Diffusion weighted MRI and neutrophil lymphocyte ratio non-invasively predict infection in pancreatic necrosis: a

Rommel Sandhyav1,2, Nihar Mohapatra2, Nikhil Agrawal2,3

  • 1Department of HPB Surgery and Liver Transplantation, Aster RV Hospital, Bangalore, -560078, India.

ANZ Journal of Surgery
|November 5, 2024
PubMed
Abstract

Insights

Infected pancreatic necrosis (IPN) in acute pancreatitis (AP) can be predicted non-invasively using diffusion-weighted MRI (DW-MRI) and neutrophil-lymphocyte ratio (NLR). These tools can help determine the need for intervention in AP patients.

Area of Science:

  • Radiology
  • Gastroenterology
  • Medical Diagnostics

Background:

  • Infected pancreatic necrosis (IPN) significantly increases mortality in acute pancreatitis (AP).
  • Accurate and timely diagnosis of IPN is crucial for guiding appropriate clinical management.
  • Non-invasive diagnostic methods are needed to avoid invasive procedures in AP patients.

Purpose of the Study:

  • To evaluate diffusion-weighted magnetic resonance imaging (DW-MRI) and clinico-laboratory parameters as non-invasive predictors of IPN.
  • To assess the diagnostic accuracy of DW-MRI and neutrophil-lymphocyte ratio (NLR) in identifying IPN.

Main Methods:

  • Prospective study involving patients with acute pancreatitis.
  • Diffusion restriction (DR) on DW-MRI and various clinico-laboratory parameters were assessed.
  • Statistical analyses, including univariate, multivariate, and ROC curve analyses, were performed.

Main Results:

  • Multivariate analysis identified DR on DW-MRI and NLR as significant independent predictors of IPN.
  • DW-MRI demonstrated high sensitivity (94.1%) and specificity (78.6%) for IPN prediction.
  • NLR showed an area under the ROC curve of 0.85, with a best cutoff >3.5.

Conclusions:

  • DW-MRI and NLR are effective non-invasive tools for predicting IPN in acute pancreatitis.
  • These methods can aid clinicians in deciding the necessity of interventions for AP.
  • Non-invasive prediction of IPN can optimize patient management and potentially reduce mortality.