Urethral sphincter insufficiency following radical prostatectomy (RP) is a common cause of non-neurogenic stress urinary incontinence (SUI). Artificial urinary sphincter (AUS) insertion remains the standard of care for fit patients with SUI refractory to non-operative interventions. The proximal urethra is a common location for uncomplicated AUS placement. However, previous failed AUS, urethroplasty, or pelvic radiotherapy (RT) may compromise urethral tissue requiring technique modifications that optimise outcomes. In these situations, transcorporal cuff (TC) placement has been well described to facilitate continence restoration in men where there is no other feasible option other than urinary diversion or permanent incontinence. In the traditional TC approach, the procedure may be complicated by haematoma due to difficulty in completely closing the corporal defects behind the urethra. This narrated video demonstrates the tunical flap (TF) modification for transcorporal AUS implantation via a perineal and penoscrotal approach in patients with prior failed AUS placements secondary to urethral erosion. The TF technique for transcorporal AUS insertion provides circumferential reinforcement with tunica albuginea from the corpora cavernosa. Here, we show how this technique provides additional urethral support for compromised urethral tissue to help prevent cuff erosion. The TF preserves the corporal volume and does not limit candidacy for future penile prosthesis implantation. In our early results, there have been no postoperative haematoma formation with this technique.
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http://dx.doi.org/10.21037/tau-23-641 | DOI Listing |
BMC Surg
January 2025
Department of Obstetrics and Gynecology, Firoozgar Clinical Research and Development Center (FCRDC), School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Background: Complete Cytoreduction (CC) in ovarian cancer (OC) has been associated with better outcomes. Outcomes after CC have a multifactorial and interrelated cause that may not be predictable by conventional statistical methods. Artificial intelligence (AI) may be more accurate in predicting outcomes.
View Article and Find Full Text PDFInt J Urol
January 2025
Department of Urology, National Defense Medical College, Saitama, Japan.
Objectives: Limited data exist on surgical outcomes following artificial urinary sphincter (AUS) implantation in patients with a history of urethroplasty for urethral stricture. This study aimed to evaluate the surgical outcomes of AUS implantation in such patients, focusing on the risk of urethral erosion.
Methods: We retrospectively reviewed 14 male patients who developed severe urinary incontinence following urethroplasty for urethral stricture and subsequently underwent AUS implantation at our center between March 2012 and January 2024.
Sci Rep
January 2025
Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Korea.
Recently, as the number of cancer patients has increased, much research is being conducted for efficient treatment, including the use of artificial intelligence in genitourinary pathology. Recent research has focused largely on the classification of renal cell carcinoma subtypes. Nonetheless, the broader categorization of renal tissue into non-neoplastic normal tissue, benign tumor and malignant tumor remains understudied.
View Article and Find Full Text PDFJ Clin Med
January 2025
Department of Urology, University of Rennes, 35000 Rennes, France.
The artificial urinary sphincter has been an effective treatment for stress urinary incontinence caused by intrinsic sphincter deficiency in women. However, the use of this device has been limited by the technical difficulties and risks associated with the open implantation procedure. Preliminary studies using robotic techniques have shown promising results, but only one small study has compared robotic to open procedures.
View Article and Find Full Text PDFWorld J Urol
January 2025
Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-dong Road, Wuhan, Hubei, 430060, P.R. China.
Purpose: To develop a deep learning (DL) model based on primary tumor tissue to predict the lymph node metastasis (LNM) status of muscle invasive bladder cancer (MIBC), while validating the prognostic value of the predicted aiN score in MIBC patients.
Methods: A total of 323 patients from The Cancer Genome Atlas (TCGA) were used as the training and internal validation set, with image features extracted using a visual encoder called UNI. We investigated the ability to predict LNM status while assessing the prognostic value of aiN score.
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