (relative risk [RR] = 3.06, 95% CI: 1.25 to 7.46), with amygdala only LBs (RR = 8.56 (95% CI: 1.83 to 40.3), and with LB scores 7 to 10 (RR = 3.83, 95% CI: 1.33 to 11.0). There was an association between all amygdala LBs cases (amygdala only LBs + LB scores 7 to 10) and major depression (RR = 4.77, 95% CI: 1.78 to 12.7), but no association was noted between LBs and depression in the absence of amygdala LBs (RR = 0.96, 95% CI: 0.46 to 1.06).
Lewy bodies (LBs) in the amygdala and in cortical areas increase the risk for major depression in Alzheimer disease. What is common in these two groups is the presence of LBs in the amygdala. That is, all of the cases with cortical LBs also had LBs in the amygdala, making this region the critical area for the development of depression.
Neurology 08/2006; 67(4):660-5. · 8.31 Impact Factor
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ABSTRACT: We propose a novel fluid image registration strategy based on an information-theoretic measure, the Jensen-Renyi divergence (JRD) of two images. We modified the definition of JRD, which is based on the joint histogram of two images, to develop a variational approach in which driving forces are applied throughout the deforming image to maximize the JRD between it and the target image. A viscous fluid regularizer was applied to guarantee diffeomorphic (i.e., smooth, one-to-one) deformation mappings. The resulting partial differential equation (PDE) was solved iteratively by convolving the applied force field with the Green's function of the linear differential operator. The fluid JRD method provided accurate, robust correspondences for registrations requiring large deformations in 2D and 3D. Finally, we applied our algorithm to tensor-based morphometry (i.e. shape analysis) of 3D brain MRIs from 26 HIV/AIDS patients and 14 matched healthy control subjects, showing that the algorithm can help identify subtle and clinically significant differences in brain structure. Detected white matter changes were correlated with cognitive impairment in AIDS. These techniques may help measure and visualize disease burden in drug trials and in morphometric studies of degenerative brain disease
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on; 05/2006
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O.T. Carmichael,
P.M. Thompson,
R.A. Dutton,
A. Lu,
S.E. Lee,
J.Y. Lee,
L.H. Kuller,
O.L. Lopez,
H.J. Aizenstein,
C.C. Meltzer,
Yanxi Liu,
A.W. Toga, J.T. Becker
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ABSTRACT: We present a fully-automated technique for visualizing localized cerebral ventricle shape differences between large clinical subject groups who have received a magnetic resonance (MR) image scan. The technique combines a robust, automated technique for ventricular segmentation with a 3D surface-based radial thickness mapping approach that allows spatially-localized statistical tests of relative shape differences between clinical groups. The technique is used to analyze localized ventricular expansion in Alzheimer's disease (AD) and mild cognitive impairment (MCI) in a large cohort of community-dwelling elderly individuals (N=339). The resulting maps are the first to chart localized ventricular dilation in a cohort of this size. Besides showing patterns of ventricular expansion that may be consistent with the spatial progression of AD-related pathology, the maps reveal new information about localized ventricular atrophy that may have been overlooked to date. A detailed understanding of spatial atrophy patterns may be useful for early disease detection or for patient monitoring in drug trials
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on; 05/2006
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O L Lopez, J T Becker,
W J Jagust,
A Fitzpatrick,
M C Carlson,
S T DeKosky,
J Breitner,
C G Lyketsos,
B Jones,
C Kawas,
L H Kuller
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ABSTRACT: To describe the neuropsychological characteristics of mild cognitive impairment (MCI) subgroups identified in the Cardiovascular Health Study (CHS) cognition study.
MCI was classified as MCI-amnestic type (MCI-AT): patients with documented memory deficits but otherwise normal cognitive function; and MCI-multiple cognitive deficits type (MCI-MCDT): impairment of at least one cognitive domain (not including memory), or one abnormal test in at least two other domains, but who had not crossed the dementia threshold. The MCI subjects did not have systemic, neurological, or psychiatric disorders likely to affect cognition.
MCI-AT (n = 10) had worse verbal and non-verbal memory performance than MCI-MCDT (n = 28) or normal controls (n = 374). By contrast, MCI-MCDT had worse language, psychomotor speed, fine motor control, and visuoconstructional function than MCI-AT or normal controls. MCI-MCDT subjects had memory deficits, though they were less pronounced than in MCI-AT. Of the MCI-MCDT cases, 22 (78.5%) had memory deficits, and 6 (21.5%) did not. MCI-MCDT with memory disorders had more language deficits than MCI-MCDT without memory disorders. By contrast, MCI-MCDT without memory deficits had more fine motor control deficits than MCI-MCDT with memory deficits.
The most frequent form of MCI was the MCI-MCDT with memory deficits. However, the identification of memory impaired MCI groups did not reflect the true prevalence of MCI in a population, as 16% of all MCI cases and 21.5% of the MCI-MCDT cases did not have memory impairment. Study of idiopathic amnestic and non-amnestic forms of MCI is essential for an understanding of the aetiology of MCI.
Journal of Neurology Neurosurgery & Psychiatry 03/2006; 77(2):159-65. · 4.76 Impact Factor
