Detection of Coronary Inflammation Using CT: The CRISP-CT Study


It has long been known that atherosclerosis is an inflammatory disease.1 The recent CANTOS (Canakinumab Anti-Inflammatory Thrombosis Outcomes Study) provided the most compelling evidence to date on the inflammatory hypothesis of atherothrombosis, highlighting the dual diagnostic and therapeutic benefit of detecting and targeting high levels of residual systemic inflammation in secondary cardiovascular prevention.2,3 However, circulating inflammatory biomarkers such as high-sensitivity C-reactive protein may lack specificity for vascular inflammation, underlining the need for more targeted approaches in identifying vascular inflammation at the earliest stages of atherosclerosis. Positron emission tomography (PET) radiotracers, such as 18F-NaF (sodium fluoride) and 68Ga-dotatate have been developed to address this unmet need.4,5 However, PET imaging has higher radiation exposure than standard coronary computed tomography angiography (CCTA), increased costs, and limited availability in many clinical settings. Developing new approaches to extract functional information from established first-line diagnostic tests such as CCTA would therefore be of great clinical value.

Perivascular Adipose Tissue and Atherosclerosis

Perivascular adipose tissue (PVAT) describes the layer of fat that is found attached to the human arteries (e.g., coronary tree) and often forms a continuous entity with the adventitial layers of these vessels.6 Far from being an innocent bystander, an expanding body of evidence has now identified PVAT as a critical regulator of vascular function (e.g., tone, inflammation, redox state, and cell migration) in both homeostasis and disease.7-9 Our recent work has revealed the existence of a bidirectional interplay between the arterial wall and its PVAT. For instance, PVAT can sense increased levels of oxidative stress in the adjacent coronary artery and respond by modifying its secretory profile (inside-to-outside signaling).10,11 Moreover, as we have recently described, inflammatory molecules from the diseased coronary arteries may also diffuse into the surrounding PVAT, where they block the ability of perivascular adipocytes to grow and accumulate intracellular lipids.12 Taken together, these observations suggest that PVAT may function as a sensor of vascular biology.

Perivascular Fat Attenuation Index: From Bench to Bedside

In our recent work, we hypothesized that coronary artery inflammation induces a shift of the composition of the adjacent PVAT from the lipid to the aqueous phase. This creates a three-dimensional shift of PVAT's attenuation in CCTA. We then used a radiotranscriptomic approach, in which we scanned 1,400 adipose tissue biopsies and generated a new biomarker, the Fat Attenuation Index (FAI), that captures changes in CT attenuation driven by inflammation-induced lipolysis within the adipose tissue.12 In addition, in paired biopsies from PVAT attached to the coronary artery and non-PVAT found ~20 mm away from the vascular wall, we confirmed the existence of an in vivo perivascular gradient in adipocyte size and lipid content in patients with advanced atherosclerosis.12 In order to link the new observations with coronary inflammation, we developed a new analysis algorithm using traditional CCTA (namely the perivascular FAI) that captures this perivascular gradient in PVAT composition as a spatial shift in perivascular CT attenuation (Figure 1).6,12 When applied in a cohort of 273 CCTA scans, patients with coronary artery disease (CAD) had a steeper perivascular attenuation gradient compared with healthy individuals, which was captured by perivascular FAI.12 In further analyses, we observed that culprit lesions in patients with acute myocardial infarction were associated with locally increased perivascular FAI compared with proximal or distal reference segments, or stable lesions from the same patients and patients with stable CAD.12 Interestingly, perivascular FAI was found to be dynamic, decreasing significantly around the culprit lesions when measured again 5 weeks after the index event.12

Figure 1: PVAT as a Sensor of Coronary Inflammation: The Perivascular FAI

Figure 1
In the presence of a local pro-inflammatory environment, PVAT undergoes phenotypic changes (increased lipolysis, smaller adipocyte size) that can be captured as changes in PVAT attenuation using the computed tomography (CT) derived perivascular FAI. Reproduced with permission from Antoniades et al.19

The CRISP-CT Study

Having established that perivascular FAI may function as an imaging biomarker of coronary inflammation and atherosclerosis, we sought to explore the potential prognostic value of this method in real-life populations undergoing clinically indicated CCTA. The CRISP-CT (Cardiovascular Risk Prediction Using Computed Tomography) study was designed as a post-hoc analysis of prospectively collected data from two large cardiac CT centers in Europe (Erlangen University Hospital in Germany; n = 1,872 patients) and the United States (Cleveland Clinic in Ohio; n = 2,040 patients).13 Perivascular FAI mapping was performed around standardized reference segments in the right coronary artery (RCA), left anterior descending artery (LAD), and left circumflex artery (LCX) (Figure 2). All patients were followed for adverse clinical events, including all-cause and cardiac-specific mortality. The primary objective of the study was to explore the prognostic value of perivascular FAI mapping for adverse clinical events independent of traditional risk factors and the standard interpretation of CCTA scans, which includes the presence and extent of coronary atherosclerosis and coronary calcium and presence of high-risk plaque features.14

Figure 2: Perivascular FAI Mapping

Figure 2
An example of perivascular FAI mapping around the proximal RCA, LAD, and LCX. Reproduced with permission from Oikonomou et al.13

Over a median follow-up of 60 and 48 months respectively, elevated perivascular FAI (fully weighted for a number of technical, anatomical, and biological characteristics) around the right coronary and left anterior descending arteries was independently associated with a higher risk of all-cause and cardiac mortality in both cohorts.13 An optimal cut-point was adjudicated at -70.1 Hounsfield Unites (HU), with higher FAI values linked to an almost ninefold and fivefold higher risk of cardiac mortality in the derivation and validation cohorts, respectively (Figure 3).13 Notably, perivascular FAI mapping significantly improved the prognostic performance of a baseline model consisting of traditional cardiovascular risk factors and comprehensive CCTA assessment. Furthermore, perivascular FAI retained its prognostic value in both patients with and without CAD at baseline, suggesting that it may carry value in both primary and secondary prevention.13

Figure 3: Perivascular FAI and All-Cause/Cardiac Mortality in the CRISP-CT Study

Figure 3
Prognostic value of high (versus low) perivascular FAI for all-cause and cardiac mortality in the derivation (A-B) and validation (C-D) cohorts of the CRISP-CT study. Reproduced with permission from Oikonomou et al.13

Perivascular Fat Attenuation as a New Metric in CCTA

Our findings have introduced a new dimension in the interpretation of CCTA scans. By dissociating risk prediction from the simple presence and extent of atherosclerosis, we have introduced a functional biomarker that exploits the unique ability of PVAT to sense its environment, thus providing information about coronary biology even in the absence of visible atherosclerosis. This could revolutionize the field of CCTA imaging, with several other groups now focusing on PVAT as a source of diagnostic and prognostic biomarkers. Hedgire et al. have described macroscopic perivascular fat stranding around areas of acute plaque rupture and spontaneous coronary artery dissection, possibly flagging the effects of a local, intense pro-inflammatory environment.15 In an independent study, Goeller et al. have replicated the basic principle behind our findings, showing that unstable coronary lesions are associated with higher PVAT attenuation (or radiodensity) compared with stable lesions.16 More notably, Kwiecinski et al. have demonstrated a strong positive association between 18F-NaF uptake, a PET radiotracer of micro-calcification and vascular inflammation, and PVAT radiodensity on CCTA imaging (r = 0.68, p < 0.001),17 thus confirming our previous observations on the strong links between PVAT phenotyping and coronary inflammation.12 However, because FAI is a quantitative metric derived from routine CCTA imaging, special care should be taken to account for several clinical and technical variables that may confound the obtained values, including but not limited to the background adipocyte size, scanning settings, and coronary segment analysed.18,19 Appropriate adjustments should be made, and further research is currently underway to provide a reference map for values obtained across different protocols and scanners.

Of note, the clinical potential of perivascular FAI mapping has been highlighted in the most recent recommendations on noninvasive coronary imaging with cardiac computed tomography and magnetic resonance imaging.20 Similar to the introduction of high-risk plaque features into the standardized reporting guidelines for CCTA,21 perivascular FAI could provide an additional, "functional" dimension in CCTA reporting, thus maximizing the diagnostic and prognostic yield of one of the most commonly used noninvasive diagnostic tests in cardiovascular imaging.22,23


In summary, we have described the successful clinical translation and application of a novel CCTA-derived metric of coronary inflammation, the perivascular FAI. By capturing the effects of coronary inflammation on the microstructure of the adjacent PVAT, perivascular FAI provides an early marker of coronary inflammation and atherosclerosis, which is applicable even in the absence of visible coronary lesions. In an analysis of 3,912 CCTA scans from 2 independent and diverse cohorts in the CRISP-CT study, perivascular FAI mapping showed incremental value for the prediction of adverse clinical events beyond traditional risk factors and CCTA indices. These findings highlight perivascular FAI as a new dimension in the interpretation of CCTA scans, which can pave the way toward a more personalized assessment of coronary health and guide the deployment of appropriate interventions in both primary and secondary cardiovascular prevention.


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Keywords: Angina, Stable, Coronary Artery Disease, C-Reactive Protein, Sodium Fluoride, Risk Factors, Lipolysis, Secondary Prevention, Prognosis, Lipids, Diagnostic Tests, Routine, Cardiovascular Diseases, Follow-Up Studies, Antibodies, Monoclonal, Coronary Artery Disease, Atherosclerosis, Coronary Vessel Anomalies, Positron-Emission Tomography, Adipose Tissue, Thrombosis, Adipocytes, Myocardial Infarction, Inflammation, Magnetic Resonance Imaging, Biopsy, Algorithms, Oxidation-Reduction, Oxidative Stress, Homeostasis, Cohort Studies

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