International journal of urology : official journal of the Japanese Urological Association · 2026
Artificial Intelligence-Based Objective Evaluation of Nerve-Sparing Status Combined With Preserved Urethral Length Predicts Urinary Continence Recovery After Robot-Assisted Radical Prostatectomy.
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Ando Satoshi, Del Aguila Moraga Diego Andres, Hoshina Hayato, Kawahira Hiroshi, Nakaguchi Toshiya, Fujimura Tetsuya
Аннотация
OBJECTIVES: To evaluate nerve-sparing status objectively using an artificial intelligence method applied to intraoperative images and to determine whether combining this assessment with preserved urethral length improves prediction of urinary continence recovery after robot-assisted radical prostatectomy.
METHODS: We analyzed 195 patients with intraoperative still images from robot-assisted radical prostatectomy performed between May 2020 and 2022. Images were evaluated with a deep learning image classification model that determined whether the neurovascular bundle was preserved. Patients were categorized into two groups: those with both preserved urethral length of at least 26 mm and artificial intelligence-assessed neurovascular bundle preservation, and all other patients. The primary endpoint was time to urinary continence recovery. Kaplan-Meier analysis and Cox proportional hazards models were used.
RESULTS: Artificial intelligence reclassified neurovascular bundle preservation in 60 of 195 patients (30.8%), including 48 cases of surgeon overestimation and 12 of underestimation. Patients who met both criteria had significantly better urinary continence recovery than the other patients, with higher continence rates at 30, 60, 90, and 365 days after surgery on log-rank testing. In multivariable Cox models, the combined factor independently predicted continence recovery at 60, 90, and 365 days, with hazard ratios of 1.99, 1.78, and 1.49 and corresponding 95% confidence intervals of 1.07-3.72, 1.07-2.95, and 1.09-2.04 (p values 0.03, 0.03, and 0.01, respectively).
CONCLUSIONS: Objective evaluation of nerve-sparing status using artificial intelligence, when combined with preserved urethral length, improves prediction of early urinary continence recovery after robot-assisted radical prostatectomy and may provide an indicator of surgical quality.
METHODS: We analyzed 195 patients with intraoperative still images from robot-assisted radical prostatectomy performed between May 2020 and 2022. Images were evaluated with a deep learning image classification model that determined whether the neurovascular bundle was preserved. Patients were categorized into two groups: those with both preserved urethral length of at least 26 mm and artificial intelligence-assessed neurovascular bundle preservation, and all other patients. The primary endpoint was time to urinary continence recovery. Kaplan-Meier analysis and Cox proportional hazards models were used.
RESULTS: Artificial intelligence reclassified neurovascular bundle preservation in 60 of 195 patients (30.8%), including 48 cases of surgeon overestimation and 12 of underestimation. Patients who met both criteria had significantly better urinary continence recovery than the other patients, with higher continence rates at 30, 60, 90, and 365 days after surgery on log-rank testing. In multivariable Cox models, the combined factor independently predicted continence recovery at 60, 90, and 365 days, with hazard ratios of 1.99, 1.78, and 1.49 and corresponding 95% confidence intervals of 1.07-3.72, 1.07-2.95, and 1.09-2.04 (p values 0.03, 0.03, and 0.01, respectively).
CONCLUSIONS: Objective evaluation of nerve-sparing status using artificial intelligence, when combined with preserved urethral length, improves prediction of early urinary continence recovery after robot-assisted radical prostatectomy and may provide an indicator of surgical quality.