Creation of synthetic contrast-enhanced computed tomography images using deep neural networks to screen for renal cell carcinoma.

In this study, we elucidate if synthetic contrast enhanced computed tomography images created from plain computed tomography images using deep neural networks could be used for screening, clinical diagnosis, and postoperative follow-up of small-diameter renal tumors. This retrospective, multicenter study included 155 patients (artificial intelligence training cohort [n = 99], validation cohort [n = 56]) who underwent surgery for small-diameter (≤40 mm) renal tumors, with the pathological diagnosis of renal cell carcinoma, during 2010-2020. We created a learned deep neural networks using pix2pix.

Impact of the coronavirus disease 2019 pandemic on the number of undergoing radical nephroureterectomy and postoperative adjuvant systematic therapy for upper tract urothelial carcinomas in Japan: A multicenter retrospective study.

Objectives: The coronavirus disease 2019 pandemic has affected cancer management worldwide. For upper tract urothelial carcinomas, delays in treatments are not recommended even during the pandemic. We investigated the impact of the pandemic on patients with these carcinomas who underwent radical nephroureterectomy (RNU) and adjuvant systematic therapy before and after COVID-19 spread in Japan.