Evangelos Tzolos1, Michelle C Williams2, Priscilla McElhinney3, Andrew Lin3, Kajetan Grodecki3, Guadalupe Flores Tomasino3, Sebastien Cadet3, Jacek Kwiecinski4, Mhairi Doris1, Philip D Adamson1, Alastair J Moss1, Shirjel Alam1, Amanda Hunter1, Anoop S V Shah5, Nicholas L Mills1, Tania Pawade1, Chengjia Wang1, Jonathan R Weir-McCall6, Giles Roditi7, Edwin J R van Beek2, Leslee J Shaw8, Edward D Nicol9, Daniel S Berman3, Piotr J Slomka3, Marc R Dweck1, David E Newby1, Damini Dey10. 1. British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom. 2. British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging Facility, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom. 3. Departments of Imaging (Division of Nuclear Medicine), Medicine, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA. 4. Departments of Imaging (Division of Nuclear Medicine), Medicine, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland. 5. Department of Non-Communicable Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom. 6. Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom. 7. Institute of Clinical Sciences, University of Glasgow, United Kingdom. 8. Icahn School of Medicine, Mount Sinai, New York, USA. 9. Royal Brompton and Harefield NHS Foundation Trust Departments of Cardiology and Radiology, London, United Kingdom; National Heart and Lung Institute, Faculty of Medicine, Imperial College, London, United Kingdom. 10. Departments of Imaging (Division of Nuclear Medicine), Medicine, and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA. Electronic address: Damini.dey@cshs.org.
Abstract
BACKGROUND: Pericoronary adipose tissue (PCAT) attenuation and low-attenuation noncalcified plaque (LAP) burden can both predict outcomes. OBJECTIVES: This study sought to assess the relative and additive values of PCAT attenuation and LAP to predict future risk of myocardial infarction. METHODS: In a post hoc analysis of the multicenter SCOT-HEART (Scottish Computed Tomography of the Heart) trial, the authors investigated the relationships between the future risk of fatal or nonfatal myocardial infarction and PCAT attenuation measured from coronary computed tomography angiography (CTA) using multivariable Cox regression models including plaque burden, obstructive coronary disease, and cardiac risk score (incorporating age, sex, diabetes, smoking, hypertension, hyperlipidemia, and family history). RESULTS: In 1,697 evaluable participants (age: 58 ± 10 years), there were 37 myocardial infarctions after a median follow-up of 4.7 years. Mean PCAT was -76 ± 8 HU and median LAP burden was 4.20% (IQR: 0%-6.86%). PCAT attenuation of the right coronary artery (RCA) was predictive of myocardial infarction (HR: 1.55; P = 0.017, per 1 SD increment) with an optimum threshold of -70.5 HU (HR: 2.45; P = 0.01). In multivariable analysis, adding PCAT-RCA of ≥-70.5 HU to an LAP burden of >4% (the optimum threshold for future myocardial infarction; HR: 4.87; P < 0.0001) led to improved prediction of future myocardial infarction (HR: 11.7; P < 0.0001). LAP burden showed higher area under the curve compared to PCAT attenuation for the prediction of myocardial infarction (AUC = 0.71 [95% CI: 0.62-0.80] vs AUC = 0.64 [95% CI: 0.54-0.74]; P < 0.001), with increased area under the curve when the 2 metrics are combined (AUC = 0.75 [95% CI: 0.65-0.85]; P = 0.037). CONCLUSION: Coronary CTA-defined LAP burden and PCAT attenuation have marked and complementary predictive value for the risk of fatal or nonfatal myocardial infarction.
BACKGROUND: Pericoronary adipose tissue (PCAT) attenuation and low-attenuation noncalcified plaque (LAP) burden can both predict outcomes. OBJECTIVES: This study sought to assess the relative and additive values of PCAT attenuation and LAP to predict future risk of myocardial infarction. METHODS: In a post hoc analysis of the multicenter SCOT-HEART (Scottish Computed Tomography of the Heart) trial, the authors investigated the relationships between the future risk of fatal or nonfatal myocardial infarction and PCAT attenuation measured from coronary computed tomography angiography (CTA) using multivariable Cox regression models including plaque burden, obstructive coronary disease, and cardiac risk score (incorporating age, sex, diabetes, smoking, hypertension, hyperlipidemia, and family history). RESULTS: In 1,697 evaluable participants (age: 58 ± 10 years), there were 37 myocardial infarctions after a median follow-up of 4.7 years. Mean PCAT was -76 ± 8 HU and median LAP burden was 4.20% (IQR: 0%-6.86%). PCAT attenuation of the right coronary artery (RCA) was predictive of myocardial infarction (HR: 1.55; P = 0.017, per 1 SD increment) with an optimum threshold of -70.5 HU (HR: 2.45; P = 0.01). In multivariable analysis, adding PCAT-RCA of ≥-70.5 HU to an LAP burden of >4% (the optimum threshold for future myocardial infarction; HR: 4.87; P < 0.0001) led to improved prediction of future myocardial infarction (HR: 11.7; P < 0.0001). LAP burden showed higher area under the curve compared to PCAT attenuation for the prediction of myocardial infarction (AUC = 0.71 [95% CI: 0.62-0.80] vs AUC = 0.64 [95% CI: 0.54-0.74]; P < 0.001), with increased area under the curve when the 2 metrics are combined (AUC = 0.75 [95% CI: 0.65-0.85]; P = 0.037). CONCLUSION: Coronary CTA-defined LAP burden and PCAT attenuation have marked and complementary predictive value for the risk of fatal or nonfatal myocardial infarction.
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