Data Coordinating Center for the Type 1 Diabetes in Acute Pancreatitis Consortium

急性胰腺炎联盟 1 型糖尿病数据协调中心

• 批准号: 10471067
• 负责人: Vernon M Chinchilli
• 金额: $ 176.91万
• 依托单位: PENNSYLVANIA STATE UNIV HERSHEY MED CTR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-17 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10471067
• 关键词: 3-Dimensional; Agreement; Artificial Intelligence; Atrophic; Biological Markers; Certification; Clinical Trials; Collection; Complication; Data; Data Analyses; Data Collection; Data Coordinating Center; Diabetes Mellitus; Early Diagnosis; Eligibility Determination; Endocrinologist; Enrollment; Evaluation; Evolution; Exocrine pancreatic insufficiency; Eye; Fatty acid glycerol esters; Funding; Gastroenterologist; Goals; Human; Image; Image Analysis; Imaging Techniques; Individual; Infiltration; Institutional Review Boards; Insulin-Dependent Diabetes Mellitus; Knowledge; Laboratories; Location; Longitudinal Studies; Magnetic Resonance Imaging; Manuscripts; Measurement; Measures; Metabolic; Metabolic dysfunction; Monitor; Morphology; National Institute of Diabetes and Digestive and Kidney Diseases; Natural History; Pancreas; Pancreatic Diseases; Participant; Pathogenesis; Patients; Perfusion; Persons; Phenotype; Policies; Population; Prediabetes syndrome; Preparation; Process; Prospective Studies; Protocols documentation; Psoas Muscles; Publications; Reporting; Research Design; Risk; Risk Assessment; Safety; Sample Size; Serial Magnetic Resonance Imaging; Services; Shapes; Signal Transduction; Staging; Standardization; Statistical Data Interpretation; Testing; Texture; Training; Visit; acute pancreatitis; arm; clinical center; clinical practice; cyber security; data exchange; data management; deep learning algorithm; diabetic patient; experience; extracellular; follow-up; image archival system; image reconstruction; imaging biomarker; non-invasive imaging; pancreas imaging; radiologist; risk stratification; sarcopenia; tool

PROJECT SUMMARY / ABSTRACT According to recent reports, pancreatogenic DM, a known complication of acute pancreatitis, may occur more frequently than previously recognized. Currently, limited data exist on well-phenotyped post-AP subjects from prospective studies to confirm this information. The Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC) was formed in 2020 to fulfill this knowledge gap (RFA-DK-19-023). The primary longitudinal study of the T1DAPC is the DREAM study which is funded and will begin enrolling patients in September 2021. The IMMINENT study is being proposed as the imaging biomarker arm of the DREAM study. Patients who experienced AP will enroll in the DREAM study and a subset of those participants will enroll in the IMMINENT study to have serial MRI examinations at 3, 12, 24 and 33 months. Preliminary data suggest that certain features on MRI not currently used in clinical practice can be useful in risk the assessment of DM. The hypothesis of the IMMINENT is that by identifying parenchymal changes in post-AP patients, MR imaging can differentiate at-risk individuals from those who will remain euglycemic. To achieve this goal, we will use several quantitative MR imaging techniques to interrogate the parenchyma. In addition to the advanced MRI analysis, we will use artificial intelligence and deep learning algorithms to detect changes that are not visible to the human eye. Our purpose is to observe and understand the natural history of DM after AP and demonstrate that MR imaging can reflect underlying pathophysiologic changes and serve as a biomarker of DM. We believe data generated from IMMINENT will enhance our understanding of the pathogenesis of post-AP DM. If successful, we will develop a quantitative composite risk score using useful MRI features. This composite risk score can be used for monitoring the risk of metabolic dysfunction in practice or clinical trials. As part of the T1DAPC (a multicenter collaborative network), we propose an excellent opportunity to investigate the post-AP DM by incorporating dedicated pancreas radiologists, gastroenterologists, endocrinologists, a data coordinating center, MR image analysis, and AI labs.

项目摘要/摘要