Purpose: Prostate cancer (PCa) is the second most common cancer in men. The urge to guide treatment tactics based on personal clinical risk factors has evolved in the era of human genome sequencing. To date, personalized approaches to managing PCa patients have not yet been developed. Radiogenomics is a relatively new term, used to refer to the study of genetic variation associated with imaging features of the tumour in order to improve the prognostication of the disease course.
Material and methods: The study is a review of recent knowledge regarding potential clinical applications of radiogenomics in personalized treatment of PCa.
Results: Recent investigations have proven that by combining data on individual genetic tumour features, and radiomic profiling (radiologic-molecular correlation), with traditional staging procedures in order to personalize treatment of PCa, an improved prognostication of PCa course can be performed, and overtreatment of indolent cancer can be avoided. It was found that a combination of multiparametric MRI and gene expression data allowed the detection of radiomic features of PCa, which correlated with a number of gene signatures associated with adverse outcomes.
It was revealed that several molecular markers may drive tumour upstaging, allowed the distinction between the PCa
stages, and correlated with aggressiveness-related radiomic features.
Conclusions: The radiogenomics of PCa is not a comprehensively investigated area of oncourology. The combination
of genomics and radiomics as integrative parts of precision medicine in the future has the potential to become the
foundation for a personalized approach to the management of PCa.

 To summarize, being an attractive research topic, the radiogenomics of PCa currently is not a comprehensively investigated area of oncourology. According to preliminary research findings conducted in this field, the combination of genomics and radiomics (and presumably metabolomics, proteomics, and transcriptomics) as integrative parts of precision medicine in the future has the potential to become the foundation for a personalized approach to the management of PCa. However, there are a number of hindrances to achieving this goal, such as relatively small numbers of patients included in current studies, a lack of available large randomized controlled trials, the need to use complex integrated methods of big data analysis, the comparatively high cost of genomic profiling and imaging methods, and the question of whether, before we include any potential genomic or transcriptomic marker into radiogenomic analysis, it should first be validated in order to prove its separate clinical value. If so, it greatly and significantly shifts the horizon of the actual use of radiogenomics in clinical practice, owing to the need for a huge body of future research.