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Abstract #4106

Final Gleason Score Prediction Using Discriminant Analysis and Support Vector Machine Based on Preoperative Multiparametric MR Imaging of Prostate Cancer at 3T

Fusun Citak Er 1 , Metin Vural 2 , Omer Acar 3 , Tarik Esen 4 , Aslihan Onay 2 , and Esin Ozturk-Isik 5

1 Genetics and Bioengineering, Yeditepe University, Istanbul, Turkey, 2 Department of Radiology, VKF American Hospital, Istanbul, Turkey, 3 Department of Urology, VKF American Hospital, Istanbul, Turkey, 4 School of Medicine, Koc University, Istanbul, Turkey, 5 Department of Biomedical Engineering, Yeditepe University, Istanbul, Turkey

This study aims to evaluate the performances of linear and quadratic discriminant analysis and linear and non-linear support vector machine (SVM) for estimation of final Gleason score preoperatively for prostate cancer. The digital rectal examination (DRE) findings, age, prostate specific antigen (PSA) level, index lesion size, biopsy Gleason score, ADC, Likert scales of T2, diffusion weighted, and dynamic contrast enhanced (DCE) MRI were used as predictors for estimating the final Gleason score based on the pathologic analysis after prostatectomy. The results of our study indicated that linear SVM and linear discriminant analysis performed well in predicting final Gleason score.

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