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Prostate cancer (PCa) is predominantly an acinar adenocarcinoma arising from the prostatic glandular epithelium, with tumor grade assessed using the International Society of Urological Pathology (ISUP) Grade Group classification, reflecting the degree of glandular differentiation and underlying molecular heterogeneity. PCa exhibits wide clinical behavior heterogeneity, ranging from indolent disease to aggressive forms with poor outcomes. Accurate prognostic assessment is, therefore, essential for guiding treatment selection and monitoring disease progression. This review examines recent advances in imaging and non-imaging biomarkers that contribute to improved risk stratification, treatment planning, and disease monitoring. Particular attention is given to multiparametric magnetic resonance imaging (mpMRI), whole-body magnetic resonance imaging (WB-MRI), positron emission tomography/computed tomography (PET/CT), positron emission tomography/magnetic resonance imaging (PET/MRI), computed tomography (CT), and transrectal ultrasound (TRUS), evaluated for their capacity not only to detect disease but also to predict recurrence, progression, and survival outcomes. In parallel, the prognostic role of non-imaging biomarkers is discussed, including the prostate-specific antigen (PSA), histopathological grading, biochemical and inflammatory biomarkers, as well as genomic classifiers and circulating tumor DNA (ctDNA). Emerging approaches such as radiomics, liquid-biopsy-derived molecular profiles, and artificial intelligence (AI)-based multimodal integration are highlighted for their potential to enhance individualized decision making. This review underscores the importance of combining imaging and molecular information to refine prognostic models and accelerate the translation of precision medicine in PCa.
Khazaei et al. (Wed,) studied this question.