This core component of the Diabetes RElated to Acute pancreatitis and its Mechanisms (DREAM) study will examine the hypothesis that advanced magnetic resonance imaging (MRI) techniques can reflect underlying pathophysiologic changes and provide imaging biomarkers that predict diabetes mellitus (DM) after acute pancreatitis (AP). A subset of participants in the DREAM study will enroll and undergo serial MRI examinations using a specific research protocol. The aim of the study is to differentiate at-risk individuals from those who remain euglycemic by identifying parenchymal features after AP. Performing longitudinal MRI will enable us to observe and understand the natural history of post-AP DM. We will compare MRI parameters obtained by interrogating tissue properties in euglycemic, prediabetic, and incident diabetes subjects and correlate them with metabolic, genetic, and immunological phenotypes. Differentiating imaging parameters will be combined to develop a quantitative composite risk score. This composite risk score will potentially have the ability to monitor the risk of DM in clinical practice or trials. We will use artificial intelligence, specifically deep learning, algorithms to optimize the predictive ability of MRI. In addition to the research MRI, the DREAM study will also correlate clinical computed tomography and MRI scans with DM development.
Tirkes Temel, Chinchilli Vernon M, Bagci Ulas, Parker Jason G, Zhao Xuandong, Dasyam Anil K, Feranec Nicholas, Grajo Joseph R, Shah Zarine K, Poullos Peter D, Spilseth Benjamin, Zaheer Atif, Xie Karen L, Wachsman Ashley M, Campbell-Thompson Martha, Conwell Darwin L, Fogel Evan L, Forsmark Christopher E, Hart Phil A, Pandol Stephen J, Park Walter G, Pratley Richard E, Yazici Cemal, Laughlin Maren R, Andersen Dana K, Serrano Jose, Bellin Melena D, Yadav Dhiraj