scholarly journals Detrusorrhaphy during Robot-Assisted Radical Prostatectomy: Early Recovery of Urinary Continence and Surgical Technique

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Tae Young Shin ◽  
Yong Seong Lee

Robot-assisted radical prostatectomy (RARP) has largely replaced open radical prostatectomy as the standard surgical treatment for prostate cancer. However, postoperative urinary incontinence still persists and has a significant impact on quality of life. We report the superior results of the detrusorrhaphy technique during RARP that helps achieve early continence. Our prospective study involved 95 consecutive patients who underwent RARP between March 2015 and May 2017; fifty patients underwent RARP using the new detrusorrhaphy technique (group 1) and 45 underwent standard RARP (group 2). The postoperative oncological and functional outcomes were compared between the two groups. The postoperative continence was assessed at 0 day, 1 week, 4 weeks, 8–12 weeks, and 6 months after catheter removal. Continence was defined as the use of no pad over a 24 h period. Mean operative time in groups 1 and 2 were 250 and 220 min, respectively. Intraoperative complications were not encountered in any patient. The continence rates after catheter removal in groups 1 and 2 were 68% and 0% at 0 day, 78% and 17.8% at 1 week, 86% and 64.4% at 4 weeks, 92% and 73.3% at 8–12 weeks, and 100% and 91.1% at 6 months, respectively. In the multivariate analysis, the nerve sparing technique, D’Amico risk groups, and prostate volume were involved in the early recovery of urinary continence. The detrusorrhaphy technique is simple, safe, and feasible, which helped achieve earlier continence. It showed significantly better outcomes than those achieved with the standard RARP technique in terms of urinary incontinence. Nevertheless, our findings need to be validated in further studies.

2017 ◽  
Vol 197 (4S) ◽  
Author(s):  
Yuji MAEDA ◽  
Toshimitsu MISAKI ◽  
Osamu UEKI ◽  
Tetsuyuki KUROKAWA ◽  
Yukinosuke OSHINOYA ◽  
...  

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 310-310
Author(s):  
Makoto Sumitomo ◽  
Atsushi Teramoto ◽  
Naohiko Fukami ◽  
Kosuke Fukaya ◽  
Kenji Zennami ◽  
...  

310 Background: Urinary incontinence remains one of the most bothersome postoperative complications even after robot-assisted radical prostatectomy (RARP). We aimed to make a novel prediction system that can be used preoperatively to inform patients of the accuracy of early recovery of urinary continence after RARP using a deep learning (DL) model from magnetic resonance imaging (MRI) information and preoperative clinicopathological parameters. Methods: A retrospective cohort study was conducted on prostate cancer (PC) patients who had undergone RARP at our hospital between August 2015 and July 2019. Patients using no pads/no leakage of urine or the use of a safety pad within 3 months after RARP is categorized into “good” continence and others into “no good” continence. MRI DICOM data from axial, coronal and sagittal imaging as well as preoperative clinicopathological covariates (age, BMI, prostate volume, serum PSA level, Gleason score, clinical stage) were assessed. Supervised DL algorithms, which included AdaBoost, Naive Bayes, Neural Network, Random Forest, and SVM were trained and tested as binary classifiers (good or no good). To evaluate the DL models from the testing data set, their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), as well as area under the receiver operating characteristic curve (AUC) were analyzed. Results: Data were available for 497 patients in the study period. The AdaBoost DL algorithm using MRI information in addition to clinicopathological parameters had the highest performance with sensitivity at 92%, specificity at 77%, PPV at 79%, NPV at 91%, and AUC at 84% for predicting good continence, while that using clinicopathological parameters only had the performance with sensitivity at 50%, specificity at 69%, PPV at 60%, NPV at 60%, and AUC at 60%. Conclusions: Our results suggest that the DL algorithms using MRI imaging information are highlighted as an accurate method for strongly predicting early recovery of urinary continence after RARP. Thus, DL predictions may help allocation of treatment strategies for PC patients who dislike prolonged urinary incontinence after RARP.


2009 ◽  
Vol 23 (7) ◽  
pp. 1115-1119 ◽  
Author(s):  
Atsushi Takenaka ◽  
Hideo Soga ◽  
Iori Sakai ◽  
Yuzo Nakano ◽  
Hideaki Miyake ◽  
...  

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