Background And Objective: While the modern artificial urinary sphincter (AUS) has benefited from incremental innovation, which has improved both device efficacy and complication rates, the foundational technology in use in Boston Scientific's AMS800 can be traced back to the fundamental hydraulic tenets of the AS721. Research and development in adaptive technology and electronic integration stand to further improve AUS outcomes.
Methods: The Medline online retrieval system was queried using the MeSH terms "artificial urinary sphincter", "electronic", "complications", "history", and "development" in various combinations. Publications were reviewed if applicable, and their reference lists were used to collect additional articles as needed. Final article inclusion was based on senior author discretion.
Key Content And Findings: The AMS800 AUS is the gold standard for male stress incontinence implants. A 2015 consensus conference set out the goals for sphincter device development in the coming decades. A future ideal sphincter would adjust cuff pressure dynamically as well as function with minimal manipulation, or even via electronic control. Multiple new devices are in various states of development. During the next decade, artificial urinary sphincter technology is likely to include multiple Food and Drug Administration (FDA)-approved devices with varying features aimed at satisfying the 2015 consensus conference goal for an "ideal" AUS.
Conclusions: The future of stress incontinence therapy lies in both continued innovation for the AUS, as well as advances in regenerative medicine. Electronic and adaptive developments in AUS technology will increase device safety, efficacy, and longevity while improving the user and caregiver experience. For some, regenerative medicine may even make AUS technology obsolete.
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http://dx.doi.org/10.21037/tau-22-858 | DOI Listing |
Int 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.
Cells
December 2024
Department of Mechanical Engineering, Tufts University, Medford, MA 02155, USA.
The development of noninvasive methods for bladder cancer identification remains a critical clinical need. Recent studies have shown that atomic force microscopy (AFM), combined with pattern recognition machine learning, can detect bladder cancer by analyzing cells extracted from urine. However, these promising findings were limited by a relatively small patient cohort, resulting in modest statistical significance.
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