Person:

Kubicki, Marek

We introduce a method for combining fiber tracking from diffusion-tensor (DT) imaging with cortical gray matter parcellation from structural high-spatial-resolution 3D spoiled gradient-recalled acquisition in the steady state images. We applied this method to a tumor case to determine the impact of the tumor on white matter architecture. We conclude that this new method for combining structural and DT imaging data is useful for understanding cortical connectivity and the localization of fiber tracts and their relationship with cortical anatomy and brain abnormalities.

Voxel-based morphometry (VBM) may afford a more rapid and extensive survey of gray matter abnormalities in schizophrenia than manually drawn region of interest (ROI) analysis, the current gold standard in structural MRI. Unfortunately, VBM has not been validated by comparison with ROI analyses, nor used in first-episode patients with schizophrenia or affective psychosis, who lack structural changes associated with chronicity. An SPM99-based implementation of VBM was used to compare a group of 16 patients with first-episode schizophrenia and a group of 18 normal controls and, as a further comparison, 16 first-episode patients with affective psychosis. All groups were matched for age and handedness. High spatial resolution structural images were normalized to the SPM99 template and then segmented, smoothed, and subjected to an ANCOVA. Schizophrenia vs control group comparisons: Voxel-by-voxel comparison of gray matter densities showed that only the left STG region was significantly different when corrected for multiple comparisons P < .05), consistent with our previously reported manual ROI results. Analysis of the extent of voxel clusters, replicated with permutation analyses, revealed group differences in bilateral anterior cingulate gyri and insula (not previously examined by us with manually drawn ROI) and unilateral parietal lobe, but not in medial temporal lobe (where our ROI analysis had shown differences). However, use of a smaller smoothing kernel and a small volume correction revealed left-sided hippocampal group differences. Affective psychosis comparisons: When the same statistical thresholding criteria were used, no significant differences between affective psychosis patients and controls were noted. Since a major interest was whether patients with affective psychosis shared some anatomical abnormalities with schizophrenia, we applied a small volume correction and searched within the regions that were significantly less dense in schizophrenia compared to control subjects. With this statistical correction, the insula showed, bilaterally, the same pattern of differences in affective disorder subjects as that in schizophrenic subjects, whereas both left STG and left hippocampus showed statistical differences between affectives and schizophrenics, indicating the abnormalities specific to first-episode schizophrenia. These findings suggest both the promise and utility of VBM in evaluating gray matter abnormalities. They further suggest the importance of comparing VBM findings with more traditional ROI analyses until the reasons for the differences between methods are determined.

Objective: Disruptions in connectivity between the frontal and temporal lobes may explain some of the symptoms observed in schizophrenia. Conventional magnetic resonance imaging (MRI) studies, however, have not shown compelling evidence for white matter abnormalities, because white matter fiber tracts cannot be visualized by conventional MRI. Diffusion tensor imaging is a relatively new technique that can detect subtle white matter abnormalities in vivo by assessing the degree to which directionally organized fibers have lost their normal integrity. The first three diffusion tensor imaging studies in schizophrenia showed lower anisotropic diffusion, relative to comparison subjects, in whole-brain white matter, prefrontal and temporal white matter, and the corpus callosum, respectively. Here the authors focus on fiber tracts forming temporal-frontal connections. Method: Anisotropic diffusion was assessed in the uncinate fasciculus, the most prominent white matter tract connecting temporal and frontal brain regions, in 15 patients with chronic schizophrenia and 18 normal comparison subjects. A 1.5-T GE Echospeed system was used to acquire 4-mm-thick coronal line-scan diffusion tensor images. Maps of the fractional anisotropy were generated to quantify the water diffusion within the uncinate fasciculus. Results: Findings revealed a group-by-side interaction for fractional anisotropy and for uncinate fasciculus area, derived from automatic segmentation. The patients with schizophrenia showed a lack of normal left-greater-than-right asymmetry seen in the comparison subjects. Conclusions: These findings demonstrate the importance of investigating white matter tracts in vivo in schizophrenia and support the hypothesis of a disruption in the normal pattern of connectivity between temporal and frontal brain regions in schizophrenia.

Objective: Previous research has noted functional and structural temporal lobe abnormalities in schizophrenia that relate to symptoms such as auditory hallucinations and thought disorder. The goal of the study was to determine whether the functional abnormalities are present in schizophrenia at early stages of auditory processing. Method: Functional magnetic resonance imaging activity was examined during the presentation of the mismatch stimuli, which are deviant tones embedded in a series of standard tones. The mismatch stimuli are used to elicit the mismatch negativity, an early auditory event-related potential. Ten patients with schizophrenia and 10 comparison subjects were presented the mismatch stimuli condition and a control condition in which only one tone was presented repeatedly. Results: The superior temporal gyrus showed the most prevalent and consistent activation. The superior temporal gyrus showed less activation in the schizophrenic subjects than in the comparison subjects only during the mismatch stimuli condition. Conclusions: This result is consistent with those of mismatch negativity event-related potential studies and suggests that early auditory processing is abnormal in chronic schizophrenia.

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.

Background: The hippocampus has been shown to be abnormal in schizophrenia. The fornix is one of the main fiber tracts connecting the hippocampus with other brain regions. Few studies have evaluated the fornix in schizophrenia, however. A focus on fornix abnormalities and their association with hippocampal abnormalities might figure importantly in our understanding of the pathophysiology of schizophrenia. Methods: Line-scan diffusion tensor imaging (DTI) was used to evaluate diffusion in the fornix in 24 male patients with chronic schizophrenia and 31 male control subjects. Maps of fractional anisotropy (FA) and mean diffusivity (Dm), which are indices sensitive to white-matter integrity, were generated to quantify diffusion within the fornix. We used high spatial resolution magnetic resonance imaging (MRI) to measure hippocampal volume. Results: FA and cross-sectional area of the fornix were significantly reduced in patients compared with control subjects. Dm was significantly increased, whereas hippocampal volume was bilaterally reduced in patients. Reduced hippocampal volume was correlated with increased mean Dm and reduced cross-sectional area of the fornix for patients. Patients also showed a significant correlation between reduced scores on neuropsychologic measures of declarative-episodic memory and reduced hippocampal volumes. Conclusions: These findings demonstrate a disruption in fornix integrity in patients with schizophrenia.

Both post-mortem and neuroimaging studies have contributed significantly to what we know about the brain and schizophrenia. MRI studies of volumetric reduction in several brain regions in schizophrenia have confirmed early speculations that the brain is disordered in schizophrenia. There is also a growing body of evidence suggesting that a disturbance in connectivity between different brain regions, rather than abnormalities within the separate regions themselves, are responsible for the clinical symptoms and cognitive dysfunctions observed in this disorder. Thus an interest in white matter fiber tracts, subserving anatomical connections between distant, as well as proximal, brain regions, is emerging. This interest coincides with the recent advent of diffusion tensor imaging (DTI), which makes it possible to evaluate the organization and coherence of white matter fiber tracts. This is an important advance as conventional MRI techniques are insensitive to fiber tract direction and organization, and have not consistently demonstrated white matter abnormalities. DTI may, therefore, provide important new information about neural circuitry, and it is increasingly being used in neuroimaging studies of psychopathological disorders. Of note, in the past five years 18 DTI studies in schizophrenia have been published, most describing white matter abnormalities. Questions still remain, however, regarding what we are measuring that is abnormal in this disease, and how measures obtained using one method correspond to those obtained using other methods? Below we review the basic principles involved in MR-DTI, followed by a review of the different methods used to evaluate diffusion. Finally, we review MR-DTI findings in schizophrenia.

Background: Using diffusion tensor imaging (DTI), we previously reported abnormalities in two critical white matter tracts in schizophrenia, the uncinate fasciculus (UF) and the cingulum bundle (CB), both related to fronto–temporal connectivity. Here, we investigate these two bundles in unmedicated subjects with schizotypal personality disorder (SPD). Methods: Fifteen male SPD subjects and 15 male control subjects were scanned with line-scan DTI. Fractional anisotropy (FA) and mean diffusivity (Dm) were used to quantify water diffusion, and cross-sectional area was defined with a directional threshold method. Exploratory correlation analyses were evaluated with Spearman’s rho, followed by post hoc hierarchical regression analyses. Results: We found bilaterally reduced FA in the UF of SPD subjects. For CB, there was no significant group difference for FA or Dm measures. Additionally, in SPD, reduced FA in the right UF was correlated with clinical symptoms, including ideas of reference, suspiciousness, restricted affect, and social anxiety. In contrast, left UF area was correlated with measures of cognitive function, including general intelligence, verbal and visual memory, and executive performance. Conclusions: These findings in SPD suggest altered fronto–temporal connectivity through the UF, similar to findings in schizophrenia, and intact neocortical–limbic connectivity through the CB, in marked contrast with what has been reported in schizophrenia.

Hemisphere asymmetry was explored in normal healthy subjects and in patients with schizophrenia using a novel voxel-based tensor analysis applied to fractional anisotropy (FA) of the diffusion tensor. Our voxel-based approach, which requires precise spatial normalization to remove the misalignment of fiber tracts, includes generating a symmetrical group average template of the diffusion tensor by applying nonlinear elastic warping of the demons algorithm. We then normalized all 32 diffusion tensor MRIs from healthy subjects and 23 from schizophrenic subjects to the symmetrical average template. For each brain, six channels of tensor component images and one T2-weighted image were used for registration to match tensor orientation and shape between images. A statistical evaluation of white matter asymmetry was then conducted on the normalized FA images and their flipped images. In controls, we found left-higher-than-right anisotropic asymmetry in the anterior part of the corpus callosum, cingulum bundle, the optic radiation, and the superior cerebellar peduncle, and right-higher-than-left anisotropic asymmetry in the anterior limb of the internal capsule and the anterior limb’s prefrontal regions, in the uncinate fasciculus, and in the superior longitudinal fasciculus. In patients, the asymmetry was lower, although still present, in the cingulum bundle and the anterior corpus callosum, and not found in the anterior limb of the internal capsule, the uncinate fasciculus, and the superior cerebellar peduncle compared to healthy subjects. These findings of anisotropic asymmetry pattern differences between healthy controls and patients with schizophrenia are likely related to neuro-developmental abnormalities in schizophrenia.

This paper describes a novel user-guided method for grouping fibers from diffusion tensor MRI tractography into bundles. The method finds fibers, that passing through user-defined ROIs, still fit to the underlying data model given by the diffusion tensor. This is achieved by filtering the data and the ROIs with a kernel derived from a geodesic metric between tensors. A standard approach using binary decisions defining tracts passing through ROIs is critically dependent on ROIs that includes all trace lines of interest. The method described in this paper uses a softer decision mechanism through a kernel which enables grouping of bundles driven less exact, or even single point, ROIs. The method analyzes the responses obtained from the convolution with a kernel function along the fiber with the ROI data. Results in real data shows the feasibility of the approach to fiber bundling.