An automated technique for the quantitative assessment of 3D-MRSI data from patients with glioma.
Although proton magnetic resonance spectroscopic imaging (1H-MRSI) has been shown to be effective for localizing tumor in patients with gliomas, it is not a routinely used clinical tool. This is due, in part, to the lack of a standardized, objective method for analyzing spectra. We present an automated technique for a) selecting a population of voxels from each patient that have the spectral features of normal brain regions, and b) using the selected voxels as internal controls for quantifying the probability of abnormality at each voxel location. The technique was demonstrated on a phantom, 14 normal volunteers, and 30 patients with histologically proven tumor. In addition, we demonstrated the usefulness of the method for monitoring patients in serial studies from two glioma patients with progressive disease.
McKnight
T R
TR
Department of Radiology, University of California, San Francisco, California 94143, USA. mcknight@mrsc.ucsf.edu
Noworolski
S M
SM
Vigneron
D B
DB
Nelson
S J
SJ
D000328:Adult; D001224:Aspartic Acid / Q000031:analogs & derivatives / Q000378:metabolism; D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000473:pathology; D002794:Choline / Q000378:metabolism; D005260:Female; D005910:Glioma / Q000175:diagnosis* / Q000473:pathology; D006801:Humans; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D015233:Models, Statistical; D019047:Phantoms, Imaging
D001224:Aspartic Acid; C000179:N-acetylaspartate; D002794:Choline