Clinical MRI Scanners (clinical + mri_scanners)

Distribution by Scientific Domains

Selected Abstracts

Computer-aided detection of brain tumor invasion using multiparametric MRI

Todd R. Jensen PhD
Abstract Purpose To determine the potential of using a computer-aided detection method to intelligently distinguish peritumoral edema alone from peritumor edema consisting of tumor using a combination of high-resolution morphological and physiological magnetic resonance imaging (MRI) techniques available on most clinical MRI scanners. Materials and Methods This retrospective study consisted of patients with two types of primary brain tumors: meningiomas (n = 7) and glioblastomas (n = 11). Meningiomas are typically benign and have a clear delineation of tumor and edema. Glioblastomas are known to invade outside the contrast-enhancing area. Four classifiers of differing designs were trained using morphological, diffusion-weighted, and perfusion-weighted features derived from MRI to discriminate tumor and edema, tested on edematous regions surrounding tumors, and assessed for their ability to detect nonenhancing tumor invasion. Results The four classifiers provided similar measures of accuracy when applied to the training and testing data. Each classifier was able to identify areas of nonenhancing tumor invasion supported with adjunct images or follow-up studies. Conclusion The combination of features derived from morphological and physiological imaging techniques contains the information necessary for computer-aided detection of tumor invasion and allows for the identification of tumor invasion not previously visualized on morphological, diffusion-weighted, and perfusion-weighted images and maps. Further validation of this approach requires obtaining spatially coregistered tissue samples in a study with a larger sample size. J. Magn. Reson. Imaging 2009;30:481,489. 2009 Wiley-Liss, Inc. [source]

Compressed sensing MRI with multichannel data using multicore processors

Ching-Hua Chang
Abstract Compressed sensing (CS) is a promising method to speed up MRI. Because most clinical MRI scanners are equipped with multichannel receive systems, integrating CS with multichannel systems may not only shorten the scan time but also provide improved image quality. However, significant computation time is required to perform CS reconstruction, whose complexity is scaled by the number of channels. In this article, we propose a reconstruction procedure that uses ubiquitously available multicore central processing unit to accelerate CS reconstruction from multiple channel data. The experimental results show that the reconstruction efficiency benefits significantly from parallelizing the CS reconstructions and pipelining multichannel data into multicore processors. In our experiments, an additional speedup factor of 1.6,2.0 was achieved using the proposed method on a quad-core central processing unit. The proposed method provides a straightforward way to accelerate CS reconstruction with multichannel data for parallel computation. Magn Reson Med, 2010. 2010 Wiley-Liss, Inc. [source]

Imaging single mammalian cells with a 1.5 T clinical MRI scanner

Paula Foster-Gareau
Abstract In the present work, we demonstrate that the steady-state free precession (SSFP) imaging pulse sequence FIESTA (fast imaging employing steady state acquisition) used in conjunction with a custom-built insertable gradient coil and customized RF coils can be used to detect individual SPIO-labeled cells using a commonly available 1.5 T clinical MRI scanner. This work provides the first evidence that single-cell tracking will be possible using clinical MRI scanners, opening up new possibilities for cell tracking and monitoring of cellular therapeutics in vivo in humans. Magn Reson Med 49:968,971, 2003. 2003 Wiley-Liss, Inc. [source]

In vivo measurement of brain metabolites using two-dimensional double-quantum MR spectroscopy,exploration of GABA levels in a ketogenic diet

Zhiyue J. Wang
Abstract A localized proton 2D double-quantum (DQ) spin-echo spectroscopy technique was implemented on 1.5 T clinical MRI scanners for the detection of ,-aminobutyrate (GABA) in the brain. The 2D approach facilitates separation of peaks overlapping with GABA in 1D DQ-filtered (DQF) spectra. This technique was applied to four normal adult volunteers and four children with intractable epilepsy. The coefficient of variation of the level of GABA and overlapping macromolecules at F2 = 3.0 ppm and F1 = 4.8 ppm was 0.08 in normal subjects. Three patients received 2D MRS scans before and after initiation of the ketogenic diet (KD): one patient showed a trend of decreasing GABA throughout the study, and two patients showed low initial GABA levels that increased over time. In addition to major metabolites and GABA, low-level metabolites (valine, leucine, and glutathione) were also identified in the 2D spectra. Magn Reson Med 49:615,619, 2003. 2003 Wiley-Liss, Inc. [source]