Risk Prediction Beyond Stenosis: What CT is Teaching Us About Coronary Atherosclerosis

Over the past decade, the cardiovascular community embarked on a journey to optimize noninvasive imaging of atherosclerotic cardiovascular disease with the eventual goal of translating into improved characterization of coronary artery disease (CAD) and subsequent risk stratification for adverse cardiac events. Such efforts have been spearheaded by technological advances and improved scanning methodologies during acquisition of coronary computed tomography angiography (CCTA). In this expert analysis, we discuss this extensive journey and, most importantly, emphasize what lessons CCTA has taught us about coronary atherosclerosis above and beyond the traditional measures of angiographic diameter stenosis, which thus far has been the go-to method for characterization of the severity and extent of CAD.

Is There Stenosis or Ischemia?

With the spatial resolution of current computed tomography (CT) scanners, advanced histological plaques (classification IV to VIII according to the Stary gradation1 for histological assessment of atherosclerosis) are reliably visualized, and only very early atherosclerotic lesions (Stary classification I and II) fall below the resolution of current-generation CT scanners.2 This high sensitivity for atherosclerosis detection has made CCTA a frequently used test to rule out CAD for diagnostic or prognostic purposes. When atherosclerosis further progresses, it can lead to stenosis formation with or without reductions in myocardial blood flow. It is at this stage of the evolution of CAD that existent noninvasive stress tests (such as myocardial perfusion imaging and stress echocardiography) are able to detect CAD. Initially, the detection of mild, non-obstructive CAD was deemed as clinically insignificant because only severely stenotic—and as a direct consequence, ischemia-provoking—CAD was an indication for revascularization to improve symptoms and/or prognosis.

The Importance of Atherosclerosis

Recent insights reveal that the identification of any atherosclerosis can impact outcomes, even if the severity of CAD does not meet the criteria for being categorized as obstructive based on diameter stenosis measures. Mortality rates adjusted for clinical risk are doubled in patients with a mild amount of coronary artery calcium (calcium score 11 to 100) compared with the complete absence of coronary calcification. Also, patients with extensive non-obstructive CAD demonstrate an impaired prognosis3 and may even have as many events as patients with obstructive CAD.4,5 For the prediction of CAD that is hemodynamically significant, on the other hand, quantitative measures obtained from CCTA have been shown to be as useful as and often superior to the conventional measure of diameter stenosis. For instance, aggregate plaque volume (calculated as all plaque volume summed from the coronary artery ostium to the distal portion of the lesion divided by the corresponding vessel volume) had better discrimination for the presence of physiologically significant CAD compared with the gold standard fractional flow reserve measurement, with a higher area under the curve (AUC) than diameter stenosis (AUC 0.85; 95% confidence interval, 0.74-0.97 vs. AUC 0.68; 95% confidence interval, 0.54-0.83).6

Besides volumetric measures of atherosclerosis, CCTA visualizes the whole coronary tree (including vessel wall and epicardial fat), which allows for assessment for plaque composition or specific high-risk markers that need more than luminography for elucidation. Automated plaque software packages allow quantification of whole heart atherosclerosis by accurate lumen and vessel wall annotation of the 17 coronary segments. Based on attenuation (thresholds are defined through ranges in Hounsfield Units), CT-identified plaque can be divided into calcified and non-calcified (fibrous, fibro-fatty, or low-attenuation) plaque.7 In addition, markers that are present in thin cap fibroatheromas (plaques vulnerable to causing future acute coronary syndrome [ACS] events) can be measured with CCTA, including positive remodeling and spotty calcification. Early prognostic studies have demonstrated the ability of high-risk plaque to predict mid-term likelihood of ACS. Among 4,423 patients undergoing CCTA due to known or suspected CAD, 88 ACS events occurred during 3.9 ± 2.4 years of follow-up.8 Of the patients with high-risk plaque, 16.3% developed ACS compared with 1.4% in the patients without high-risk plaque. In contrast, 5.5% of the patients with ≥70% stenosis developed ACS versus 2.1% in the patients without. Given the multitude of atherosclerotic features that consist of visual and quantitative measures, the clinically relevant question remains whether just any measure of plaque volume or burden is enough to risk stratify and subsequently tailor medical therapy, irrespective of qualitative measures of high-risk plaque as well as composition measures. To this end, Chang et al. performed a nested case-control study of patients who underwent CCTA, where 234 ACS cases had been 1:1 propensity matched to 234 controls based on cardiovascular risk factors and number of vessels with obstructive CAD.9 This matching procedure provided adequate power to investigate the independent value of quantitative plaque evaluation over overall plaque burden. Predictors for ACS beyond stenosis were maximal cross-sectional plaque burden, fibrofatty and necrotic core plaque volume, and the presence of high-risk plaque. Although increasing diameter stenosis portended higher risk, only 25% of the culprit precursors were obstructive, thus highlighting the importance of whole plaque evaluation.

Moreover, CCTA can be used to assess the implications of medical therapy on high-risk plaque features. Most recently, 80 patients were evaluated for the effect of low-dose colchicine therapy in addition to optimal medical therapy on low attenuation plaque volume after an ACS event.10 The study showed that colchicine therapy was significantly associated with greater reduction in low attenuation plaque volume in only a short period of time, which is a direct testament to the ability of CCTA to assess for evolution in plaque morphology and further improve our ability to assess incident risk.

To date, CCTA reporting is guided by assessment of per-patient maximal stenosis (0%, 1-24%, 25-49%, 50-69%, 70-99%, 100%) and the presence of high-risk plaque.11 The growth of evidence that a comprehensive quantitative assessment can improve identification of individuals at risk for several clinical outcomes beyond visual reads is essential in the era of personalized, yet precise, health care delivery.

However, for application into clinical practice, improved understanding of relevant cut-off values and further improvements in quantification software that require less manual adjustment are needed. Also, most evidence of improved risk stratification has been derived from observational data. Future prospective trials with treatment focused on adverse plaque characteristics need to be performed to assess impact on relevant clinical outcomes.


Since its introduction in the early 2000s for clinical use, CCTA has greatly advanced to the point that it is no longer considered an imaging modality just for the exclusion of high-grade coronary stenosis but is fast becoming a reliable noninvasive method for the identification and quantification of atherosclerotic plaque. As a consequence, CCTA is currently the only method that allows for whole-heart quantification and characterization of coronary atherosclerosis in a noninvasive manner. It has enabled us to thoroughly analyze individual coronary lesions—the primary disease process—rather than focusing on byproducts of CAD such as the conventional measures of stenosis severity (e.g., lumen narrowing) and ischemia (e.g., inadequate blood supply). We are now able to detect atherosclerotic plaque characteristics as well as quantitative measures that are associated with higher future risk well beyond the occurrence of myocardial ischemia, which is the threshold at which current functional measures are able to detect the presence of CAD. This evidence supports the establishment of detailed coronary plaque assessment as the benchmark for evaluation of all patients with suspected CAD.

Figure 1: Detailed Quantitative Evaluation of Left Anterior Descending Lesion With High-Risk Features

Figure 1
Figure shows an extensive quantitative evaluation of a lesion in the proximal left anterior descending coronary artery with low attenuation plaque, spotty calcification, and positive remodeling (orange arrows).


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  2. Leschka S, Seitun S, Dettmer M, et al. Ex vivo evaluation of coronary atherosclerotic plaques: characterization with dual-source CT in comparison with histopathology. J Cardiovasc Comput Tomogr 2010;4:301-8.
  3. Lin FY, Shaw LJ, Dunning AM, et al. Mortality risk in symptomatic patients with nonobstructive coronary artery disease: a prospective 2-center study of 2,583 patients undergoing 64-detector row coronary computed tomographic angiography. J Am Coll Cardiol 2011;58:510-9.
  4. Budoff MJ, Shaw LJ, Liu ST, et al. Long-term prognosis associated with coronary calcification: observations from a registry of 25,253 patients. J Am Coll Cardiol 2007;49:1860-70.
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  6. Nakazato R, Shalev A, Doh JH, et al. Aggregate plaque volume by coronary computed tomography angiography is superior and incremental to luminal narrowing for diagnosis of ischemic lesions of intermediate stenosis severity. J Am Coll Cardiol 2013;62:460-7.
  7. Park HB, Lee BK, Shin S, et al. Clinical Feasibility of 3D Automated Coronary Atherosclerotic Plaque Quantification Algorithm on Coronary Computed Tomography Angiography: Comparison with Intravascular Ultrasound. Eur Radiol 2015;25:3073-83.
  8. Motoyama S, Ito H, Sarai M, et al. Plaque Characterization by Coronary Computed Tomography Angiography and the Likelihood of Acute Coronary Events in Mid-Term Follow-Up. J Am Coll Cardiol 2015;66:337-46.
  9. Chang HJ, Lin FY, Lee SE, et al. Coronary Atherosclerotic Precursors of Acute Coronary Syndromes. J Am Coll Cardiol 2018;71:2511-22.
  10. Vaidya K, Arnott C, Martínez GJ, et al. Colchicine Therapy and Plaque Stabilization in Patients With Acute Coronary Syndrome: A CT Coronary Angiography Study. JACC Cardiovasc Imaging 2018;11:305-16.
  11. Cury RC, Abbara S, Achenbach S, et al. Coronary Artery Disease - Reporting and Data System (CAD-RADS): An Expert Consensus Document of SCCT, ACR and NASCI: Endorsed by the ACC. JACC Cardiovasc Imaging 2016;9:1099-113.

Clinical Topics: Acute Coronary Syndromes, Invasive Cardiovascular Angiography and Intervention, Noninvasive Imaging, Atherosclerotic Disease (CAD/PAD), Interventions and ACS, Interventions and Coronary Artery Disease, Interventions and Imaging, Angiography, Echocardiography/Ultrasound, Nuclear Imaging

Keywords: Diagnostic Imaging, Coronary Artery Disease, Plaque, Atherosclerotic, Exercise Test, Echocardiography, Stress, Myocardial Perfusion Imaging, Constriction, Pathologic, Acute Coronary Syndrome, Cross-Sectional Studies, Case-Control Studies, Prospective Studies, Area Under Curve, Cardiovascular Diseases, Coronary Angiography, Risk Factors, Coronary Stenosis, Calcinosis, Atherosclerosis, Myocardial Ischemia

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