Measurement of adipose body composition using an artificial intelligence-based CT Protocol and its association with severe acute pancreatitis in hospitalized patients.
Authors
Affiliations (8)
Affiliations (8)
- Division of Gastroenterology and Hepatology, University of Washington, Seattle, WA, USA; Division of Medicine, Mayo Clinic, Jacksonville, FL, USA.
- Division of Medicine, Mayo Clinic, Jacksonville, FL, USA.
- Division of Internal Medicine, Indiana University, Indianapolis, IN, USA.
- Division of Radiology, Mayo Clinic, Rochester, MN, USA.
- Digital Innovation Lab, Mayo Clinic, Jacksonville, FL, USA.
- Division of Cancer Biology, Mayo Clinic, Jacksonville, FL, USA.
- Division of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, FL, USA.
- Division of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, FL, USA. Electronic address: [email protected].
Abstract
The clinical utility of body composition in predicting the severity of acute pancreatitis (AP) remains unclear. We aimed to measure body composition using artificial intelligence (AI) to predict severe AP in hospitalized patients. We performed a retrospective study of patients hospitalized with AP at three tertiary care centers in 2018. Patients with computer tomography (CT) imaging of the abdomen at admission were included. A fully automated and validated abdominal segmentation algorithm was used for body composition analysis. The primary outcome was severe AP, defined as having persistent single- or multi-organ failure as per the revised Atlanta classification. 352 patients were included. Severe AP occurred in 35 patients (9.9%). In multivariable analysis, adjusting for male sex and first episode of AP, intermuscular adipose tissue (IMAT) was associated with severe AP, OR = 1.06 per 5 cm<sup>2</sup>, p = 0.0207. Subcutaneous adipose tissue (SAT) area approached significance, OR = 1.05, p = 0.17. Neither visceral adipose tissue (VAT) nor skeletal muscle (SM) was associated with severe AP. In obese patients, a higher SM was associated with severe AP in unadjusted analysis (86.7 vs 75.1 and 70.3 cm<sup>2</sup> in moderate and mild, respectively p = 0.009). In this multi-site retrospective study using AI to measure body composition, we found elevated IMAT to be associated with severe AP. Although SAT was non-significant for severe AP, it approached statistical significance. Neither VAT nor SM were significant. Further research in larger prospective studies may be beneficial.