Building the first-ever digital twin of the bladder

Men ages 50 to 60 have an 80 percent chance of having some degree of bladder outlet obstruction (BOO) due to an enlarged prostate  – which causes multiple symptoms that can  impact their lives physically and psychologically.

The bladder, an incredibly complex organ, has its own electrical system and can change its constituents and geometry through a growth and remodeling process. However, in bladders with BOO, the urethral resistance increases and forces the muscle cells within the bladder to generate larger pressures to void.  Over time, the bladder adapts with a growth and remodeling response that causes changes in bladder size, tissue composition, and functionality. While effective at first, over time symptoms like frequent and sudden urges to urinate or recurrent urinary tract infections begin to appear. Prolonged BOO can even lead to irreversible complications including urinary retention, bladder stones and kidney failure.

A group of interdisciplinary researchers from across the globe received $3,201,394  from the National Institutes of Health through a five-year R01 grant  to develop a digital twin of a bladder that can simulate normal and BOO-affected bladder function and provide a tool to evaluate treatments.

“Our team, which is composed of engineers, medical doctors, biologists, and computer scientists, is highly multidisciplinary so we can properly simulate the key components of the organ in normal and BOO bladders,” said Anne Robertson, co-principal investigator and distinguished service professor of mechanical engineering and materials science at the University of Pittsburgh Swanson School of Engineering. “The connection between changes to the BOO bladder wall structure and bladder functionality are not understood. Our digital twin of the bladder, informed by extensive data, will enable us to better understand this connection.”

Alongside Robertson, Naoki Yoshimura, Professor of Urology, Professor of Pharmacology and Chemical Biology and UPMC Endowed Chair of Neurourology Research, will be representing Pitt.

Generating New Treatments and Data

By using a rat model of BOO and corresponding computational data, the digital twin will be able to predict the success of a particular form of treatment – both pharmacological and surgical.

The more the model learns, the more it can accurately predict the best course of treatment.

Currently, surgical outcomes have a low success rate, which is why there is such a need to understand the underlying issues of BOO.

“We have an opportunity here to capitalize and build on the tools and computational

approaches that have already been developed for other organs to rapidly increase our

understanding of bladder biomechanics,” said Dr. Paul Watton, co-principal investigator and Head of the Complex Systems Modellings research group, Department of Computer Science at the University of Sheffield.

The bladder, despite its complexity and vitality, is one of the few organs to not have its own digital twin. For example, digital models of the heart have been available for years.

“By creating this computational model of a real physiological system, we can gain data in real time and try different interventions to prime our model so it can be used on a patient-specific basis in the future,” Robertson said. “The idea would be that a medical doctor could put an individual’s own measurements and clinical information into the model and then provide a patient tailored  treatment.”

The project, “A Digital Twin for Designing Bladder Treatment informed by Bladder Outlet Obstruction Mechanobiology (BOOM),” began in July 2023.

Other researchers on this project:

  • Kang Kim, University of Pittsburgh
  • Yasutake Tobe, University of Pittsburgh
  • Simon Watkins, University of Pittsburgh
  • Spandan Maiti, University of Pittsburgh
  • Alan Watson, University of Pittsburgh
  • Kanako Matsuoka, University of Pittsburgh
  • Tadanobu Kamijo, University of Pittsburgh
  • Richard Clayton,  University of Sheffield

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