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Abstract #1329

Radiomic biomarker extracted from PI-RADS 3 patients support more efficient and robust prostate cancer diagnosis: a multi-center study

Longfei Li1,2, Rui Yang3, Xin Chen4, Cheng Li2, Hairong Zheng2, Yusong Lin1, Zaiyi Liu4, and Shanshan Wang2
1the Collaborative Innovation Center for Internet Healthcare , School of Information Engineering, Zhengzhou University, Zhengzhou, China, 2Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 3Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China, 4Department of Radiology, Guangdong Provincial People’s Hospital, Guangzhou, China


Prostate Imaging Reporting and Data System (PI-RADS) based on multi-parametric MRI classifies patients into 5 categories (PI-RADS 1-5) for routine clinical diagnosis guidance. However, there is no consensus on whether PI-RADS 3 patients should go through biopsies. Mining features from these hard samples (HS) is meaningful for physicians to achieve accurate diagnoses. Currently, the mining of HS biomarkers is insufficient, and the effectiveness and robustness of HS biomarkers for prostate cancer diagnosis have not been explored. In this study, biomarkers from different data distributions are constructed. Results show that HS biomarkers can achieve better performances in different data distributions.

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