Coronary Artery Calcium Scores and Atherosclerotic Cardiovascular Disease Risk Stratification in Smokers

Comparing coronary artery cross-sectional area among asymptomatic South Asian, White, and Black participants: the MASALA and CARDIA studies

BACKGROUND

South Asian individuals have high risk of atherosclerotic cardiovascular disease (ASCVD). Some investigators suggest smaller coronary artery size may be partially responsible.

METHODS

We compared the left anterior descending (LAD) artery cross-sectional area (CSA) (lumen and arterial wall) among South Asians in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study with White and Black participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study, adjusting for BMI, height, and other ASCVD risk factors. We used thin-slice non-contrast cardiac computed tomography to measure LAD CSA. We used linear regression models to determine whether race/ethnicity was associated with LAD CSA after adjusting for demographic factors, BMI, height, coronary artery calcium (CAC), and traditional cardiovascular risk factors.

RESULTS

Our sample included 3,353 participants: 513 self-identified as South Asian (44.4% women), 1286 as Black (59.6% women), and 1554 as White (53.5% women). After adjusting for age, BMI, height, there was no difference in LAD CSA between South Asian men and women compared to White men and women, respectively. After full adjustment for CVD risk factors, LAD CSA values were: South Asian women (19.9 mm2, 95% CI [18.8 - 20.9]) and men (22.3 mm2, 95% CI [21.4 - 23.2]; White women (20.0 mm2, 95% CI [19.4-20.5]) and men (23.6 mm2, 95% CI [23.0-24.2]); and Black women (21.6 mm2, 95% CI [21.0 - 22.2]) and men (26.0 mm2, 95% CI [25.3 - 26.7]). Height, BMI, hypertension, CAC, and age were positively associated with LAD CSA; current and former cigarette use were inversely associated.

CONCLUSIONS

South Asian men and women have similar LAD CSA to White men and women, and smaller LAD CSA compared to Black men and women, respectively, after accounting for differences in body size. Future studies should determine whether LAD CSA is associated with future ASCVD events.

Evaluation of Conventional Cardiovascular Risk Factors and Ordinal Coronary Artery Calcium Scoring in a Lung Cancer Screening Cohort

(1) Background: Lung cancer screening (LCS) consists of low-dose computed tomography (LDCT) results to reduce lung cancer-related mortality. The LCS program has a unique opportunity to impact CVD mortality by providing tools for CVD risk assessment and implementing preventative strategies. In this study, we estimated standardized CVD risk (SCORE) and assessed the prevalence of coronary artery calcium (CAC) in a Polish LCS cohort. (2) Methods: In this observational study, 494 LCS participants aged 50-79 years with a cigarette smoking history of at least 30 pack-years were included. Medical history, anthropometric measurements, blood pressure measurements, serum glucose, and cholesterol levels were assessed in one visit. CVD risk assessment using SCORE tables was performed. The results were compared to the general population (NATPOL 2011 study). On LDCT scans, CAC was classified using an Ordinal Score ranging from 0 to 12. (3) Results: The prevalence of classic cardiovascular risk factors was very high. Among study participants, 83.7% of men and 40.7% of women were classified with a very high CVD SCORE risk (>10%). CAC was reported in 190 (47%) participants. Calcification was categorized as severe (CAC ≥ 4) in 84 (21%) participants. (4) Conclusions: Due to the high cardiovascular risk, intensive preventive strategies are recommended for LCS participants.

An interpretable ensemble learning model facilitates early risk stratification of ischemic stroke in intensive care unit: Development and external validation of ICU-ISPM

Ischemic stroke (IS) is a common and severe condition that requires intensive care unit (ICU) admission, with high mortality and variable prognosis. Accurate and reliable predictive tools that enable early risk stratification can facilitate interventions to improve patient outcomes; however, such tools are currently lacking. In this study, we developed and validated novel ensemble learning models based on soft voting and stacking methods to predict in-hospital mortality from IS in the ICU using two public databases: MIMIC-IV and eICU-CRD. Additionally, we identified the key predictors of mortality and developed a user-friendly online prediction tool for clinical use. The soft voting ensemble model, named ICU-ISPM, achieved an AUROC of 0.861 (95% CI: 0.829-0.892) and 0.844 (95% CI: 0.819-0.869) in the internal and external test cohorts, respectively. It significantly outperformed the APACHE scoring system and was more robust than individual models. ICU-ISPM obtained the highest performance compared to other models in similar studies. Using the SHAP method, the model was interpretable, revealing that GCS score, age, and intubation were the most important predictors of mortality. This model also provided a risk stratification system that can effectively distinguish between low-, medium-, and high-risk patients. Therefore, the ICU-ISPM is an accurate, reliable, interpretable, and clinically applicable tool, which is expected to assist clinicians in stratifying IS patients by the risk of mortality and rationally allocating medical resources. Based on ICU-ISPM, an online risk prediction tool was further developed, which was freely available at: http://ispm.idrblab.cn/.

Significant Incidental Findings in the National Lung Screening Trial

Importance

Low-dose computed tomography (LDCT) lung screening has been shown to reduce lung cancer mortality. Significant incidental findings (SIFs) have been widely reported in patients undergoing LDCT lung screening. However, the exact nature of these SIF findings has not been described.

Objective

To describe SIFs reported in the LDCT arm of the National Lung Screening Trial and classify SIFs as reportable or not reportable to the referring clinician (RC) using the American College of Radiology's white papers on incidental findings.

Design, Setting, and Participants

This was a retrospective case series study of 26 455 participants in the National Lung Screening Trial who underwent at least 1 screening examination with LDCT. The trial was conducted from 2002 to 2009, and data were collected at 33 US academic medical centers.

Main Outcomes and Measures

Significant incident findings were defined as a final diagnosis of a negative screen result with significant abnormalities that were not suspicious for lung cancer or a positive screen result with emphysema, significant cardiovascular abnormality, or significant abnormality above or below the diaphragm.

Results

Of 26 455 participants, 10 833 (41.0%) were women, the mean (SD) age was 61.4 (5.0) years, and there were 1179 (4.5%) Black, 470 (1.8%) Hispanic/Latino, and 24 123 (91.2%) White individuals. Participants were scheduled to undergo 3 screenings during the course of the trial; the present study included 75 126 LDCT screening examinations performed for 26 455 participants. A SIF was reported for 8954 (33.8%) of 26 455 participants who were screened with LDCT. Of screening tests with a SIF detected, 12 228 (89.1%) had a SIF considered reportable to the RC, with a higher proportion of reportable SIFs among those with a positive screen result for lung cancer (7632 [94.1%]) compared with those with a negative screen result (4596 [81.8%]). The most common SIFs reported included emphysema (8677 [43.0%] of 20 156 SIFs reported), coronary artery calcium (2432 [12.1%]), and masses or suspicious lesions (1493 [7.4%]). Masses included kidney (647 [3.2%]), liver (420 [2.1%]), adrenal (265 [1.3%]), and breast (161 [0.8%]) abnormalities. Classification was based on free-text comments; 2205 of 13 299 comments (16.6%) could not be classified. The hierarchical reporting of final diagnosis in NLST may have been associated with an overestimate of severe emphysema in participants with a positive screen result for lung cancer.

Conclusions and Relevance

This case series study found that SIFs were commonly reported in the LDCT arm of the National Lung Screening Trial, and most of these SIFs were considered reportable to the RC and likely to require follow-up. Future screening trials should standardize SIF reporting.

Simultaneous assessment of heart and lungs with gated high-pitch ultra-low dose chest CT using artificial intelligence-based calcium scoring

Purpose

The combined testing for coronary artery and pulmonary diseases is of clinical interest as risk factors are shared. In this study, a novel ECG-gated tin-filtered ultra-low dose chest CT protocol (GCCT) for integrated heart and lung acquisition and the applicability of artificial intelligence (AI)-based coronary artery calcium scoring were assessed.

Methods

In a clinical registry of 10481 patients undergoing heart and lung CT, GCCT was applied in 44 patients on a dual-source CT. Coronary calcium scans (CCS) with 120 kVp, 100 kVp, and tin-filtered 100 kVp (Sn100) of controls, matched with regard to age, sex, and body-mass index, were retrieved from the registry (n_total=176, 66.5 (59.4-74.0) years, 52 men). Automatic tube current modulation was used in all scans. In 20 patients undergoing GCCT and Sn100 CCS, Agatston scores were measured both semi-automatically by experts and by AI, and classified into six groups (0, <10, <100, <400, <1000, ≥1000).

Results

Effective dose decreased significantly from 120 kVp CCS (0.50 (0.41-0.61) mSv) to 100 kVp CCS (0.34 (0.26-0.37) mSv) to Sn100 CCS (0.14 (0.11-0.17) mSv). GCCT showed higher values (0.28 (0.21-0.32) mSv) than Sn100 CCS but lower than 120 kVp and 100 kVp CCS (all p < 0.05) despite greater scan length. Agatston scores correlated strongly between GCCT and Sn100 CCS in semi-automatic and AI-based measurements (both ρ = 0.98, p < 0.001) resulting in high agreement in Agatston score classification (κ = 0.97, 95% CI 0.92-1.00; κ = 0.89, 95% CI 0.79-0.99). Regarding chest findings, further diagnostic steps were recommended in 28 patients.

Conclusions

GCCT allows for reliable coronary artery disease and lung cancer screening with ultra-low radiation exposure. GCCT-derived Agatston score shows excellent agreement with standard CCS, resulting in equivalent risk stratification.

Comparing the pooled cohort equations and coronary artery calcium scores in a symptomatic mixed Asian cohort

Background

The value of pooled cohort equations (PCE) as a predictor of major adverse cardiovascular events (MACE) is poorly established among symptomatic patients. Coronary artery calcium (CAC) assessment further improves risk prediction, but non-Western studies are lacking. This study aims to compare PCE and CAC scores within a symptomatic mixed Asian cohort, and to evaluate the incremental value of CAC in predicting MACE, as well as in subgroups based on statin use.

Methods

Consecutive patients with stable chest pain who underwent cardiac computed tomography were recruited. Logistic regression was performed to determine the association between risk factors and MACE. Cohort and statin-use subgroup comparisons were done for PCE against Agatston score in predicting MACE.

Results

Of 501 patients included, mean (SD) age was 53.7 (10.8) years, mean follow-up period was 4.64 (0.66) years, 43.5% were female, 48.3% used statins, and 50.0% had no CAC. MI occurred in 8 subjects while 9 subjects underwent revascularization. In the general cohort, age, presence of CAC, and ln(Volume) (OR = 1.05, 7.95, and 1.44, respectively) as well as age and PCE score for the CAC = 0 subgroup (OR = 1.16 and 2.24, respectively), were significantly associated with MACE. None of the risk factors were significantly associated with MACE in the CAC > 0 subgroup. Overall, the PCE, Agatston, and their combination obtained an area under the receiver operating characteristic curve (AUC) of 0.501, 0.662, and 0.661, respectively. Separately, the AUC of PCE, Agatston, and their combination for statin non-users were 0.679, 0.753, and 0.734, while that for statin-users were 0.585, 0.615, and 0.631, respectively. Only the performance of PCE alone was statistically significant (p = 0.025) when compared between statin-users (0.507) and non-users (0.783).

Conclusion

In a symptomatic mixed Asian cohort, age, presence of CAC, and ln(Volume) were independently associated with MACE for the overall subgroup, age and PCE score for the CAC = 0 subgroup, and no risk factor for the CAC > 0 subgroup. Whilst the PCE performance deteriorated in statin versus non-statin users, the Agatston score performed consistently in both groups.

Using a machine learning-based risk prediction model to analyze the coronary artery calcification score and predict coronary heart disease and risk assessment

OBJECTIVES

To calculate the coronary artery calcification score (CACS) obtained from coronary artery computed tomography angiography (CCTA) examination and combine it with the influencing factors of coronary artery calcification (CAC), which is then analyzed by machine learning (ML) to predict the probability of coronary heart disease(CHD).

METHODS

All patients who were admitted to the Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University from January 2019 to March 2022, suspected of CHD, and underwent CCTA inspection were retrospectively selected. The degree of CAC was quantified based on the Agatston score. To compare the correlation between the CACS and clinical-related factors, we collected 31 variables, including hypertension, diabetes, smoking, hyperlipidemia, among others. ML models containing the random forest (RF), radial basis function neural network (RBFNN),support vector machine (SVM),K-Nearest Neighbor algorithm (KNN) and kernel ridge regression (KRR) were used to assess the risk of CHD based on CACS and clinical-related factors.

RESULTS

Among the five ML models, RF achieves the best performance about accuracy (ACC) (78.96%), sensitivity (SN) (93.86%), specificity(Spe) (51.13%), and Matthew's correlation coefficient (MCC) (0.5192).It also has the best area under the receiver operator characteristic curve (ROC) (0.8375), which is far superior to the other four ML models.

CONCLUSION

Computer ML model analysis confirmed the importance of CACS in predicting the occurrence of CHD, especially the outstanding RF model, making it another advancement of the ML model in the field of medical analysis.

Machine learning derived ECG risk score improves cardiovascular risk assessment in conjunction with coronary artery calcium scoring

Background

Precision estimation of cardiovascular risk remains the cornerstone of atherosclerotic cardiovascular disease (ASCVD) prevention. While coronary artery calcium (CAC) scoring is the best available non-invasive quantitative modality to evaluate risk of ASCVD, it excludes risk related to prior myocardial infarction, cardiomyopathy, and arrhythmia which are implicated in ASCVD. The high-dimensional and inter-correlated nature of ECG data makes it a good candidate for analysis using machine learning techniques and may provide additional prognostic information not captured by CAC. In this study, we aimed to develop a quantitative ECG risk score (eRiS) to predict major adverse cardiovascular events (MACE) alone, or when added to CAC. Further, we aimed to construct and validate a novel nomogram incorporating ECG, CAC and clinical factors for ASCVD.

Methods

We analyzed 5,864 patients with at least 1 cardiovascular risk factor who underwent CAC scoring and a standard ECG as part of the CLARIFY study (ClinicalTrials.gov Identifier: NCT04075162). Events were defined as myocardial infarction, coronary revascularization, stroke or death. A total of 649 ECG features, consisting of measurements such as amplitude and interval measurements from all deflections in the ECG waveform (53 per lead and 13 overall) were automatically extracted using a clinical software (GE Muse™ Cardiology Information System, GE Healthcare). The data was split into 4 training (S_tr) and internal validation (S_v) sets [S_tr (1): S_v (1): 50:50; S_tr (2): S_v (2): 60:40; S_tr (3): S_v (3): 70:30; S_tr (4): S_v (4): 80:20], and the results were compared across all the subsets. We used the ECG features derived from S_tr to develop eRiS. A least absolute shrinkage and selection operator-Cox (LASSO-Cox) regularization model was used for data dimension reduction, feature selection, and eRiS construction. A Cox-proportional hazards model was used to assess the benefit of using an eRiS alone (M_ecg), CAC alone (M_cac) and a combination of eRiS and CAC (M_ecg+cac) for MACE prediction. A nomogram (M_nom) was further constructed by integrating eRiS with CAC and demographics (age and sex). The primary endpoint of the study was the assessment of the performance of M_ecg, M_cac, M_ecg+cac and M_nom in predicting CV disease-free survival in ASCVD.

Findings

Over a median follow-up of 14 months, 494 patients had MACE. The feature selection strategy preserved only about 18% of the features that were consistent across the various strata (S_tr). The M_ecg model, comprising of eRiS alone was found to be significantly associated with MACE and had good discrimination of MACE (C-Index: 0.7, p = <2e-16). eRiS could predict time-to MACE (C-Index: 0.6, p = <2e-16 across all S_v). The M_ecg+cac model was associated with MACE (C-index: 0.71). Model comparison showed that M_ecg+cac was superior to M_ecg (p = 1.8e-10) or M_cac (p < 2.2e-16) alone. The M_nom, comprising of eRiS, CAC, age and sex was associated with MACE (C-index 0.71). eRiS had the most significant contribution, followed by CAC score and other clinical variables. Further, M_nom was able to identify unique patient risk-groups based on eRiS, CAC and clinical variables.

Conclusion

The use of ECG features in conjunction with CAC may allow for improved prognostication and identification of populations at risk. Future directions will involve prospective validation of the risk score and the nomogram across diverse populations with a heterogeneity of treatment effects.

Reporting Coronary Artery Calcium on Low-Dose Computed Tomography Impacts Statin Management in a Lung Cancer Screening Population

Background

Cigarette smoking is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). Concomitant use of low-dose computed tomography (LDCT) for coronary artery calcium (CAC) scoring with lung cancer screening (LCS) has been proposed to further determine ASCVD risk and mortality. We aimed to determine the validity of LDCT in identifying CAC and its impact on statin management.

Methods

We conducted a retrospective review from November 2020 to May 2021 of Military Health System (MHS) beneficiaries who received LCS with LDCT and were referred for CAC scoring with electrocardiogram-gated CT. Of the 190 participants initially identified, 170 met study eligibility. The Agatston method was used to score CAC on both scan types.

Results

Participants had a mean (SD) age of 62.1 (4.6) years and were 70.6% male. CAC was seen more on ECG-gated CT compared with LDCT (88% vs 74%, P < .001). The Spearman correlation and Kendall W coefficient of concordance of CAC scores between the 2 scan types was 0.945 (P < .001) and 0.643, respectively. The κ statistic between CAC scores on the 2 different scans was 0.49 (SEκ = 0.048; 95% CI, -0.726-1.706), and the weighted κ statistic was 0.711. Bland-Altman analysis demonstrated a mean bias of 111.45 Agatston units, with limits of agreement between -268.64 and 491.54, suggesting CAC scores on electrocardiogram-gated CT were on average about 111 units higher than those on LDCT. There was a statistically significant proportion of nonstatin participants who met statin criteria based on additional CAC reporting (P < .001).

Conclusions

CAC scores are highly correlated and concordant between LDCT and electrocardiogram-gated CT. Smokers undergoing annual LDCT may benefit from concomitant CAC scoring to help stratify ASCVD risk.

Harnessing imaging biomarkers to refine individualized cardiovascular disease risk: a case-based discussion

Traditional models of cardiovascular risk assessment rely on population-level risk factors and may not accurately capture individualized risk. Imaging biomarkers such as plaque characterization and pericoronary fat inflammation may offer refined risk prediction and allow physicians to personalize care-plans for cardiovascular disease prevention. The integration of plaque morphology and pericoronary inflammation into clinical care is highlighted using a case-based discussion. This article reviews the existing body of evidence supporting the use of novel biomarkers in an individualized comprehensive risk assessment algorithm.

Clinical applications of cardiac computed tomography: a consensus paper of the European Association of Cardiovascular Imaging-part I

Cardiac computed tomography (CT) was introduced in the late 1990's. Since then, an increasing body of evidence on its clinical applications has rapidly emerged. From an initial emphasis on its technical efficiency and diagnostic accuracy, research around cardiac CT has now evolved towards outcomes-based studies that provide information on prognosis, safety, and cost. Thanks to the strong and compelling data generated by large, randomized control trials, the scientific societies have endorsed cardiac CT as pivotal diagnostic test for the management of appropriately selected patients with acute and chronic coronary syndrome. This consensus document endorsed by the European Association of Cardiovascular Imaging is divided into two parts and aims to provide a summary of the current evidence and to give updated indications on the appropriate use of cardiac CT in different clinical scenarios. This first part focuses on the most established applications of cardiac CT from primary prevention in asymptomatic patients, to the evaluation of patients with chronic coronary syndrome, acute chest pain, and previous coronary revascularization.

Coronary Artery Calcifications and Cardiac Risk After Radiation Therapy for Stage III Lung Cancer

PURPOSE

Heart dose and heart disease increase the risk for cardiac toxicity associated with radiation therapy. We hypothesized that computed tomography (CT) coronary calcifications are associated with cardiac toxicity and may help ascertain baseline heart disease.

METHODS AND MATERIALS

We analyzed the cumulative incidence of cardiac events in patients with stage III non-small cell lung cancer receiving median 74 Gy on prospective dose-escalation trials. Events were defined as symptomatic effusion, pericarditis, unstable angina, infarction, significant arrhythmia, and/or heart failure. Coronary calcifications were delineated on simulation CTs using radiation software program (130 HU threshold). Calcifications were defined as "none," "low," and "high," with median volume dividing low and high.

RESULTS

Of 109 patients, 26 had cardiac events at median 26 months (range, 1-84 months) after radiation therapy. Median follow-up in surviving patients was 8.8 years (range, 2.3-17.3). On simulation CTs, 64 patients (59%) had coronary calcifications with median volume 0.2 cm³ (range, 0.01-8.3). Only 16 patients (15%) had baseline coronary artery disease. Cardiac events occurred in 7% (3 of 45), 29% (9 of 31), and 42% (14 of 33) of patients with no, low, and high calcifications, respectively. Calcification burden was associated with cardiac toxicity on univariate (low vs none: hazard ratio [HR] 5.0, P = .015; high vs none: HR 8.1, P < .001) and multivariate analyses (low vs none: HR 7.0, P = .005, high vs none: HR 10.6, P < .001, heart mean dose: HR 1.1/Gy, P < .001). Four-year competing risk-adjusted event rates for no, low, and high calcifications were 4%, 23%, and 34%, respectively.

CONCLUSIONS

The presence of coronary calcifications is a cardiac risk factor that can identify high-risk patients for medical referral and help guide clinicians before potentially cardiotoxic cancer treatments.

Subclinical cardiovascular disease and utility of coronary artery calcium score

ASCVD are the leading causes of mortality and morbidity among Globe. Evaluation of patients' comprehensive and personalized risk provides risk management strategies and preventive interventions to achieve gain for patients. Framingham Risk Score (FRS) and Systemic Coronary Risk Evaluation Score (SCORE) are two well studied risk scoring models, however, can miss some (20-35%) of future cardiovascular events. To obtain more accurate risk assessment recalibrating risk models through utilizing novel risk markers have been studied in last 3 decades and both ESC and AHA recommends assessing Family History, hs-CRP, CACS, ABI, and CIMT. Subclinical Cardiovascular Disease (SCVD) has been conceptually developed for investigating gradually progressing asymptomatic development of atherosclerosis and among these novel risk markers it has been well established by literature that CACS having highest improvement in risk assessment. This review study mainly selectively discussing studies with CACS measurement. A CACS = 0 can down-stratify risk of patients otherwise treated or treatment eligible before test and can reduce unnecessary interventions and cost, whereas CACS ≥ 100 is equivalent to statin treatment threshold of ≥ 7.5% risk level otherwise statin ineligible before test. Since inflammation, insulin resistance, oxidative stress, dyslipidemia and ongoing endothelial damage due to hypertension could lead to CAC, ASCVD linked with comorbidities. Recent cohort studies have shown a CACS 100-300 as a sign of increased cancer risk. Physical activity, dietary factors, cigarette use, alcohol consumption, metabolic health, family history of CHD, aging, exposures of neighborhood environment and non-cardiovascular comorbidities can determine CACs changes.

Coronary artery calcium is associated with long-term mortality from lung cancer: Results from the Coronary Artery Calcium Consortium

BACKGROUND AND AIMS

Coronary artery calcium (CAC) scores have been shown to be associated with CVD and cancer mortality. The use of CAC scores for overall and lung cancer mortality risk prediction for patients in the Coronary Artery Calcium Consortium was analyzed.

METHODS

We included 55,943 patients aged 44-84 years without known heart disease from the CAC Consortium. There were 1,088 cancer deaths, among which 231 were lung cancer, identified by death certificates with a mean follow-up of 12.2 ± 3.9 years. Fine-and-Gray competing-risk regression was used for overall and lung cancer-specific mortality, accounting for the competing risk of CVD death and after adjustment for CVD risk factors. Subdistribution hazard ratios (SHR) were reported.

RESULTS

The mean age of all patients was 57.1 ± 8.6 years, 34.9% were women, and 89.6% were white. Overall, CAC was strongly associated with cancer mortality. Lung cancer mortality increased with increasing CAC scores, with rates per 1000-person years of 0.2 (95% CI: 0.1-0.3) for CAC = 0 and 0.8 (95% CI: 0.6-1.0) for CAC ≥400. Compared with CAC = 0, hazards were increased for those with CAC ≥400 for lung cancer mortality [SHR: 1.7 (95% CI: 1.2-2.6)], which was driven by women [SHR: 2.3 (95% CI: 1.1-4.8)], but not significantly increased for men. Risks were higher in those with positive smoking history [SHR: 2.2 (95% CI: 1.2-4.2)], with associations driven by women [SHR: 4.0 (95% CI: 1.4-11.5)].

CONCLUSIONS

CAC scores were associated with increased risks for lung cancer mortality, with strongest associations for current and former smokers, especially in women. Used in conjunction with other clinical variables, our data pinpoint a potential synergistic use of CAC scanning beyond CVD risk assessment for identification of high-risk lung cancer screening candidates.

Use of cardiovascular imaging in risk restratification of the diabetic patient

PURPOSE OF REVIEW

Diabetes mellitus is no longer considered a cardiovascular disease (CVD) risk equivalent, but the optimal methods of risk stratification are a matter of debate. The coronary calcium score (CCS) is a measure of the burden of atherosclerosis and is widely used for CVD risk stratification in the general population. We review recently published data to describe the role of the CCS in people with diabetes mellitus.

RECENT FINDINGS

People with diabetes mellitus have 10-year event rates for CVD and CVD mortality that are considered high, at a much lower level of CCS than the general population. Different categories of CCS are pertinent to men and women with diabetes mellitus. CCS may be particularly useful in clinical settings when CVD risk is known to be increased but difficult to quantify, for example peri-menopausal women, young persons with diabetes, type 1 diabetic individuals and others. With modern techniques, the radiation dose of a CSS has fallen to levels wherein screening and surveillance could be considered.

SUMMARY

The CCS is able to quantify CVD risk in people with diabetes mellitus when there is clinical uncertainty and identifies those with very high event rates. Future research should aim to identify effective risk reduction strategies in this important group.

Impact on All-Cause and Cardiovascular Mortality Rates of Coronary Artery Calcifications Detected during Organized, Low-Dose, Computed-Tomography Screening for Lung Cancer: Systematic Literature Review and Meta-Analysis

Simple Summary

The results of several randomized studies showed the efficacy of organized, low-dose, computed-tomography (CT) scan lung-cancer screening in lowering all-cause and lung-cancer-specific mortality rates. Low-dose CT scans can also detect and quantify coronary artery calcifications (CACs). By means of meta-analysis, we were able to show that the presence of CACs in CT performed in this setting was associated with an enhanced risk of cardiovascular and all-cause mortality for men and women. These finding plead for the implementation of preventive interactions against cardiovascular risk in lung-cancer screening-program participants found to have CACs.

Abstract

Although organized, low-dose, computed-tomography (CT) scan lung-cancer screening has been shown to lower all-cause and lung-cancer-specific mortality, the primary cause of death for subjects eligible for such screening remains cardiovascular (CV) mortality. This meta-analysis study was undertaken to evaluate the impact of screening-scan-detected coronary artery calcifications (CACs) on CV and all-cause mortality. We conducted a systematic review and meta-analysis of studies reporting CV mortality according to the Agatson CAC score for participants in a lung-cancer screening program of randomized clinical or cohort studies. PubMed, Embase, and Cochrane databases were screened in June 2020. Two authors independently selected articles and extracted data. Six studies, including 20,175 subjects, were retained. CV and all-cause mortality rates were higher for subjects with CAC scores >0, with respective relative risks of 2.02 [95% CI 1.23–3.32] and 2.29 [95% CI 1.00–5.21]. Both mortality rates were even higher for those with high CAC scores (>400 or >1000). CACs are more common in men than in women, with an odds ratio of 1.49 [95% CI 1.40–1.59]. The presence of CAC is associated with CV mortality with an RR of 2.05 [95% CI 1.20–3.57] in men and 2.37 [CI 95% 1.29–5.09] in women, respectively. Analysis of lung-cancer-screening scans for CACs is a tool able to predict CV mortality. Prospective studies within those programs are needed to assess the benefit of primary CV prevention based on CAC detection.

Cardiovascular Risk in the Lung Cancer Screening Population: A Multicenter Study Evaluating the Association Between Coronary Artery Calcification and Preventive Statin Prescription

OBJECTIVE

Coronary artery calcification (CAC) is a marker of atherosclerotic cardiovascular disease (ASCVD), the leading cause of death in individuals receiving lung cancer screening (LCS) with low-dose CT. Our purpose was to determine the proportion of the LCS population eligible for primary ASCVD preventive statin therapy by American College of Cardiology/American Heart Association guidelines, assess statin prescription rates among statin-eligible individuals, and determine associations of CAC on downstream statin prescribing within 90 days of LCS.

METHODS

Individuals receiving LCS between January 1, 2016, and December 31, 2018, across three centers were retrospectively enrolled. Statin eligibility in individuals without pre-existing ASCVD was determined by 2013 American College of Cardiology/American Heart Association guidelines: (1) low-density lipoprotein ≥190 mg/dL, (2) diabetes, or (3) ASCVD risk score ≥7.5%. CAC presence and severity (mild, moderate, heavy) were extracted from LCS reports. Variation in statin prescription rates and associations between CAC and statin prescription were determined using mixed-effects logistic regression.

RESULTS

Of 5,495 individuals receiving LCS, 31.4% (1,724 of 5,495) had pre-existing ASCVD. Of the remaining 3,771 individuals, 73.6% were statin eligible (2,777 of 3,771). However, most lacked statin prescription (60.5%, 1,681 of 2,777). CAC was associated with downstream statin prescribing (adjusted odds ratio = 2.60, 95% confidence interval: 1.12-6.02), with a higher likelihood of statin prescribing with increasing CAC severity (adjusted odds ratio = 2.21, 95% confidence interval: 1.35-3.60).

CONCLUSION

Although most of the LCS population is eligible for guideline-directed statin therapy, statins are underprescribed in this group. Radiologist reporting of CAC at LCS reflects a potential opportunity to raise awareness of ASCVD risk and improve preventive statin prescribing.

Risk factors for myocardial injury and death in patients with COVID-19: insights from a cohort study with chest computed tomography

AIMS

Whether pulmonary artery (PA) dimension and coronary artery calcium (CAC) score, as assessed by chest computed tomography (CT), are associated with myocardial injury in patients with coronavirus disease 2019 (COVID-19) is not known. The aim of this study was to explore the risk factors for myocardial injury and death and to investigate whether myocardial injury has an independent association with all-cause mortality in patients with COVID-19.

METHODS AND RESULTS

This is a single-centre cohort study including consecutive patients with laboratory-confirmed COVID-19 undergoing chest CT on admission. Myocardial injury was defined as high-sensitivity troponin I >20 ng/L on admission. A total of 332 patients with a median follow-up of 12 days were included. There were 68 (20.5%) deaths; 123 (37%) patients had myocardial injury. PA diameter was higher in patients with myocardial injury compared with patients without myocardial injury [29.0 (25th-75th percentile, 27-32) mm vs. 27.7 (25-30) mm, P < 0.001). PA diameter was independently associated with an increased risk of myocardial injury [adjusted odds ratio 1.10, 95% confidence interval (CI) 1.02-1.19, P = 0.01] and death [adjusted hazard ratio (HR) 1.09, 95% CI 1.02-1.17, P = 0.01]. Compared with patients without myocardial injury, patients with myocardial injury had a lower prevalence of a CAC score of zero (25% vs. 55%, P < 0.001); however, the CAC score did not emerge as a predictor of myocardial injury by multivariable logistic regression. Myocardial injury was independently associated with an increased risk of death by multivariable Cox regression (adjusted HR 2.25, 95% CI 1.27-3.96, P = 0.005). Older age, lower estimated glomerular filtration rate, and lower PaO2/FiO2 ratio on admission were other independent predictors for both myocardial injury and death.

CONCLUSIONS

An increased PA diameter, as assessed by chest CT, is an independent risk factor for myocardial injury and mortality in patients with COVID-19. Myocardial injury is independently associated with an approximately two-fold increased risk of death.

Multifocal cardiovascular calcification in patients with established cardiovascular disease; prevalence, risk factors, and relation with recurrent cardiovascular disease

Aims

The aim is to investigate (multifocal) cardiovascular calcification in patients with established cardiovascular disease (CVD), regarding prevalence, risk factors, and relation with recurrent CVD or vascular interventions. Coronary artery calcification (CAC), thoracic aortic calcification (TAC) (including ascending aorta, aortic arch, descending aorta), mitral annular calcification (MAC), and aortic valve calcification (AVC) are studied.

Methods

The study concerned 568 patients with established CVD enrolled in the ORACLE cohort. All patients underwent computed tomography. Prevalence of site-specific and multifocal calcification was determined. Ordinal regression analyses were performed to quantify associations of risk factors with cardiovascular calcification, and Cox regression analyses to determine the relation between calcium scores and recurrent CVD or vascular interventions.

Results

Calcification was multifocal in 76% (N = 380) of patients with calcification. Age (per SD) was associated with calcification at all locations (lowest OR 2.17; 99%CI 1.54–3.11 for ascending aorta calcification). Diabetes mellitus and systolic blood pressure were associated with TAC, whereas male sex was a determinant of CAC. TAC and CAC were related to the combined endpoint CVD or vascular intervention (N = 68). In a model with all calcium scores combined, only CAC was related to the combined outcome (HR 1.39; 95%CI 1.15–1.68).

Conclusion

Cardiovascular calcification is generally multifocal in patients with established CVD. Differences in associations between risk factors and calcification at various anatomical locations stress the divergence in pathophysiological pathways. CAC is most strongly related to recurrent CVD or vascular interventions independent of traditional risk factors, and independent of heart valve and thoracic aorta calcification.

Impact of Slice Thickness on the Predictive Value of Lung Cancer Screening Computed Tomography in the Evaluation of Coronary Artery Calcification

Background

Image reconstruction thickness may impact quantitative coronary artery calcium scoring (CACS) from lung cancer screening computed tomography (LCSCT), limiting its application in practice.

Methods and Results

We evaluated Agatston‐based quantitative CACS from 1.25‐mm LCSCT and cardiac computed tomography for agreement in 87 patients. We then evaluated Agatston‐based quantitative CACS from 1.25‐, 2.5‐, and 5.0‐mm slice thickness LCSCT for agreement in 258 patients. Secondary analysis included the impact of slice thickness on predictive value of 4‐year outcomes. Median age of patients who underwent 1.25‐mm LCSCT and cardiac computed tomography was 63 years (interquartile interval, 57, 68). CACS from 1.25‐mm LCSCT and cardiac computed tomography demonstrated a strong Pearson correlation, R=0.9770 (0.965, 0.985), with good agreement. The receiver operating characteristic curve areas under the curve for cardiac computed tomography and LCSCT were comparable at 0.8364 (0.6628, 1.01) and 0.8208 (0.6431, 0.9985), respectively (P=0.733). Median age of patients who underwent LCSCT with 3 slice thicknesses was 66 years (interquartile interval, 63, 73). Compared with CACS from 1.25‐mm scans, CACS from 2.5‐ and 5.0‐mm scans demonstrated strong Pearson correlations, R=0.9949 (0.9935, 0.996) and R=0.9478 (0.9338, 0.959), respectively, though bias was largely negative for 5.0‐mm scans. Receiver operating characteristic curve areas under the curve for 1.25‐, 2.5‐, and 5.0‐mm scans were comparable at 0.7040 (0.6307, 0.7772), 0.7063 (0.6327, 0.7799), and 0.7194 (0.6407, 0.7887), respectively (P=0.6487). When using individualized high‐risk thresholds derived from respective receiver operating characteristic curves, all slice thicknesses demonstrated similar prognostic value.

Conclusions

Slice thickness is an important consideration when interpreting Agatston CACS from LCSCTs. Despite the absence of ECG gating, it appears reasonable to report CACS from either 1.25‐ or 2.5‐mm slice thickness LCSCT to help stratify cardiovascular risk. Conversely, 5.0‐mm scans largely underidentify calcium, limiting practical use within the established CACS values used to categorize cardiovascular risk.

Evaluation of cardiovascular risk in a lung cancer screening cohort

INTRODUCTION

Lung cancer screening (LCS) by low-dose computed tomography (LDCT) offers an opportunity to impact both lung cancer and coronary heart disease mortality through detection of coronary artery calcification (CAC). Here, we explore the value of CAC and cardiovascular disease (CVD) risk assessment in LCS participants in the Lung Screen Uptake Trial (LSUT).

METHODS

In this cross-sectional study, current and ex-smokers aged 60-75 were invited to a 'lung health check'. Data collection included a CVD risk assessment enabling estimation of 10 year CVD risk using the QRISK2 score. Participants meeting the required lung cancer risk underwent an ungated, non-contrast LDCT. Descriptive data, bivariate associations and a multivariate analysis of predictors of statin use are presented.

RESULTS

Of 1005 individuals enrolled, 680 were included in the final analysis. 421 (61.9%) had CAC present and in 49 (7.2%), this was heavy. 668 (98%) of participants had a QRISK2≥10% and QRISK2 was positively associated with increasing CAC grade (OR 4.29 (CI 0.93 to 19.88) for QRISK2=10%-20% and 12.29 (CI 2.68 to 56.1) for QRISK2≥20% respectively). Of those who qualified for statin primary prevention (QRISK2≥10%), 56.8% did not report a history of statin use. In the multivariate analysis statin use was associated with age, body mass index and history of hypertension and diabetes.

CONCLUSIONS

LCS offers an important opportunity for instituting CVD risk assessment in all LCS participants irrespective of the presence of LDCT-detected CAC. Further studies are needed to determine whether CAC could enhance uptake and adherence to primary preventative strategies.

Use of coronary artery calcium testing to improve coronary heart disease risk assessment in a lung cancer screening population: The Multi-Ethnic Study of Atherosclerosis (MESA)

BACKGROUND

Assessment of coronary artery calcium (CAC) during lung cancer screening chest computed tomography (CT) represents an opportunity to identify asymptomatic individuals at increased coronary heart disease (CHD) risk. We determined the improvement in CHD risk prediction associated with the addition of CAC testing in a population recommended for lung cancer screening.

METHODS

We included 484 out of 6814 Multi-Ethnic Study of Atherosclerosis (MESA) participants without baseline cardiovascular disease who met U.S. Preventive Service Task Force CT lung cancer screening criteria and underwent gated CAC testing. 10 year-predicted CHD risks with and without CAC were calculated using a validated MESA-based risk model and categorized into low (<5%), intermediate (5%-10%), and high (≥10%). The net reclassification improvement (NRI) and change in Harrell's C-statistic by adding CAC to the risk model were subsequently determined.

RESULTS

Of 484 included participants (mean age = 65; 39% women; 32% black), 72 (15%) experienced CHD events over the course of follow-up (median = 12.5 years). Adding CAC to the MESA CHD risk model resulted in 17% more participants classified into the highest or lowest risk categories and a NRI of 0.26 (p = 0.001). The C-statistic improved from 0.538 to 0.611 (p = 0.01).

CONCLUSIONS

CHD event rates were high in this lung cancer screening eligible population. These individuals represent a high-risk population who merit consideration for CHD prevention measures regardless of CAC score. Although overall discrimination remained poor with inclusion of CAC scores, determining whether those reclassified to an even higher risk would benefit from more aggressive preventive measures may be important.

Coronary Calcium Score and Cardiovascular Risk

Coronary artery calcium (CAC) is a highly specific feature of coronary atherosclerosis. On the basis of single-center and multicenter clinical and population-based studies with short-term and long-term outcomes data (up to 15-year follow-up), CAC scoring has emerged as a widely available, consistent, and reproducible means of assessing risk for major cardiovascular outcomes, especially useful in asymptomatic people for planning primary prevention interventions such as statins and aspirin. CAC testing in asymptomatic populations is cost effective across a broad range of baseline risk. This review summarizes evidence concerning CAC, including its pathobiology, modalities for detection, predictive role, use in prediction scoring algorithms, CAC progression, evidence that CAC changes the clinical approach to the patient and patient behavior, novel applications of CAC, future directions in scoring CAC scans, and new CAC guidelines.