Modern Approaches to Prostate Cancer Diagnosis: From PSA to AI-Assisted Imaging
DOI:
https://doi.org/10.12775/JEHS.2026.91.70678Keywords
Prostate cancer, Diagnosis, Multiparametric MRI, PSMA PET, Prostate-specific antigen, Fusion biopsy, Molecular biomarkers, PCA3, 4Kscore, Prostate Health Index, Artificial intelligence, Radiomics, Machine learning, Pathomics, Active surveillanceAbstract
Background. Prostate cancer is one of the most common malignancies in men, and its early diagnosis remains challenging due to the lack of specific symptoms in the initial stages. Aim. This review aimed to present current methods used in prostate cancer diagnosis, with emphasis on modern imaging, biomarkers, and artificial intelligence.Materials and methods. A focused narrative review of the relevant literature was conducted, including studies on PSA testing, prostate biopsy, multiparametric MRI, MRI/TRUS fusion biopsy, PSMA PET, molecular biomarkers, and AI-based diagnostic tools.
Summary. Traditional methods remain important but have limited specificity. Modern imaging techniques improve lesion detection and biopsy targeting, while biomarkers such as PCA3, PHI, and 4Kscore support risk stratification. AI shows growing potential in imaging and histopathological analysis.
Conclusions. An integrated diagnostic approach may improve the detection of clinically significant prostate cancer while reducing unnecessary biopsies, overdiagnosis, and overtreatment.
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