Purpose The goal of the study was an assessment of the diagnostic performance of diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) of magnetic resonance imaging (MRI) in distinguishing local recurrence (LR) of renal cell carcinoma (RCC) from benign conditions after partial nephrectomy. Material and methods Thirty-nine patients after partial nephrectomy for solid RCC were enrolled in the study. Patients were followed up using MRI, which included DWI sequence ( b = 800 s/mm 2 ). All patients with MRI features of LR were included in the main group ( n = 14) and patients without such features – into the group of comparison ( n = 25). Apparent diffusion coefficient (ADC) values of suspicious lesions were recorded. In all patients with signs of locally recurrent RCC, surgical treatment was performed followed by pathologic analysis. Results The mean ADC values of recurrent RCC demonstrated significantly higher numbers compared to benign fibrous tissues and were 1.64 ± 0.15 × 10 -3 mm 2 /s vs. 1.02 ± 0.26 × 10 -3 mm 2 /s ( p < 0.001). The mean ADC values of RCCs’ LR and benign post-op changes in renal scar substantially differed from mean ADC values of healthy kidneys’ parenchyma; the latter was 2.58 ± 0.05 × 10 -3 mm 2 /s ( p < 0.001). In ROC analysis, the use of ADC with a threshold value of 1.28 × 10 -3 mm 2 /s allowed us to differentiate local recurrence of RCC from benign postoperative changes with 100% sensitivity, 80% specificity, and accuracy: AUC = 0.980 ( p < 0.001). Conclusions The apparent diffusion coefficient of DWI of MRI can be used as a potential imaging marker for the diagnosis of local recurrence of RCC.

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.

Prostate cancer (PCa) is the most common malignancy in men. The role of the apparent diffusion coefficient (ADC) of biparametric MRI (biMRI) which is a study without the use of dynamic contrast enhancement (DCE), in detection of PCa is still not comprehensively investigated. Objective. The goal of the study was to assess the role of ADC of biMRI as an imaging marker of clinically significant PCa Materials and methods. The study involved 78 men suspected of having PCa. All patients underwent a comprehensive clinical examination, which included multiparametric MRI of the prostate, a component of which was biMRI. The MRI data was evaluated according to the PI-RADS system version 2.1. Results. The distribution of patients according to the PI-RADS system was as follows: 1 point – 9 (11.54 %) patients, 2 points – 12 (15.38 %) patients, 3 points – 25 (32.05 %) patients, 4 points – 19 (24.36 %) patients and 5 points – 13 (16.67 %) patients. In a subgroup of patients with 5 points, clinically significant PCa was detected in 100 % of cases. In the subgroup of patients with tumors of 4 points clinically significant PCa was diagnosed in 16 of 19 (84.21 %) cases, and in 3 (15.79 %) patients – clinically insignificant tumor. In the subgroup of patients with 3 points, clinically significant PCa was diagnosed in 11 of 25 (44.0 %) cases, in 8 (32.0 %) patients – clinically insignificant tumor and in 6 (24.0 %) patients – benign prostatic hyperplasia. PCa with a score of ≥ 7 on the Gleason scale showed significantly lower mean values of ADC of the diffusion-weighted MRI images compared to tumors with a score of < 7 on the Gleason scale: (0.86 ± 0.07) x 10-3 mm2/s vs (1.08 ± 0.04) x 10-3 mm2/s (р < 0.05). Conclusions. The obtained results testify to the high informativeness of biMRI in the diagnosis of prostate cancer. The use of ADC allowed to differentiate clinically significant and insignificant variants of the tumor, as well as benign changes in prostate tissues and can be considered as a potential imaging marker of PCa. Key words: prostate cancer, diagnosis, biparametric MRI, marker, apparent diffusion coefficient, PI-RADS.