Biomedical subjects

C F Westin

Publications and source records attributed to C F Westin.

9 recordsLinked to original sources

PubMed2006

A method for clustering white matter fiber tracts.

BACKGROUND/PURPOSE: Despite its potential for visualizing white matter fiber tracts in vivo, diffusion tensor tractography has found only limited applications in clinical research in which specific anatomic connections between distant regions need to be evaluated. We introduce a robust method for fiber clustering that guides the separation of anatomically distinct fiber tracts and enables further estimation of anatomic connectivity between distant brain regions. METHODS: Line scanning diffusion tensor images (LSDTI) were acquired on a 1.5T magnet. Regions of interest for several anatomically distinct fiber tracts were manually drawn; then, white matter tractography was performed by using the Runge-Kutta method to interpolate paths (fiber traces) following the major directions of diffusion, in which traces were seeded only within the defined regions of interest. Next, a fully automatic procedure was applied to fiber traces, grouping them according to a pairwise similarity function that takes into account the shapes of the fibers and their spatial locations. RESULTS: We demonstrated the ability of the clustering algorithm to separate several fiber tracts which are otherwise difficult to define (left and right fornix, uncinate fasciculus and inferior occipitofrontal fasciculus, and corpus callosum fibers). CONCLUSION: This method successfully delineates fiber tracts that can be further analyzed for clinical research purposes. Hypotheses regarding specific fiber connections and their abnormalities in various neuropsychiatric disorders can now be tested.

Adolescent↗

PubMed2005

DTI and MTR abnormalities in schizophrenia: analysis of white matter integrity.

Diffusion tensor imaging (DTI) studies in schizophrenia demonstrate lower anisotropic diffusion within white matter due either to loss of coherence of white matter fiber tracts, to changes in the number and/or density of interconnecting fiber tracts, or to changes in myelination, although methodology as well as localization of such changes differ between studies. The aim of this study is to localize and to specify further DTI abnormalities in schizophrenia by combining DTI with magnetization transfer imaging (MTI), a technique sensitive to myelin and axonal alterations in order to increase specificity of DTI findings. 21 chronic schizophrenics and 26 controls were scanned using Line-Scan-Diffusion-Imaging and T1-weighted techniques with and without a saturation pulse (MT). Diffusion information was used to normalize co-registered maps of fractional anisotropy (FA) and magnetization transfer ratio (MTR) to a study-specific template, using the multi-channel daemon algorithm, designed specifically to deal with multidirectional tensor information. Diffusion anisotropy was decreased in schizophrenia in the following brain regions: the fornix, the corpus callosum, bilaterally in the cingulum bundle, bilaterally in the superior occipito-frontal fasciculus, bilaterally in the internal capsule, in the right inferior occipito-frontal fasciculus and the left arcuate fasciculus. MTR maps demonstrated changes in the corpus callosum, fornix, right internal capsule, and the superior occipito-frontal fasciculus bilaterally; however, no changes were noted in the anterior cingulum bundle, the left internal capsule, the arcuate fasciculus, or inferior occipito-frontal fasciculus. In addition, the right posterior cingulum bundle showed MTR but not FA changes in schizophrenia. These findings suggest that, while some of the diffusion abnormalities in schizophrenia are likely due to abnormal coherence, or organization of the fiber tracts, some of these abnormalities may, in fact, be attributed to or coincide with myelin/axonal disruption.

Adolescent↗

PubMed2001

Three-dimensional adaptive filtering in magnetic resonance angiography.

In order to enhance 3D image data from magnetic resonance angiography (MRA), a novel method based on the theory of multidimensional adaptive filtering has been developed. The purpose of the technique is to suppress image noise while enhancing important structures. The method is based on local structure estimation using six 3D orientation selective filters, followed by an adaptive filtering step controlled by the local structure information. The complete filtering procedure requires approximately 3 minutes of computational time on a standard workstation for a 256 x 256 x 64 data set. The method has been evaluated using a mathematical vessel model and in vivo MRA data (both phase contrast and time of flight (TOF)). 3D adaptive filtering results in a better delineation of small blood vessels and efficiently reduces the high-frequency noise. Depending on the data acquisition and the original data type, contrast-to-noise ratio (CNR) improvements of up to 179% (8.9 dB) were observed. 3D adaptive filtering may provide an alternative to prolonging the scan time or using contrast agents in MRA when the CNR is low.

Algorithms↗

PubMed2001

CURVES: curve evolution for vessel segmentation.

The vasculature is of utmost importance in neurosurgery. Direct visualization of images acquired with current imaging modalities, however, cannot provide a spatial representation of small vessels. These vessels, and their branches which show considerable variations, are most important in planning and performing neurosurgical procedures. In planning they provide information on where the lesion draws its blood supply and where it drains. During surgery the vessels serve as landmarks and guidelines to the lesion. The more minute the information is, the more precise the navigation and localization of computer guided procedures. Beyond neurosurgery and neurological study, vascular information is also crucial in cardiovascular surgery, diagnosis, and research. This paper addresses the problem of automatic segmentation of complicated curvilinear structures in three-dimensional imagery, with the primary application of segmenting vasculature in magnetic resonance angiography (MRA) images. The method presented is based on recent curve and surface evolution work in the computer vision community which models the object boundary as a manifold that evolves iteratively to minimize an energy criterion. This energy criterion is based both on intensity values in the image and on local smoothness properties of the object boundary, which is the vessel wall in this application. In particular, the method handles curves evolving in 3D, in contrast with previous work that has dealt with curves in 2D and surfaces in 3D. Results are presented on cerebral and aortic MRA data as well as lung computed tomography (CT) data.

Algorithms↗

PubMed2001

Serial intraoperative magnetic resonance imaging of brain shift.

OBJECTIVE: A major shortcoming of image-guided navigational systems is the use of preoperatively acquired image data, which does not account for intraoperative changes in brain morphology. The occurrence of these surgically induced volumetric deformations ("brain shift") has been well established. Maximal measurements for surface and midline shifts have been reported. There has been no detailed analysis, however, of the changes that occur during surgery. The use of intraoperative magnetic resonance imaging provides a unique opportunity to obtain serial image data and characterize the time course of brain deformations during surgery. METHODS: The vertically open intraoperative magnetic resonance imaging system (SignaSP, 0.5 T; GE Medical Systems, Milwaukee, WI) permits access to the surgical field and allows multiple intraoperative image updates without the need to move the patient. We developed volumetric display software (the 3D Slicer) that allows quantitative analysis of the degree and direction of brain shift. For 25 patients, four or more intraoperative volumetric image acquisitions were extensively evaluated. RESULTS: Serial acquisitions allow comprehensive sequential descriptions of the direction and magnitude of intraoperative deformations. Brain shift occurs at various surgical stages and in different regions. Surface shift occurs throughout surgery and is mainly attributable to gravity. Subsurface shift occurs during resection and involves collapse of the resection cavity and intraparenchymal changes that are difficult to model. CONCLUSION: Brain shift is a continuous dynamic process that evolves differently in distinct brain regions. Therefore, only serial imaging or continuous data acquisition can provide consistently accurate image guidance. Furthermore, only serial intraoperative magnetic resonance imaging provides an accurate basis for the computational analysis of brain deformations, which might lead to an understanding and eventual simulation of brain shift for intraoperative guidance.

Adult↗

PubMed2000

Sensitivity profiles from an array of coils for encoding and reconstruction in parallel (SPACE RIP).

A new parallel imaging technique was implemented which can result in reduced image acquisition times in MRI. MR data is acquired in parallel using an array of receiver coils and then reconstructed simultaneously with multiple processors. The method requires the initial estimation of the 2D sensitivity profile of each coil used in the receiver array. These sensitivity profiles are then used to partially encode the images of interest. A fraction of the total number of k-space lines is consequently acquired and used in a parallel reconstruction scheme, allowing for a substantial reduction in scanning and display times. This technique is in the family of parallel acquisition schemes such as simultaneous acquisition of spatial harmonics (SMASH) and sensitivity encoding (SENSE). It extends the use of the SMASH method to allow the placement of the receiver coil array around the object of interest, enabling imaging of any plane within the volume of interest. In addition, this technique permits the arbitrary choice of the set of k-space lines used in the reconstruction and lends itself to parallel reconstruction, hence allowing for real-time rendering. Simulated results with a 16-fold increase in temporal resolution are shown, as are experimental results with a 4-fold increase in temporal resolution. Magn Reson Med 44:301-308, 2000.

Brain↗

PubMed2000

Affine adaptive filtering of CT data.

A novel method for resampling and enhancing image data using multidimensional adaptive filters is presented. The underlying issue that this paper addresses is segmentation of image structures that are close in size to the voxel geometry. Adaptive filtering is used to reduce both the effects of partial volume averaging by resampling the data to a lattice with higher sample density and to reduce the image noise level. Resampling is achieved by constructing filter sets that have subpixel offsets relative to the original sampling lattice. The filters are also frequency corrected for ansisotropic voxel dimensions. The shift and the voxel dimensions are described by an affine transform and provides a model for tuning the filter frequency functions. The method has been evaluated on CT data where the voxels are in general non cubic. The in-plane resolution in CT image volumes is often higher by a factor of 3-10 than the through-plane resolution. The method clearly shows an improvement over conventional resampling techniques such as cubic spline interpolation and sinc interpolation.

Humans↗

PubMed1999

Multi-component apparent diffusion coefficients in human brain.

The signal decay with increasing b-factor at fixed echo time from brain tissue in vivo has been measured using a line scan Stejskal-Tanner spin echo diffusion approach in eight healthy adult volunteers. The use of a 175 ms echo time and maximum gradient strengths of 10 mT/m allowed 64 b-factors to be sampled, ranging from 5 to 6000 s/ mm2, a maximum some three times larger than that typically used for diffusion imaging. The signal decay with b-factor over this extended range showed a decidedly non-exponential behavior well-suited to biexponential modeling. Statistical analyses of the fitted biexponential parameters from over 125 brain voxels (15 x 15 x 1 mm3 volume) per volunteer yielded a mean volume fraction of 0.74 which decayed with a typical apparent diffusion coefficient around 1.4 microm2/ms. The remaining fraction had an apparent diffusion coefficient of approximately 0.25 microm2/ms. Simple models which might explain the non-exponential behavior, such as intra- and extracellular water compartmentation with slow exchange, appear inadequate for a complete description. For typical diffusion imaging with b-factors below 2000 s/mm2, the standard model of monoexponential signal decay with b-factor, apparent diffusion coefficient values around 0.7 microm2/ms, and a sensitivity to diffusion gradient direction may appear appropriate. Over a more extended but readily accessible b-factor range, however, the complexity of brain signal decay with b-factor increases, offering a greater parametrization of the water diffusion process for tissue characterization.

Adult↗

PubMed1998

Magnetic resonance imaging shows orientation and asymmetry of white matter fiber tracts.

Apparent diffusion tensor maps of the human brain were acquired with a magnetic resonance imaging sequence (Gudbjartsson, H., Maier, S.E., Mulkern, R.V., M6rocz, I.A., Patz, S., Jolesz, F.A., Magn. Reson. Med. 36 (1996) 509-519). It was shown that the geometric nature of the apparent diffusion tensors can quantitatively characterize the tissue structure. Display of the orientation and directional uniformity of the water diffusion in the brain demonstrated most of the known major anatomical constituents of human white matter. A comparison of corresponding anatomic regions in the white matter of both hemispheres in 24 healthy volunteers revealed that fiber tracts within the anterior limb of the internal capsule have a significantly higher (P < 0.01) measure of alignment in the right hemisphere. This method offers a unique tool for the in vivo demonstration of neural connectivity in healthy and diseased brain.

Anisotropy↗