Radiomic biomarker extracted from PI-RADS 3 patients support more eìcient and robust prostate cancer diagnosis: a multi-center study
This addresses a clinical uncertainty in prostate cancer diagnosis for physicians, though it appears incremental as it builds on existing PI-RADS frameworks.
The study tackled the problem of uncertain biopsy decisions for PI-RADS 3 prostate cancer patients by constructing radiomic biomarkers from these hard samples, achieving better diagnostic performance across different data distributions.
Prostate Imaging Reporting and Data System (PI-RADS) based on multi-parametric MRI classiêes 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 insuìcient, and the eéectiveness and robustness of HS biomarkers for prostate cancer diagnosis have not been explored. In this study, biomarkers from diéerent data distributions are constructed. Results show that HS biomarkers can achieve better performances in diéerent data distributions.