Image: Pictured left to right: Professor Naoki Yoshimura and Professor Anne Robertson from the University of Pittsburgh with Dr Paul Watton from the University of Sheffield.
By Cristina D’Imperio
Anne Robertson, PhD, McGowan affiliated faculty, is collaborating with researchers from the University of Pittsburgh and the University of Sheffield to develop the digital twin of a bladder.
The project, titled “A Digital Twin for Designing Bladder Treatment informed by Bladder Outlet Obstruction Mechanobiology (BOOM),” has been awarded a $3.2 million R01 grant from the National Institutes of Health (NIH) to help design patient-specific treatments for those with bladder outlet obstruction (BOO).
BOO can negatively impact men as they age and is characterized by a blockage that stops or slows the flow of urine from the bladder. Symptoms include abdominal pain, the sensation of a continuously full bladder, and trouble urinating. Men between the ages of 50 and 60 have an 80% chance of experiencing some degree of BOO.
Over 200 million people globally are affected by symptoms related to BOO. However, as Dr. Robertson states, “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.”
Currently, surgical procedures to treat BOO are only 70% effective. A digital representation of the bladder, however, would not only enable a greater understanding of BOO but also how it can be more effectively treated, both surgically and pharmacologically. The project seeks to make use of state-of-the-art studies of BOO in rat models and corresponding computational data as a basis for the development of the new digital technology.
“By creating this computational model of a real physiological system,” says Dr. Robertson, “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.” Adjusting the digital twin in real time with personalized data would enable clinicians to better predict the success of a treatment on individual patients.
In short, Dr. Robertson maintains, “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.”
Other researchers on this project include:
- Paul Watton, co-principal investigator, University of Sheffield
- Naoki Yoshimura, University of Pittsburgh
- Kang Kim, University of Pittsburgh
- Yasutaka 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
Read more from Pitt’s Swanson School of Engineering here.
Read more from the University of Sheffield here.