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. We examined the quality of the synthetic enhanced computed tomography images created using this deep neural networks and compared them with real enhanced computed tomography images using the zero-mean normalized cross-correlation parameter. We assessed concordance rates between real and synthetic images and diagnoses according to 10 urologists by creating a receiver operating characteristic curve and calculating the area under the curve. The synthetic computed tomography images were highly concordant with the real computed tomography images, regardless of the existence or morphology of the renal tumor. Regarding the concordance rate, a greater area under the curve was obtained with synthetic computed tomography (area under the curve = 0.892) than with only computed tomography (area under the curve = 0.720; p < 0.001). In conclusions, this study is the first to use deep neural networks to create a high-quality synthetic computed tomography image that was highly concordant with a real computed tomography image. Our synthetic computed tomography images could be used for urological diagnoses and clinical screening.

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. METHODS: This multicenter retrospective study included 304 patients who underwent RNU for upper tract urothelial carcinomas between May 1, 2019, and December 31, 2021, in Aichi, Japan. The patients were categorized into three groups based on whether they underwent surgery in the prepandemic (before infection spread in Japan), early pandemic (between confirmation of the first case and vaccination initiation), and late pandemic (after the start of vaccination in Japan) phases. The patient characteristics, diagnostic methods, pathological findings, and postoperative therapy were compared among the three phases. RESULTS: Overall, 74, 152, and 78 patients underwent RNU in the prepandemic, early pandemic, and late pandemic phases, respectively. The number of patients who underwent preoperative ureteroscopy decreased significantly from the prepandemic phase to the late pandemic phase due to pandemic-related restrictions (p = 0.016). There was no difference in the time to the first visit or pathological findings. Among patients classified as high-risk according to existing clinical trials, the proportion receiving adjuvant systematic therapy after RNU decreased significantly from 52.3% to 19% (p = 0.003). CONCLUSIONS: There was no difference in the pathological findings. The number of patients receiving appropriate adjuvant systematic therapy decreased during the pandemic.