Diffusion Tensor Imaging, Structural Connectivity, and Schizophrenia

A fundamental tenet of the “disconnectivity” theories of schizophrenia is that the disorder is ultimately caused by abnormal communication between spatially disparate brain structures. Given that the white matter fasciculi represent the primary infrastructure for long distance communication in the brain, abnormalities in these fiber bundles have been implicated in the etiology of schizophrenia. Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that enables the visualization of white matter macrostructure in vivo, and which has provided unprecedented insight into the existence and nature of white matter abnormalities in schizophrenia. The paper begins with an overview of DTI and more commonly used diffusion metrics and moves on to a brief review of the schizophrenia literature. The functional implications of white matter abnormalities are considered, particularly with respect to myelin's role in modulating the transmission velocity of neural discharges. The paper concludes with a speculative hypothesis about the relationship between gray and white matter abnormalities associated with schizophrenia

Tubular Surface Evolution for Segmentation of the Cingulum Bundle From DW-MRI

Presented at the 2nd MICCAI Workshop on Mathematical Foundations of Computational Anatomy: Geometrical and Statistical Methods for Biological Shape Variability Modeling, September 6th, 2008, Kimmel Center, New York, USA.This work provides a framework for modeling and extracting the Cingulum Bundle (CB) from Diffusion-Weighted Imagery (DW-MRI) of the brain. The CB is a tube-like structure in the brain that is of potentially of tremendous importance to clinicians since it may be helpful in diagnosing Schizophrenia. This structure consists of a collection of fibers in the brain that have locally similar diffusion patterns, but vary globally. Standard region-based segmentation techniques adapted to DW-MRI are not suitable here because the diffusion pattern of the CB cannot be described by a global set of simple statistics. Active surface models extended to DW-MRI are not suitable since they allow for arbitrary deformations that give rise to unlikely shapes, which do not respect the tubular geometry of the CB. In this work, we explicitly model the CB as a tube-like surface and construct a general class of energies defined on tube-like surfaces. An example energy of our framework is optimized by a tube that encloses a region that has locally similar diffusion patterns, which differ from the diffusion patterns immediately outside. Modeling the CB as a tube-like surface is a natural shape prior. Since a tube is characterized by a center-line and a radius function, the method is reduced to a 4D (center-line plus radius) curve evolution that is computationally much less costly than an arbitrary surface evolution. The method also provides the center-line of CB, which is potentially of clinical significance

The Application of DTI to Investigate White Matter Abnormalities in Schizophrenia

Schizophrenia is a serious and disabling mental disorder that affects approximately 1% of the general population, with often devastating effects on the psychological and financial resources of the patient, family, and larger community. The etiology of schizophrenia is not known, although it likely involves several interacting biological and environmental factors that predispose an individual to schizophrenia. However, although the underlying pathology remains unknown, it has been believed that brain abnormalities would ultimately be linked to the etiology of schizophrenia. This theory was rekindled in the 1970s, when the first computer-assisted tomography (CT) study showed enlarged lateral ventricles in schizophrenia. Since that time, there have been many improvements in MR acquisition and image processing, including the introduction of positron emission tomography (PET), followed by functional MR (fMRI), and diffusion tensor imaging (DTI). These advances have led to an appreciation of the critical role that brain abnormalities play in schizophrenia. While structural MRI has proven to be useful in investigating and detecting gray matter abnormalities in schizophrenia, the investigation of white matter has proven to be more challenging as white matter appears homogeneous on conventional MRI and the fibers connecting different brain regions cannot be appreciated. With the development of DTI, we are now able to investigate white matter abnormalities in schizophrenia

Voxel-based morphometry (VBM) studies in schizophrenia—can white matter changes be reliably detected with VBM?

Voxel-Based Morphometry (VBM) is a hypothesis-free, whole-brain, voxel-by-voxel analytic method that attempts to compare imaging data between populations. Schizophrenia studies have utilized this method to localize differences in Diffusion Tensor Imaging (DTI) derived Fractional Anisotropy (FA), a measure of white matter integrity, between patients and healthy controls. The number of publications has grown, although it is unclear how reliable and reproducible this method is, given the subtle white matter abnormalities expected in schizophrenia. Here we analyze and combine results from 23 studies published to date that use VBM to study schizophrenia in order to evaluate the reproducibility of this method in DTI analysis. Coordinates of each region reported in DTI VBM studies published thus far in schizophrenia were plotted onto a Montreal Neurological Institute atlas, and their anatomical locations were recorded. Results indicated that the reductions of FA in patients with schizophrenia were scattered across the brain. Moreover, even the most consistently reported regions were reported independently in less than 35% of the papers studied. Other instances of reduced FA were replicated at an even lower rate. Our findings demonstrate striking inconsistency, with none of the regions reported in much more than a third of the published papers. Poor replication rate suggests that the application of VBM to DTI data may not be the optimal way for studying the subtle microstructural abnormalities that are being hypothesized in schizophrenia

On Describing Human White Matter Anatomy: The White Matter Query Language

The main contribution of this work is the careful syntactical definition of major white matter tracts in the human brain based on a neuroanatomist’s expert knowledge. We present a technique to formally describe white matter tracts and to automatically extract them from diffusion MRI data. The framework is based on a novel query language with a near-to-English textual syntax. This query language allows us to construct a dictionary of anatomical definitions describing white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This enables automated coherent labeling of white matter anatomy across subjects. We use our method to encode anatomical knowledge in human white matter describing 10 association and 8 projection tracts per hemisphere and 7 commissural tracts. The technique is shown to be comparable in accuracy to manual labeling. We present results applying this framework to create a white matter atlas from 77 healthy subjects, and we use this atlas in a proof-of-concept study to detect tract changes specific to schizophrenia.Psycholog

Neuropsychological disturbance in schizophrenia: A diffusion tensor imaging study.

Patients with schizophrenia and healthy control subjects underwent both neuropsychological evaluation and magnetic resonance diffusion tensor imaging, during which the cingulum bundle (CB) and the uncinate fasciculus (UF) were defined with fiber tractography and their integrity was quantified. On the basis of prior findings, it was hypothesized that neuropsychological disturbance in schizophrenia may be characterized, in part, by 2 dissociable functional neuroanatomical relationships: (a) executive functioning–CB integrity and (b) episodic memory–UF integrity. In support of the hypothesis, hierarchical regression results indicated that reduced white matter of the CB and the UF differentially and specifically predicted deficits in executive functioning and memory, respectively. Neuropsychological correlates of the CB also extended to lower generalized intelligence, as well as to reduced visual memory that may be related to failures of contextual monitoring of to-be-remembered scenes. Reduced white matter of the CB and the UF may each make distinct contributions to neuropsychological disturbance in schizophrenia

Neuropsychological Correlates of Diffusion Tensor Imaging in Schizophrenia.

Patients with schizophrenia (n = 41) and healthy comparison participants (n = 46) completed neuropsychological measures of intelligence, memory, and executive function. A subset of each group also completed magnetic resonance diffusion tensor imaging (DTI) studies (fractional anisotropy and cross-sectional area) of the uncinate fasciculus (UF) and cingulate bundle (CB). Patients with schizophrenia showed reduced levels of functioning across all neuropsychological measures. In addition, selective neuropsychological–DTI relationships emerged. Among patients but not controls, lower levels of declarative–episodic verbal memory correlated with reduced left UF, whereas executive function errors related to performance monitoring correlated with reduced left CB. The data suggested abnormal DTI patterns linking declarative–episodic verbal memory deficits to the left UF and executive function deficits to the left CB among patients with schizophrenia

Gray matter alterations in early aging: A diffusion magnetic resonance imaging study

Many studies have observed altered neurofunctional and structural organization in the aging brain. These observations from functional neuroimaging studies show a shift in brain activity from the posterior to the anterior regions with aging (PASA model), as well as a decrease in cortical thickness, which is more pronounced in the frontal lobe followed by the parietal, occipital, and temporal lobes (retrogenesis model). However, very little work has been done using diffusion MRI (dMRI) with respect to examining the structural tissue alterations underlying these neurofunctional changes in the gray matter. Thus, for the first time, we propose to examine gray matter changes using diffusion MRI in the context of aging. In this work, we propose a novel dMRI based measure of gray matter “heterogeneity” that elucidates these functional and structural models (PASA and retrogenesis) of aging from the viewpoint of diffusion MRI. In a cohort of 85 subjects (all males, ages 15–55 years), we show very high correlation between age and “heterogeneity” (a measure of structural layout of tissue in a region-of-interest) in specific brain regions. We examine gray matter alterations by grouping brain regions into anatomical lobes as well as functional zones. Our findings from dMRI data connects the functional and structural domains and confirms the “retrogenesis” hypothesis of gray matter alterations while lending support to the neurofunctional PASA model of aging in addition to showing the preservation of paralimbic areas during healthy aging

Thalamo-frontal white matter alterations in chronic schizophrenia

Diffusion tensor imaging (DTI) and fiber tractography are useful tools for reconstructing white matter tracts (WMT) in the brain. Previous tractography studies have sought to segment reconstructed WMT into anatomical structures using several approaches, but quantification has been limited to extracting mean values of diffusion indices. Delineating WMT in schizophrenia is of particular interest because schizophrenia has been hypothesized to be a disorder of disrupted connectivity, especially between frontal and temporal regions of the brain. In this study, we aim to differentiate diffusion properties of thalamo-frontal pathways in schizophrenia from normal controls. We present a quantitative group comparison method, which combines the strengths of both tractography-based and voxel-based studies. Our algorithm extracts white matter pathways using whole brain tractography. Functionally relevant bundles are selected and parsed from the resulting set of tracts, using an internal capsule (IC) region of interest (ROI) as “source”, and different Brodmann area (BA) ROIs as “targets”. The resulting bundles are then longitudinally parameterized so that diffusion properties can be measured and compared along the WMT. Using this processing pipeline, we were able to find altered diffusion properties in male patients with chronic schizophrenia in terms of fractional anisotropy (FA) decreases and mean diffusivity (MD) increases in precise and functionally relevant locations. These findings suggest that our method can enhance the regional and functional specificity of DTI group studies, thus improving our understanding of brain function