Use of coronary artery calcium score and coronary CT angiography to guide cardiovascular prevention and treatment

Abstract

Currently, cardiovascular risk stratification to guide preventive therapy relies on clinical scores based on cardiovascular risk factors. However, the discriminative power of these scores is relatively modest. The use of coronary artery calcium score (CACS) and coronary CT angiography (CCTA) has surfaced as methods for enhancing the estimation of risk and potentially providing insights for personalized treatment in individual patients. CACS improves overall cardiovascular risk prediction and may be used to improve the yield of statin therapy in primary prevention, and possibly identify patients with a favorable risk/benefit relationship for antiplatelet therapies. CCTA holds promise to guide anti-atherosclerotic therapies and to monitor individual response to these treatments by assessing individual plaque features, quantifying total plaque volume and composition, and assessing peri-coronary adipose tissue. In this review, we aim to summarize current evidence regarding the use of CACS and CCTA for guiding lipid-lowering and antiplatelet therapy and discuss the possibility of using plaque burden and plaque phenotyping to monitor response to anti-atherosclerotic therapies.

Introduction

Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death in developed nations and carries a significant economic burden worldwide. ¹ Interventions to minimize the risk of ASCVD events include the adoption of lifestyle changes at the population level and the use of preventive pharmacotherapy in selected individuals in whom the potential benefits are expected to outweigh its risks and costs. These therapies may include lipid-lowering medication and antiplatelet agents. However, the allocation of these interventions represents a major problem since universal pharmacological treatment is unfeasible, and cardiovascular events are notoriously difficult to predict. The current approach relies on cardiovascular risk stratification using clinical scores based on traditional risk factors. Although useful, these risk assessment models have several important limitations. ² They represent a snapshot of the current state of an individual, not accounting for previous exposure, its magnitude, or individual susceptibility. ² Consequently, risk calculators have a modest discriminative power and are thought to result in sizeable overtreatment. ³ Conversely, and especially in younger people, a large proportion of those who do experience a cardiovascular event would not fulfill the criteria for preventive treatment before its occurrence. ⁴ Therefore, there is a great unmet clinical need to identify the individuals at greater risk of experiencing ASCVD events so that preventive therapies can be targeted to those who really need them. Subclinical atherosclerosis, particularly the quantification of coronary artery calcium score (CACS), is a powerful risk marker, outperforming traditional risk factors and coronary stenosis.^5,6 On the other hand, coronary computed tomography angiography (CCTA), with its ability to characterize both calcified and non-calcified plaques, has been proposed by some as the best noninvasive tool to assess atherosclerotic burden and the risk of future cardiovascular events.

In this short review, we aim to summarize the current evidence regarding the use of CACS for guiding lipid-lowering and antiplatelet therapy and discuss the possibility of using plaque burden and plaque phenotyping by CCTA to monitor response to anti-atherosclerotic therapies.

Atherosclerotic burden versus coronary stenosis

Historically, our understanding of coronary artery disease (CAD) has evolved from stenosis-centered thinking to an ischemia-centered framework and, more recently, to the recognition of atherosclerotic burden as the main driver of cardiovascular events. ⁷ This evolution in thinking has paralleled the development of invasive and noninvasive tools which enable us to study each of these attributes of CAD. Much of the evidence on the role of atherosclerotic burden as arguably the most important risk marker has come from CACS and CCTA studies.^8–10

Coronary artery calcium is a direct measure of an individual’s coronary calcified atherosclerotic plaque burden and is currently performed using a standardized non-contrast ECG-gated CT protocol.^11,12 Early studies on coronary artery calcification used various imaging techniques, such as chest radiography and fluoroscopy, demonstrating CAC’s potential in predicting obstructive CAD. ¹³ Later, electron-beam computed tomography introduced cardiac gating, enabling precise CAC quantification. However, this technique was replaced by multidetector CT, offering improved imaging capabilities. Modern multidetector CT scans, requiring minimal time and radiation, allow both gated and non-gated studies for CAC assessment, both semiquantitative (ordinal scores) and quantitative. ¹³ The most common way of quantifying CAC is the Agatston score, but other measures of coronary calcification such as CAC mass or CAC volume may be used, with some advantages in specific settings. ¹⁴ In the Agatston score, coronary calcification is defined as a lesion of at least three consecutive pixels (or 1 mm²) with a density ⩾130 Hounsfield units (HU). Using dedicated software, calcifications in coronary arteries are manually selected and quantified with the Agatston score, which is the weighted sum of the area of each calcified plaque multiplied by a factor (between 1 and 4) related to the corresponding CT density. ¹⁵

Higher values of CACS are strongly associated with an increased risk of cardiovascular disease (CVD) events,^12,16,17 even in younger individuals, as shown in the CARDIA (Coronary Artery Risk Development in Young Adults) study. ¹⁸ In fact, the risk of events in patients with very high CACS is similar to those with a prior cardiovascular event regardless of age, sex, and race/ethnicity. ¹² In addition, studies have shown that the regional distribution of CAC (in particular the total number of coronary arteries with CAC) adds prognostic information to the Agatston score, with higher risk in those with more diffuse plaque distributions. ¹⁹

In a sub-study of the CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter) registry, the incidence of major adverse cardiovascular events (MACE) increased with higher CACS, with the highest rates observed in individuals with a CACS ⩾ 300. ²⁰ Among those with a CACS ⩾ 300 and no known CVD, the rate of MACEs, and all-cause mortality were similar to those with established ASCVD. ²⁰ Conversely, the absence of CAC (CACS = 0) is linked to a low long-term risk of CVD, even in patients classified as high risk based on traditional risk factors.^1,12,21

While luminal stenosis remains frequently the main concern of physicians caring for patients with suspected or known CAD, there is growing evidence that atherosclerotic burden is a crucial component of risk assessment. This notion stems from two main findings. First, most acute coronary syndromes (ACS) are caused by rupture or erosion of non-obstructive plaques (<50% stenosis) since these are much more prevalent than obstructive ones.^22–25 Second, when adjusted for atherosclerotic burden, the risk of major CVD events is similar between patients with obstructive and non-obstructive CAD. ²⁵ In fact, patients with extensive non-obstructive CAD (CACS 400–1000) have higher event rates than patients with obstructive CAD but less extensive calcified atherosclerotic burden (CACS 100–399). ²⁵ Therefore, plaque burden, and not stenosis per se, seems to be the main predictor of risk for CVD events and death. ²⁵

In addition, CAC progression has been associated with a higher risk for myocardial infarction (MI) ²⁶ and all-cause mortality. ¹⁷ In the HNR (Heinz Nixdorf Recall) study, with CT scans spaced 5 years apart, CAC surging was studied in a cohort of individuals who had CAC = 0 at the first examination. ²⁷ The probability of incident CAC at 5 years steadily increased with age, from 23% in men 45–49 years of age to 67% in the 70–74 years of age category. ²⁷ In women, new onset of CAC was seen in 15% (age 45–49 years) and 43% (age 70–74 years), respectively. ²⁷

In the MESA (Multiethnic Study on Atherosclerosis) study, CACS increased by about 20–25% per year, and about 20% of subjects with CACS = 0 progressed to CACS >0 within 4–5 years. ²⁸ Because CAC progression is most strongly predicted by baseline CAC, the distribution of CAC is always heavily right-skewed, underscoring the exponential nature of CAC change over time. ²⁸ Patients who exhibit a CAC = 0 both at baseline CT and at 5 years (‘double zero’) have the best coronary disease prognosis. ²⁹

Given its wealth of evidence regarding risk stratification, low cost, and wide availability, CACS may be used in selected asymptomatic individuals to assess ASCVD risk. ⁹ The current debate revolves around the necessity for a new CAC score. There is a growing body of evidence suggesting that incorporating extra-coronary calcification, such as aortic valve, aortic, and mitral annular calcifications, may enhance risk prediction, especially for stroke and other cardiovascular outcomes. ³⁰

Incorporation of CAC in PTP

Current European ³¹ and American guidelines ³² recommend the estimation of pretest probability (PTP) of obstructive CAD based on contemporary tabular methods using age, sex, and typicality of symptoms. Both guidelines agree that, when available, information on the presence and amount of coronary artery calcifications may be useful for enhancing the estimation of PTP. However, it aims to select the diagnostic modality to assess the presence of CAD, not to identify patients who do not require further testing. In addition, the Diamond-Forrester PTP overestimates the likelihood of obstructive CAD, exposing patients to further unnecessary testing,^33,34 while the 2019 ESC recommended PTP underestimates it. ³⁵ Furthermore, the last decades have witnessed a marked decline in the prevalence of obstructive CAD among patients undergoing diagnostic testing, prompting several updates to this model, and downgrading PTP values. ³⁶ By incorporating CAC in clinical likelihood (CL) models, Winther et al. ³⁷ designed two models for the estimation of the CL of obstructive CAD: a risk factor-weighted model (RF-CL) and a CACS-weighted model (CACS-CL). When compared to the guideline-recommended Juarez-Orozco et al.’s ³⁸ method, these models showed a more accurate prediction of obstructive CAD in Northern European and North American cohorts. Compared to patient characteristics and risk factors, the addition of CACS allowed for a significant improvement in discriminative power and categorized more patients as having low CL of CAD, who need no further testing. ³⁷ Therefore, CACS may be considered as part of the early diagnostic work-up of patients with suspected CAD in the future since it has a major impact on the likelihood estimation of obstructive CAD.

Using CACS to guide lipid-lowering therapy

By enhancing and refining CVD risk stratification, CACS may help guide lipid-lowering therapy for individuals in primary prevention. ⁹ In a large observational study of 13,644 patients without preexisting ASCVD followed for a median of 9 years, the effect of statin use on MACE was significantly related to the severity of CACS, with the number needed to treat (NNT) to prevent one initial MACE ranging from 100 (CACS 1–100) to 12 (CACS > 100). ³⁹ Importantly, in patients with CACS = 0, statin therapy did not seem to affect the event rate. Likewise, an analysis of the MESA study including more than 6000 patients followed for 14 years suggests that the absolute and relative risk reductions in ASCVD events provided by statin therapy are proportional to CACS. ⁴⁰ In patients with CACS > 400, statin use was associated with a 10% absolute risk reduction (NNT = 10). ⁴⁰ Likewise, in an analysis including patients from the MESA study who met the inclusion criteria of the JUPITER (Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin) trial, ⁴¹ the 5-year NNT to prevent one cardiovascular event ranged from 124 for subjects with CACS = 0 to 19 for those with CACS > 100.

CACS also has the potential to raise patients’ awareness of cardiovascular risk and promote the prescription of preventive therapies by primary care physicians.^42,43 This is particularly beneficial for patients with non-obstructive CAD, as a high proportion of patients are at risk for ACS and could greatly benefit from comprehensive prevention. ⁴⁴ A recent meta-analysis of six studies including more than 11,000 individuals showed that those with CACS > 0 were more likely to initiate and maintain lipid-lowering therapies, more likely to initiate anti-hypertensive or antiplatelet medications and, notably, more likely to adhere to lifestyle modifications. ⁴⁵

Based on these and other data, current guidelines^46,47 provide a IIa recommendation to perform CACS to improve ASCVD risk stratification among borderline to intermediate-risk patients (5% to <20% 10-year risk) to aid in the shared decision on whether to withhold or initiate statin therapy. CACS = 0 appears to be the strongest negative predictor of ASCVD events when compared to other measures of subclinical CVD measures or biomarkers and allows downward reclassification (‘derisking’) of a substantial proportion of patients who are currently considered eligible for primary prevention with statin therapy. ⁴⁸ For those with intermediate risk and CACS = 0, in the absence of high-risk features, it is reasonable to defer statin therapy^9,40 and reassess CACS in 3–5 years. ⁴⁹

For patients exhibiting a CACS ranging from 1 to 99, it is advisable to contemplate the initiation of statin therapy of at least moderate intensity.^46,47 Conversely, individuals with a CACS of 100 or higher (or those positioned at the 75th percentile or beyond) should be offered statin therapy of moderate to high intensity.^46,47 The more recent expert consensus from the American College of Cardiology in 2022 further elaborates on the significance of CACS and suggests the possibility of adding ezetimibe for patients with a CACS of 100 or higher, provided that their low-density lipoprotein cholesterol (LDL-C) remains at or above 70 mg/dL. In addition, among patients with a CACS of 1000 or higher, who maintain an LDL-C level of 70 mg/dL or more despite being on statins and/or ezetimibe, consideration of PCSK9 inhibitors is recommended. ⁵⁰

Thus, assessing CACS can aid in tailoring aggressive risk factor interventions based on atherosclerotic plaque burden and actual risk in the primary prevention setting. This approach may avoid unnecessary statin therapy for individuals with low CACS and minimal 10-year event risk, a strategy often referred to as ‘derisking’. ¹³

Using CACS to guide antiplatelet therapy in patients without known ASCVD

The routine recommendation of low-dose aspirin (75–100 mg/day) for primary prevention patients has been reconsidered due to numerous trials indicating that the risk of bleeding offsets the potential benefits of CVD risk reduction.^51–53 Consequently, in primary prevention, the decision to initiate low-dose aspirin should be individualized, based on each patient’s risk–benefit profile. CACS may be useful in guiding decisions on antiplatelet therapy. Recent studies^40,54 found that CACS ⩾ 100 (especially CACS > 400) can identify subgroups where aspirin may yield a net benefit. On the other hand, in patients with CACS < 100, the risk of bleeding with aspirin probably outweighs its benefits. Nevertheless, evidence regarding aspirin in primary prevention is more controversial and neither American nor European guidelines suggest explicit means for identifying patients who may benefit from this therapy.

Limitations of CACS

Several limitations of using CACS to guide preventive therapy must be acknowledged. By assessing only calcified plaques, CACS tends to underestimate total atherosclerotic burden and may miss the presence of atherosclerosis that is entirely non-calcified, a finding which is not uncommon in younger patients.^8,55–57

Moreover, there are no randomized control trials (RCTs) showing the benefits of guiding preventive therapy by CACS results. The St Francis Heart study addressed this issue, showing that, in apparently healthy men and women aged 50–70 years with CACS at or above the 80th percentile for age and gender, treatment with atorvastatin may reduce ASCVD events, especially in subjects with CACS >400. ⁵⁸ However, these effects did not achieve conventional levels of statistical significance. ⁵⁸ The ongoing ROBINSCA (Risk or Benefit in Screening for Cardiovascular Disease) trial ⁵⁹ and the 10-year follow-up results of the DANCAVAS (Danish Cardiovascular Screening) trial ⁶⁰ will bring more information on the potential usefulness of cardiovascular screening with CACS. Nevertheless, the criticism of the absence of RCTs can also be extended to current guideline-recommended risk models. ⁶¹

Other limitations of CACS include the use of ionizing radiation, the possibility of incidental findings, and incremental costs, although CACS is cost-effective in a variety of settings.^60,62,63 In addition, serial CACS measurements in patients already treated with statin therapy have limited utility since statins tend to increase plaque density and thus increase CACS, despite being associated with slower progression of overall coronary atherosclerosis volume and reduction of high-risk plaque (HRP) features.^9,64

Importantly and despite concerns about heightened downstream testing when evaluating CACS, the National Lipid Association’s 2020 Scientific Statement emphasizes the need to refrain from such testing. ⁶⁵ Specifically, for adults with left main calcification, multi-vessel coronary involvement, or a high CACS without clinically relevant symptoms, stress testing or invasive coronary angiography is not recommended. ⁶⁵

Future directions for CAC quantification

Quantifying coronary artery calcification usually involves manual identification and marking of calcified lesions in each image section, a time-consuming process demanding a moderate level of expertise. Therefore, the development of an automated, precise postprocessing method is desired to reduce the need for human–observer interaction. ¹⁵ The main difficulty is differentiating coronary from non-coronary calcification (e.g. mitral annular calcification). The recent evolution of artificial intelligence-based technologies in medical imaging, including deep learning with convolutional neural networks (CNNs), has accelerated progress in CACS assessment, providing promising results for future clinical applications in this field. ¹⁵ Lessmann et al. ⁶⁶ used sequential CNNs to classify CAC as well as valve and aortic calcifications on chest CT images. This strategy achieved good performance (F1 value of 0.68–0.90) in calcium detection and strong agreement (75–91%) with manual reference standards in cardiovascular risk categorization. Also, another deep learning-based automated calcium scoring method for non-contrast ECG-triggered cardiac CT showed high accuracy when compared to manually obtained reference scores in 511 patients, by relying on a combination of multiple CNNs for understanding the context of the CT image. ⁶⁷ This study showed that 93.2% of patients were classified into the same risk category as the human observers. ⁶⁷

Phenotyping CAD with CCTA

Recent data suggest that the overall amount of coronary plaque by CCTA is a major predictor of incident CVD events, surpassing coronary stenosis and clinical variables. The ability to non-invasively detect calcified and non-calcified plaque is a unique attribute of CCTA. ⁹ CCTA seems especially important in patients likely to have a higher prevalence of non-calcified plaques: young (age <45–50 years) and female individuals. ⁵⁵

The use of CCTA for risk assessment has taken essentially three different (but not mutually exclusive) approaches: (1) qualitative assessment with identification of ‘high-risk’ plaque features; (2) quantitative measurement of total coronary plaque volume and plaque composition ⁹ ; and (3) assessment of peri-coronary adipose tissue.

Searching for HRP

HRP characteristics, such as low-attenuation plaques (LAP), non-calcified plaques, spotty calcification, positive remodeling, or the napkin-ring sign (low-attenuation core with a higher attenuation rim), may identify high-risk CAD even in the presence of a CACS = 0.^10,25,68 Currently, the presence of two or more of these features is required to define an HRP. ⁹ Several studies have found correlations between the presence of these features and ASCVD events: LAP identifies the presence of a large rupture-prone necrotic core ⁶⁹ and is associated with acute thrombotic events, even in the presence of non-obstructive stenosis, ¹⁰ increasing the risk of ACS up to eightfold. ⁹ Positive remodeling dissociates plaque size from the degree of luminal stenosis during the early stages of plaque growth ⁹ and has been associated with an 11-fold increased risk for ACS. ²³ In a post hoc analysis of the SCOT-HEART (Scottish Computed Tomography of the HEART) trial, these two features were the strongest predictors of MACE independently of CACS and stenosis.^24,70 The napkin-ring sign, predominantly found in high-risk lesions such as in thin cap fibroatheroma, ⁷¹ was considered causative of plaque rupture and has been described in culprit ACS lesions.^72,73 These adverse coronary plaque features have an independent predictive value for MACE beyond risk factors, obstructive stenosis, and CACS.^9,68,74

A screening strategy based on the active search for HRP with CCTA has several limitations. Even though HRP characteristics confer a high relative risk of MACE, the absolute risk remains relatively low since most of these features tend to regress over time, ‘healing’ with calcification. ⁸ Moreover, and contrarily to percent atheroma volume (PAV), HRP features do not seem to be predictive of plaque progression.^44,75 So, despite all the evidence, it still remains unknown if and how these features can be used to select high-risk patients who may benefit from preventative treatments such as aggressive lipid-lowering therapies ⁷² or antiplatelet agents.

Quantification of plaque volume and composition

Although methods for quantifying atherosclerotic plaque have been available for many years, the time and expertise required for analyzing the whole coronary tree severely limited their use in clinical practice. Recent software developments incorporating machine learning techniques facilitate the quantitative assessment of plaque volume and composition. Most of these have been shown to correlate with pathology and/or invasive imaging,^76,77 opening up new perspectives for the non-invasive study of coronary atherosclerosis.

Plaque volume, particularly non-calcified plaque volume, has been shown to provide superior predictive value for cardiovascular events over lumen stenosis and clinical risk profile.^44,73,78 In the PROSPECT (Providing Regional Observations to Study Predictors of Events in the Coronary Tree) trial, ⁷³ lesion characteristics assessed by intravascular ultrasound that were predictive of events included a large plaque burden, a small luminal area, and thin cap fibroatheromas. Using CCTA, these results were supported by Zhao et al. ⁷⁹ : non-culprit lesions responsible for unanticipated MACEs were frequently characterized by a large plaque burden and low-density non-calcified plaque volume, a small minimal luminal area, or a combination of these adverse plaque characteristics. In the ICONIC study, ⁸⁰ non-calcified plaque volume and, in particular, low-density non-calcified plaque volume, was the strongest discriminator of future ACS even if nearly two-thirds of culprit lesions were non-obstructive. Conversely, increasingly dense calcified plaques were associated with lower rates of ACS. ⁸⁰

Quantitative plaque composition may also be important to assess the likelihood of plaque progression. In the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) study, PAV was the best quantitative measure of coronary atherosclerotic plaque burden, ⁷⁵ and plaque progression measured by annual rate of change in PAV was associated with higher rates of MACE. ⁴⁴ Plaque progression was faster in older patients; while women had faster progression of calcified plaque, men showed more rapid progression of non-calcified plaque. ⁷⁵ Yoon et al. ⁸¹ also found that plaque progression varied among different plaque clusters, with adverse cardiac events more common in those with fibro-fatty and fibrous plaques. Calcified plaque drove progression in advanced and stabilized plaques, while fibrous plaque progression occurred mainly in those with necrotic cores. ⁸¹

Staging coronary atherosclerosis according to clinically relevant plaque composition may in the future provide a framework for physicians to initiate, intensify, or de-intensify therapy. ⁸² Some authors have proposed staging atherosclerotic plaque burden using different thresholds ⁸² based on the finding that atherosclerotic plaque burden assessed by quantitative CCTA was related to stenosis severity and extent as well as the presence of myocardial ischemia. If validated, this classification could provide a framework for gauging the intensity of anti-atherosclerotic therapies in individual patients. Moreover, this type of quantitative assessment opens up the possibility of using CCTA to visualize the effects of therapy on the atherosclerotic plaque of individual patients. However, additional research is necessary to ascertain whether fluctuations in vessel volume over time (caused by shifts in cardiovascular fitness, body composition, or vasodilator usage) might introduce changes that need to be considered when interpreting alterations in PAV on consecutive CCTA. ⁴⁴ Also, measurement variation is higher in smaller plaque volumes and may not include smaller coronary artery segments. ⁷² There are currently no RCTs using the quantification of plaque volume and composition to guide preventive therapies.

Quantification of epicardial and peri-coronary adipose tissue

Adipose tissue is recognized as a key regulator of cardiovascular health and disease, exerting both protective and deleterious effects on the cardiovascular system. ⁸³ Epicardial and peri-coronary adipose tissue are markers of visceral obesity and inflammation features evaluated by CCTA that have proven to be associated with coronary atherosclerosis and cardiovascular events. ⁸⁴ An increase in vessel inflammation represented by perivascular adipose tissue density is independently associated with the progression of the lipid component of coronary atherosclerotic plaques, as shown by Lee et al. ⁸⁵ In the recent ORFAN (Oxford Risk Factors and Noninvasive Imaging Study) ⁸³ study, the authors found that by adding automated assessment of epicardial adipose tissue volume into a clinical model led to significant improvement in the ability to detect obstructive CAD on CCTA and to predict future MI. Beyond CAD-related outcomes, epicardial adipose tissue volume quantification also improved prognostic assessment for stroke, postoperative atrial fibrillation, and all-cause mortality, regardless of the body mass index. ⁸³

Potential role of CCTA in the primary prevention setting

Although both CACS and CCTA offer valuable insights into individual ASCVD risk, the data supporting the effectiveness of CACS in optimizing treatment allocation for primary prevention are extensive, although mainly observational. Conversely, there is very limited data available for CCTA in this context. Indeed, despite CCTA’s role as a standard of care for the diagnosis of obstructive CAD in symptomatic patients, current prevention guidelines do not include indications for preventive measures based on atherosclerotic plaque quantification using CCTA.

Moreover, the increased cost, requirement for iodinated contrast, and processing/reading times remain obvious obstacles to its potential adoption as a standard test for risk assessment in asymptomatic patients. ⁸⁶ Furthermore, no data show that CCTA improves risk classification and treatment allocation in primary prevention beyond what can be achieved by assessment of CACS. ⁴⁸ In particular, its potential value in changing clinical management beyond what can be achieved by CACS assessment is unknown. Lastly, since CCTA offers details on lumen stenosis, there is a concern about the potential overuse of procedures such as coronary catheterization and revascularization. ⁸⁷ Therefore, future research should confirm that employing CCTA in primary prevention does not lead to a rise in unnecessary downstream testing, undermining the potential benefits of using CCTA.^48,87

The only RCT assessing the use of CCTA in asymptomatic patients, the FACTOR-64 study, ⁸⁸ a trial that recruited high-risk asymptomatic diabetic patients, failed to demonstrate a clinical outcome benefit. However, there was a low annual event rate (<2%), and there were no significant differences between groups in terms of LDL-C or HbA1c. Similarly, in the CONFIRM long-term registry of 1226 patients undergoing CCTA and followed for 6 years, CCTA did not provide incremental prognostic benefit above and beyond CAD risk factors and CACS. ⁸⁹ The ongoing SCOT-HEART 2 (NCT03920176) and DANE-HEART (NCT05677386) trials, among others, will hopefully help us understand the potential clinical impact of a CCTA-based strategy to guide primary prevention therapies.

While awaiting further studies, prudent use of CCTA in asymptomatic populations involves targeting high-risk individuals not adequately identified by traditional ASCVD risk scoring. ⁸⁷ Ideal candidates for CCTA to detect subclinical atherosclerosis may include selected patients with a family history of premature ASCVD, diabetes, smokers, HIV infection on anti-retroviral therapy, and South Asian descent with a significant family history, among other risk factors. ⁸⁷

Limitations of CCTA

Despite all the useful information provided by CCTA, several limitations must be acknowledged: reliable interpretation requires good image quality, and quantitative measures from scans with reduced quality (e.g. morbid obesity, tachycardia, respiratory motion) may be unreliable. ⁷² Also, exposure to radiation requires some consideration, along with the use of iodinated contrast. ⁹ Most importantly, many questions remain unanswered, such as who and when to scan, how to use the wealth of information provided by CCTA to provide evidence-based preventive therapy, and how to monitor response to such treatments.

Conclusion

CACS and CCTA have emerged as methods to enhance risk estimation and potentially individualize treatment. CACS improves overall cardiovascular risk prediction and may be used to improve the yield of statin therapy in primary prevention, and possibly identify patients with a favorable risk/benefit relationship for antiplatelet therapies. CCTA holds promise to guide anti-atherosclerotic therapies and to monitor individual response to these treatments by assessing individual plaque features, quantifying total plaque volume and composition, and assessing peri-coronary adipose tissue. Although CCTA provides important information regarding prognosis in symptomatic patients, there is no strong evidence to support its use in the primary prevention setting and its potential incremental value in this setting is a matter of debate. Ongoing randomized clinical trials will assess the effectiveness of each of these strategies to improve patient outcomes.

Appendix

List of abbreviations

• ACS Acute coronary syndrome

• AI Artificial intelligence

• ASCVD Atherosclerotic cardiovascular disease

• CACS Coronary artery calcium score

• CAD Coronary artery disease

• CCTA Coronary CT angiography

• CNN Convolutional neural networks

• CVD Cardiovascular disease

• HRP High-risk plaque

• LAP Low-attenuating plaques

• LDL-C Low-density lipoprotein cholesterol

• MACE Major adverse cardiovascular events

• MI Myocardial infarction

• NNT Number needed to treat

• PAV Percent atheroma volume

• PTP Pretest probability

• RCT Randomized control trials