Medical Imaging Informatics and AI wins 2016 PPMI Data Challenge

November 29, 2016, The Michael J Fox Foundation named the winners of the 2016 Parkinson's Progression Markers Initiative Data Challenge (PPMI). The foundation asked researchers to provide a model of Parkingson's disease subtypes or baseline predictors using PPMI data, in order to better accelerate testing of new treatments for Parkinson's. These models would allow researchers to better design clinical trials and choose better patient volunteers in these studies.

2016 PPMI Data Challenge winners with Michael J. Fox
Winner Dr. Duygu Tosun-Turgut (center) met with Michael J. Fox and MJFF Co-founder and Executive Vice Chairman Debi Brooks in New York City earlier this month.

The winners were Duygu Tosun-Turgut, PhD, Assistant Professor of Radiology and Biomedical Imaging at UC San Francisco and co-director of the Center for Imaging of Neurodegenerative Diseases at the San Francisco Veterans Affairs Health Care System; and Fei Wang, PhD, assistant professor of health care policy and research at Weill Cornell Medicine. Each received a $25,000 award furnished by MJFF and supported in part by GE Healthcare. Dr. Tosun-Turgut, PhD is the Director and Founder of the Medical Imaging Informatics and AI department at UCSF.

"The Parkinson's Progression Markers Initiative offers a rich pool of open-access data from which to make connections that advance our understanding of Parkinson's disease and impact how we approach drug development," explained Mark Frasier, PhD, MJFF senior vice president of research programs. "The award encouraged scientists from other disciplines to lend their expertise to our efforts to find a cure. Drs. Tosun-Turgut and Wang have provided a strong basis to build on."

Dr. Tosun-Turgut was able to show that an MRI scan of brain structure and functionality (diffusion tensor imaging) and Unified Parkinson's Disease Rating Scale III (motor examination) total score at baseline were the best factors for determining an accurate Parkinson's diagnosis. "Parkinson's is a highly variable disease, which hinders clinicians' ability to give patients a clear prognosis and researchers' ability to efficiently measure the impact of treatments on the disease process," said Dr. Tosun-Turgut. "Identifying early clinical markers of rate of progression can benefit clinical care and testing of new therapies."

Learn more about this award at the Michael J Fox Foundation and PPMI