前列腺MRI深度学习模型通过PI-RADS指导的学习有效区分中危病例，在检测csPCa的AUC（0.73-0.88）显著优于放射科医生和临床模型 ...

前列腺癌PI-RADS 5级病灶中11.4%活检阴性，通过多因素分析发现前列腺体积＞60cc、正常DRE、既往阴性活检、过渡区病灶及TRUS未发现可疑低回声是独立预测因素，联合应用可提升诊断准确性至AUC≥0.84，为个体化随访策略提供依据。 多参数磁共振成像（mpMRI）在前列 ...

Men overestimate the risks for clinically significant prostate cancer based on prostate MRI PI-RADS findings, regardless of the context in which those risks are presented, suggesting that clinicians ...

PI-RADS version 2.1 demonstrated improved detection of clinically significant prostate cancer in the transition zone. For detecting clinically significant prostate cancer (csPCa), prostate imaging ...

Adding baseline MRI to conventional prostate cancer risk stratification could improve prognostic accuracy, potentially affecting active surveillance and treatment decisions for some patients, ...

Survival impact of initial local therapy selection for men under 60 with high risk prostate cancer. Prostate cancer (PCa) in 696 hypogonadal men with and without long-term testosterone therapy (TTh): ...