Showing papers by "Martha E. Shenton published in 2007"

Progressive and Interrelated Functional and Structural Evidence of Post-Onset Brain Reduction in Schizophrenia

Abstract: Context Progressive brain abnormalities in schizophrenia remain controversial. Evidence of interrelated progressive functional impairment would buttress the case for structural progression. Mismatch negativity (MMN) is reduced in chronic but not first-hospitalized schizophrenia and may index progressive structural changes. Objective To determine whether MMN shows associations with underlying auditory cortex gray matter at first hospitalization and progressive reduction longitudinally. Design Cross-sectional (first hospitalization) and longitudinal (1.5-year follow-up). Setting A private psychiatric hospital. Participants Protocol entrance: MMN and magnetic resonance imaging at first hospitalization in 20 subjects with schizophrenia, 21 subjects with bipolar disorder with psychosis, and 32 control subjects. Longitudinal electrophysiologic testing: MMN in 16 subjects with schizophrenia, 17 subjects with bipolar disorder, and 20 control subjects. Longitudinal electrophysiologic testing and magnetic resonance imaging: MMN and magnetic resonance imaging in 11 subjects with schizophrenia, 13 subjects with bipolar disorder, and 13 control subjects. At each time point, reported samples were group matched for age, handedness, and parental socioeconomic status. Interventions Electrophysiologic testing and high-resolution structural magnetic resonance imaging. Main Outcome Measures Mismatch negativity amplitude and Heschl gyrus and planum temporale gray matter volumes. Results Initially, groups did not differ in MMN amplitude. Subjects with schizophrenia showed associations between MMN and Heschl gyrus ( r = −0.52; P = .02) not present in the other groups. At longitudinal MMN testing, schizophrenia showed MMN reduction ( P = .004). Only schizophrenia evinced longitudinal left hemisphere Heschl gyrus reduction ( P = .003), highly correlated with MMN reduction ( r = 0.6; P = .04). Conclusions At first hospitalization for schizophrenia, MMN indexed left hemisphere Heschl gyrus gray matter volume, consistent with variable progression of prehospitalization cortical reduction. Longitudinally, the interrelated progressive reduction of functional and structural measures suggests progressive pathologic processes early in schizophrenia. An active process of progressive cortical reduction presents a potential therapeutic target. Mismatch negativity may be a simple, sensitive, and inexpensive index not only of this progressive pathologic process but also of successful intervention.

Orbitofrontal volume deficit in schizophrenia and thought disorder

Abstract: Orbitofrontal Cortex (OFC) structural abnormality in schizophrenia has not been well characterized, probably due to marked anatomical variability and lack of consistent definitions. We previously reported OFC sulcogyral pattern alteration and its associations with social disturbance in schizophrenia, but OFC volume associations with psychopathology and cognition have not been investigated. We compared chronically treated schizophrenia patients with healthy control (HC) subjects, using a novel, reliable parcellation of OFC subregions and their association with cognition, especially the Iowa Gambling Task (IGT), and with schizophrenic psychopathology including thought disorder. Twenty-four patients with schizophrenia and 25 age-matched HC subjects underwent MRI. OFC Regions of Interest (ROI) were manually delineated according to anatomical boundaries: Gyrus Rectus (GR); Middle Orbital Gyrus (MiOG); and Lateral Orbital Gyrus (LOG). The OFC sulcogyral pattern was also classified. Additionally, MiOG probability maps were created and compared between groups in a voxel-wise manner. Both groups underwent cognitive evaluations using the IGT, Wisconsin Card Sorting Test, and Trail Making Test (TMT). An 11% bilaterally smaller MiOG volume was observed in schizophrenia, compared with HC (F(1,47) = 17.4, P = 0.0001). GR and LOG did not differ, although GR showed a rightward asymmetry in both groups (F(1,47) = 19.2, P < 0.0001). The smaller MiOG volume was independent of the OFC sulcogyral pattern, which differed in schizophrenia and HC (chi2 = 12.49, P = 0.002). A comparison of MiOG probability maps suggested that the anterior heteromodal region was more affected in the schizophrenia group than the posterior paralimbic region. In the schizophrenia group, a smaller left MiOG was strongly associated with worse 'positive formal thought disorder' (r = -0.638, P = 0.001), and a smaller right MiOG with a longer duration of the illness (r = -0.618, P = 0.002). While schizophrenics showed poorer performance than HC in the IGT, performance was not correlated with OFC volume. However, within the HC group, the larger the right hemisphere MiOG volume, the better the performance in the IGT (r = 0.541, P = 0.005), and the larger the left hemisphere volume, the faster the switching attention performance for the TMT, Trails B (r = -0.608, P = 0.003). The present study, applying a new anatomical parcellation method, demonstrated a subregion-specific OFC grey matter volume deficit in patients with schizophrenia, which was independent of OFC sulcogyral pattern. This volume deficit was associated with a longer duration of illness and greater formal thought disorder. In HC the finding of a quantitative association between OFC volume and IGT performance constitutes, to our knowledge, the first report of this association.

Shape modeling and analysis with entropy-based particle systems

Abstract: This paper presents a new method for constructing compact statistical point-based models of ensembles of similar shapes that does not rely on any specific surface parameterization. The method requires very little preprocessing or parameter tuning, and is applicable to a wider range of problems than existing methods, including nonmanifold surfaces and objects of arbitrary topology. The proposed method is to construct a point-based sampling of the shape ensemble that simultaneously maximizes both the geometric accuracy and the statistical simplicity of the model. Surface point samples, which also define the shape-to-shape correspondences, are modeled as sets of dynamic particles that are constrained to lie on a set of implicit surfaces. Sample positions are optimized by gradient descent on an energy function that balances the negative entropy of the distribution on each shape with the positive entropy of the ensemble of shapes. We also extend the method with a curvature-adaptive sampling strategy in order to better approximate the geometry of the objects. This paper presents the formulation; several synthetic examples in two and three dimensions; and an application to the statistical shape analysis of the caudate and hippocampus brain structures from two clinical studies.

Free-Form B-spline Deformation Model for Groupwise Registration

Abstract: In this work, we extend a previously demonstrated entropy based groupwise registration method to include a free-form deformation model based on B-splines. We provide an efficient implementation using stochastic gradient descents in a multi-resolution setting. We demonstrate the method in application to a set of 50 MRI brain scans and compare the results to a pairwise approach using segmentation labels to evaluate the quality of alignment. Our results indicate that increasing the complexity of the deformation model improves registration accuracy significantly, especially at cortical regions.

A Hierarchical Algorithm for MR Brain Image Parcellation

Abstract: We introduce an algorithm for segmenting brain magnetic resonance (MR) images into anatomical compartments such as the major tissue classes and neuro-anatomical structures of the gray matter. The algorithm is guided by prior information represented within a tree structure. The tree mirrors the hierarchy of anatomical structures and the subtrees correspond to limited segmentation problems. The solution to each problem is estimated via a conventional classifier. Our algorithm can be adapted to a wide range of segmentation problems by modifying the tree structure or replacing the classifier. We evaluate the performance of our new segmentation approach by revisiting a previously published statistical group comparison between first-episode schizophrenia patients, first-episode affective psychosis patients, and comparison subjects. The original study is based on 50 MR volumes in which an expert identified the brain tissue classes as well as the superior temporal gyrus, amygdala, and hippocampus. We generate analogous segmentations using our new method and repeat the statistical group comparison. The results of our analysis are similar to the original findings, except for one structure (the left superior temporal gyrus) in which a trend-level statistical significance (p = 0.07) was observed instead of statistical significance.

Altered orbitofrontal sulcogyral pattern in schizophrenia

Abstract: Orbitofrontal alteration in schizophrenia has not been well characterized, likely due to marked anatomical variability. To investigate the presence of such alterations, we evaluated the sulcogyral pattern of this 'H-shaped' sulcus. Fifty patients with schizophrenia (100 hemispheres) and 50 age- and gender-matched control subjects (100 hemispheres) were evaluated using 3D high-spatial resolution MRI. Based on a previous study by Chiavaras and Petrides (2000), the sulcogyral pattern of the 'H-shaped' sulcus, which forms the boundaries of major orbitofrontal gyri, was classified into three types (Type I, II and III, in order of frequency) within each hemisphere. Chi-square analysis was performed to compare the sulcogyral pattern, and categorical regression was applied to investigate clinical/cognitive associations. The control data replicated the orbitofrontal sulcogyral pattern reported by Chiavaras and Petrides (P = 0.90-0.95), where the distribution was significantly different between the left and right hemisphere (Type I: right > left, Type II, III: left > right, chi2 = 6.41, P = 0.041). For schizophrenics, the distribution differed significantly from controls (chi2 = 11.90, P = 0.003), especially in the right hemisphere (chi2 = 13.67, P = 0.001). Moreover, the asymmetry observed in controls was not present in schizophrenia (chi2 = 0.13, P = 0.94). Specifically, the most frequent Type I expression was decreased and the rarest Type III expression was increased in schizophrenia, relative to controls. Furthermore, patients with Type III expression in any hemisphere evinced poorer socioeconomic status, poorer cognitive function, more severe symptoms and impulsivity, compared to patients without Type III expression. In contrast, patients with Type I in any hemisphere showed better cognitive function and milder symptoms compared to patients without Type I. Structurally, patients with Type III had significantly smaller intra-cranial contents (ICC) volumes than did patients without Type III (t(40) = 2.29, P = 0.027). The present study provides evidence of altered distribution of orbitofrontal sulcogyral pattern in schizophrenia, possibly reflecting a neurodevelopmental aberration in schizophrenia. Such altered sulcogyral pattern is unlikely to be due to secondary effects of the illness such as medication. Moreover, the structural association between Type III and small ICC volume, observed in the patient group, may suggest that Type III expression could be part of a systematic neurodevelopmental alteration, given that the small ICC volume could reflect early reduction of cranial growth driven by brain growth. The observed contrasting association of Type III expression with poorer outcome, and that of Type I expression with better outcome, further suggests clinical heterogeneity, and possible differences in treatment responsiveness in schizophrenia.

Episodic memory and neuroimaging of hippocampus and fornix in chronic schizophrenia.

Abstract: A group of 44 patients with schizophrenia and 43 age-matched controls completed psychometrically-matched tasks of recall and recognition. The patients showed similarly depressed scores across both recall and recognition matched tasks, independent of their reduced IQ and executive functioning scores. In addition, reduced memory scores correlated in the expected direction with magnetic resonance imaging (MRI) of the hippocampus and diffusion tension imaging (DTI) of the fornix for subsets of both patients and controls that had available these structural imaging measures. Reduced executive functioning also correlated with lower fornix integrity for the patient subset. However, increased hippocampal volume correlated, in the negative direction, with lower scores for executive functioning and IQ in the control subset. Implications of these results are discussed.

Global medical shape analysis using the Laplace-Beltrami spectrum

Abstract: This paper proposes to use the Laplace-Beltrami spectrum (LBS) as a global shape descriptor for medical shape analysis, allowing for shape comparisons using minimal shape preprocessing: no registration, mapping, or remeshing is necessary. The discriminatory power of the method is tested on a population of female caudate shapes of normal control subjects and of subjects with schizotypal personality disorder.

Statistical shape analysis of brain structures using spherical wavelets

Abstract: We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests and a spherical wavelet (SWC) shape representation. As an application, we analyze two brain structures, the caudate nucleus and the hippocampus, and compare the results obtained to shape analysis using a sampled point representation. Our results show that the SWC representation indicates new areas of significance preserved under the FDR correction for both the left caudate nucleus and left hippocampus. Additionally, the spherical wavelet representation provides a natural way to interpret the significance results in terms of scale in addition to knowing the spatial location of the regions

Global Medical Shape Analysis Using the Volumetric Laplace Spectrum

Abstract: This paper proposes to use the volumetric Laplace spectrum as a global shape descriptor for medical shape analysis. The approach allows for shape comparisons using minimal shape preprocessing. In particular, no registration, mapping, or remeshing is necessary. All computations can be performed directly on the voxel representations of the shapes. The discriminatory power of the method is tested on a population of female caudate shapes (brain structure) of normal control subjects and of subjects with schizotypal personality disorder. The behavior and properties of the volumetric Laplace spectrum are discussed extensively for both the Dirichlet and Neumann boundary condition showing advantages of the Neumann spectra. Both, the computations of spectra on 3D voxel data for shape matching as well as the use of the Neumann spectrum for shape analysis are completely new.

The Impact of Atlas Formation Methods on Atlas-Guided Brain Segmentation

Abstract: We analyze the impact of atlas construction within the context of an atlas-guided segmenter applied to a morphometry study in neuroanatomy. Auto- matic segmenters often rely on anatomical information encoded via probabilis- tic atlases. These atlases are frequently constructed by registering collections of training data. In this paper, we study the impact of registration methods as well as the training data on automatic segmentation results. With respect to registra- tion, we focus our comparison on pairwise vs. group-wise methods and fixed vs. online coordinate systems. For the training data, we consider collections of pop- ulation specific and general population data. To study the impact of these factors, we revisit a previously published statistical group comparison that was based on manual segmentations. For each atlas type, we record the group differences based on automatic segmentations and compare these findings to the original ones. Fur- thermore, we measure the Dice overlap between manual and automatic segmen- tations. Our results indicate some advantages for coordinate systems that are de- veloped in an online fashion.

The role of retrieval inhibition in the associative memory impairment of schizophrenia

Abstract: To examine retrieval-induced forgetting (RIF) in schizophrenia, subjects studied category-exemplar words taken from either strong or weak categories, and then practiced retrieval by completing category word-stems on half of the word pairs. Patients had reduced recall and recognition, but showed the expected RIF effect of better recall of unpracticed items from unpracticed categories than for unpracticed items from practiced categories. By contrast, patients and controls showed differing RIF for recognition as a function of categorical dominance: whereas controls showed RIF only for dominant category exemplar word pairs, patients showed RIF for both dominant and weak categories. Different patterns of baseline practiced retrieval for weak associate pairs in schizophrenia may explain this finding. The results failed to support faulty RIF in the associative memory impairment of schizophrenia.

Joint Registration and Clustering of Images.

Abstract: We demonstrate an EM-based algorithm that jointly registers and clusters a group of images using an affine transformation model. The output is a small number of prototype images that represent the different modes of the population. The proposed algorithm can be viewed as a generalization of other well-known atlas construction algorithms, where the collection of prototypes represent multiple atlases for that population. Our experiments indicate that the employment of multiple atlases improves the localization of the underlying structure in a new subject.

Outlier rejection for diffusion weighted imaging

Abstract: This paper introduces an outlier rejection and signal reconstruction method for high angular resolution diffusion weighted imaging. The approach is based on the thresholding of Laplacian measurements over the sphere of the apparent diffusion coefficient profiles defined for a given set of gradient directions. Exemplary results are presented.

Automatic Segmentation Using Non-Rigid Registration.

Abstract: Many neuroanatomy studies rely on brain tissue segmentations of magnetic resonance images (MRI). We present a segmentation tool, which performs this task automatically by analyzing the MRIs as well as tissue specific spatial priors. The priors are aligned to the patient through a non-rigid registration method. The segmentation itself is parameterized by an XML file making the approach easily adjustable to various segmentation problems. The tool is hidden beneath a ‘one-button’ user interface, which is simple to install and is applicable to a wide variety of image acquisition protocols.

Left temporal lobe abnormalities in schizophrenia and thought disorder: a quantitative mri study

Abstract: THOUGHT DISORDER: A QUANTITATIVE MRI STUDY MARTHA E. SHENTON1, Ph.D., RON KIKINIS5, M.D., FERENC A. JOLESZ5, M.D., SETH D. POLLAK1,2, M.A., MARJORIE LEMAY5, M.D., CYNTHIA G. WIBLE2,5, Ph.D., HIROTO HOKAMA2,5, M.D., JOHN MARTIN5, B.S., DAVE METCALF5, B.S., MICHAEL COLEMAN1, M.A., ROBERT W. McCARLEY2,M.D. 1 Department of Psychiatry, Harvard Medical School, Boston 2 Brockton Veteran Affairs Medical Center, Brockton, MA 3 Massachusetts Mental Health Center, Boston 4 McLean Hospital, Belmont, MA 5Department of Radiology, Harvard Medical School and the MRI Division, Surgical Planning Laboratory, Brigham and Women's Hospital, both in Boston

Semi-Automatic Parcellation of the Corpus Striatum

Abstract: The striatum is the input component of the basal ganglia from the cerebral cortex. It includes the caudate, putamen, and nucleus accumbens. Thus, the striatum is an important component in limbic frontal-subcortical circuitry and is believed to be relevant both for reward-guided behaviors and for the expression of psychosis. The dorsal striatum is composed of the caudate and putamen, both of which are further subdivided into pre- and post-commissural components. The ventral striatum (VS) is primarily composed of the nucleus accumbens. The striatum can be functionally divided into three broad regions: 1) a limbic; 2) a cognitive and 3) a sensor-motor region. The approximate corresponding anatomic subregions for these 3 functional regions are: 1) the VS; 2) the pre/post-commissural caudate and the pre-commissural putamen and 3) the post-commissural putamen. We believe assessing these subregions, separately, in disorders with limbic and cognitive impairment such as schizophrenia may yield more informative group differences in comparison with normal controls than prior parcellation strategies of the striatum such as assessing the caudate and putamen. The manual parcellation of the striatum into these subregions is currently defined using certain landmark points and geometric rules. Since identification of these areas is important to clinical research, a reliable and fast parcellation technique is required. Currently, only full manual parcellation using editing software is available; however, this technique is extremely time intensive. Previous work has shown successful application of heuristic rules into a semi-automatic platform1. We present here a semi-automatic algorithm which implements the rules currently used for manual parcellation of the striatum, but requires minimal user input and significantly reduces the time required for parcellation.