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Aromatase activity has commonly been associated with male infertility characterized by testicular dysfunction with low serum testosterone and/or testosterone to estradiol ratio. In this subset of patients, and particularly in those with hypogonadism, elevated levels of circulating estradiol may establish a negative feedback on the hypothalamic-pituitary-testicular axis by suppressing follicle-stimulating hormone (FSH) and luteinizing hormone (LH) production and impaired spermatogenesis. Hormonal manipulation via different agents such as selective estrogen modulators or aromatase inhibitors to increase endogenous testosterone production and improve spermatogenesis in the setting of infertility is an off-label option for treatment. We carried out a systematic review and meta-analysis of the literature of the past 30 years in order to evaluate the benefits of the use of aromatase inhibitors in the medical management of infertile/hypoandrogenic males. Overall, eight original articles were included and critically evaluated. Either steroidal (Testolactone) or nonsteroidal (Anastrozole and Letrozole) aromatase inhibitors were found to statistically improve all the evaluated hormonal and seminal outcomes with a safe tolerability profile. While the evidence is promising, future prospective randomized placebo-controlled multicenter trials are necessary to better define the efficacy of these medications.

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.

Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep learning (DL) model is teaching computers to learn by example, something that human beings are doing naturally. AI is revolutionizing healthcare. Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. The enormous quantity of data coming from the prostate tumor genome requires fast, reliable and accurate computing power provided by machine learning algorithms. Radiotherapy is an essential part of the treatment of prostate cancer and it is often difficult to predict its toxicity for the patients. Artificial intelligence could have a future potential role in predicting how a patient will react to the therapy side effects. These technologies could provide doctors with better insights on how to plan radiotherapy treatment. The extension of the capabilities of surgical robots for more autonomous tasks will allow them to use information from the surgical field, recognize issues and implement the proper actions without the need for human intervention.

Although music has been shown to alleviate pain and anxiety during transrectal PBx, limited evidence is available regarding its impact in the transperineal (TP) setting. This study aimed to investigate the effect of music on pain perception during office-based TP PBx. This prospective, comparative, non-randomized study enrolled biopsy-naïve patients undergoing TP PBx between March 2024 and March 2025. A total of 200 patients were equally assigned to the intervention group (listening to music during PBx) or the control group. Pain was assessed using the Visual Analog Scale (VAS) at six predefined timepoints (T0–T5). A differential pain score (D-VAS) was calculated at each timepoint, using the VAS score at T0 as the baseline. Changes over time between the two groups were analyzed using independent t-tests and a linear mixed-effects model. An interaction term between music and timepoints was included to test whether the effect of music on pain perception varied across the different stages of the procedure. Compared with controls, D-VAS was significantly lower in the music group at the first core (T3, p  = 0.025), last core (T4, p  < 0.001) and at discharge (T5, p  < 0.001). No significant differences were observed during local anesthesia (T1-T2). The Mixed-effects model confirmed these findings and revealed that both pain perception and the relative analgesic effect of music varied accross different stages of the procedure. Listening to music was associated with lower pain perception during TP PBx, particularly during biopsy sampling phases, and resulted in lower pain levels at discharge.

Purpose Urinary incontinence (UI) after radical prostatectomy (RP) is an early side effect after catheter removal. This systematic review and meta‐analysis were conducted to compare different forms of non‐invasive treatments for post‐RP UI and to analyse whether the addition of biofeedback (BF) and/or pelvic floor muscle electric stimulation (PFES) to PF muscle exercise (PFME) alone can improve results in terms of continence recovery rate. Materials and Methods A literature search was performed following the PRISMA guidelines. We performed a cumulative meta‐analysis to explore the trend in the effect sizes across subgroups during a 12‐months follow‐up. Results Twenty‐six articles were selected. At baseline after RP and catheter removal, mean pad weight varied extremely. At 1‐ and 3‐months intervals, mean difference in pad weight recovery from baseline was significantly higher using guided programs (BF, PFES or both) than using PFME alone (3‐months: PFME 111.09 g (95%CI 77.59‐144.59), BF 213.81 g (95%CI −80.51‐508‐13), PFES 306.88 g (95%CI 158.11‐455.66), BF + PFES 266.31 g (95%CI 22.69‐302.93); P < .01), while at 6‐ and 12‐months differences were similar (P > .04). At 1‐ and 3‐months intervals, event rate (ER) of continence recovery was significantly higher using guided programs than using PFME alone (3‐months: PFME 0.40 (95%CI 0.30‐0.49), BF 0.49 (95%CI 0.31‐0.67), PFES 0.57 (95%CI 0.46‐0.69), BF + PFES 0.75 (95%CI 0.60‐0.91); P < .01), while at 6‐ and 12‐months ERs were similar. Conclusions Regarding non‐invasive treatment of UI secondary to RP, the addition of guided programs using BF or/and PFES demonstrated to improve continence recovery rate, particularly in the first 3‐month interval, when compared with the use of PFME alone.

Artificial intelligence is highly regarded as the most promising future technology that will have a great impact on healthcare across all specialties. Its subsets, machine learning, deep learning, and artificial neural networks, are able to automatically learn from massive amounts of data and can improve the prediction algorithms to enhance their performance. This area is still under development, but the latest evidence shows great potential in the diagnosis, prognosis, and treatment of urological diseases, including bladder cancer, which are currently using old prediction tools and historical nomograms. This review focuses on highly significant and comprehensive literature evidence of artificial intelligence in the management of bladder cancer and investigates the near introduction in clinical practice.

Bladder cancer (BC) is characterized by high incidence and recurrence rates together with genomic instability and elevated mutation degree. Currently, cystoscopy combined with cytology is routinely used for diagnosis, prognosis and disease surveillance. Such an approach is often associated with several side effects, discomfort for the patient and high economic burden. Thus, there is an essential demand of non-invasive, sensitive, fast and inexpensive biomarkers for clinical management of BC patients. In this context, liquid biopsy represents a very promising tool that has been widely investigated over the last decade. Liquid biopsy will likely be at the basis of patient selection for precision medicine, both in terms of treatment choice and real-time monitoring of therapeutic effects. Several different urinary biomarkers have been proposed for liquid biopsy in BC, including DNA methylation and mutations, protein-based assays, non-coding RNAs and mRNA signatures. In this review, we summarized the state of the art on different available tests concerning their potential clinical applications for BC detection, prognosis, surveillance and response to therapy.

Novel molecular imaging opportunities to preoperatively diagnose renal cell carcinoma is under development and will add more value in limiting the postoperative renal function loss and morbidity. We aimed to comprehensively review the research on single photon emission computed tomography/computed tomography (SPECT/CT) and positron emission tomography computed tomography (PET-CT) molecular imaging and to enhance the urologists’ and radiologists’ knowledge of the current research pattern. We identified an increase in prospective and also retrospective studies that researched to distinguish between benign and malignant lesions and between different clear cell renal cell carcinoma subtypes, with small numbers of patients studied, nonetheless with excellent results on specificity, sensitivity and accuracy, especially for 99mTc-sestamibi SPECT/CT that delivers quick results compared to a long acquisition time for girentuximab PET-CT, which instead gives better image quality. Nuclear medicine has helped clinicians in evaluating primary and secondary lesions, and has lately returned with new and exciting insights with novel radiotracers to reinforce its diagnostic potential in renal carcinoma. To further limit the renal function loss and post-surgery morbidity, future research is mandatory to validate the results and to clinically implement the diagnostic techniques in the context of precision medicine.

Background: Up to 15% of couples are infertile and male factor infertility accounts for approximately 50% of these cases. Male infertility is a multifactorial pathological condition. The genetic of male infertility is very complex and at least 2000 genes are involved in its etiology. Genetic testing by next-generation sequencing (NGS) technologies can be relevant for its diagnostic value in male infertile patients. Therefore, the aim of this study was to implement the diagnostic offer with the use of an NGS panel for the identification of genetic variants. Methods: We developed an NGS gene panel that we used in 22 male infertile patients. The panel consisted of 110 genes exploring the genetic causes of male infertility; namely spermatogenesis failure due to single-gene mutations, central hypogonadism, androgen insensitivity syndrome, congenital hypopituitarism, and primary ciliary dyskinesia. Results: NGS and a subsequent sequencing of the positive pathogenic or likely pathogenic variants, 5 patients (23%) were found to have a molecular defect. In particular, pathogenic variants were identified in TEX11, CCDC39, CHD7, and NR5A1 genes. Moreover, 14 variants of unknown significance and 7 novel variants were found that require further functional studies and family segregation. Conclusion: This extended NGS-based diagnostic approach may represent a useful tool for the diagnosis of male infertility. The development of a custom-made gene panel by NGS seems capable of reducing the proportion of male idiopathic infertility.