Yi-Yu Chou

Generalized Tensor-Based Morphometry of HIV/AIDS Using Multivariate Statistics on Deformation Tensors

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 Hotellings 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-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.

Boosting power for clinical trials using classifiers based on multiple biomarkers

Machine learning methods pool diverse information to perform computer-assisted diagnosis and predict future clinical decline. We introduce a machine learning method to boost power in clinical trials. We created a Support Vector Machine algorithm that combines brain imaging and other biomarkers to classify 737 Alzheimers disease Neuroimaging initiative (ADNI) subjects as having Alzheimers disease (AD), mild cognitive impairment (MCI), or normal controls. We trained our classifiers based on example data including: MRI measures of hippocampal, ventricular, and temporal lobe volumes, a PET-FDG numerical summary, CSF biomarkers (t-tau, p-tau, and Abeta(42)), ApoE genotype, age, sex, and body mass index. MRI measures contributed most to Alzheimers disease (AD) classification; PET-FDG and CSF biomarkers, particularly Abeta(42), contributed more to MCI classification. Using all biomarkers jointly, we used our classifier to select the one-third of the subjects most likely to decline. In this subsample, fewer than 40 AD and MCI subjects would be needed to detect a 25% slowing in temporal lobe atrophy rates with 80% power--a substantial boosting of power relative to standard imaging measures.

Hippocampal Atrophy and Ventricular Enlargement in Normal Aging, Mild Cognitive Impairment (MCI), and Alzheimer Disease

Alzheimer disease (AD) is the most common type of dementia worldwide. Hippocampal atrophy and ventricular enlargement have been associated with AD but also with normal aging. We analyzed 1.5-T brain magnetic resonance imaging data from 46 cognitively normal elderly individuals (NC), 33 mild cognitive impairment and 43 AD patients. Hippocampal and ventricular analyses were conducted with 2 novel semiautomated segmentation approaches followed by the radial distance mapping technique. Multiple linear regression was used to assess the effects of age and diagnosis on hippocampal and ventricular volumes and radial distance. In addition, 3-dimensional map correction for multiple comparisons was made with permutation testing. As expected, most significant hippocampal atrophy and ventricular enlargement were seen in the AD versus NC comparison. Mild cognitive impairment patients showed intermediate levels of hippocampal atrophy and ventricular enlargement. Significant effects of age on hippocampal volume and radial distance were seen in the pooled sample and in the NC and AD groups considered separately. Age-associated differences were detected in all hippocampal subfields and in the frontal and body/occipital horn portions of the lateral ventricles. Aging affects both the hippocampus and lateral ventricles independent of AD pathology, and should be included as covariate in all structural, hippocampal, and ventricular analyses when possible.

Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls

We aimed to improve on the single-atlas ventricular segmentation method of (Carmichael, O.T., Thompson, P.M., Dutton, R.A., Lu, A., Lee, S.E., Lee, J.Y., Kuller, L.H., Lopez, O.L., Aizenstein, H.J., Meltzer, C.C., Liu, Y., Toga, A.W., Becker, J.T., 2006. Mapping ventricular changes related to dementia and mild cognitive impairment in a large community-based cohort. IEEE ISBI. 315-318) by using multi-atlas segmentation, which has been shown to lead to more accurate segmentations (Chou, Y., Leporé, N., de Zubicaray, G., Carmichael, O., Becker, J., Toga, A., Thompson, P., 2008. Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimers disease, NeuroImage 40(2): 615-630); with this method, we calculated minimal numbers of subjects needed to detect correlations between clinical scores and ventricular maps. We also assessed correlations between emerging CSF biomarkers of Alzheimers disease pathology and localizable deficits in the brain, in 80 AD, 80 mild cognitive impairment (MCI), and 80 healthy controls from the Alzheimers Disease Neuroimaging Initiative. Six expertly segmented images and their embedded parametric mesh surfaces were fluidly registered to each brain; segmentations were averaged within subjects to reduce errors. Surface-based statistical maps revealed powerful correlations between surface morphology and 4 variables: (1) diagnosis, (2) depression severity, (3) cognitive function at baseline, and (4) future cognitive decline over the following year. Cognitive function was assessed using the mini-mental state exam (MMSE), global and sum-of-boxes clinical dementia rating (CDR) scores, at baseline and 1-year follow-up. Lower CSF Abeta(1-42) protein levels, a biomarker of AD pathology assessed in 138 of the 240 subjects, were correlated with lateral ventricular expansion. Using false discovery rate (FDR) methods, 40 and 120 subjects, respectively, were needed to discriminate AD and MCI from normal groups. 120 subjects were required to detect correlations between ventricular enlargement and MMSE, global CDR, sum-of-boxes CDR and clinical depression scores. Ventricular expansion maps correlate with pathological and cognitive measures in AD, and may be useful in future imaging-based clinical trials.

Brain Structure Changes Visualized in Early- and Late-Onset Blind Subjects

We examined 3D patterns of volume differences in the brain associated with blindness, in subjects grouped according to early and late onset. Using tensor-based morphometry, we mapped volume reductions and gains in 16 early-onset (EB) and 16 late-onset (LB) blind adults (onset <5 and >14 years old, respectively) relative to 16 matched sighted controls. Each subjects structural MRI was fluidly registered to a common template. Anatomical differences between groups were mapped based on statistical analysis of the resulting deformation fields revealing profound deficits in primary and secondary visual cortices for both blind groups. Regions outside the occipital lobe showed significant hypertrophy, suggesting widespread compensatory adaptations. EBs but not LBs showed deficits in the splenium and the isthmus. Gains in the non-occipital white matter were more widespread in the EBs. These differences may reflect regional alterations in late neurodevelopmental processes, such as myelination, that continue into adulthood.

Sex differences in brain structure in auditory and cingulate regions

We applied a new method to visualize the three-dimensional profile of sex differences in brain structure based on MRI scans of 100 young adults. We compared 50 men with 50 women, matched for age and other relevant demographics. As predicted, left hemisphere auditory and language-related regions were proportionally expanded in women versus men, suggesting a possible structural basis for the widely replicated sex differences in language processing. In men, primary visual, and visuo-spatial association areas of the parietal lobes were proportionally expanded, in line with prior reports of relative strengths in visuo-spatial processing in men. We relate these three-dimensional patterns to prior functional and structural studies, and to theoretical predictions based on nonlinear scaling of brain morphometry.

Multivariate statistics of the jacobian matrices in tensor based morphometry and their application to HIV/AIDS

Tensor-based morphometry (TBM) is widely used in computational anatomy as a means to understand shape variation between structural brain images. A 3D nonlinear registration technique is typically used to align all brain images to a common neuroanatomical template, and the deformation fields are analyzed statistically to identify group differences in anatomy. However, the differences are usually computed solely from the determinants of the Jacobian matrices that are associated with the deformation fields computed by the registration procedure. Thus, much of the information contained within those matrices gets thrown out in the process. Only the magnitude of the expansions or contractions is examined, while the anisotropy and directional components of the changes are ignored. Here we remedy this problem by computing multivariate shape change statistics using the strain matrices. As the latter do not form a vector space, means and covariances are computed on the manifold of positive-definite matrices to which they belong. We study the brain morphology of 26 HIV/AIDS patients and 14 matched healthy control subjects using our method. The images are registered using a high-dimensional 3D fluid registration algorithm, which optimizes the Jensen-Rényi divergence, an information-theoretic measure of image correspondence. The anisotropy of the deformation is then computed. We apply a manifold version of Hotellings T2 test to the strain matrices. Our results complement those found from the determinants of the Jacobians alone and provide greater power in detecting group differences in brain structure.

Mapping Brain Abnormalities in Boys with Autism

Children with autism spectrum disorder (ASD) exhibit characteristic cognitive and behavioral differences, but no systematic pattern of neuroanatomical differences has been consistently found. Recent neurodevelopmental models posit an abnormal early surge in subcortical white matter growth in at least some autistic children, perhaps normalizing by adulthood, but other studies report subcortical white matter deficits. To investigate the profile of these alterations in 3D, we mapped brain volumetric differences using a relatively new method, tensor‐based morphometry. 3D T1‐weighted brain MRIs of 24 male children with ASD (age: 9.5 years ± 3.2 SD) and 26 age‐matched healthy controls (age: 10.3 ± 2.4 SD) were fluidly registered to match a common anatomical template. Autistic children had significantly enlarged frontal lobes (by 3.6% on the left and 5.1% on the right), and all other lobes of the brain were enlarged significantly, or at trend level. By analyzing the applied deformations statistically point‐by‐point, we detected significant gray matter volume deficits in bilateral parietal, left temporal and left occipital lobes (P = 0.038, corrected), trend‐level cerebral white matter volume excesses, and volume deficits in the cerebellar vermis, adjacent to volume excesses in other cerebellar regions. This profile of excesses and deficits in adjacent regions may (1) indicate impaired neuronal connectivity, resulting from aberrant myelination and/or an inflammatory process, and (2) help to understand inconsistent findings of regional brain tissue excesses and deficits in autism. Hum Brain Mapp, 2009.

Pattern of hippocampal shape and volume differences in blind subjects.

Numerous studies in animals and humans have shown that the hippocampus (HP) is involved in spatial navigation and memory. Blind subjects, in particular, must memorize extensive information to compensate for their lack of immediate updating of spatial information. Increased demands on spatial cognition and memory may be associated with functional and structural HP plasticity. Here we examined local size and shape differences in the HP of blind and sighted individuals. A 3D parametric mesh surface was generated to represent right and left HPs in each individual, based on manual segmentations of 3D volumetric T1-weighted MR images of 22 blind subjects and 28 matched controls. Using a new surface mapping algorithm described in (Shi, Y., Thompson, P.M., de Zubicaray, G.I., Rose, S.E., Tu, Z., Dinov, I., Toga, A.W., Direct mapping of hippocampal surfaces with intrinsic shape context, NeuroImage, Available online May 24, (In Press).), we created an average hippocampal surface for the controls, and computed its normal distance to each individual surface. Statistical maps were created to visualize systematic anatomical differences between groups, and randomization tests were performed to correct for multiple comparisons. In both scaled and unscaled data, the anterior right HP was significantly larger, and the posterior right HP significantly smaller in blind individuals. No significant differences were found for left HP. These differences may reflect adaptive responses to sensory deprivation, and/or increased functional demands on memory systems. They offer a neuroanatomical substrate for future correlations with measures of navigation performance or functional activations related to variations in cognitive strategies.

Hippocampal and ventricular changes in Parkinson's disease mild cognitive impairment

We analyzed T1-weighted brain magnetic resonance imaging data of 100 cognitively normal elderly controls (NC), 127 cognitively normal Parkinsons disease (PD; PDCN) and 31 PD-associated mild cognitive impairment (PDMCI) subjects from the Norwegian ParkWest study. Using automated segmentation methods, followed by the radial distance technique and multiple linear regression we studied the effect of clinical diagnosis on hippocampal and ventricular radial distance while adjusting for age, education, and scanning site. PDCN subjects had significantly smaller bilateral hippocampal radial distance relative to NC. Nonamnestic PDMCI subjects showed smaller right hippocampal radial distance relative to NC. PDMCI subjects showed significant enlargement of all portions of the lateral ventricles relative to NC and significantly larger bilateral temporal and occipital and left frontal lateral ventricular expansion relative to PDCN subjects. Nonamnestic PDMCI subjects showed significant ventricular enlargement spanning all parts of the lateral ventricle while those with amnestic PDMCI showed changes localized to the left occipital horn. Hippocampal atrophy and lateral ventricular enlargement show promise as structural biomarkers for PD.