The uncinate fasciculus and extraversion in schizotypal personality disorder: a diffusion tensor imaging study.
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Axons↗
Biomedical subjects
Carl-Fredrik Westin
Publications and source records attributed to Carl-Fredrik Westin.
Geometrically constrained two-tensor model for crossing tracts in DWI.
MR diffusion tensor imaging (DTI) of the brain and spine provides a unique tool for both visualizing directionality and assessing intactness of white matter fiber tracts in vivo. At the spatial resolution of clinical MRI, much of primate white matter is composed of interdigitating fibers. Analyses based on an assumed single diffusion tensor per voxel yield important information about the average diffusion in the voxel but fail to reveal structure in the presence of crossing tracts. Until today, all clinical scans assume only one tensor, causing potential serious errors in tractography. Since high angular resolution imaging remains, so far, untenable for routine clinical use, a method is proposed whereby the single-tensor field is augmented with additional information gleaned from standard clinical DTI. The method effectively resolves two distinct tract directions within voxels, in which only two tracts are assumed to exist. The underlying constrained two-tensor model is fitted in two stages, utilizing the information present in the single-tensor fit. As a result, the necessary MRI time can be drastically reduced when compared with other approaches, enabling widespread clinical use. Upon evaluation in simulations and application to in vivo human brain DTI data, the method appears to be robust and practical and, if correctly applied, could elucidate tract directions at critical points of uncertainty.
Animals↗
A new strategy for respiration compensation, applied toward 3D free-breathing cardiac MRI.
In thorax and abdomen imaging, image quality may be affected by breathing motion. Cardiac MR images are typically obtained while the patient holds his or her breath, to avoid respiration-related artifacts. Although useful, breath-holding imposes constraints on scan duration, which in turn limits the achievable resolution and SNR. Longer scan times would be required to improve image quality, and effective strategies are needed to compensate for respiratory motion. A novel approach at respiratory compensation, targeted toward 3D free-breathing cardiac MRI, is presented here. The method aims at suppressing the negative effects of respiratory-induced cardiac motion while capturing the heart's beating motion. The method is designed so that the acquired data can be reconstructed in two different ways: First, a time series of images is reconstructed to quantify and correct for respiratory motion. Then, the corrected data are reconstructed a final time into a cardiac-phase series of images to capture the heart's beating motion. The method was implemented, and initial results are presented. A cardiac-phase series of 3D images, covering the entire heart, was obtained for two free-breathing volunteers. The present method may prove especially useful in situations where breath-holding is not an option, for example, for very sick, mentally impaired or infant patients.
Artifacts↗
Fornix integrity and hippocampal volume in male schizophrenic patients.
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 (D(m)), 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. D(m) was significantly increased, whereas hippocampal volume was bilaterally reduced in patients. Reduced hippocampal volume was correlated with increased mean D(m) 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.
Adult↗
A Bayesian approach for stochastic white matter tractography.
White matter fiber bundles in the human brain can be located by tracing the local water diffusion in diffusion weighted magnetic resonance imaging (MRI) images. In this paper, a novel Bayesian modeling approach for white matter tractography is presented. The uncertainty associated with estimated white matter fiber paths is investigated, and a method for calculating the probability of a connection between two areas in the brain is introduced. The main merits of the presented methodology are its simple implementation and its ability to handle noise in a theoretically justified way. Theory for estimating global connectivity is also presented, as well as a theorem that facilitates the estimation of the parameters in a constrained tensor model of the local water diffusion profile.
Algorithms↗
A review of diffusion tensor imaging studies in 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.
Anisotropy↗
Fronto-temporal disconnectivity in schizotypal personality disorder: a diffusion tensor imaging study.
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 (D(m)) 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 D(m) 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.
Adolescent↗
Resampling fMRI time series.
The problem of selecting a threshold for the statistical parameter maps in functional MRI (fMRI) is a delicate issue. The use of advanced test statistics and/or the complex dependence structure of fMRI noise may preclude parametric statistical methods for finding appropriate thresholds. Non-parametric statistical methodology has been presented as a feasible alternative. In this paper, we discuss resampling methods for finding thresholds in single subject fMRI analysis. It is shown that the presence of a BOLD response in the time series biases the estimation of the temporal autocorrelation, which in turn leads to biased thresholds. Therefore, proposed resampling methods based on Fourier and wavelet transforms, which employ implicit and weak models of the temporal noise characteristic, may produce erroneous thresholds. In contrast, resampling based on a pre-whitening transform, which is driven by an explicit noise model, is robust to the presence of a BOLD response. The size of the bias is, however, largely dependent on the complexity of the experimental design. While blocked designs can induce large biases, event-related designs generate significantly smaller biases. Results supporting these claims are provided.
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Group-Slicer: a collaborative extension of 3D-Slicer.
In this paper, we describe a first step towards a collaborative extension of the well-known 3D-Slicer; this platform is nowadays used as a standalone tool for both surgical planning and medical intervention. We show how this tool can be easily modified to make it collaborative so that it may constitute an integrated environment for expertise exchange as well as a useful tool for academic purposes.
Electroencephalography↗
Uncertainty in white matter fiber tractography.
In this work we address the uncertainty associated with fiber paths obtained in white matter fiber tractography. This uncertainty, which arises for example from noise and partial volume effects, is quantified using a Bayesian modeling framework. The theory for estimating the probability of a connection between two areas in the brain is presented, and a new model of the local water diffusion profile is introduced. We also provide a theorem that facilitates the estimation of the parameters in this diffusion model, making the presented method simple to implement.
Algorithms↗
A Hamilton-Jacobi-Bellman approach to high angular resolution diffusion tractography.
This paper describes a new framework for white matter tractography in high angular resolution diffusion data. A direction-dependent local cost is defined based on the diffusion data for every direction on the unit sphere. Minimum cost curves are determined by solving the Hamilton-Jacobi-Bellman using an efficient algorithm. Classical costs based on the diffusion tensor field can be seen as a special case. While the minimum cost (or equivalently the travel time of a particle moving along the curve) and the anisotropic front propagation frameworks are related, front speed is related to particle speed through a Legendre transformation which can severely impact anisotropy information for front propagation techniques. Implementation details and results on high angular diffusion data show that this method can successfully take advantage of the increased angular resolution in high b-value diffusion weighted data despite lower signal to noise ratio.
Algorithms↗
A segmentation and reconstruction technique for 3D vascular structures.
In the context of stroke therapy simulation, a method for the segmentation and reconstruction of human vasculature is presented and evaluated. Based on CTA scans, semi-automatic tools have been developed to reduce dataset noise, to segment using active contours, to extract the skeleton, to estimate the vessel radii and to reconstruct the associated surface. The robustness and accuracy of our technique are evaluated on a vascular phantom scanned in different orientations. The reconstructed surface is compared to a surface generated by marching cubes followed by decimation and smoothing. Experiments show that the proposed technique reaches a good balance in terms of smoothness, number of triangles, and distance error. The reconstructed surface is suitable for real-time simulation, interactive navigation and visualization.
Algorithms↗
Rigid overlay of volume sonography and MR image data of the female pelvic floor using a fiducial based alignment--feasibility due to a case series.
The visual combination of different medical image acquisition techniques (modalities) can lead to new modalities with enhanced informative content. In this paper, we present an overlay technique of magnetic resonance (MR) and 3D US image data sets of the female anal canal (internal and external sphincter) as a base for a new diagnostic modality. It is a new field of the application of the overlay technique. Three corresponding MR and US volume data sets from the female pelvic floor region were filtered using adaptive filtering techniques and overlayed (=registered rigidly) with a landmark based alignment method.
Feasibility Studies↗
In vivo visualization of white matter fiber tracts of preterm- and term-infant brains with diffusion tensor magnetic resonance imaging.
OBJECTIVE: The goal of this study was to test the feasibility of visualizing a 3-dimensional structure of cerebral white matter fiber tracts in preterm infants, postconceptional age (PCA) 28 weeks to term, by using volumetric diffusion tensor magnetic resonance imaging (DTI) data. MATERIALS AND METHOD: We combined tractography algorithms and visualization methods, currently available for adult DTI data, to trace the pixelated principal direction of a diffusion tensor originating from regions-of-interest with high fractional anisotropy. Consequently, white matter fiber bundles from the genu and the splenium of corpus callosum, the corticospinal tracts, the inferior fronto-occipital fasciculi, and optic radiations were visualized. RESULTS: Our results suggest that major white matter tracts of preterm infant brains, with PCAs ranging from 28 weeks to term (40 weeks old), can be successfully visualized despite the small brain volume and low anisotropy. CONCLUSION: The feasibility of fiber tractography in preterm neonates with DTI may add a new dimension in detection and characterization of white matter injuries of preterm infants.
Algorithms↗
Identification of translational displacements between N-dimensional data sets using the high-order SVD and phase correlation.
This paper presents an extension of the phase correlation image alignment method to N-dimensional data sets. By the Fourier shift theorem, the motion model for translational shifts between N-dimensional images can be represented as a rank-one tensor. Through use of a high-order singular value decomposition, the phase correlation between two N-dimensional data sets can be decomposed to independently identify translational displacements along each dimension with subpixel resolution. Using three-dimensional MRI data sets, we demonstrate the effectiveness of this approach relative to other N-dimensional image registration methods.
Algorithms↗
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.
Biomarkers↗
White matter tract clustering and correspondence in populations.
We present a novel method for finding white matter fiber correspondences and clusters across a population of brains. Our input is a collection of paths from tractography in every brain. Using spectral methods we embed each path as a vector in a high dimensional space. We create the embedding space so that it is common across all brains, consequently similar paths in all brains will map to points near each other in the space. By performing clustering in this space we are able to find matching fiber tract clusters in all brains. In addition, we automatically obtain correspondence of tractographic paths across brains: by selecting one or several paths of interest in one brain, the most similar paths in all brains are obtained as the nearest points in the high-dimensional space.
Algorithms↗
Capturing intraoperative deformations: research experience at Brigham and Women's Hospital.
During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures and tumor margin has lead, over the past decade, to the development of sophisticated intraoperative imaging techniques to enhance visualization. However, both rigid motion due to patient placement and nonrigid deformations occurring as a consequence of the surgical intervention disrupt the correspondence between preoperative data used to plan surgery and the intraoperative configuration of the patient's brain. Similar challenges are faced in other interventional therapies, such as in cryoablation of the liver, or biopsy of the prostate. We have developed algorithms to model the motion of key anatomical structures and system implementations that enable us to estimate the deformation of the critical anatomy from sequences of volumetric images and to prepare updated fused visualizations of preoperative and intraoperative images at a rate compatible with surgical decision making. This paper reviews the experience at Brigham and Women's Hospital through the process of developing and applying novel algorithms for capturing intraoperative deformations in support of image guided therapy.
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