New Imaging Biomarker of Coronary Inflammation Shows Prognostic Value Exceeding All Current Noninvasive Measures

Perivascular fat attenuation index could transform primary and secondary prevention

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A novel imaging biomarker that quantifies perivascular fat has been found to predict all-cause and cardiac mortality above and beyond clinical risk factors and current coronary CT interpretation methods. So finds a new study published in The Lancet by UK researchers at the University of Oxford working with colleagues in Germany and at Cleveland Clinic.

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High values of the biomarker — known as the perivascular fat attenuation index (FAI) — around the right coronary artery effectively identified individuals at risk of death in two large, independent and substantially different patient cohorts: a derivation cohort in Erlangen, Germany, and a validation cohort at Cleveland Clinic.

“The perivascular fat attenuation index is the first noninvasive biomarker of coronary inflammation measured by traditional coronary CT angiography,” says co-first author Milind Desai, MD, Professor of Medicine at Cleveland Clinic Lerner College of Medicine and a Cleveland Clinic cardiologist. “Our study validates the prognostic role of this index over and above the presence of coronary stenosis or calcification. We now have, for the first time, a biomarker derived from a fairly routine imaging study that measures residual cardiovascular risk with independent and incremental value over modern risk scores and other noninvasive tests. This could have transformative effects on primary and secondary prevention.”

Homing in on signals in perivascular fat

The investigation, known as the Cardiovascular Risk Prediction using Computed Tomography (CRISP-CT) study, was also reported as a late-breaking presentation at the European Society of Cardiology Congress 2018. It builds on recent work by the Oxford researchers showing that coronary artery inflammation inhibits adipogenesis in adjacent perivascular fat. Specifically, signals released from the inflamed coronary artery spread to perivascular adipose tissue, impeding local adipogenesis.

The researchers developed the perivascular FAI as an imaging biomarker to quantify inflammation-induced changes in perivascular fat, enabling early detection of coronary inflammation via routine coronary CT angiography. But the index’s utility for clinical risk stratification was uncertain, prompting the CRISP-CT study.

“We hypothesized that the perivascular FAI could predict future adverse events among patients undergoing coronary CT angiography — independent of the extent of coronary stenosis or other components of risk scores — and thereby flag high-risk patients who stand to benefit from more aggressive therapeutic management,” Dr. Desai explains.

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Similar findings in two large cohorts

To test this hypothesis, the researchers prospectively collected data from the two cohorts of consecutive patients undergoing coronary CT angiography — 1,872 patients in Germany from 2005 to 2009 (derivation cohort) and 2,040 patients at Cleveland Clinic from 2008 to 2016 (validation cohort). Median patient age in the cohorts was 62 and 53 years, respectively.

Perivascular fat attenuation was mapped around the three major coronary arteries — proximal right, left anterior descending and left circumflex. The prognostic value of the perivascular FAI was assessed for all-cause and cardiac mortality in multivariate regression models. Median follow-up was 72 months in the derivation cohort and 54 months in the validation cohort.

In each cohort, 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 one another. In view of this, the researchers used the perivascular FAI value around the right coronary artery as a representative marker of global coronary inflammation (hazard ratio [HR] for cardiac mortality of 2.15 [95% CI, 1.33-3.48] in the derivation cohort and 2.06 [95% CI, 1.50-2.83] in the validation cohort).

Further analysis showed that the optimal perivascular FAI cutoff in the derivation cohort was –70.1 Hounsfield units (HU) or higher (HR = 9.04 [95% CI, 3.35-24.40] for cardiac mortality and HR = 2.55 [95% CI, 1.65-3.92] for all-cause mortality). This cutoff value was confirmed in the validation cohort (HR = 5.62 [95% CI, 2.90-10.88] for cardiac mortality and HR = 3.69 [95% CI, 2.26-6.02] for all-cause mortality).

“Among patients undergoing coronary CT angiography, a perivascular FAI cutoff of –70.1 HU or higher identified those at a fivefold to ninefold elevated adjusted risk for cardiac death,” observes Dr. Desai. “This association remained robust after appropriate sensitivity and subgroup analyses. Most notably, the perivascular FAI significantly improved risk discrimination in both cohorts beyond current risk models.”

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Implications for primary and secondary prevention

Dr. Desai and his co-investigators note that their findings are particularly important because half of myocardial infarctions occur in the absence of substantial coronary stenosis and most coronary CT angiograms do not reveal relevant coronary atherosclerosis.

“The perivascular FAI identifies patients who are at risk due to atherosclerotic plaques that may be minor but are highly inflamed or unstable,” says Dr. Desai. “These are patients who might not get flagged otherwise. This biomarker could help guide early deployment of intensive measures of primary prevention.”

The findings also suggest that routine coronary CT angiography could potentially help identify the residual inflammatory risk that’s captured by the perivascular FAI, he adds. “Future studies are justified to explore whether targeting this marker by intensifying existing therapies or developing newer therapies could help modify risk of future coronary events. Such trials could confirm whether the perivascular FAI is the highly sought noninvasive biomarker to guide personalized medicine in this secondary prevention setting.

“More importantly,” he concludes, “it demonstrates the value of cross-continent collaboration to develop and validate newer technologies.”

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