2650-P: Multiorgan Magnetic Resonance–Based Imaging Improves Risk Stratification and Supports Treatment Allocation in Individuals with Clinical Obesity

Introduction and Objective: BMI-based criteria may not be sufficiently sensitive to identify people at-risk of poor cardiometabolic outcomes. We evaluated whether multi-organ imaging could improve prediction of obesity-related health outcomes and inform treatment allocation. Methods: We tested associations between 14 imaging-derived phenotypes and incident type 2 diabetes (T2D), cardiovascular (CV) and liver events (LRE), and mortality. Associations between clinical measures in standard of care (BMI ≥30 kg/m2, adiposity-based preclinical and clinical obesity, T2D, hypertension, dyslipidaemia) were also examined. We modelled the impact of risk-guided treatment from published outcome data, using tirzepatide as an example. Results: 23,087 UK Biobank participants were included (median age 64 years, 50% female, 18% BMI ≥30 kg/m2, 30% had preclinical obesity and 31% had clinical obesity). The median follow-up time was 4.3 years.Clinical obesity, elevated pancreatic and liver fat and elevated iron-corrected T1 (cT1, a measure of liver disease activity and severity) were associated with an increased risk of incident T2D (adjusted Cox proportional hazard ratio, HR, 27, 95% CI 16-47).Addition of information from multi-organ MRI improved stratification of individuals at highest risk of any incident hospitalisation (HR 6.3, 2.0-19) compared to clinical measures alone (HR 2.5, 2.0-3.2).Elevated liver cT1, reduced LVEF, and low skeletal muscle were together associated with increased all-cause mortality (HR 4.4, 1.1-18.0). Adding MRI measurements of LVEF and cT1, to obesity status for guiding allocation of tirzepatide treatment, reduced the number needed to treat to prevent one death from 159 to 20. Conclusion: Quantitative multi-organ MRI, of the liver, pancreas, heart and body composition, could refine stratification of individuals with obesity to predict new-onset diabetes, and provides a framework for identifying individuals likely to benefit most from obesity treatment.

Duke Scholars

Author Amreen Dinani Medicine, Gastroenterology