Design and Rationale for the Use of Magnetic Resonance Imaging Biomarkers to Predict Diabetes after Acute Pancreatitis in the D iabetes RE lated to A cute Pancreatitis and Its M echanisms Study: From the Type 1 Diabetes in Acute Pancreatitis Consortium

Type 1 Diabetes in Acute Pancreatitis Consortium (T1DAPC)

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)586-592
Number of pages7
JournalPancreas
Volume51
Issue number6
DOIs
StatePublished - Jul 1 2022

Keywords

  • 3D - three-dimensional
  • ACL - Artificial Intelligence Core Lab
  • AI - artificial intelligence
  • AP - acute pancreatitis
  • CBD - common bile duct
  • CIAL - Core Image Analysis Lab
  • CT
  • CT - computed tomography
  • DCE MRI - dynamic contrast-enhanced MRI
  • DL - deep learning
  • DM - diabetes mellitus
  • DREAM - Diabetes RElated to Acute pancreatitis and its Mechanisms
  • DWI - diffusion-weighted imaging
  • EPD - exocrine pancreas dysfunction
  • IMMINENT - Imaging Morphology of Pancreas in Diabetic Patients Following Acute Pancreatitis
  • IVIM - intravoxel incoherent motion
  • MRCP - MR cholangiopancreatography
  • MRI
  • MRI - magnetic resonance imaging
  • Pre-DM - prediabetes
  • SFTP - secure file transfer protocol
  • SIR - signal intensity ratio
  • SegCaps - deep capsule-based segmentation networks
  • T1D - type 1 diabetes mellitus
  • T1DAPC - Type 1 Diabetes in Acute Pancreatitis Consortium
  • T2D - type 2 diabetes mellitus
  • artificial intelligence
  • eGFR - estimated glomerular filtration rate
  • pancreas
  • perfusion
  • volume

ASJC Scopus subject areas

  • Endocrinology
  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Hepatology

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