Radiomics analysis of pancreas based on dual-energy computed tomography for the detection of type 2 diabetes mellitus.

Objective: To utilize radiomics analysis on dual-energy CT images of the pancreas to establish a quantitative imaging biomarker for type 2 diabetes mellitus.

Materials And Methods: In this retrospective study, 78 participants (45 with type 2 diabetes mellitus, 33 without) underwent a dual energy CT exam. Pancreas regions were segmented automatically using a deep learning algorithm.

Pancreatic fat fraction in dual-energy computed tomography as a potential quantitative parameter in the detection of type 2 diabetes mellitus.

Purpose: To investigate the clinical value of measuring pancreatic fat fraction using dual-energy computed tomography (DECT) in association with type 2 diabetes mellitus (T2DM).

Materials And Methods: This retrospective study included patients who underwent abdominal DECT between September 2021 and July 2022. The fat fractions in the head, body, and tail of the pancreas were calculated using fat maps generated from unenhanced DECT images, and CT values were measured at the same locations.