1 LENITEM Laboratory of Epidemiology, Neuroimaging & Telemedicine IRCCS Centro S. Giovanni di Dio FBF, Brescia, Italy 2 Machine Vision Laboratory, Department of Mathemat ics and Computer Science, University of Udine, Udin e, Italy 3 Neuroradiology Unit, Hospital Città di Brescia, B rescia 4 Laboratory of Neuro Imaging, Department of Neurol ogy, UCLA School of Medicine, Los Angeles, CA, USA 5 Psychogeriatrics Ward – IRCCS Centro S. Giovanni di Dio FBF, Brescia, Italy 6 AFaR Associazione Fatebenefratelli per la Ricerca , Rome, Italy

Callosal volume reduction has been observed in patients with bipolar disorder, but whether these deficits reflect genetic vulnerability to the illness remains unresolved. Here, we used computational methods to map corpus callosum abnormalities in a population-based sample of twin pairs discordant for bipolar disorder. Twenty-one probands with bipolar I disorder (mean age 44.4 ± 7.5 years; 48% female), 19 of their non-bipolar co-twins, and 34 demographically matched control twin individuals underwent magnetic resonance imaging. Three-dimensional callosal surface models were created to visualize its morphologic variability and to localize group differences. Neurocognitive correlates of callosal area differences were additionally investigated in a subsample of study participants. Bipolar (BPI) probands, but not their co-twins, showed significant callosal thinning and area reduction, most pronounced in the genu and splenium, relative to healthy twins. Altered callosal curvature was additionally observed in BPI probands. In bipolar probands and co-twins, genu and splenium midsagittal areas were significantly correlated with verbal processing speed and response inhibition. These findings suggest that aberrant connections between cortical regions—possibly reflecting decreased myelination of white matter tracts—may be involved in bipolar pathophysiology. However, findings of callosal thinning appear to be disease related, rather than reflecting genetic vulnerability to bipolar illness.

Background: Both familial and sporadic Alzheimer’s disease (AD) result in progressive cortical and subcortical atrophy. Familial autosomal dominant AD (FAD) allows us to study AD brain changes presymptomatically. Methods: 33 subjects at risk for FAD (25 for PSEN1 and 8 for APP mutations; 22 mutation carriers and 11 controls) and 3 demented PSEN1 mutation carriers underwent T1-weighted MPRAGE 1.5T MRI. Using the hippocampal radial distance and cortical pattern matching techniques, we investigated the effects of carrier status and dementia diagnosis on cortical and hippocampal atrophy. All analyses were corrected for age and relative age (years to median age of disease onset in the family). Results: The dementia cases had pronounced cortical atrophy in the lateral and medial parietal, posterior cingulate and frontal cortices and hippocampal atrophy bilaterally relative to both nondemented carriers and controls. Nondemented carriers did not show significant cortical thinning or hippocampal atrophy relative to controls. Conclusions: FAD is associated with thinning of the posterior association and frontal cortices and hippocampal atrophy. Larger sample sizes may be necessary to reliably identify cortical atrophy in presymptomatic carriers.

Localized Components Analysis (LoCA) is a new method for describing surface shape variation in an ensemble of objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations, and the formulation of locality is flexible enough to incorporate properties such as symmetry. This paper demonstrates that LoCA can provide intuitive presentations of shape differences associated with sex, disease state, and species in a broad range of biomedical specimens, including human brain regions and monkey crania.

Sulcal and gyral landmarks on the human cerebral cortex are required for various studies of the human brain. Whether used directly to examine sulcal geometry, or indirectly to drive cortical surface registration methods, the accuracy of these landmarks is essential. While several methods have been developed to automatically identify sulci and gyri, their accuracy may be insufficient for certain neuroanatomical studies. We describe a semi-automated procedure that delineates a sulcus or gyrus given a limited number of user-selected points. The method uses a graph theory approach to identify the lowest-cost path between the points, where the cost is a combination of local curvature features and the distance between vertices on the surface representation. We implemented the algorithm in an interface that guides the user through a cortical surface delineation protocol, and we incorporated this tool into our BrainSuite software. We performed a study to compare the results produced using our method with results produced using Display, a popular tool that has been used extensively for manual delineation of sulcal landmarks. Six raters were trained on the delineation protocol. They performed delineations on 12 brains using both software packages. We performed a statistical analysis of 3 aspects of the delineation task: time required to delineate the surface, registration accuracy achieved compared to an expert-delineated gold-standard, and variation among raters. Our new method was shown to be faster to use, to provide reduced inter-rater variability, and to provide results that were at least as accurate as those produced using Display.

OBJECTIVES:There is compelling evidence that pathological high-frequency oscillations (HFOs), called fast ripples (FR, 150-500Hz), reflect abnormal synchronous neuronal discharges in areas responsible for seizure genesis in patients with mesial temporal lobe epilepsy (MTLE). It is hypothesized that morphological changes associated with hippocampal atrophy (HA) contribute to the generation of FR, yet there is limited evidence that hippocampal FR-generating sites correspond with local areas of atrophy.METHODS:Interictal HFOs were recorded from hippocampal microelectrodes in 10 patients with MTLE. Rates of FR and ripple discharge from each microelectrode were evaluated in relation to local measures of HA obtained using 3-dimensional magnetic resonance imaging (MRI) hippocampal modeling.RESULTS:Rates of FR discharge were 3 times higher in areas of significant local HA compared with rates in nonatrophic areas. Furthermore, FR occurrence correlated directly with the severity of damage in these local atrophic regions. In contrast, we found no difference in rates of ripple discharge between local atrophic and nonatrophic areas.INTERPRETATION:The proximity between local HA and microelectrode-recorded FR suggests that morphological changes such as neuron loss and synaptic reorganization may contribute to the generation of FR. Pathological HFOs, such as FR, may provide a reliable surrogate marker of abnormal neuronal excitability in hippocampal areas responsible for the generation of spontaneous seizures in patients with MTLE. Based on these data, it is possible that MRI-based measures of local HA could identify FR-generating regions, and thus provide a noninvasive means to localize epileptogenic regions in hippocampus.

Purpose: Current evidence suggests that the mechanisms underlying depth electrode recorded seizures beginning with hypersynchronous (HYP) onset patterns are functionally distinct from those giving rise to low-voltage fast (LVF) onset seizures. However, both groups have been associated with hippocampal atrophy (HA), indicating a need to clarify the anatomic correlates of each ictal onset type. We used three-dimensional (3D) hippocampal mapping to quantify HA and determine whether each onset group exhibited a unique distribution of atrophy consistent with the functional differences that distinguish the two onset morphologies.Methods: Sixteen nonconsecutive patients with medically refractory epilepsy were assigned to HYP or LVF groups according to ictal onset patterns recorded with intracranial depth electrodes. Using preimplant magnetic resonance imaging (MRI), levels of volumetrically defined HA were determined by comparison with matched controls, and the distribution of local atrophy was mapped onto 3D hippocampal surface models.Results: HYP and LVF groups exhibited significant and equivalent levels of HA ipsilateral to seizure onset. Patients with LVF onset seizures also showed significant contralateral volume reductions. On ipsilateral contour maps HYP patients exhibited an atrophy pattern consistent with classical hippocampal sclerosis (HS), whereas LVF atrophy was distributed more laterally and diffusely. Contralateral LVF maps also showed regions of subicular atrophy.Discussion: The HS-like distribution of atrophy and the restriction of HA to the ipsilateral hippocampus in HYP patients are consistent with focal hippocampal onsets, and suggest a mechanism utilizing intrahippocampal circuitry. In contrast, the bilateral distribution of nonspecific atrophy in the LVF group may reflect mechanisms involving both hippocampal and extrahippocampal networks.

In this paper, we propose an automated approach for the joint detection of major sulci on cortical surfaces. By representing sulci as nodes in a graphical model, we incorporate Markovian relations between sulci and formulate their detection as a maximum a posteriori (MAP) estimation problem over the joint space of major sulci. To make the inference tractable, a sample space with a finite number of candidate curves is automatically generated at each node based on the Hamilton-Jacobi skeleton of sulcal regions. Using the AdaBoost algorithm, we learn both individual and pairwise shape priors of sulcal curves from training data, which are then used to define potential functions in the graphical model based on the connection between AdaBoost and logistic regression. Finally belief propagation is used to perform the MAP inference and select the joint detection results from the sample spaces of candidate curves. In our experiments, we quantitatively validate our algorithm with manually traced curves and demonstrate the automatically detected curves can capture the main body of sulci very accurately. A comparison with independently detected results is also conducted to illustrate the advantage of the joint detection approach.

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.

Progressive brain atrophy in HIV/AIDS is associated with impaired psychomotor performance, perhaps partly reflecting cerebellar degeneration; yet little is known about how HIV/AIDS affects the cerebellum. We visualized the three-dimensional profile of atrophy in 19 HIV-positive patients (age: 42.9±8.3 years) versus 15 healthy controls (age: 38.5±12.0 years). We localized consistent patterns of subregional atrophy with an image analysis method that automatically deforms each patient's scan, in three dimensions, to match a reference image. Atrophy was greatest in the posterior cerebellar vermis (14.9% deficit) and correlated with depression severity (P=0.009, corrected), but not with dementia, alcohol/substance abuse, CD4+T-cell counts, or viral load. Profound cerebellar deficits in HIV/AIDS (P=0.007, corrected) were associated with depression, suggesting a surrogate disease marker for antiretroviral trials.

The 22q11.2 deletion syndrome (velocardiofacial/DiGeorge syndrome) is a neurogenetic condition associated with visuospatial deficits, as well as elevated rates of attentional disturbance, mood disorder, and psychosis. Previously, we detected pronounced cortical thinning in superior parietal and right parieto-occipital cortices in patients with this syndrome, regions critical for visuospatial processing. Here we applied cortical pattern-matching algorithms to structural magnetic resonance images obtained from 21 children with confirmed 22q11.2 deletions (ages 8-17) and 13 demographically matched comparison subjects, in order to map cortical thickness across the medial hemispheric surfaces. In addition, cortical models were remeshed in frequency space to compute their surface complexity. Cortical maps revealed a pattern of localized thinning in the ventromedial occipital-temporal cortex, critical for visuospatial representation, and the anterior cingulate, a key area for attentional control. However, children with 22q11.2DS showed significantly increased gyral complexity bilaterally in occipital cortex. Regional gray matter volumes, particularly in medial frontal cortex, were strongly correlated with both verbal and nonverbal cognitive functions. These findings suggest that aberrant parieto-occipital brain development, as evidenced by both increased complexity and cortical thinning in these regions, may be a neural substrate for the deficits in visuospatial and numerical understanding characteristic of this syndrome.

Declarative memory impairments are common in patients with bipolar illness, suggesting underlying hippocampal pathology. However, hippocampal volume deficits are rarely observed in bipolar disorder. Here we used surface-based anatomic mapping to examine hippocampal anatomy in bipolar patients treated with lithium relative to matched control subjects and unmedicated patients with bipolar disorder. High-resolution brain magnetic resonance images were acquired from 33 patients with bipolar disorder (21 treated with lithium and 12 unmedicated), and 62 demographically matched healthy control subjects. Three-dimensional parametric mesh models were created from manual tracings of the hippocampal formation. Total hippocampal volume was significantly larger in lithium-treated bipolar patients compared with healthy controls (by 10.3%; p=0.001) and unmedicated bipolar patients (by 13.9%; p=0.003). Statistical mapping results, confirmed by permutation testing, revealed localized deficits in the right hippocampus, in regions corresponding primarily to cornu ammonis 1 subfields, in unmedicated bipolar patients, as compared to both normal controls (p=0.01), and in lithium-treated bipolar patients (p=0.03). These findings demonstrate the sensitivity of these anatomic mapping methods for detecting subtle alterations in hippocampal structure in bipolar disorder. The observed reduction in subregions of the hippocampus in unmedicated bipolar patients suggests a possible neural correlate for memory deficits frequently reported in this illness. Moreover, increased hippocampal volume in lithium-treated bipolar patients may reflect postulated neurotrophic effects of this agent, a possibility warranting further study in longitudinal investigations.

We investigated the associations between Boston naming and the animal fluency tests and cortical atrophy in 19 probable AD and 5 multiple domain amnestic mild cognitive impairment patients who later converted to AD. We applied a surface-based computational anatomy technique to MRI scans of the brain and then used linear regression models to detect associations between animal fluency and Boston Naming Test (BNT) performance and cortical atrophy. The global permutation-corrected significance for the maps associating BNT performance with cortical atrophy was p = .0124 for the left and p = .0196 for the right hemisphere and for the animal fluency maps p = .055 for the left and p = .073 for the right hemisphere. The degree of language impairment correlated with cortical atrophy in the left temporal and parietal lobes (BA 20, 21, 37, 39, 40, and 7), bilateral frontal lobes (BA 8, 9, and 44) and the right temporal pole (BA 38). Using a novel 3D mapping technique, we demonstrated that in AD language abilities are strongly influenced by the integrity of the perisylvian cortical regions.

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

35% of HIV-infected patients have cognitive impairment, but the profile of HIV-induced brain damage is still not well understood. Here we used tensor-based morphometry (TBM) to visualize brain deficits and clinical/anatomical correlations in HIV/AIDS. To perform TBM, we developed a new MRI-based analysis technique that uses fluid image warping, and a new a-entropy-based information-theoretic measure of image correspondence, called the Jensen-Renyi divergence (JRD).Methods: 3D T1-weighted brain MRIs of 26 AIDS patients (CDC stage C and/or 3 without HIV-associated dementia; 47.2 +/- 9.8 years; 25M/1F; CD4+ T-cell count: 299.5 +/- 175.7/mu l; log(10) plasma viral load: 2.57 +/- 1.28 RNA copies/ml) and 14 RIV-seronegative controls (37.6 +/- 12.2 years; 8M/ 6F) were fluidly registered by applying forces throughout each deforming image to maximize the JRD between it and a target image (from a control subject). The 3D fluid registration was regularized using the linearized Cauchy-Navier operator. Fine-scale volumetric differences between diagnostic groups were mapped. Regions were identified where brain atrophy correlated with clinical measures.Results: Severe atrophy (similar to 15-20% deficit) was detected bilaterally in the primary and association sensorimotor areas. Atrophy of these regions, particularly in the white matter, correlated with cognitive impairment (P=0.033) and CD4(+) T-lymphocyte depletion (P=0.005). Conclusion: TBM facilitates 3D visualization of AIDS neuropathology in living patients scanned with MRI. Severe atrophy in frontoparietal and striatal areas may underlie early cognitive dysfunction in AIDS patients, and may signal the imminent onset of AIDS dementia complex. (c) 2006 Elsevier Inc. All rights reserved.

12 We investigated the associations between Boston naming and the animal fluency tests and cortical atrophy in 19 probable AD and 5 13 multiple domain amnestic mild cognitive impairment patients who later converted to AD. We applied a surface-based computational 14 anatomy technique to MRI scans of the brain and then used linear regression models to detect associations between animal fluency 15 and Boston Naming Test (BNT) performance and cortical atrophy. The global permutation-corrected significance for the maps associ16 ating BNT performance with cortical atrophy was p = .0124 for the left and p = .0196 for the right hemisphere and for the animal fluency 17 maps p = .055 for the left and p = .073 for the right hemisphere. The degree of language impairment correlated with cortical atrophy in 18 the left temporal and parietal lobes (BA 20, 21, 37, 39, 40, and 7), bilateral frontal lobes (BA 8, 9, and 44) and the right temporal pole 19 (BA 38). Using a novel 3D mapping technique, we demonstrated that in AD language abilities are strongly influenced by the integrity of 20 the perisylvian cortical regions. 21 ! 2007 Published by Elsevier Inc.

Abstract: Population-based brain mapping provides great insight into the trajectory of aging and dementia, as well as brain changes that normally occur over the human life span. We describe three novel brain mapping techniques, cortical thickness mapping , tensor-based morphometry (TBM) , and hippocampal surface modeling , which offer enormous power for measuring disease progression in drug trials, and shed light on the neuroscience of brain degeneration in Alzheimer's disease (AD) and mild cognitive impairment (MCI). We report the first time-lapse maps of cortical atrophy spreading dynamically in the living brain, based on averaging data from populations of subjects with Alzheimer's disease and normal subjects imaged longitudinally with MRI. These dynamic sequences show a rapidly advancing wave of cortical atrophy sweeping from limbic and temporal cortices into higher-order association and ultimately primary sensorimotor areas, in a pattern that correlates with cognitive decline. A complementary technique, TBM, reveals the 3D profile of atrophic rates, at each point in the brain. A third technique, hippocampal surface modeling , plots the profile of shape alterations across the hippocampal surface. The three techniques provide moderate to highly automated analyses of images, have been validated on hundreds of scans, and are sensitive to clinically relevant changes in individual patients and groups undergoing different drug treatments. We compare time-lapse maps of AD, MCI, and other dementias, correlate these changes with cognition, and relate them to similar time-lapse maps of childhood development, schizophrenia, and HIV-associated brain degeneration. Strengths and weaknesses of these different imaging measures for basic neuroscience and drug trials are discussed.

In this paper we propose an automated approach for joint sulci detection on cortical surfaces by using graphical models and boosting techniques to incorporate shape priors of major sulci and their Markovian relations. For each sulcus, we represent it as a node in the graphical model and associate it with a sample space of candidate curves, which is generated automatically using the Hamilton-Jacobi skeleton of sulcal regions. To take into account individual as well as joint priors about the shape of major sulci, we learn the potential functions of the graphical model using AdaBoost algorithm to select and fuse information from a large set of features. This discriminative approach is especially powerful in capturing the neighboring relations between sulcal lines, which are otherwise hard to be captured by generative models. Using belief propagation, efficient inferencing is then performed on the graphical model to estimate each sulcus as the maximizer of its final belief. On a data set of 40 cortical surfaces, we demonstrate the advantage of joint detection on four major sulci: central, precentral, postcentral and the sylvian fissure.