Frontiers in Cardiovascular Medicine (Mar 2022)

Incremental Prognostic Value of Pericoronary Adipose Tissue Thickness Measured Using Cardiac Magnetic Resonance Imaging After Revascularization in Patients With ST-Elevation Myocardial Infarction

  • Yue Ma,
  • Quanmei Ma,
  • Xiaonan Wang,
  • Tongtong Yu,
  • Yuxue Dang,
  • Jin Shang,
  • Guangxiao Li,
  • Yang Hou

DOI
https://doi.org/10.3389/fcvm.2022.781402
Journal volume & issue
Vol. 9

Abstract

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Background and AimPericoronary adipose tissue (PCAT) reflects pericoronary inflammation and is associated with coronary artery disease. We aimed to identify the association between local PCTA thickness using cardiac magnetic resonance (CMR) and prognosis of patients with ST-elevation myocardial infarction (STEMI), and to investigate the incremental prognostic value of PCAT thickness in STEMI after reperfusion.MethodsA total of 245 patients with STEMI (mean age, 55.61 ± 10.52 years) who underwent CMR imaging within 1 week of percutaneous coronary intervention therapy and 35 matched controls (mean age, 53.89 ± 9.45 years) were enrolled. PCAT thickness indexed to body surface area at five locations, ventricular volume and function, infarct-related parameters, and global strain indices were evaluated using CMR. Associations between PCAT thickness index and 1-year major adverse cardiovascular events (MACE) after STEMI were calculated. The prognostic value of the standard model based on features of clinical and CMR and updated model including PACT thickness index were further assessed.ResultsPatients with MACE had a more significant increase in PCAT thickness index at superior interventricular groove (SIVGi) than patients without MACE. The SIVGi was significantly associated with left ventricular ejection fraction (LVEF), infarct size, and global deformation. SIVGi > 4.98 mm/m2 was an independent predictor of MACE (hazard ratio, 3.2; 95% CI: 1.6–6.38; p < 0.001). The updated model significantly improved the power of prediction and had better discrimination ability than that of the standard model for predicting 1-year MACE (areas under the ROC curve [AUC] = 0.8 [95% CI: 0.74–0.87] vs. AUC = 0.76 [95% CI: 0.68–0.83], p < 0.05; category-free net reclassification index [cfNRI] = 0.38 [95% CI: 0.1–0.53, p = 0.01]; integrated discrimination improvement [IDI] = 0.09 [95% CI: 0.01–0.18, p = 0.02]).ConclusionsThis study demonstrated SIVGi as an independent predictor conferred incremental value over standard model based on clinical and CMR factors in 1-year MACE predictions for STEMI.

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