Showing papers by "Martha E. Shenton published in 2001"

Longitudinal MRI study of hippocampal volume in trauma survivors with PTSD.

Abstract: Objective: The authors prospectively explored whether a reduction in the volume of the hippocampus occurs in recent trauma survivors who develop posttraumatic stress disorder (PTSD). Method: Thirty-seven survivors of traumatic events were assessed within a week of the traumatic event and 6 months later. The assessment included magnetic resonance imaging of the brain (including 124 coronal slices of 1.5-mm thickness), psychometric testing, and structured clinical interviews. The Clinician-Administered PTSD Scale conferred PTSD diagnoses at 6 months. Results: Ten subjects (27%) had PTSD at 6 months. The subjects with PTSD did not differ from those without PTSD in hippocampal volume (right or left) at 1 week or 6 months. There was no reduction in hippocampal volume in the PTSD subjects between 1 week and 6 months. Conclusions: Smaller hippocampal volume is not a necessary risk factor for developing PTSD and does not occur within 6 months of expressing the disorder. This brain abnormality might occur in individuals with chronic or complicated PTSD.

Shape versus Size: Improved Understanding of the Morphology of Brain Structures

Abstract: Standard practice in quantitative structural neuroimaging is a segmentation into bram tissue, subcortical structures, fluid space and lesions followed by volume calculations of gross structures. On the other hand, it is evident that object characterization by size does only capture one of multiple aspects of a full structural characterization. Desirable parameters are local and global parameters like length, elongation, bending, width, complexity, bumpiness and many more. In neuroimaging research there is increasing evidence that shape analysis of brain structures provides new information which is not available by conventional volumetric measurements. This motivates development of novel morphometry analysis techniques answering clinical research questions which have been asked for a long time but which remained unanswered due to the lack of appropriate measurement tools. Challenges are the choice of biologically meaningful shape representations, robustness to noise and small perturbations, and the ability to capture the shape properties of populations that represent natural biological shape variation. This paper describes experiments with two different shape representation schemes, a fine-scale, global surface characterization using spherical harmonics, and a coarsely sampled medial representation (3D skeleton). Driving applications are the detection of group differences of amhygdala-hippocampal shapes in schizophrenia and the analysis of ventricular shape similarity in a mono/dizygotic twin study. The results clearly demonstrate that shape captures information on structural similarity or difference which is not accessible by volume analysis. Improved global and local structure characterization as proposed herein might help to explain pathological changes in neurodevelopment/neurodegeneration in terms of their biological meaning.

Prefrontal cortex, negative symptoms, and schizophrenia: an MRI study.

Abstract: The present study measured prefrontal cortical gray and white matter volume in chronic, male schizophrenic subjects who were characterized by a higher proportion of mixed or negative symptoms than previous patients that we have evaluated. Seventeen chronic male schizophrenic subjects and 17 male control subjects were matched on age and handedness. Regions of interest (ROI) were measured using high-resolution magnetic resonance (MR) acquisitions consisting of contiguous 1.5-mm slices of the entire brain. No significant differences were found between schizophrenic and control subjects in mean values for prefrontal gray matter volume in either hemisphere. However, right prefrontal white matter was significantly reduced in the schizophrenic group. In addition, right prefrontal gray matter volume was significantly correlated with right hippocampal volume in the schizophrenic, but not in the control group. Furthermore, an analysis in which the current data were combined with those from a previous study showed that schizophrenic subjects with high negative symptom scores had significantly smaller bilateral white matter volumes than those with low negative symptom scores. White matter was significantly reduced in the right hemisphere in this group of schizophrenic subjects. Prefrontal volumes were also associated with negative symptom severity and with volumes of medial–temporal lobe regions — two results that were also found previously in schizophrenic subjects with mostly positive symptoms. These results underscore the importance of temporal–prefrontal pathways in the symptomatology of schizophrenia, and they suggest an association between prefrontal abnormalities and negative symptoms.

Prefrontal Gray Matter Volume Reduction in First Episode Schizophrenia

Abstract: Functional measures have consistently shown prefrontal abnormalities in schizophrenia. However, structural magnetic resonance imaging (MRI) findings of prefrontal volume reduction have been less consistent. In this study, we evaluated prefrontal gray matter volume in first episode (first hospitalized) patients diagnosed with schizophrenia, compared with first episode patients diagnosed with affective psychosis and normal comparison subjects, to determine the presence in and specificity of prefrontal abnormalities to schizophrenia. Prefrontal gray and white matter volumes were measured from first episode patients with schizophrenia (n = 17), and from gender and parental socio-economic status-matched subjects with affective (mainly manic) psychosis (n = 17) and normal comparison subjects (n = 17), age-matched within a narrow age range (18--29 years). Total (left and right) prefrontal gray matter volume was significantly reduced in first episode schizophrenia compared with first episode affective psychosis and comparison subjects. Follow-up analyses indicated significant left prefrontal gray matter volume reduction and trend level reduction on the right. Schizophrenia patients showed 9.2% reduction on the left and 7.7% reduction on the right compared with comparison subjects. White matter volumes did not differ among groups. These data suggest that prefrontal cortical gray matter volume reduction is selectively present at first hospitalization in schizophrenia but not affective psychosis.

A functional magnetic resonance imaging study of auditory mismatch in schizophrenia.

Abstract: 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.

Deformation Analysis for Shape Based Classification

Abstract: Statistical analysis of anatomical shape differences between two different populations can be reduced to a classification problem, i.e., learning a classifier function for assigning new examples to one of the two groups while making as few mistakes as possible. In this framework, feature vectors representing the shape of the organ are extracted from the input images and are passed to the learning algorithm. The resulting classifier then has to be interpreted in terms of shape differences between the two groups back in the image domain. We propose and demonstrate a general approach for such interpretation using deformations of outline meshes to represent shape differences. Given a classifier function in the feature space, we derive a deformation that corresponds to the differences between the two classes while ignoring shape variability within each class. The algorithm essentially estimates the gradient of the classification function with respect to node displacements in the outline mesh and constructs the deformation of the mesh that corresponds to moving along the gradient vector. The advantages of the presented algorithm include its generality (we derive it for a wide class of non-linear classifiers) as well as its flexibility in the choice of shape features used for classification. It provides a link from the classifier in the feature space back to the natural representation of the original shapes as surface meshes. We demonstrate the algorithm on artificial examples, as well as a real data set of the hippocampus-amygdala complex in schizophrenia patients and normal controls.

A Novel Nonrigid Registration Algorithm and Applications

Abstract: In this paper we describe a new algorithm for nonrigid registration of brain images based on an elastically deformable model. The use of registration methods has become an important tool for computer-assisted diagnosis and surgery. Our goal was to improve analysis in various applications of neurology and neurosurgery by improving nonrigid registration.A local gray level similarity measure is used to make an initial sparse displacement field estimate. The field is initially estimated at locations determined by local features, and then a linear elastic model is used to infer the volumetric deformation across the image. The associated partial differential equation is solved by a finite element approach. A model of empirically observed variability of the brain was created from a dataset of 154 young adults. Both homogeneous and inhomogeneous elasticity models were compared. The algorithm has been applied to medical applications including intraoperative images of neurosurgery showing brain shift and a study of gait and balance disorder.

Phase-Based User-Steered Image Segmentation

Abstract: This paper presents a user-steered segmentation algorithm based on the livewire paradigm. Livewire is an image-feature driven method that finds the optimal path between user-selected image locations, thus reducing the need to manually define the complete boundary. We introduce an image feature based on local phase, which describes local edge symmetry independent of absolute gray value. Because phase is amplitude invariant, the measurements are robust with respect to smooth variations, such as bias field inhomogeneities present in all MR images. In order to enable validation of our segmentation method, we have created a system that continuously records user interaction and automatically generates a database containing the number of user interactions, such as mouse events, and time stamps from various editing modules. We have conducted validation trials of the system and obtained expert opinions regarding its functionality.

Surface Based Atlas Matching of the Brain Using Deformable Surfaces and Volumetric Finite Elements

Abstract: The automatic identification and localization of structures in magnetic resonance (MR) brain images are a major part of the processing work for the neuroradiologist in numerous clinical applications, such as functional mapping and surgical planning. To aid in this task, a considerable amount of research has been directed toward the development of 3D standardized atlases of the human brain (e.g. [5]). These provide an invariant reference system and the possibility of template matching, allowing anatomical and functional structures in new scans to be identified and analyzed.

Perioperative Use of Transcranial Magnetic Stimulation

Abstract: :A practical means of noninvasively stimulating the cortex was developed in the mid-1980s. Both electrical and magnetic stimulating pulses applied transcranially were shown to be capable of exciting motor cortex. Transcranial magnetic stimulation (TCMS), compared with transcranial electrical