Computer aided diagnosis of prostate cancer in central gland using GOIA-sLASER 1H MRS
Neda Gholizadeh1, Peter B Greer1,2, John Simpson1,2, Peter Lau2,3, Arend Heerschap4, and Saadallah Ramadan1,3
1The University of Newcastle, Newcastle, Australia, 2Calvary Mater Newcastle, Newcastle, Australia, 3Hunter Medical Research Institute (HMRI), Newcastle, Australia, 4Radboud University Medical Center, Nijmegen, Nijmegen, Netherlands
The aim of the work described in this paper is twofold. First, evaluate the efficacy of the GOIA-sLASER magnetic resonance spectroscopic imaging (MRSI) using a 3T MRI scanner in detecting central gland prostate cancer with an external phased-array coil. Second, to develop risk predictor tools using a non-linear support vector machine (SVM) classification algorithm to analyse MRSI data. This research revealed a relatively high accuracy, sensitivity and specificity for pathological discrimination between normal vs cancer, low risk vs high risk cancer and low risk vs intermediate risk cancer using high quality prostate GOIA-sLASER MRSI.
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