Article: Impact of the COVID-19 pandemic on urology residency training in Italy - Minerva Urologica e Nefrologica 2020 August;72(4):505-9 - Minerva Medica - Journals

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.

Background: Upper tract urothelial carcinoma (UTUC) is a rare disease with a potentially dismal prognosis. We systematically compared international guidelines on UTUC to analyze similitudes and differences among them. Methods: We conducted a search on MEDLINE/PubMed for guidelines related to UTUC from 2010 to the present. In addition, we manually explored the websites of urological and oncological societies and journals to identify pertinent guidelines. We also assessed recommendations from the International Bladder Cancer Network, the Canadian Urological Association, the European Society for Medical Oncology, and the International Consultation on Bladder Cancer, considering their expertise and experience in the field. Results: Among all the sources, only the American Urologist Association (AUA), European Association of Urology (EAU), and the National Comprehensive Cancer Network (NCCN) guidelines specifically report data on diagnosis, treatment, and follow-up of UTUC. Current analysis reveals several differences between all three sources on diagnostic work-up, patient management, and follow-up. Among all, AUA and EAU guidelines show more detailed indications. Conclusions: Despite the growing incidence of UTUC, only AUA, EAU, and NCCN guidelines deal with this cancer. Our research depicted high variability in reporting recommendations and opinions. In this regard, we encourage further higher-quality research to gain evidence creating higher grade consensus between guidelines.

Article: 3D imaging technologies in minimally-invasive kidney and prostate cancer surgery: which is the urologists’ perception? - Minerva Urology and Nephrology 2021 Mar 26 - Minerva Medica - Journals