BACKGROUND AND PURPOSE: MR diffusion tensor imaging permits detailed visualization of white matter fiber tracts. This technique, unlike T2-weighted imaging, also provides information about fiber direction. We present findings of normal white matter fiber tract anatomy at high resolution obtained by using line scan diffusion tensor imaging.
METHODS: Diffusion tensor images in axial, coronal, and sagittal sections covering the entire brain volume were obtained with line scan diffusion imaging in six healthy volunteers. Images were acquired for b factors 5 and 1000 s/mm(2) at an imaging resolution of 1.7 x 1.7 x 4 mm. For selected regions, images were obtained at a reduced field of view with a spatial resolution of 0.9 x 0.9 x 3 mm. For each pixel, the direction of maximum diffusivity was computed and used to display the course of white matter fibers.
RESULTS: Fiber directions derived from diffusion tensor imaging were consistent with known white matter fiber anatomy. The principal fiber tracts were well observed in all cases. The tracts that were visualized included the following: the arcuate fasciculus; superior and inferior longitudinal fasciculus; uncinate fasciculus; cingulum; external and extreme capsule; internal capsule; corona radiata; auditory and optic radiation; anterior commissure; corpus callosum; pyramidal tract; gracile and cuneatus fasciculus; medial longitudinal fasciculus; rubrospinal, tectospinal, central tegmental, and dorsal trigeminothalamic tract; superior, inferior, and middle cerebellar peduncle; pallidonigral and strionigral fibers; and root fibers of the oculomotor and trigeminal nerve.
CONCLUSION: We obtained a complete set of detailed white matter fiber anatomy maps of the normal brain by means of line scan diffusion tensor imaging at high resolution. Near large bone structures, line scan produces images with minimal susceptibility artifacts.
New medical imaging modalities offering multi-valued data, such as phase contrast MRA and diffusion tensor MRI, require general representations for the development of automated algorithms. In this paper we propose a unified framework for the registration of medical volumetric multi-valued data using local matching. The paper extends the usual concept of similarity between two pieces of data to be matched, commonly used with scalar (intensity) data, to the general tensor case. Our approach to registration is based on a multiresolution scheme, where the deformation field estimated in a coarser level is propagated to provide an initial deformation in the next finer one. In each level, local matching of areas with a high degree of local structure and subsequent interpolation are performed. Consequently, we provide an algorithm to assess the amount of structure in generic multi-valued data by means of gradient and correlation computations. The interpolation step is carried out by means of the Kriging estimator, which provides a novel framework for the interpolation of sparse vector fields in medical applications. The feasibility of the approach is illustrated by results on synthetic and clinical data.
BACKGROUND: Recent investigations using MRI suggest that older persons with mobility impairment have a greater volume of abnormal cerebral white matter compared with persons with normal mobility, thus raising the possibility that those with impairment have lesions in areas critical for the control of mobility. OBJECTIVE: To utilize automated image analysis methods to localize the specific regions of abnormal white matter that distinguish subjects with lower mobility from subjects with higher mobility. METHODS: Tissue classification was performed on subjects' dual-echo long repetition time spin-echo MRI using computer algorithms operating on intensity criteria integrated with anatomic information. Statistical analysis of group differences was obtained after spatially normalizing each brain to a standard reference brain. RESULTS: Four discrete periventricular regions, including bilaterally symmetric frontal and bilateral occipitoparietal regions, were identified as being sensitive (frontal) or specific (occipitoparietal) in discriminating the subjects with lower mobility from subjects with higher mobility. The symmetry of these lesions in individual subjects suggested pathology other than arteriolar infarction. CONCLUSIONS: These results suggest that damage to discrete frontal and occipitoparietal periventricular white matter locations may be associated with a mobility disorder of aging.
This paper presents processing and visualization techniques for Diffusion Tensor Magnetic Resonance Imaging (DT-MRI). In DT-MRI, each voxel is assigned a tensor that describes local water diffusion. The geometric nature of diffusion tensors enables us to quantitatively characterize the local structure in tissues such as bone, muscle, and white matter of the brain. This makes DT-MRI an interesting modality for image analysis. In this paper we present a novel analytical solution to the Stejskal-Tanner diffusion equation system whereby a dual tensor basis, derived from the diffusion sensitizing gradient configuration, eliminates the need to solve this equation for each voxel. We further describe decomposition of the diffusion tensor based on its symmetrical properties, which in turn describe the geometry of the diffusion ellipsoid. A simple anisotropy measure follows naturally from this analysis. We describe how the geometry or shape of the tensor can be visualized using a coloring scheme based on the derived shape measures. In addition, we demonstrate that human brain tensor data when filtered can effectively describe macrostructural diffusion, which is important in the assessment of fiber-tract organization. We also describe how white matter pathways can be monitored with the methods introduced in this paper. DT-MRI tractography is useful for demonstrating neural connectivity (in vivo) in healthy and diseased brain tissue.
PURPOSE: To assess the reproducibility and accuracy compared to radiologists of three automated segmentation pipelines for quantitative magnetic resonance imaging (MRI) measurement of brain white matter signal abnormalities (WMSA).
MATERIALS AND METHODS: WMSA segmentation was performed on pairs of whole brain scans from 20 patients with multiple sclerosis (MS) and 10 older subjects who were positioned and imaged twice within 30 minutes. Radiologist outlines of WMSA on 20 sections from 16 patients were compared with the corresponding results of each segmentation method.
RESULTS: The segmentation method combining expectation-maximization (EM) tissue segmentation, template-driven segmentation (TDS), and partial volume effect correction (PVEC) demonstrated the highest accuracy (the absolute value of the Z-score was 0.99 for both groups of subjects), as well as high interscan reproducibility (repeatability coefficient was 0.68 mL in MS patients and 1.49 mL in aging subjects).
CONCLUSION: The addition of TDS to the EM segmentation and PVEC algorithms significantly improved the accuracy of WMSA volume measurements, while also improving measurement reproducibility.
OBJECTIVE: The corpus callosum, the largest white matter tract in the brain, is a midline structure associated with the formation of the hippocampus, septum pellucidum, and cingulate cortex, which have been implicated in the pathogenesis of schizophrenia. Corpus callosum shape deformation, therefore, may reflect a midline neurodevelopmental abnormality.
METHOD: Corpus callosum area and shape were analyzed in 14 first-episode psychotic patients with schizophrenia, 19 first-episode psychotic patients with affective disorder, and 18 normal comparison subjects.
RESULTS: No statistically significant corpus callosum area differences between groups were found, but there were differences in the structure's shape between the patients with schizophrenia and the comparison subjects. A correlation between width and angle of the corpus callosum was found in patients with affective disorder.
CONCLUSIONS: Corpus callosum shape abnormalities in first-episode psychotic patients with schizophrenia may reflect a midline neurodevelopmental abnormality.
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.
Evidence suggests that some structural brain abnormalities in schizophrenia are neurodevelopmental in origin. There is also growing evidence to suggest that shape deformations in brain structure may reflect abnormalities in neurodevelopment. While many magnetic resonance (MR) imaging studies have investigated brain area and volume measures in schizophrenia, fewer have focused on shape deformations. In this MR study we used a 3D shape representation technique, based on spherical harmonic functions, to analyze left and right amygdala-hippocampus shapes in each of 15 patients with schizophrenia and 15 healthy controls matched for age, gender, handedness and parental socioeconomic status. Left/right asymmetry was also measured for both shape and volume differences. Additionally, shape and volume measurements were combined in a composite analysis. There were no differences between groups in overall volume or shape. Left/right amygdala-hippocampal asymmetry, however, was significantly larger in patients than controls for both relative volume and shape. The local brain regions responsible for the left/right asymmetry differences in patients with schizophrenia were in the tail of the hippocampus (including both the inferior aspect adjacent to parahippocampal gyrus and the superior aspect adjacent to the lateral geniculate nucleus and more anteriorly to the cerebral peduncles) and in portions of the amygdala body (including the anterior-superior aspect adjacent to the basal nucleus). Also, in patients, increased volumetric asymmetry tended to be correlated with increased left/right shape asymmetry. Furthermore, a combined analysis of volume and shape asymmetry resulted in improved differentiation between groups. Classification function analyses correctly classified 70% of cases using volume, 73.3% using shape, and 87% using combined volume and shape measures. These findings suggest that shape provides important new information toward characterizing the pathophysiology of schizophrenia, and that combining volume and shape measures provides improved group discrimination in studies investigating brain abnormalities in schizophrenia. An evaluation of shape deformations also suggests local abnormalities in the amygdala-hippocampal complex in schizophrenia.
Magnetic resonance diffusion tensor imaging (DTI) is a new technique that can be used to visualize and measure the diffusion of water in brain tissue; it is particularly useful for evaluating white matter abnormalities. In this paper, we review research studies that have applied DTI for the purpose of understanding neuropsychiatric disorders. We begin with a discussion of the principles involved in DTI, followed by a historical overview of magnetic resonance diffusion-weighted imaging and DTI and a brief description of several different methods of image acquisition and quantitative analysis. We then review the application of this technique to clinical populations. We include all studies published in English from January 1996 through March 2002 on this topic, located by searching PubMed and Medline on the key words "diffusion tensor imaging" and "MRI." Finally, we consider potential future uses of DTI, including fiber tracking and surgical planning and follow-up.
BACKGROUND: The fusiform gyrus (occipitotemporal gyrus) is thought to be critical for face recognition and may possibly be associated with impaired facial recognition and interpretation of facial expression in schizophrenia. of postmortem studies have suggested that fusiform gyrus volume is reduced in schizophrenia, but there have been no in vivo structural studies of the fusiform gyrus in schizophrenia using magnetic resonance imaging.
METHODS: High-spatial resolution magnetic resonance images were used to measure the gray matter volume of the fusiform gyrus in 22 patients with first-episode schizophrenia (first hospitalization), 20 with first-episode affective psychosis (mainly manic), and 24 control subjects.
RESULTS: Patients with first-episode schizophrenia had overall smaller relative volumes (absolute volume/intracranial contents) of fusiform gyrus gray matter compared with controls (9%) and patients with affective psychosis (7%). For the left fusiform gyrus, patients with schizophrenia showed an 11% reduction compared with controls and patients with affective psychosis. Right fusiform gyrus volume differed in patients with schizophrenia only compared with controls (8%).
CONCLUSION: Schizophrenia is associated with a bilateral reduction in fusiform gyrus gray matter volume that is evident at the time of first hospitalization and is different from the presentation of affective psychosis.
OBJECTIVE: "Cognitive" circuits anatomically link the frontal lobe to subcortical structures; therefore, pathology in any of the core components of these circuits, such as in the caudate nucleus, may result in neurobehavioral syndromes similar to those of the frontal lobe. Neuroleptic medication, however, affects the size of the caudate nucleus. For this reason, individuals diagnosed with schizotypal personality disorder offer an ideal group for the measurement of the caudate nucleus because they may be genetically related to individuals with schizophrenia but do not require neuroleptic treatment because of their less severe symptoms.
METHOD: Magnetic resonance imagining (MRI) scans obtained on a 1.5-T magnet with 1.5-mm contiguous slices were used to measure the caudate nucleus and lateral ventricles in 15 right-handed male subjects with schizotypal personality disorder who had no previous neuroleptic exposure and in 14 normal comparison subjects. Subjects were group matched for parental socioeconomic status, handedness, and gender.
RESULTS: First, the authors found significantly lower left and right absolute (13.1%, 13.2%) and relative (9.1%, 9.2%) caudate nucleus volumes in never-medicated subjects with schizotypal personality disorder than in normal subjects. Second, they found significant, inverse correlations between caudate nucleus volume and the severity of perseveration in two distinct working memory tasks in these neuroleptic-naive subjects with schizotypal personality disorder.
CONCLUSIONS: These data are consistent with the findings of reduced caudate nucleus volume reported in studies of neuroleptic-naive patients experiencing their first episode of schizophrenia and support the association of intrinsic pathology in the caudate nucleus with abnormalities in working memory in the schizophrenia spectrum.
RATIONALE AND OBJECTIVES: The authors performed this study to document the deformations that occur between pretreatment magnetic resonance (MR) imaging and intraoperative MR imaging during brachytherapy. MATERIALS AND METHODS: MR images obtained at 1.5 and 0.5 T in 10 patients with prostate cancer were analyzed for changes in the shape and substructure of the prostate. Three-dimensional models of the prostate were obtained. The authors measured anteroposterior dimension; total gland, peripheral zone, and central gland volumes; transverse dimension; and superoinferior height. RESULTS: Gland deformations were seen at visual inspection of the three-dimensional models. The anteroposterior dimension of the total gland, central gland, and peripheral zone increased from 1.5- to 0.5-T imaging (median dimension, 4.9, 1.5, and 1.8 mm, respectively), and the increase was greatest in the peripheral zone (P < .05, all comparisons). There was a decrease in the transverse dimension from 1.5- to 0.5-T imaging (median, 4.5 mm; P < .005). The total gland volume and the superoinferior height did not show a statistically significant change. CONCLUSION: There were significant deformations in the shape of the prostate, especially in the peripheral zone, between the two imaging studies. The likely causes of the shape change are differences in rectal filling (endorectal coil used in 1.5-T studies vs obturator in 0.5-T studies) and/or changes in patient position (supine vs lithotomy). These findings suggest that pretreatment images alone may not be reliable for accurate therapy planning. It may be useful to integrate pre-and intraoperative data.
The increased use of image-guided surgery systems during neurosurgery has brought to prominence the inaccuracies of conventional intraoperative navigation systems caused by shape changes such as those due to brain shift. We propose a method to track the deformation of the brain and update preoperative images using intraoperative MR images acquired at different crucial time points during surgery. We use a deformable surface matching algorithm to capture the deformation of boundaries of key structures (cortical surface, ventricles and tumor) throughout the neurosurgical procedure, and a linear finite element elastic model to infer a volumetric deformation. The boundary data are extracted from intraoperative MR images using a real-time intraoperative segmentation algorithm. The algorithm has been applied to a sequence of intraoperative MR images of the brain exhibiting brain shift and tumor resection. Our results characterize the brain shift after opening of the dura and at the different stages of tumor resection, and brain swelling afterwards. Analysis of the average deformation capture was assessed by comparing landmarks identified manually and the results indicate an accuracy of 0.7+/-0.6 mm (mean+/-S.D.) for boundary surface landmarks, of 0.9+/-0.6 mm for landmarks inside the boundary surfaces, and 1.6+/-0.9 mm for landmarks in the vicinity of the tumor.
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.