Is the time right for a new initiative in mathematical modeling of the lower urinary tract? ICI‐RS 2023

• Published in: Neurourology and urodynamics 2024-08, Vol.43 (6), p.1303-1310
• Main Authors: Damaser, Margot S., Valentini, Françoise A., Clavica, Francesco, Giarenis, Ilias
• Format: Article
• Language: English
• Subjects: Artificial intelligence; bladder; Humans; Literature reviews; Lower Urinary Tract Symptoms - diagnosis; Lower Urinary Tract Symptoms - physiopathology; mathematical modeling; Mathematical models; mechanical modeling; Models, Biological; Models, Theoretical; nomogram; Nomograms; statistical modeling; Statistical models; Urethra; Urethra - physiology; Urinary Bladder - physiology; Urinary Bladder - physiopathology; Urinary tract; Urodynamics; Urogenital system
• ISSN: 0733-2467; 1520-6777; 1520-6777
• DOI: 10.1002/nau.25362

Introduction A session at the 2023 International Consultation on Incontinence – Research Society (ICI‐RS) held in Bristol, UK, focused on the question: Is the time right for a new initiative in mathematical modeling of the lower urinary tract (LUT)? The LUT is a complex system, comprising various synergetic components (i.e., bladder, urethra, neural control), each with its own dynamic functioning and high interindividual variability. This has led to a variety of different types of models for different purposes, each with advantages and disadvantages. Methods When addressing the LUT, the modeling approach should be selected and sized according to the specific purpose, the targeted level of detail, and the available computational resources. Four areas were selected as examples to discuss: utility of nomograms in clinical use, value of fluid mechanical modeling, applications of models to simplify urodynamics, and utility of statistical models. Results A brief literature review is provided along with discussion of the merits of different types of models for different applications. Remaining research questions are provided. Conclusions Inadequacies in current (outdated) models of the LUT as well as recent advances in computing power (e.g., quantum computing) and methods (e.g., artificial intelligence/machine learning), would dictate that the answer is an emphatic “Yes, the time is right for a new initiative in mathematical modeling of the LUT.”