Pranav Kolluri Rose Hills
T2D and Prediction of Bone Strength Loss Using Learning Models
It is increasingly being recognized that diabetic bone disease, associated with an increased risk of bone fractures, cannot be detected effectively using traditional detection methods for osteoporosis. This is because patients with Type 2 Diabetes (T2D), despite having normal or even high bone densities, are still prone to fractures. The Bone Quality Research Lab at UCSF has established that deficits in the cortical bone structure are associated with T2D and the increased fracture potential found in those with T2D. My research will further develop this finding by determining if T2D status, marrow, or vessel metrics predict longitudinal increase in porosity and decrease in strength. This work will contribute to further understanding of whether cortical pore content can be used as a predictor for cortical degradation, as well as furthering our understanding of how such degradation takes place and what potential targets exist for future therapeutic studies. With the number of T2D patients, and thus severe bone fractures, this project will serve as a potential signal for future bone-strength loss and enable future therapeutics.
Message To Sponsor
Thank you for your generous support in funding my fellowship during the Summer of 2023. This opportunity will undoubtedly be a pivotal moment in my academic and professional journey, allowing me to gain valuable insights and experience at the intersection of computer science and medicine. Your contribution is greatly appreciated, and I am grateful for the chance to pursue my passions and make a meaningful impact in the world.