Jason Moore
Pennsylvania State University, PA·Biomedical Engineering
Colonoscopy is one of the most common procedures in American medicine. More than 19 million are performed in the US each year, and they let doctors find and treat diseases such as colon cancer without open surgery.
- Fields
Biomedical Engineering
Engineering
Medicine & Clinical Research
- Topics
colonoscopy
endoscopy
surgical training
- Grants
- 1 known grant, through Apr 2027
What they work on
- Build and validate a dataset of colon shapes by automatically measuring centerline geometry in 959 patient virtual colonoscopies from The Cancer Imaging Archive, and refine sensor processing in the MAFT sensorized manikin trainer.
- Develop and validate a 3D optimization model that solves for the best endoscope steering controls for a given colon shape, reaching the cecum in optimal time with minimal trauma, and execute it across the full colon dataset.
- Test whether a virtual coach delivering personalized, optimization-based feedback on the sensorized manikin raises physicians' cecal intubation rate and adenoma detection rate and lowers endoscope forces, in human studies with attendings and residents.
- Implement MAFT in the Hershey Medical Center surgical residency and assess residents' colonoscopy skill with cecal intubation rate, adenoma detection rate, and GAGES assessment.
More about the research
Yet the procedure is costly, and success depends heavily on the physician's skill: doctors typically reach the accepted 90% completion rate only after hundreds of patient cases. This project asks whether a sensor-equipped practice model paired with computer-generated coaching can help physicians learn faster and handle the scope more gently.
Why it matters
Physicians who learn colonoscopy faster and more reliably could complete more procedures, miss fewer precancerous growths, and apply less force that can injure the colon. Better training could help reduce the cost of one of the most expensive screening tests routinely given to healthy adults and improve colon cancer screening for patients. The colon geometry dataset and optimal steering strategies may also inform future training tools.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Alba Alfonso-Garcia
University of California-Davis, CA·Biomedical Engineering
Build a database of in vivo fluorescence lifetime imaging (FLIm) signatures from colorectal lesions in 200 patients undergoing routine colonoscopy, correlating each label-free autofluorescence signature with histopathology to define markers of lesion type.
Jeremy Brown
Johns Hopkins University, MD·Biomedical Engineering·Early-career
Speed up how robotic-surgery trainees learn to judge tissue forces by sight, by giving them titrated extra haptic feedback of tool–tissue forces and contact vibrations in user studies.
Sarah Miller
Icahn School of Medicine at Mount Sinai, NY·Public Health & Epidemiology
Refine the eNav Toolkit, a web app for colorectal cancer screening decisions, reminders, bowel-prep instructions and education, through two rounds of field testing with 10 federally qualified health center (FQHC) patients each.
The school
Pennsylvania State University: 60 labs on PI Pages, $1.3B a year on research, 743 research doctorates a year.
Reach out
A start for your email. Fill in the brackets.