Athina C. Tsili

Background and Objectives: Clear cell renal cell carcinoma (ccRCC) demonstrates substantial molecular and clinical heterogeneity, limiting the prognostic accuracy of conventional staging system and complicating treatment selection. CT-based radiomics and radiogenomics have emerged as promising non-invasive approaches for predicting molecular biomarkers. This review aimed to evaluate the current evidence regarding CT-based radiogenomics for the prediction of molecular markers in ccRCC, with emphasis on methodological approaches, predictive performance, and clinical applicability. Materials and Methods: A comprehensive literature search of PubMed/MEDLINE, Scopus, and Cochrane Library databases was performed for original studies published between January 2012 and December 2025. Eligible studies included patients with histopathologically confirmed ccRCC, performed CT-based radiomics feature extraction, and investigated molecular or genetic biomarkers using machine learning (ML) methods. Data regarding CT acquisition phase, segmentation strategy, radiomics features, ML algorithms, investigated biomarkers, and model performance metrics were extracted. Results and Discussion: Twenty-five retrospective studies were included. CT-based radiomics demonstrated promising performance in predicting gene mutations, including Von Hippel–Lindau (VHL), Polybromo 1 (PBRM1), BRCA1-associated protein 1 (BAP1), SET domain containing 2 (SETD2), and Lysine demethylase 5C (KDM5C), with reported area under the curve (AUC) values reaching 0.987. Radiogenomic models also showed utility in assessing hypoxia-related pathways, lipid metabolism signatures, programmed cell death profiles, immune-related markers, and tumor microenvironment characteristics, including programmed death-ligand 1 (PD-L1), Cluster of Differentiation 68 (CD68+) tumor-associated macrophages (TAMs), Cytotoxic T-Lymphocyte–Associated Protein 4 (CTLA-4), Forkhead Box P3 (FOXP3), and Ki-67 proliferation index. Predictive performance varied across biomarkers, with AUCs generally ranging from 0.68 to 0.91. Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), Adaptive Boosting (AdaBoost), and Gradient Boosting algorithms were most commonly applied. Conclusions: CT-based radiogenomics represents a promising non-invasive tool for molecular characterization and risk stratification in ccRCC. Standardized multicenter prospective studies, methodological homogeneity, and external validation are required before routine clinical implementation.

Background: Renal cell carcinoma (RCC) is a global health challenge characterized by significant histological heterogeneity. Conventional contrast-enhanced CT often struggles to differentiate RCC from solid benign renal tumors like fat-poor angiomyolipoma (fpAML) and renal oncocytoma (RO), leading to potential surgical overtreatment. CT-based radiomics has emerged as a promising non-invasive approach that extracts high-dimensional quantitative imaging features to support lesion characterization and may contribute toward more comprehensive, biopsy-adjacent decision support, although it does not yet replace histopathological assessment. Methods: This review systematically evaluates the predictive performance of CT-based radiomics in characterizing solid renal tumors. A literature search was conducted in PubMed/MEDLINE, Cochrane, and Scopus databases for original research published between 2012 and 2025. The review focuses on four key areas: differentiating benign renal tumors from RCC, clear cell (ccRCC) from non-ccRCC, fpAML from RCC, and RO from RCC. Results: In total, 47 studies were assessed, including 11,999 patients. CT-based radiomics demonstrates high diagnostic performance across all categories. Median Area Under the Curve values were 0.830 (0.747–0.900) for benign vs. malignant differentiation, 0.900 (0.861–0.910) for ccRCC vs. non-ccRCC, 0.912 (0.879–0.933) for fpAML vs. RCC, and 0.885 (0.841–0.947) for RO vs. RCC. The integration of radiomic features with clinical parameters into combined nomograms consistently yielded the highest predictive accuracy. Conclusions: Radiomics provides a non-invasive, objective method to characterize renal tumors, potentially reducing unnecessary surgeries and enabling personalized treatment. However, widespread clinical adoption remains limited by a lack of protocol standardization, the need for automated segmentation, and the requirement for prospective, multicenter validation.

Background/Objectives: Germ Cell Neoplasia In Situ (GCNIS) is considered the precursor lesion for the majority of testicular germ cell tumors (TGCTs). The aim of this study was to evaluate whether first-order radiomics features derived from volumetric diffusion tensor imaging (DTI) metrics—specifically apparent diffusion coefficient (ADC) and fractional anisotropy (FA) histogram parameters—can detect GCNIS. Methods: This study included 15 men with TGCTs and 10 controls. All participants underwent scrotal MRI, including DTI. Volumetric ADC and FA histogram metrics were calculated for the following tissues: group 1, TGCT; group 2: testicular parenchyma adjacent to tumor, histologically positive for GCNIS; and group 3, normal testis. Non-parametric statistics were used to assess differences in ADC and FA histogram parameters among the three groups. Pearson’s correlation analysis was followed by ordinal regression analysis to identify key predictive histogram parameters. Results: Widespread distributional differences (p < 0.05) were observed for many ADC and FA variables, with both TGCTs and GCNIS showing significant divergence from normal testes. Among the ADC statistics, the 10th percentile and skewness (p = 0.042), range (p = 0.023), interquartile range (p = 0.021), total energy (p = 0.033), entropy and kurtosis (p = 0.027) proved the most significant predictors for tissue classification. FA_energy (p = 0.039) was the most significant fingerprint of the carcinogenesis among the FA metrics. These parameters correctly characterized 88.8% of TGCTs, 87.5% of GCNIS tissues and 100% of normal testes. Conclusion: Radiomics features derived from volumetric ADC and FA histograms have promising potential to differentiate TGCTs, GCNIS, and normal testicular tissue, aiding early detection and characterization of pre-cancerous lesions.

Ovarian tumors are rare in the pediatric population, yet they are the most common type of malignancy in tumors of the female genital tract. Both non-neoplastic and neoplastic ovarian lesions are seen in children and adolescents. Most pediatric ovarian tumors are benign. Germ cell tumors constitute the majority of ovarian tumors in the pediatric cohort, and mature teratoma is the most prevalent histologic type. However, 3–8% % of ovarian tumors in children and adolescents are malignant. Accurate characterization of ovarian masses in the pediatric population is crucial to determine the appropriate treatment, which should be minimally invasive and focused on preserving fertility. Transabdominal US is the main imaging modality for the assessment of pediatric ovarian masses. MRI represents a valuable adjunct tool for the evaluation of sonographically indeterminate ovarian lesions. This technique is also recommended for tumor staging and follow-up. CT is often used in emergency situations or when there are contraindications for MRI. Imaging findings, along with clinical features and laboratory results, play a crucial role in the characterization of ovarian masses in the pediatric population. This narrative review was based on a comprehensive literature search of articles about imaging findings of ovarian masses in the pediatric population, published between 1977 and April 2025. Data were obtained from the PubMed database, using the following keywords: “imaging”, “ovarian tumors”, ovarian masses”, and “pediatric”. This article aims to provide an overview of the role of imaging in the assessment of ovarian masses in the pediatric age group.

Urogenital neoplasms represent some of the most common malignancies

Purpose To assess the role of 3.0 T Diffusion Tensor Imaging (DTI) and Fiber Tractography (FT) of the testes in the work-up of nonobstructive azoospermia (NOA). Methods This prospective study included consecutive NOA men and controls. A 3.0 T scrotal MRI was performed, including DTI. The testicular apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were calculated. FT reconstructions were created. The Kruskal–Wallis test, followed by pairwise comparisons, assessed differences in testicular ADC and FA between NOA histologic phenotypes (group 1: hypospermatogenesis; group 2: maturation arrest; and group 3: Sertoli cell-only syndrome) and normal testes. The Mann–Whitney-U test compared ADC and FA between NOA testes with positive and negative sperm retrieval. Visual assessment of the testicular fiber tracts was performed. Fiber tracts fewer in number, of reduced thickness, disrupted and/or disorganized were considered “abnormal”. Chi-square tests and binary logistic regression analysis assessed variations in testicular fiber tracts morphology. Results Twenty-nine NOA men (mean age: 39 ± 5.93 years) and 20 controls (mean age: 26 ± 5.83 years) were included for analysis. Higher ADC (p < 0.001) and FA (p < 0.001) was observed in NOA testes compared to controls. Differences in FA were found between groups 1 and 3 (0.07 vs 0.10, p = 0.26) and groups 2 and 3 (0.07 vs 0.10, p = 0.03), but not between groups 1 and 2 (p = 0.66). An increase in FA was observed in NOA testes with Sertoli cell-only syndrome compared to hypospermatogenesis and maturation arrest. FA was higher in NOA testes with negative results for the presence of sperm compared to those with positive results (0.09 vs 0.07, p = 0.006). FT showed “abnormal” fiber tracts in NOA testes (p < 0.001). Conclusion 3.0 T DTI and FT provide an insight into deranged spermatogenesis in NOA testes. Graphical Abstract

Purpose To evaluate the feasibility of diffusion tensor imaging (DTI) and fiber tractography (FT) of the normal epididymis and to determine normative apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values. Methods Twenty-eight healthy volunteers underwent MRI of the scrotum, including DTI on a 3.0 T system. For each anatomic part of the epididymis (head, body and tail) free-hand regions of interest were drawn and the mean ADC and FA were measured by two radiologists in consensus. Parametric statistical tests were used to determine intersubject differences in ADC and FA between the anatomic parts of each normal epididymis and between bilateral epididymides. Fiber tracts of the epididymis were reconstructed using the MR Diffusion tool. Results The mean ADC and FA of the normal epididymis was 1.31 × 10^–3 mm²/s and 0.20, respectively. No differences in ADC (p = 0.736) and FA (p = 0.628) between the anatomic parts of each normal epididymis were found. Differences (p = 0.020) were observed in FA of the body between the right and the left epididymis. FT showed the fiber tracts of the normal epididymis. Main study’s limitations include the following: small number of participants with narrow age range, absence of histologic confirmation and lack of quantitative assessment of the FT reconstructions. Conclusion DTI and FT of the normal epididymis is feasible and allow the noninvasive assessment of the structural and geometric organization of the organ. Graphical abstract

The Ancient Greeks were great innovators in all academic fields, including medicine. Hippocrates of Kos, the Father of Medicine, established many terms for the genitourinary (GU) system, such as nephros, urethra, urogenital, and adenocarcinoma. According to Hesiod's Theogony, Aphrodite, the goddess of love and beauty, was born off the coast of Kythera, from the foam produced by Uranus's genitals, after his son Cronus had thrown them into to the sea. In this review, we present the etymology of the GU vocabulary, review the Ancient Greeks’ understanding of the GU system and the origins of Greek myths related to the male genitals.

This review aims to compare the diagnostic performance of multidetector CT (MDCT), MRI, including diffusion-weighted imaging, and FDG PET/CT in the detection of peritoneal metastases (PMs) in ovarian cancer (OC). A comprehensive search was performed for articles published from 2000 to February 2023. The inclusion criteria were the following: diagnosis/suspicion of PMs in patients with ovarian/fallopian/primary peritoneal cancer; initial staging or suspicion of recurrence; MDCT, MRI and/or FDG PET/CT performed for the detection of PMs; population of at least 10 patients; surgical results, histopathologic analysis, and/or radiologic follow-up, used as reference standard; and per-patient and per-region data and data for calculating sensitivity and specificity reported. In total, 33 studies were assessed, including 487 women with OC and PMs. On a per-patient basis, MRI (p = 0.03) and FDG PET/CT (p < 0.01) had higher sensitivity compared to MDCT. MRI and PET/CT had comparable sensitivities (p = 0.84). On a per-lesion analysis, no differences in sensitivity estimates were noted between MDCT and MRI (p = 0.25), MDCT and FDG PET/CT (p = 0.68), and MRI and FDG PET/CT (p = 0.35). Based on our results, FDG PET/CT and MRI are the preferred imaging modalities for the detection of PMs in OC. However, the value of FDG PET/CT and MRI compared to MDCT needs to be determined. Future research to address the limitations of the existing studies and the need for standardization and to explore the cost-effectiveness of the three imaging modalities is required.