Prostate Cancer Differentiation and Aggressiveness: Assessment With a Radiomic-Based Model vs. PI-RADS v2

Journal of Magnetic Resonance Imaging : JMRI
Tong ChenJunkang Shen

Abstract

Multiparametric MRI (mp-MRI) combined with machine-aided approaches have shown high accuracy and sensitivity in prostate cancer (PCa) diagnosis. However, radiomics-based analysis has not been thoroughly compared with Prostate Imaging and Reporting and Data System version 2 (PI-RADS v2) scores. To develop and validate a radiomics-based model for differentiating PCa and assessing its aggressiveness compared with PI-RADS v2 scores. Retrospective. In all, 182 patients with biopsy-proven PCa and 199 patients with a biopsy-proven absence of cancer were enrolled in our study. Conventional and diffusion-weighted MR images (b values = 0, 1000 sec/mm2 ) were acquired on a 3.0T MR scanner. A total of 396 features and 385 features were extracted from apparent diffusion coefficient (ADC) images and T2 WI, respectively. A predictive model was constructed for differentiating PCa from non-PCa and high-grade from low-grade PCa. The diagnostic performance of each radiomics-based model was compared with that of the PI-RADS v2 scores. A radiomics-based predictive model was constructed by logistic regression analysis. 70% of the patients were assigned to the training group, and the remaining were assigned to the validation group. The diagnostic eff...Continue Reading

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Citations

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Methods Mentioned

BETA
feature extraction
biopsy

Software Mentioned

Statistical Package for the Social Sciences ( SPSS
Artificial Intelligence Kit
SMOTE
RADS
PI

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