Abstract

Introduction: Intermuscular adipose tissue (IMAT) reflects skeletal muscle quality and is associated with inflammation, a key determinant in cardiometabolic disease. Coronary flow reserve (CFR), a marker of coronary microvascular dysfunction (CMD), is independently associated with BMI, inflammation and risk of heart failure, myocardial infarction and death. Using a novel neural networks algorithm for body composition analysis, we sought to investigate the relationship between skeletal muscle quality, CMD and cardiovascular outcomes. Methods: Consecutive patients (N=669) undergoing evaluation for CAD with cardiac stress PET demonstrating normal perfusion and preserved LVEF were followed over median 6 years for events (MACE), including death and hospitalization for myocardial infarction or heart failure. CFR was calculated as the stress/rest myocardial blood flow ratio. Subcutaneous fat (SAT) and IMAT areas (cm 2 ) were obtained from PET attenuation correction CTs using a fully automated algorithm validated by manual segmentation at T10 and T12 levels, respectively. Results: Median age was 63 years, 70% were female and 46% nonwhite. Nearly half of patients were obese (46% with BMI 30-61) and BMI correlated closely with SAT and IMAT (r=0.8 and 0.7, respectively, p<0.001). Independent of age, sex, race, BMI, LVEF and hypertension, CFR was associated with IMAT (β -0.10, p=0.047). In adjusted analyses, both CFR and increased IMAT were independently associated with MACE [HR 1.6 (1.1-2.4) per -1U CFR and 1.5 (1.2-1.7) per +10 cm 2 IMAT, p≤0.01]. Patients with both CMD and poor muscle quality demonstrated highest risk of MACE (adjusted p<0.02). Conclusion: Increased intermuscular fat is associated with CMD and adverse cardiovascular outcomes independently of BMI and traditional risk factors. Combined assessment of skeletal muscle quality and coronary microvascular function may help to redefine at-risk cardiometabolic phenotypes.

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