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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