Diagnosis of cerebral cryptococcoma using a computerized analysis of H-1 NMR spectra in an animal model
Dzendrowskyj, TE Dolenko, B Sorrell, TC Somorjai, RL Malik, R Mountford, CE Himmelreich, Uwe # ×
Elsevier Science Pub. Co.
Diagnostic Microbiology and Infectious Disease vol:52 issue:2 pages:101-105
Viable cryptococci load in biopsy material from an animal model of cerebral cryptococcoma were con-elated with H-1 NMR spectra and metabolite profiles. A statistical classification strategy was applied to distinguish among high-resolution H-1 NMR spectra acquired from cryptococcomas, glioblastomas, and normal brain tissue. The overall classification accuracy was 100% when a genetic-algorithm-based optimal region selection preceded the development of linear discriminant analysis-based classifiers. The method remained robust despite differences in the microbial load of the cryptococcoma group when harvested at different time points. These results indicate the feasibility of the method for diagnosis without isolation of the pathogenic microorganism and its potential for in vivo diagnosis based on computerized analysis of magnetic resonance spectra. (c) 2005 Elsevier Inc. All rights reserved.