Application and prospect of artificial intelligence in diagnostic imaging of prostate cancer

Prostate cancer is a major threat to the health of elderly men. According to GLOBOCAN 2022 data, there are over 1.4 million new prostate cancer (PCa) cases and approximately 370,000 deaths worldwide each year. The incidence rate is significantly higher in developed countries than in developing countries, and there is a trend of younger age 1 , 2 . Recent epidemiologic studies further clarify this age shift. Early-onset prostate cancer, commonly defined as diagnosis at ≤55 years of age, is now recognized as a distinct clinical entity and accounts for a meaningful proportion of prostate cancer cases in Western populations 1 , 2 . Global analyses of adolescents and young adults (15–40 years) also show a steady increase in prostate cancer incidence across all young age strata, with an average annual rise of approximately 2% since 1990 1 , 2 . Consistent with these observations, population-based cancer registry data from Jiangsu Province in China demonstrate that the age-standardized incidence has increased most rapidly among men aged 0–59 years, accompanied by a decrease in the age-standardized mean age at diagnosis and an increasing proportion of cases in younger age groups 1 , 2 . The clinical outcome of PCa is closely related to the timing of diagnosis 1 , 2 . The 5-year survival rate of patients with early localized PCa can reach 99%, while that of patients with metastatic PCa drops sharply to less than 30%. Therefore, achieving early and accurate detection and risk stratification of PCa is of great significance for formulating individualized treatment plans and reducing mortality 3 , 4 .