Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data

Abstract

Background: Coronary artery inflammation inhibits adipogenesis in adjacent perivascular fat. A novel imaging biomarker-the perivascular fat attenuation index (FAI)-captures coronary inflammation by mapping spatial changes of perivascular fat attenuation on coronary computed tomography angiography (CTA). However, the ability of the perivascular FAI to predict clinical outcomes is unknown.

Methods: In the Cardiovascular RISk Prediction using Computed Tomography (CRISP-CT) study, we did a post-hoc analysis of outcome data gathered prospectively from two independent cohorts of consecutive patients undergoing coronary CTA in Erlangen, Germany (derivation cohort) and Cleveland, OH, USA (validation cohort). Perivascular fat attenuation mapping was done around the three major coronary arteries-the proximal right coronary artery, the left anterior descending artery, and the left circumflex artery. We assessed the prognostic value of perivascular fat attenuation mapping for all-cause and cardiac mortality in Cox regression models, adjusted for age, sex, cardiovascular risk factors, tube voltage, modified Duke coronary artery disease index, and number of coronary CTA-derived high-risk plaque features.

Findings: Between 2005 and 2009, 1872 participants in the derivation cohort underwent coronary CTA (median age 62 years [range 17-89]). Between 2008 and 2016, 2040 patients in the validation cohort had coronary CTA (median age 53 years [range 19-87]). Median follow-up was 72 months (range 51-109) in the derivation cohort and 54 months (range 4-105) in the validation cohort. In both cohorts, high perivascular FAI values around the proximal right coronary artery and left anterior descending artery (but not around the left circumflex artery) were predictive of all-cause and cardiac mortality and correlated strongly with each other. Therefore, the perivascular FAI measured around the right coronary artery was used as a representative biomarker of global coronary inflammation (for prediction of cardiac mortality, hazard ratio [HR] 2·15, 95% CI 1·33-3·48; p=0·0017 in the derivation cohort, and 2·06, 1·50-2·83; p<0·0001 in the validation cohort). The optimum cutoff for the perivascular FAI, above which there is a steep increase in cardiac mortality, was ascertained as -70·1 Hounsfield units (HU) or higher in the derivation cohort (HR 9·04, 95% CI 3·35-24·40; p<0·0001 for cardiac mortality; 2·55, 1·65-3·92; p<0·0001 for all-cause mortality). This cutoff was confirmed in the validation cohort (HR 5·62, 95% CI 2·90-10·88; p<0·0001 for cardiac mortality; 3·69, 2·26-6·02; p<0·0001 for all-cause mortality). Perivascular FAI improved risk discrimination in both cohorts, leading to significant reclassification for all-cause and cardiac mortality.

Interpretation: The perivascular FAI enhances cardiac risk prediction and restratification over and above current state-of-the-art assessment in coronary CTA by providing a quantitative measure of coronary inflammation. High perivascular FAI values (cutoff ≥-70·1 HU) are an indicator of increased cardiac mortality and, therefore, could guide early targeted primary prevention and intensive secondary prevention in patients.

Funding: British Heart Foundation, and the National Institute of Health Research Oxford Biomedical Research Centre.

Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1

Perivascular FAI analysis around epicardial coronary vessels (A) Perivascular FAI phenotyping of the proximal segments of all three major epicardial coronary vessels, with corresponding FAI colour maps. (B) Example of perivascular FAI phenotyping around the proximal RCA. Perivascular fat was defined as fat within a radial distance equal to the diameter (d) of the vessel. FAI=fat attenuation index. HU=Hounsfield unit. LAD=left anterior descending artery. LCx=left circumflex artery. RCA=right coronary artery.

Figure 2

Kaplan-Meier curves of all-cause mortality and cardiac mortality with high versus low perivascular FAI High values for the perivascular FAI were ≥–70·1 HU and low perivascular FAI values were

Figure 3

Incremental prognostic value of the perivascular FAI beyond current coronary CTA-based risk stratification Comparison of time-dependent ROC curves (at 6 years) and respective AUC of two nested models for discrimination of cardiac mortality in the (A) derivation and (B) validation cohorts. Model 1 represents the current state-of-the-art in risk assessment and consisted of age, sex, risk factors (hypertension, hypercholesterolaemia, diabetes mellitus, smoker status, epicardial adipose tissue volume), modified Duke coronary artery disease index, and number of high-risk plaque features on coronary CTA. Model 2 incorporates perivascular FAI values (≥–70·1 HU vs <–70·1 HU) into model 1. AUC=area under the curve. CTA=computed tomography angiography. FAI=fat attenuation index. HU=Hounsfield unit. ROC=receiver operating characteristic.

Figure 4

Subgroup analysis of the prognostic value of the perivascular FAI in patients with and without coronary artery disease Plots show adjusted HRs for high versus low perivascular FAI values (≥–70·1 HU vs <–70·1 HU) as a prognostic biomarker for (A) all-cause mortality and (B) cardiac mortality in different patient subgroups, with or without cardiac CTA-derived features of coronary artery disease. HRs are adjusted for age, sex, and epicardial adipose tissue volume. CTA=computed tomography angiography. FAI=fat attenuation index. HU=Hounsfield unit. HR=hazard ratio.