Biomedical subjects

Xiaohong Joe Zhou

Publications and source records attributed to Xiaohong Joe Zhou.

5 recordsLinked to original sources

PubMed2006

Error propagation model for microscopic magnetic resonance elastography shear-wave images.

Microscopic magnetic resonance elastography is a high-resolution method for visualizing shear waves and assessing the biomechanical viscoelastic properties of small biological samples. In this work, we used error propagation to develop a simple analytical model that relates the signal-to-noise ratio of MR magnitude images to the variance in shear-wave maps collected using gradient-echo and spin-echo phase-contrast pulse sequences. Our model predicts results for shear-wave images in phantoms, which match the experimentally observed phase variance within 8%. This model can be used to optimize MR pulse sequences for elastography studies, as well as other phase-difference techniques in MRI.

Biomechanical Phenomena↗

PubMed2004

Analytical error propagation in diffusion anisotropy calculations.

PURPOSE: To develop an analytical formalism describing how noise and selection of diffusion-weighting scheme propagate through the diffusion tensor imaging (DTI) computational chain into variances of the diffusion tensor elements, and errors in the relative anisotropy (RA) and fractional anisotropy (FA) indices. MATERIALS AND METHODS: Singular-value decomposition (SVD) was used to determine the tensor variances, with diffusion-weighting scheme and measurement noise incorporated into the design matrix. Anisotropy errors were then derived using propagation of error. To illustrate the applications of the model, 12 data sets were acquired from each human subject, over a range of b-values (500-2500 seconds/mm2) and diffusion-weighting gradient directions (N = 6-55). The mean RA and FA values and their respective errors were calculated within a region of interest (ROI) in the splenium. The RA and FA errors as a function of b-value and N were evaluated, and a number of diffusion-weighting schemes were assessed based on a new metric, sum of diffusion tensor variances. RESULTS: When the acquisition time was held constant, the sum of the diffusion tensor variances decreased as N increased. The same trend was also observed for several diffusion-weighting schemes with constant condition number when noise in the diffusion-weighted (DW) images was assumed unity. Errors in both FA and RA increased with b-value and decreased with N. The FA error in the splenium was approximately threefold smaller than RA error, irrespective of b-value or N. CONCLUSION: The condition number may not adequately characterize the noise sensitivity for a given diffusion-weighting scheme. Signal averaging may not be as effective as increasing N, especially when N is small (e.g., N < 13). Due to its smaller error, FA is preferred over RA for quantitative DTI applications.

Adult↗

PubMed2002

Correction of concomitant magnetic field-induced image artifacts in nonaxial echo-planar imaging.

Echo-planar images acquired in nonaxial planes are often distorted. Such image distortion has limited the applications of the echo-planar imaging (EPI) technique. In this article, it is demonstrated that a considerable amount of the distortion is caused by the higher-order magnetic field concomitant with the linear magnetic field gradient, or the concomitant magnetic field. The image distortion caused by the concomitant magnetic field is more prominent when a higher gradient amplitude is used for readout. It is also shown that the concomitant magnetic field can cause ghosting and blurring. A theoretical analysis is performed for the concomitant field effect in nonaxial EPI images. A point-by-point (or line-by-line) phase correction algorithm is developed to correct the image distortion, ghosting, and blurring. A postreconstruction processing algorithm is also developed to correct image distortion with much higher computational efficiency. Experimental results show that both correction methods effectively reduce the image distortion in coronal or sagittal images.

Artifacts↗

PubMed2002

Characterization of benign and metastatic vertebral compression fractures with quantitative diffusion MR imaging.

BACKGROUND AND PURPOSE: Conventional imaging techniques cannot be used to unambiguously and reliably differentiate malignant from benign vertebral compression fractures. Our hypothesis is that these malignant and benign vertebral lesions can be better distinguished on the basis of tissue apparent diffusion coefficients (ADCs). The purpose of this study was to test this hypothesis by using a quantitative diffusion imaging technique. METHODS: Twenty-seven patients with known cancer and suspected metastatic vertebral lesions underwent 1.5-T conventional T1-weighted, T2-weighted, and contrast-enhanced T1-weighted imaging to identify the lesions. Diffusion-weighted images of the areas of interest were acquired by using a fast spin-echo diffusion pulse sequence with b values of 0-250 s/mm(2). The abnormal regions on the diffusion-weighted images were outlined by using the conventional images as guides, and the ADC values were calculated. On the basis of pathologic results and clinical findings, the cases were divided into two categories: benign compression fractures and metastatic lesions. The ADC values for each category were combined and plotted as histograms; this procedure was followed by statistical analysis. RESULTS: The patient group had 12 benign fractures and 15 metastases. The mean ADC values, as obtained from the histograms, were (1.9 +/- 0.3) x 10(-4) mm(2)/s and (3.2 +/- 0.5) x 10(-4) mm(2)/s for metastases and benign fractures, respectively. CONCLUSION: Our results indicate that quantitative ADC mapping, instead of qualitative diffusion-weighted imaging, can provide valuable information in differentiating benign vertebral fractures from metastatic lesions.

Adult↗

PubMedDate not supplied

MRI of mouse models for gliomas shows similarities to humans and can be used to identify mice for preclinical trials.

Magnetic resonance imaging (MRI) has been utilized for screening and detecting brain tumors in mice based upon their imaging characteristics appearance and their pattern of enhancement. Imaging of these tumors reveals many similarities to those observed in humans with identical pathology. Specifically, high-grade murine gliomas have histologic characteristics of glioblastoma multiforme (GBM) with contrast enhancement after intravenous administration of gadolinium diethylenetriamine pentaacetic acid (Gd-DTPA), implying disruption of the blood-brain barrier in these tumors. In contrast, low-grade murine oligodendrogliomas do not reveal contrast enhancement, similar to human tumors. MRI can be used to identify mice with brain neoplasms as inclusion criteria in preclinical trials.

Animals↗