Biomedical subjects

R M Peshock

Publications and source records attributed to R M Peshock.

94 records · Page 6Linked to original sources

PubMedDate not supplied

Three-dimensional reconstruction of skeletal muscle from MRI.

Three-dimensional (3D) reconstructions of medical images can provide useful information to the radiologist, enabling delineation and spatial correlation of anatomic structures in one image rather than consecutive two-dimensional (2D) images. Magnetic resonance imaging (MRI) is known to be a powerful technique for evaluation of skeletal muscle pathology and physiology. We investigated the role of 3D reconstruction from MRI images of pathological and healthy muscle, using volume rendering. The ability to easily delineate and recognize normal and injured muscle in the 3D images were dependent upon the original contrast between normal and injured muscle, spatial resolution, and anatomic complexity in the original slices, and also on imaging parameters such as volume averaging.

Algorithms↗

PubMedDate not supplied

A method for fully automated quantitative analysis of arterial flow using flow-sensitized MR images.

While the recent developments in the velocity-sensitive MR imaging offer great potential for non-invasive assessment of blood flow in major blood vessels, the clinical applications of this technique have been hampered by tedious, human-assisted data processing techniques. In this paper, we describe a robust system for automated extraction of quantitative as well as qualitative flow information from velocity-sensitive, phase contrast MR images. The algorithm accomplishes reliable segmentation of blood vessels using multiresolution analysis based on wavelet transform, and employs a multivariate scoring criterion to minimize the impact of imaging artifacts such as partial volume averaging and flow turbulence, which normally cause incomplete or inaccurate detection of vascular boundaries.

Algorithms↗

PubMedDate not supplied

Muscle recruitment variations during wrist flexion exercise: MR evaluation.

OBJECTIVE: Many exercise protocols used in physiological studies assume homogeneous and diffuse muscle recruitment. To test this assumption during a "standard" wrist flexion protocol, variations in muscle recruitment were assessed using MRI in eight healthy subjects. MATERIALS AND METHODS: Variations were assessed by comparing the right to the left forearms and the effect of slight (15 degrees) pronation or supination at the wrist. RESULTS: Postexercise imaging showed focal regions of increased signal intensity (SI), indicating relatively strong recruitment, most often in entire muscles, although occasionally only in subvolumes of muscles. In 15 of 26 studies, flexor carpi radialis (FCR) showed more SI than flexor carpi ulnaris, while in 11 studies SI in these muscles increased equivalently. Relatively greater FCR recruitment was seen during pronation and/or use of the nondominant side. Palmaris longus, a wrist flexor, did not appear recruited in 4 of 11 forearms in which it was present. A portion of the superficial finger flexor became hyperintense in 89% of studies, while recruitment of the deep finger flexor was seen only in 43%. CONCLUSION: Inter- and intraindividual variations in forearm muscle recruitment should be anticipated in physiological studies of standard wrist flexion exercise protocols.

Female↗

PubMedDate not supplied

A MRI gradient waveform model for automated sequence calibration.

In order to set up magnetic resonance imaging (MRI) procedures of arbitrary voxel dimensions, slice orientation, and sequence timing in a reasonable time, some form of automatic gradient pulse calibration is required. One such method, involving simulation of gradient waveforms, is presented. Waveforms are modeled based on measurements of the step response. The model used divides each transition into three time regions: a "start" region in the first 0.3 ms, a "slew" region, and a "tail" region representing decay of the eddy current compensation error. In the "slew" region, the time derivative of the gradient, G' (t), is expressed as a function of G(t). The first two regions are nonlinear with respect to demand. The mean error in the simulated gradient is generally less than 0.04 mT m-1 in spin echo sequences. Image signal/noise ratios resulting from sequences calibrated using the model are within 5% of those of empirically calibrated sequences.

Calibration↗