Deep Learning-Based Adrenal Gland Volumetry for the Prediction of Diabetes.

ABSTRACT:

Backgruound

The long-term association between adrenal gland volume (AGV) and type 2 diabetes (T2D) remains unclear. We aimed to determine the association between deep learning-based AGV and current glycemic status and incident T2D.

Methods

In this observational study, adults who underwent abdominopelvic computed tomography (CT) for health checkups (2011-2012), but had no adrenal nodules, were included. AGV was measured from CT images using a three-dimensional nnU-Net deep learning algorithm. We assessed the association between AGV and T2D using a cross-sectional and longitudinal design.

Results

We used 500 CT scans (median age, 52.3 years; 253 men) for model development and a Multi-Atlas Labeling Beyond the Cranial Vault dataset for external testing. A clinical cohort

SUBMITTER: Ku EJ 

PROVIDER: S-EPMC12765888 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature