Yue Lin, Enis C Yilmaz, Mason J Belue, Stephanie A Harmon, Jesse Tetreault, Tim E Phelps, Katie M Merriman, Lindsey Hazen, Charisse Garcia, Dong Yang, Ziyue Xu, Nathan S Lay, Antoun Toubaji, Maria J Merino, Daguang Xu, Yan Mee Law, Sandeep Gurram, Bradford J Wood, Peter L Choyke, Peter A Pinto, Baris Turkbey
Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models can assist in mpMRI interpretation, but large training data sets and extensive model testing are required. Purpose To evaluate a biparametric MRI AI algorithm for intraprostatic lesion detection and segmentation and to compare its performance with radiologist readings and biopsy results...
May 2024: Radiology