MR Spectroscopic Imaging (MRSI) enables non-invasive measurement of a number of tissue metabolite distributions and offers considerable potential as a diagnostic imaging technique. Widespread adoption of MRSI has been limited by complex requirements for data processing and analysis, which optimally require close integration of known spectral and spatial information, including MRI-derived tissue segmentation, morphological analysis, metabolite NMR characteristics, and detailed knowledge of normal tissue metabolite distributions. This Biomedical Research Partnership will address this limitation and increase the effectiveness of MRSI by developing an integrated set of data processing tools that emphasizes considerable automation and suitability for routine diagnostic imaging studies. This effort will combine multiple areas of expertise in MRSI and MRI data processing under 5 projects located at 4 institutions. Software tools will be developed for automated MRSI processing, tissue segmentation, brain region mapping, statistical analysis, and clinical presentation. The resultant technical developments will then be shared among several partners at collaborating medical research centers in the U.S.A., Europe, and Japan, where the package will be evaluated for diagnostic neuroimaging applications, with an emphasis on 1H MRSI of cancer, epilepsy and neurodegenerative disease. Results from metabolite imaging studies will be converted to standardized intensity units and transformed into normalized spatial coordinates, enabling the data to be pooled to form a database of MR-measured human metabolite values as a function of acquisition, spatial, and subject parameters. This information will then be used to enhance statistical analysis of individual MRSI studies. The developed methods will facilitate increased use of MRSI for diagnostic imaging, encourage the development of standardized MRSI acquisition, processing, and analysis methods, and map metabolite distributions in human brain.
| Maudsley, Andrew A; Govind, Varan; Saigal, Gaurav et al. (2017) Longitudinal MR Spectroscopy Shows Altered Metabolism in Traumatic Brain Injury. J Neuroimaging 27:562-569 |
| Maudsley, Andrew A; Goryawala, Mohammed Z; Sheriff, Sulaiman (2017) Effects of tissue susceptibility on brain temperature mapping. Neuroimage 146:1093-1101 |
| Lopez, Christopher J; Nagornaya, Natalya; Parra, Nestor A et al. (2017) Association of Radiomics and Metabolic Tumor Volumes in Radiation Treatment of Glioblastoma Multiforme. Int J Radiat Oncol Biol Phys 97:586-595 |
| Sabati, Mohammad; Sheriff, Sulaiman; Gu, Meng et al. (2015) Multivendor implementation and comparison of volumetric whole-brain echo-planar MR spectroscopic imaging. Magn Reson Med 74:1209-20 |
| Lecocq, Angèle; Le Fur, Yann; Maudsley, Andrew A et al. (2015) Whole-brain quantitative mapping of metabolites using short echo three-dimensional proton MRSI. J Magn Reson Imaging 42:280-9 |
| Ding, Xiao-Qi; Maudsley, Andrew A; Sabati, Mohammad et al. (2015) Reproducibility and reliability of short-TE whole-brain MR spectroscopic imaging of human brain at 3T. Magn Reson Med 73:921-8 |
| Maudsley, A A; Gupta, R K; Stoyanova, R et al. (2014) Mapping of glycine distributions in gliomas. AJNR Am J Neuroradiol 35:S31-6 |
| Parra, N Andres; Maudsley, Andrew A; Gupta, Rakesh K et al. (2014) Volumetric spectroscopic imaging of glioblastoma multiforme radiation treatment volumes. Int J Radiat Oncol Biol Phys 90:376-84 |
| Sabati, Mohammad; Zhan, Jiping; Govind, Varan et al. (2014) Impact of reduced k-space acquisition on pathologic detectability for volumetric MR spectroscopic imaging. J Magn Reson Imaging 39:224-34 |
| Levin, Bonnie E; Katzen, Heather L; Maudsley, Andrew et al. (2014) Whole-brain proton MR spectroscopic imaging in Parkinson's disease. J Neuroimaging 24:39-44 |
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