CAC-DRS: Coronary Artery Calcium Data and Reporting System. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT)

Cardiovascular Aging and Risk Assessment: How Multimodality Imaging Can Help

Aging affects the cardiovascular system, and this process may be accelerated in individuals with cardiovascular risk factors. The main vascular changes include arterial wall thickening, calcification, and stiffening, together with aortic dilatation and elongation. With aging, we can observe left ventricular hypertrophy with myocardial fibrosis and left atrial dilatation. These changes may lead to heart failure and atrial fibrillation. Using multimodality imaging, including ultrasound, computed tomography (CT), and magnetic resonance imaging, it is possible to detect these changes. Additionally, multimodality imaging, mainly via CT measurements of coronary artery calcium or ultrasound carotid intima-media thickness, enables advanced cardiovascular risk stratification and helps in decision-making about preventive strategies. The focus of this manuscript is to briefly review cardiovascular changes that occur with aging, as well as to describe how multimodality imaging may be used for the assessment of these changes and risk stratification of asymptomatic individuals.

Does the absence of breast arterial calcification (BAC 0) rule out severe coronary artery disease? A computed tomography angiography study

Background

Cardiovascular risk (CV)-stratification in females is challenging, and current models miss a high proportion at-risk. Breast arterial calcifications (BAC) are independent prognosticators, but their interaction with the coronary artery disease profile by computed tomography (CT) is controverse, and the role of BAC 0 unclear.

Objective

to investigate the interaction of BAC with coronary CT outcomes (CAC score, coronary stenosis severity and high-risk plaque (HRP).

Methods

Consecutive patients referred to mammography (MG) and coronary CTA for clinical indications within 1 year were included. Three different age groups were compared (<55 years;55-65 years;>65 years).

Results

443 patients were included. There were significant age differences for the prevalence of BAC 0 (p<0.001), BAC 0/CAC>300 AU (p=0.0023) and obstructive disease (>50% stenosis)(p=0.0048) but not for high-risk-plaque (HRP)(p=0.4905). High CAC (>300 AU) was present in only 0.82% of females with BAC 0 in less than 55 year, but significantly more often in those above 65 years (p=0.0004;OR=16.58:95% CI: 2.829-361.7) and 55 years with 12.1% and 8.4%. Obstructive coronary disease (>50% stenosis) in BAC 0 was present in 18.2%; with age-dependent differences (10.7% vs 14.7% vs 29.9%) (p=0.0003). The correlation between BAC, CAC and CADRADS was weak (r=0.246 and r=0.243, p<0.001). There was no association of BAC with HRP.

Conclusion

BAC 0 rules out severe CAC >300AU in females <55 years only, but not in those above 55 years- with adherent implications for primary prevention. However, BAC 0 does not to rule out obstructive disease and high-risk plaques in symptomatic patients among all age groups.

Cardiovascular risk and subclinical atherosclerosis in first-degree relatives of patients with premature cardiovascular disease

Background

Screening first-degree relatives (FDRs) of patients with premature coronary artery disease (CAD) is recommended but not routinely performed.

Objectives

To assess the diagnostic yield and impact on clinical management of a clinical and imaging-based screening program of FDRs delivered in the setting of routine clinical care.

Methods

We recruited FDRs of patients with premature CAD with no personal history of CAD and prospectively assessed for: 1) cardiovascular risk and presence of significant subclinical atherosclerosis (SA) defined as plaque on carotid ultrasound, stenosis >50% or extensive atherosclerosis on coronary computed tomography angiography, or coronary artery calcium scores >100 Agatston units or >75% percentile for age and sex; 2) utilization of preventive medications and lipid levels prior enrolment and after completion of the assessment.

Results

We assessed 132 FDRs (60.6% females), mean (SD) age 47(17) years old. Cardiovascular risk was high in 38.2%, moderate in 12.2%, and low in 49.6% of FDRs. SA was present in 34.1% of FDRs, including 12.5% in low, 51.9% in moderate, and 55.0% in high calculated risk groups. After assessment, LLT was initiated in 32.6% of FDRs and intensified in 16.0% leading to mean (SD) LDL-C decrease of 1.07(1.10) mmol/L in patients with high calculated risk or SA. LLT was recommended to all patients with high calculated risk, but those with SA were more likely to receive the medications from pharmacies (93.3% vs 60.0%, p = 0.006).

Conclusion

Screening the FDRs of patients with premature CAD is feasible, may have high diagnostic yield and impact risk factor management.

Detection of Coronary Artery Disease With Coronary Computed Tomography Angiography and Stress Testing in Candidates for Liver Transplant

Cardiac complications are the leading cause of morbidity and mortality in recipients of liver transplant (LT). Previous guidelines recommended stress testing to exclude coronary artery disease (CAD), although recent guidelines recommend coronary computed tomography angiography (CCTA). We aimed to assess the prevalence and predictors of CAD on CCTA and compare CCTA with stress testing in consecutive adult candidates for LT who underwent CAD noninvasive assessment between 2020 and 2023. Patients who underwent a stress test between January and December 2020 formed the stress cohort, and patients who underwent CCTA between January 2021 and September 2023 formed the CCTA cohort. There were 141 patients in the stress test cohort and 269 patients in the CCTA cohort. Stress test results were nondiagnostic or inconclusive in 18 patients (12.8%) whereas CCTA was nondiagnostic in 6 patients (2.2%). In patients evaluated with CCTA, mean coronary artery calcium (CAC) score was 332 ± 716 AU, with moderate or greater (>50%) stenosis in 33 patients (12.3%). New CAD was diagnosed in 158 patients (58.7%) using CCTA and in 5 patients (3.5%) using stress tests. Clinically actionable CAD (coronary artery calcium >100) on CCTA was present in 96 patients (35.7%). The number of CAD risk factors was associated with the presence of CAD on CCTA. In conclusion, there was a great burden of CAD, mainly nonobstructive, in a large cohort of candidates for LT who underwent CAD testing over a 4-year period. The current recommended risk-based evaluation of candidates for LT using CCTA as a first-line test was feasible and effective. Diagnosis of clinically actionable CAD on CCTA provides a vast opportunity for optimizing cardiac care in candidates for and recipients of LT.

The prognostic value of visual and automatic coronary calcium scoring from low-dose computed tomography-[15O]-water positron emission tomography

AIMS

The study aimed, firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low-dose computed tomography (CT) (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan and, secondly, to assess the added value of CAC scored from LDCT scans acquired during [15O]-water-positron emission tomography (PET) myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE).

METHODS AND RESULTS

Five hundred seventy-two consecutive patients with suspected coronary artery disease, who underwent [15O]-water-PET MPI with LDCT and a dedicated CSCT scan were included. In the reference CSCT scans, manual CAC scoring was performed, while LDCT scans were scored visually and automatically using deep learning approach. Subsequently, based on CAC score results from CSCT and LDCT scans, each patient's scan was assigned to one out of five cardiovascular risk groups (0, 1-100, 101-400, 401-1000, >1000), and the agreement in risk group classification between CSCT and LDCT scans was investigated. MACE was defined as a composite of all-cause death, non-fatal myocardial infarction, coronary revascularization, and unstable angina. The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 [95% confidence interval (CI): 0.62-0.70] and 0.58 (95% CI: 0.53-0.62), respectively. Based on visual and automatic CAC scoring from LDCT scans, patients with CAC > 100 and CAC > 400, respectively, were at increased risk of MACE, independently of ischaemic information from the [15O]-water-PET scan.

CONCLUSION

There is a moderate agreement in risk classification between visual and automatic CAC scoring from LDCT and reference CSCT scans. Visual and automatic CAC scoring from LDCT scans improve identification of patients at higher risk of MACE.

Clinical Updates in Coronary Artery Disease: A Comprehensive Review

Despite significant goals achieved in diagnosis and treatment in recent decades, coronary artery disease (CAD) remains a high mortality entity and continues to pose substantial challenges to healthcare systems globally. After the latest guidelines, novel data have emerged and have not been yet considered for routine practice. The scope of this review is to go beyond the guidelines, providing insights into the most recent clinical updates in CAD, focusing on non-invasive diagnostic techniques, risk stratification, medical management and interventional therapies in the acute and stable scenarios. Highlighting and synthesizing the latest developments in these areas, this review aims to contribute to the understanding and management of CAD helping healthcare providers worldwide.

Automated Comprehensive CT Assessment of the Risk of Diabetes and Associated Cardiometabolic Conditions

Background CT performed for various clinical indications has the potential to predict cardiometabolic diseases. However, the predictive ability of individual CT parameters remains underexplored. Purpose To evaluate the ability of automated CT-derived markers to predict diabetes and associated cardiometabolic comorbidities. Materials and Methods This retrospective study included Korean adults (age ≥ 25 years) who underwent health screening with fluorine 18 fluorodeoxyglucose PET/CT between January 2012 and December 2015. Fully automated CT markers included visceral and subcutaneous fat, muscle, bone density, liver fat, all normalized to height (in meters squared), and aortic calcification. Predictive performance was assessed with area under the receiver operating characteristic curve (AUC) and Harrell C-index in the cross-sectional and survival analyses, respectively. Results The cross-sectional and cohort analyses included 32166 (mean age, 45 years ± 6 [SD], 28833 men) and 27 298 adults (mean age, 44 years ± 5 [SD], 24 820 men), respectively. Diabetes prevalence and incidence was 6% at baseline and 9% during the 7.3-year median follow-up, respectively. Visceral fat index showed the highest predictive performance for prevalent and incident diabetes, yielding AUC of 0.70 (95% CI: 0.68, 0.71) for men and 0.82 (95% CI: 0.78, 0.85) for women and C-index of 0.68 (95% CI: 0.67, 0.69) for men and 0.82 (95% CI: 0.77, 0.86) for women, respectively. Combining visceral fat, muscle area, liver fat fraction, and aortic calcification improved predictive performance, yielding C-indexes of 0.69 (95% CI: 0.68, 0.71) for men and 0.83 (95% CI: 0.78, 0.87) for women. The AUC for visceral fat index in identifying metabolic syndrome was 0.81 (95% CI: 0.80, 0.81) for men and 0.90 (95% CI: 0.88, 0.91) for women. CT-derived markers also identified US-diagnosed fatty liver, coronary artery calcium scores greater than 100, sarcopenia, and osteoporosis, with AUCs ranging from 0.80 to 0.95. Conclusion Automated multiorgan CT analysis identified individuals at high risk of diabetes and other cardiometabolic comorbidities. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Pickhardt in this issue.

CAR and CSTR Cardiac Computed Tomography (CT) Practice Guidelines: Part 1 Coronary CT Angiography (CCTA)

Imaging the heart is one of the most technically challenging applications of Computed Tomography (CT) due to the presence of cardiac motion limiting optimal visualization of small structures such as the coronary arteries. Electrocardiographic gating during CT data acquisition facilitates motion free imaging of the coronary arteries. Since publishing the first version of the Canadian Association of Radiologists (CAR) cardiac CT guidelines, many technological advances in CT hardware and software have emerged necessitating an update. The goal of these cardiac CT practice guidelines is to present an overview of the current evidence supporting the use of cardiac CT in various clinical scenarios and to outline standards of practice for patient safety and quality of care when establishing a cardiac CT program in Canada.

Overcoming barriers to implementation: Improving incidental coronary calcium reporting on non-EKG gated chest CT scans

BACKGROUND

Current guidelines recommend the reporting of incidental coronary artery calcification (CAC) on non-electrocardigram-gated computed tomography (CT) scans of the chest. The finding of incidental moderate or severe CAC on non-cardiac non-contrast chest CT correlates with a CAC score ≥ 100 Agatston units, a guideline-based indication for a clinician-patient discussion regarding the initiation of statin therapy. In contemporary practice, whether the presence and severity of incidental CAC are routinely reported on such CT scans of the chest is unknown.

METHODS

At a major university hospital, we collected a one-month convenience sample of 297 patients who had chest CT imaging for indications other than lung cancer screening (OICT) and 42 patients who underwent lung cancer chest CT screening (LSCT). We evaluated reporting patterns of incidental CAC in the body and impression of the reports as compared to the overreading of such studies by a board-certified CT chest radiologist. We hypothesized and demonstrated that there was underreporting of incidental CAC on these scans. We then undertook an initiative to educate reporting radiologists on the importance of reporting CAC and implemented a reporting template change to encourage routine reporting. Then we repeated another one-month sample (n= 363 for the OICT and n= 63 for the LSCT groups) to evaluate reporting patterns following our intervention.

RESULTS

The presence of incidental moderate and severe CAC was systematically underreported in the OICT group (0 and 4.8 %) and the severity was never mentioned in the impression of reports. In the LSCT group, the presence of incidental moderate and severe CAC was also underreported (66.7 % and 75 %) and the severity of CAC was mentioned 50 % of the time in the impression of the reports. Following the initiation of an educational program and radiology reporting template change, there was a significant increase in reporting of moderate or severe CAC in the OICT group (0 vs. 80.0 %, p < 0.001) and (4.8 vs. 93.5 %, p < 0.001) respectively and a significant increase in the reporting of the severity of incidental CAC for those with severe CAC in the LSCT group (50 vs. 94.1 %, p=0.006).

CONCLUSION

Despite guideline recommendations, incidental CAC was underreported at a large academic center. We implemented a system that significantly improved reporting patterns of incidental CAC. Failure to report incidental CAC represents a missed opportunity to initiate preventive therapies. Hospital systems interested in improving the quality of their radiology reporting procedures should examine their practices to assure that CAC quantification is routinely performed.

Thoracic versus coronary calcification for atherosclerotic cardiovascular disease events prediction

This study compared the prognostic value of quantified thoracic artery calcium (TAC) including aortic arch on chest CT and coronary artery calcium (CAC) score on ECG-gated cardiac CT.

METHODS

A total of 2412 participants who underwent both chest CT and ECG-gated cardiac CT at the same period were included in the Multi-Ethnic Study of Atherosclerosis Exam 5. All participants were monitored for incident atherosclerotic cardiovascular disease (ASCVD) events. TAC is defined as calcification in the ascending aorta, aortic arch and descending aorta on chest CT. The quantification of TAC was measured using the Agatston method. Time-dependent receiver-operating characteristic (ROC) curves were used to compare the prognostic value of TAC and CAC scores.

RESULTS

Participants were 69±9 years of age and 47% were male. The Spearman correlation between TAC and CAC scores was 0.46 (p<0.001). During the median follow-up period of 8.8 years, 234 participants (9.7%) experienced ASCVD events. In multivariable Cox regression analysis, TAC score was independently associated with increased risk of ASCVD events (HR 1.31, 95% CI 1.09 to 1.58) as well as CAC score (HR 1.82, 95% CI 1.53 to 2.17). However, the area under the time-dependent ROC curve for CAC score was greater than that for TAC score in all participants (0.698 and 0.641, p=0.031). This was particularly pronounced in participants with borderline/intermediate and high 10-year ASCVD risk scores.

CONCLUSION

Our study demonstrated a significant association between TAC and CAC scores but a superior prognostic value of CAC score for ASCVD events. These findings suggest TAC on chest CT provides supplementary data to estimate ASCVD risk but does not replace CAC on ECG-gated cardiac CT.

Radiomics analysis of lesion-specific pericoronary adipose tissue to predict major adverse cardiovascular events in coronary artery disease

OBJECTIVE

To investigate the prognostic performance of radiomics analysis of lesion-specific pericoronary adipose tissue (PCAT) for major adverse cardiovascular events (MACE) with the guidance of CT derived fractional flow reserve (CT-FFR) in coronary artery disease (CAD).

MATERIALS AND METHODS

The study retrospectively analyzed 608 CAD patients who underwent coronary CT angiography. Lesion-specific PCAT was determined by the lowest CT-FFR value and 1691 radiomic features were extracted. MACE included cardiovascular death, nonfatal myocardial infarction, unplanned revascularization and hospitalization for unstable angina. Four models were generated, incorporating traditional risk factors (clinical model), radiomics score (Rad-score, radiomics model), traditional risk factors and Rad-score (clinical radiomics model) and all together (combined model). The model performances were evaluated and compared with Harrell concordance index (C-index), area under curve (AUC) of the receiver operator characteristic.

RESULTS

Lesion-specific Rad-score was associated with MACE (adjusted HR = 1.330, p = 0.009). The combined model yielded the highest C-index of 0.718, which was higher than clinical model (C-index = 0.639), radiomics model (C-index = 0.653) and clinical radiomics model (C-index = 0.698) (all p < 0.05). The clinical radiomics model had significant higher C-index than clinical model (p = 0.030). There were no significant differences in C-index between clinical or clinical radiomics model and radiomics model (p values were 0.796 and 0.147 respectively). The AUC increased from 0.674 for clinical model to 0.721 for radiomics model, 0.759 for clinical radiomics model and 0.773 for combined model.

CONCLUSION

Radiomics analysis of lesion-specific PCAT is useful in predicting MACE. Combination of lesion-specific Rad-score and CT-FFR shows incremental value over traditional risk factors.

Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT

OBJECTIVE

This study aimed to determine the feasibility and limitations of deep learning-based coronary calcium scoring using positron emission tomography-computed tomography (PET-CT) in comparison with coronary calcium scoring using ECG-gated non-contrast-enhanced cardiac computed tomography (CaCT).

MATERIALS AND METHODS

A total of 215 individuals who underwent both CaCT and PET-CT were enrolled in this retrospective study. The Agatston method was used to calculate the coronary artery calcium scores (CACS) from CaCT, PET-CT(reader), and PET-CT(AI) to analyse the effect of using different modalities and AI-based software on CACS measurement. The total CACS and CACS classified according to the CAC-DRS guidelines were compared between the three sets of CACS. The differences, correlation coefficients, intraclass coefficients (ICC), and concordance rates were analysed. Statistical significance was set at p < 0.05.

RESULTS

The correlation coefficient of the total CACS from CaCT and PET-CT(reader) was 0.837, PET-CT(reader) and PET-CT(AI) was 0.894, and CaCT and PET-CT(AI) was 0.768. The ICC of CACS from CaCT and PET-CT(reader) was 0.911, PET-CT(reader) and PET-CT(AI) was 0.958, and CaCT and PET-CT(AI) was 0.842. The concordance rate between CaCT and PET-CT(AI) was 73.8%, with a false-negative rate of 37.3% and a false-positive rate of 4.4%. Age and male sex were associated with an increased misclassification rate.

CONCLUSIONS

Artificial intelligence-assisted CACS measurements in PET-CT showed comparable results to CACS in coronary calcium CT. However, the relatively high false-negative results and tendency to underestimate should be of concern.

CLINICAL RELEVANCE STATEMENT

Application of automated calcium scoring to PET-CT studies could potentially select patients at high risk of coronary artery disease from among cancer patients known to be susceptible to coronary artery disease and undergoing routine PET-CT scans.

KEY POINTS

• Cancer patients are susceptible to coronary disease, and PET-CT could be potentially used to calculate coronary artery calcium score (CACS). • Calcium scoring using artificial intelligence in PET-CT automatically provides CACS with high ICC to CACS in coronary calcium CT. • However, underestimation and false negatives of CACS calculation in PET-CT should be considered.

Opportunistic Screening for Coronary Artery Disease: An Untapped Population Health Resource

BACKGROUND

Coronary artery disease is the leading cause of death in the United States. At-risk asymptomatic adults are eligible for screening with electrocardiogram-gated coronary artery calcium (CAC) CT, which aids in risk stratification and management decision-making. Incidental CAC (iCAC) is easily quantified on chest CT in patients imaged for noncardiac indications; however, radiologists do not routinely report the finding.

OBJECTIVE

To determine the clinical significance of CAC identified incidentally on routine chest CT performed for noncardiac indications.

DESIGN

An informationist developed search strategies in MEDLINE, Embase, and SCOPUS, and two reviewers independently screened results at both the abstract and full text levels. Data extracted from eligible articles included age, rate of iCAC identification, radiologist reporting frequency, impact on downstream medical management, and association of iCAC with patient outcomes.

RESULTS

From 359 unique citations, 83 research publications met inclusion criteria. The percentage of patients with iCAC ranged from 9% to 100%. Thirty-one investigations measured association(s) between iCAC and cardiovascular morbidity and mortality, and 29 identified significant correlations, including nonfatal myocardial infarction, fatal myocardial infarction, major adverse cardiovascular event, cardiovascular death, and all-cause death. iCAC was present in 20% to 100% of the patients in these cohorts, but when present, iCAC was reported by radiologists in only 31% to 44% of cases. Between 18% and 77% of patients with iCAC were not on preventive medications in studies that reported these data. Seven studies measured the effect of reporting on guideline directed medical therapy, and 5 (71%) reported an increase in medication prescriptions after diagnosis of iCAC, with one confirming reductions in low-density lipoprotein levels. Twelve investigations reported good concordance between CAC grade on noncardiac CT and Agatston score on electrocardiogram-gated cardiac CT, and 10 demonstrated that artificial intelligence tools can reliably calculate an Agatston score on noncardiac CT.

CONCLUSION

A body of evidence demonstrates that patients with iCAC on routine chest CT are at risk for cardiovascular disease events and death, but they are often undiagnosed. Uniform reporting of iCAC in the chest CT impression represents an opportunity for radiology to contribute to early identification of high-risk individuals and potentially reduce morbidity and mortality. AI tools have been validated to calculate Agatston score on routine chest CT and hold the best potential for facilitating broad adoption.

Testosterone therapy and the risk of cardiovascular disease in older, hypogonadal men

The debate over the cardiovascular (CV) implications of testosterone therapy (TT) have resulted in diverging safety recommendations and clinical guidelines worldwide. This narrative review synthesizes and critically evaluates long-term studies examining the effects of TT within the context of aging, obesity, and endogenous sex hormones on CV disease (CVD) risk to support informed clinical decision-making. Observational studies have variably linked low endogenous testosterone with increased CVD risk, while randomized controlled trials (RCTs) demonstrate that TT yields cardiometabolic benefits without increasing short-term CV risk. The TRAVERSE trial, as the first RCT powered to assess CVD events, did not show increased major adverse cardiac events (MACE) incidence; however, its limitations - specifically the maintenance of testosterone at low-normal levels, a high participant discontinuation rate, and short follow-up - warrant a careful interpretation of its results. Furthermore, findings from the TTrials cardiovascular sub-study, which showed an increase in non-calcified plaque, indicate the need for ongoing research into the long-term CV impact of TT. The decision to initiate TT should consider the current evidence gaps, particularly for older men with known CVD. The CV effects of maintaining physiological testosterone levels through exogenous means remain to be fully explored. Until more definitive evidence is available, clinical practice should prioritize individualized care and informed discussions on the potential CV implications of TT.

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.

Matrix metallopeptidase 9 contributes to the beginning of plaque and is a potential biomarker for the early identification of atherosclerosis in asymptomatic patients with diabetes

Aims

To determine the roles of matrix metallopeptidase-9 (MMP9) on human coronary artery smooth muscle cells (HCASMCs) in vitro, early beginning of atherosclerosis in vivo in diabetic mice, and drug naïve patients with diabetes.

Methods

Active human MMP9 (act-hMMP9) was added to HCASMCs and the expressions of MCP-1, ICAM-1, and VCAM-1 were measured. Act-hMMP9 (n=16) or placebo (n=15) was administered to diabetic KK.Cg-Ay/J (KK) mice. Carotid artery inflammation and atherosclerosis measurements were made at 2 and 10 weeks after treatment. An observational study of newly diagnosed drug naïve patients with type 2 diabetes mellitus (T2DM n=234) and healthy matched controls (n=41) was performed and patients had ultrasound of carotid arteries and some had coronary computed tomography angiogram for the assessment of atherosclerosis. Serum MMP9 was measured and its correlation with carotid artery or coronary artery plaques was determined.

Results

In vitro, act-hMMP9 increased gene and protein expressions of MCP-1, ICAM-1, VCAM-1, and enhanced macrophage adhesion. Exogenous act-hMMP9 increased inflammation and initiated atherosclerosis in KK mice at 2 and 10 weeks: increased vessel wall thickness, lipid accumulation, and Galectin-3+ macrophage infiltration into the carotid arteries. In newly diagnosed T2DM patients, serum MMP9 correlated with carotid artery plaque size with a possible threshold cutoff point. In addition, serum MMP9 correlated with number of mixed plaques and grade of lumen stenosis in coronary arteries of patients with drug naïve T2DM.

Conclusion

MMP9 may contribute to the initiation of atherosclerosis and may be a potential biomarker for the early identification of atherosclerosis in patients with diabetes.

Clinical trial registration

https://clinicaltrials.gov, identifier NCT04424706.

Deep learning-based coronary artery calcium score to predict coronary artery disease in type 2 diabetes mellitus

Background

Coronary artery disease (CAD) in type 2 diabetes mellitus (T2DM) patients often presents diffuse lesions, with extensive calcification, and it is time-consuming to measure coronary artery calcium score (CACS).

Objectives

To explore the predictive ability of deep learning (DL)-based CACS for obstructive CAD and hemodynamically significant CAD in T2DM.

Methods

469 T2DM patients suspected of CAD who accepted CACS scan and coronary CT angiography between January 2013 and December 2020 were enrolled. Obstructive CAD was defined as diameter stenosis ≥50%. Hemodynamically significant CAD was defined as CT-derived fractional flow reserve ≤0.8. CACS was calculated with a fully automated method based on DL algorithm. Logistic regression was applied to determine the independent predictors. The predictive performance was evaluated with area under receiver operating characteristic curve (AUC).

Results

DL-CACS (adjusted odds ratio (OR): 1.005; 95% CI: 1.003-1.006; P ＜ 0.001) was significantly associated with obstructive CAD. DL-CACS (adjusted OR:1.003; 95% CI: 1.002-1.004; P ＜ 0.001) was also an independent predictor for hemodynamically significant CAD. The AUCs, sensitivities, specificities, positive predictive values and negative predictive values of DL-CACS for obstructive CAD and hemodynamically significant CAD were 0.753 (95% CI: 0.712-0.792), 75.9%, 66.5%, 74.8%, 67.8% and 0.769 (95% CI: 0.728-0.806), 80.7%, 62.1%, 59.6% and 82.3% respectively. It took 1.17 min to perform automated measurement of DL-CACS in total, which was significantly less than manual measurement of 1.73 min (P ＜ 0.001).

Conclusions

DL-CACS, with less time-consuming, can accurately and effectively predict obstructive CAD and hemodynamically significant CAD in T2DM.

Mammography-based deep learning model for coronary artery calcification

AIMS

Mammography, commonly used for breast cancer screening in women, can also predict cardiovascular disease. We developed mammography-based deep learning models for predicting coronary artery calcium (CAC) scores, an established predictor of coronary events.

METHODS AND RESULTS

We evaluated a subset of Korean adults who underwent image mammography and CAC computed tomography and randomly selected approximately 80% of the participants as the training dataset, used to develop a convolutional neural network (CNN) to predict detectable CAC. The sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), and overall accuracy of the model's performance were evaluated. The training and validation datasets included 5235 and 1208 women, respectively [mean age, 52.6 (±10.2) years], including non-zero cases (46.8%). The CNN-based deep learning prediction model based on the Resnet18 model showed the best performance. The model was further improved using contrastive learning strategies based on positive and negative samples: sensitivity, 0.764 (95% CI, 0.667-0.830); specificity, 0.652 (95% CI, 0.614-0.710); AUROC, 0.761 (95% CI, 0.742-0.780); and accuracy, 70.8% (95% CI, 68.8-72.4). Moreover, including age and menopausal status in the model further improved its performance (AUROC, 0.776; 95% CI, 0.762-0.790). The Framingham risk score yielded an AUROC of 0.736 (95% CI, 0.712-0.761).

CONCLUSION

Mammography-based deep learning models showed promising results for predicting CAC, performing comparably to conventional risk models. This indicates mammography's potential for dual-risk assessment in breast cancer and cardiovascular disease. Further research is necessary to validate these findings in diverse populations, with a particular focus on representation from national breast screening programmes.

The Clear Value of Coronary Artery Calcification Evaluation on Non-Gated Chest Computed Tomography for Cardiac Risk Stratification

To enhance risk stratification in patients suspected of coronary artery disease, the assessment of coronary artery calcium (CAC) could be incorporated, especially when CAC can be readily assessed on previously performed non-gated chest computed tomography (CT). Guidelines recommend reporting on patients' extent of CAC on these non-cardiac directed exams and various studies have shown the diagnostic and prognostic value. However, this method is still little applied, and no current consensus exists in clinical practice. This review aims to point out the clinical utility of different kinds of CAC assessment on non-gated CTs. It demonstrates that these scans indeed represent a merely untapped and underestimated resource for risk stratification in patients with stable chest pain or an increased risk of cardiovascular events. To our knowledge, this is the first review to describe the clinical utility of different kinds of visual CAC evaluation on non-gated unenhanced chest CT. Various methods of CAC assessment on non-gated CT are discussed and compared in terms of diagnostic and prognostic value. Furthermore, the application of these non-gated CT scans in the general practice of cardiology is discussed. The clinical utility of coronary calcium assessed on non-gated chest CT, according to the current literature, is evident. This resource of information for cardiac risk stratification needs no specific requirements for scan protocol, and is radiation-free and cost-free. However, some gaps in research remain. In conclusion, the integration of CAC on non-gated chest CT in general cardiology should be promoted and research on this method should be encouraged.

Thoracic Aortic Plaque Burden and Prediction of Cardiovascular Events in Patients Undergoing 320-row Multidetector CT Coronary Angiography

AIM

Wide volume scan (WVS) coronary computed tomography angiography (CCTA) enables aortic arch visualization. This study assessed whether the thoracic aortic plaque burden (TAPB) score can predict major cardiovascular adverse events (MACE) in addition to and independently of other obstructive coronary artery disease (CAD) attributes.

METHODS

This study included patients with suspected CAD who underwent CCTA (n=455). CCTA-WVS was used to assess CAD and the prognostic capacity of TAPB scores. Data analysis included the coronary artery calcification score (CACS), CAD status and extent, and TAPB score, calculated as the sum of plaque thickness and plaque angle at five thoracic aortic segments. The primary endpoint was MACE defined as a composite event comprised of ischemic stroke, acute coronary syndrome, and cardiovascular death.

RESULTS

During a mean follow-up period of 2.8±0.9 years, 40 of 455 (8.8%) patients experienced MACE. In the Cox proportional hazards model adjusted for clinical risks (Suita cardiovascular disease risk score), we identified TAPB score (T3) as a predictor of MACE independent of CACS ＞400 (hazards ratio [HR], 2.91; 95% confidence interval [CI], 1.26-6.72; p=0.012) or obstructive CAD (HR, 2.83; 95% CI, 1.30-6.18; p=0.009). The area under the curve for predicting MACE improved from 0.75 to 0.795 (p value=0.008) when TAPB score was added to CACS ＞400 and obstructive CAD.

CONCLUSIONS

We found that comprehensive non-invasive evaluation of TAPB and CAD has prognostic value in MACE risk stratification for suspected CAD patients undergoing CCTA.

Lesion-specific pericoronary adipose tissue CT attenuation improves risk prediction of major adverse cardiovascular events in coronary artery disease

OBJECTIVES

To determine whether lesion-specific pericoronary adipose tissue CT attenuation (PCATa) is superior to PCATa around the proximal right coronary artery (PCATa-RCA) and left anterior descending artery (PCATa-LAD) for major adverse cardiovascular events (MACE) prediction in coronary artery disease (CAD).

METHODS

Six hundred and eight CAD patients who underwent coronary CTA from January 2014 to December 2018 were retrospectively included, with clinical risk factors, plaque features, lesion-specific PCATa, PCATa-RCA, and PCATa-LAD collected. MACE was defined as cardiovascular death, non-fatal myocardial infarction, unplanned revascularization, and hospitalization for unstable angina. Four models were established, encapsulating traditional factors (Model A), traditional factors and PCATa-RCA (Model B), traditional factors and PCATa-LAD (Model C), and traditional factors and lesion-specific PCATa (Model D). Prognostic performance was evaluated with C-statistic, area under receiver operator characteristic curve (AUC), and net reclassification index (NRI).

RESULTS

Lesion-specific PCATa was an independent predictor for MACE (adjusted hazard ratio = 1.108, P < .001). The C-statistic increased from 0.750 for model A to 0.762 for model B (P = .078), 0.773 for model C (P = .046), and 0.791 for model D (P = .005). The AUC increased from 0.770 for model A to 0.793 for model B (P = .027), 0.793 for model C (P = .387), and 0.820 for model D (P = .019). Compared with model A, the NRIs for models B, C, and D were 0.243 (-0.323 to 0.792, P = .392), 0.428 (-0.012 to 0.835, P = .048), and 0.708 (0.152-1.016, P = .001), respectively.

CONCLUSIONS

Lesion-specific PCATa improves risk prediction of MACE in CAD, which is better than PCATa-RCA and PCATa-LAD.

ADVANCES IN KNOWLEDGE

Lesion-specific PCATa was superior to PCATa-RCA and PCATa-LAD for MACE prediction.

Fully Automated Agatston Score Calculation From Electrocardiography-Gated Cardiac Computed Tomography Using Deep Learning and Multi-Organ Segmentation: A Validation Study

To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calcium quantification was performed using a neural network based on mask regions with convolutional neural networks (R-CNNs) for multi-organ segmentation. Manual evaluation of calcium was carried out using proprietary software. This is a retrospective study of archived data. This study used 40 patients to train the segmentation model and 110 patients were used for the validation of the algorithm. The Pearson correlation coefficient between the reference actual and the computed predictive scores shows high level of correlation (0.84; P < .001) and high limits of agreement (±1.96 SD; -2000, 2000) in Bland-Altman plot analysis. The proposed method correctly classifies the risk group in 75.2% and classifies the subjects in the same group. In total, 81% of the predictive scores lie in the same categories and only seven patients out of 110 were more than one category off. For the presence/absence of coronary artery calcifications, the deep learning model achieved a sensitivity of 90% and a specificity of 94%. Fully automated model shows good correlation compared with reference standards. Automating process reduces evaluation time and optimizes clinical calcium scoring without additional resources.

Associating the Severity of Emphysema with Coronary Flow Reserve and Left Atrial Conduit Function for the Emphysema Patients with Known or Suspected Coronary Artery Disease

PURPOSE

Pulmonary emphysema may associate with ischemic heart disease through systemic microvascular abnormality as a common pathway. Stress cardiovascular MR (CMR) allows for the assessment of global coronary flow reserve (CFR). The purpose of this study was to evaluate the association between the emphysema severity and the multiple MRI parameters in the emphysema patients with known or suspected coronary artery disease (CAD).

METHODS

A total of 210 patients with known or suspected CAD who underwent both 3.0T CMR including cine CMR, stress and rest perfusion CMR, stress and rest phase-contrast (PC) cine CMR of coronary sinus, and late gadolinium enhancement (LGE) CMR, and lung CT within 6 months were studied. Global CFR, volumes and functions of both ventricles and atria, and presence or absence of myocardial ischemia and infarction were evaluated. Emphysema severity was visually determined on lung CT by Goddard method.

RESULT

Seventy nine (71.0 ± 7.9 years, 75 male) of 210 patients with known or suspected CAD had emphysema on lung CT. Goddard score was significantly correlated with CFR (r = -0.246, P = 0.029), left ventricular end-diastolic volume index (LV EDVI) (r = -0.230, P = 0.041), right ventricular systolic volume index (RV SVI) (r = -0.280, P = 0.012), left atrial (LA) total emptying volume index (r = -0.269, P = 0.017), LA passive emptying volume index (r = -0.309, P = 0.006), LA systolic strain (Es) (r = -0.244, P = 0.030), and LA conduit strain (Ee) (r = -0.285, P = 0.011) in the patients with emphysema. Multiple linear regression analysis revealed LA conduit function was independently associated with emphysema severity as determined by Goddard method (beta = -0.361, P = 0.006).

CONCLUSION

LA conduit function independently associates with emphysema severity in the emphysema patients with known or suspected CAD after adjusting age, sex, smoking, and the CMR indexes including CFR. These findings suggest that impairment of LA function predominantly occurs prior to the reduction of the CFR in the emphysema patients with known or suspected CAD.

Visual Ordinal Coronary Artery Calcium Score from Non-Gated Chest CT Predicts Mortality After Severe Chronic Obstructive Pulmonary Disease Exacerbation

Purpose

Chronic obstructive pulmonary disease (COPD) patients often undergo chest CT for various indications. Coronary artery calcium (CAC) can be quantified visually on ungated chest CT using an ordinal score that has been shown to correlate well with traditional Agatston CAC scoring. The prognostic role of CAC was studied mainly in stable COPD patients. We aim to study the association between ordinal CAC and mortality amongst patients admitted for acute exacerbation of COPD (AECOPD).

Patients and Methods

Retrospective study of AECOPD cases with no previous coronary revascularization admitted between 1st January 2016 to 30th June 2017 with a chest CT performed during admission or within 365 days prior. Ordinal CAC scoring (scale of 0-12) was performed by an experienced CT cardiologist blinded to patient data and outcomes. Patient demographics and future clinical events were retrieved from electronic medical records.

Results

There were 93 patients included (87.1% male, mean age 75 years) with the majority (59.1%) in GOLD Stage III. There were 21 (22.6%) patients with no CAC as well as 39 (41.9%) and 33 (35.5%) with ordinal CAC of 1-3 and 4-12, respectively. There were no significant differences in Charlson Comorbidity Index (CCI) and the proportion of patients with traditional cardiovascular risk factors (namely hypertension, dyslipidaemia, diabetes and smoking status) between the ordinal CAC score groups. Over a median follow-up period of 2.9 (1.1-3.9) years, there were 51 (54.8%) deaths. An ordinal CAC score of 4-12 was the only significant predictor of mortality after multivariate Cox-regression analysis adjustment for age, gender, body mass index, prior exacerbations, FEV1, cardiovascular risk factors and CCI [HR 3.944, (95% confidence interval 1.647-9.433, p = 0.002)].

Conclusion

Ordinal CAC measured from a current or recent ungated chest CT is an independent predictor of all-cause mortality in admitted AECOPD patients with no previous coronary revascularization.

Coronary and Extra-coronary Subclinical Atherosclerosis to Guide Lipid-Lowering Therapy

PURPOSE OF REVIEW

To discuss and review the technical considerations, fundamentals, and guideline-based indications for coronary artery calcium scoring, and the use of other non-invasive imaging modalities, such as extra-coronary calcification in cardiovascular risk prediction.

RECENT FINDINGS

The most robust evidence for the use of CAC scoring is in select individuals, 40-75 years of age, at borderline to intermediate 10-year ASCVD risk. Recent US recommendations support the use of CAC scoring in varying clinical scenarios. First, in adults with very high CAC scores (CAC ≥ 1000), the use of high-intensity statin therapy and, if necessary, guideline-based add-on LDL-C lowering therapies (ezetimibe, PCSK9-inhibitors) to achieve a ≥ 50% reduction in LDL-C and optimally an LDL-C < 70 mg/dL is recommended. In patients with a CAC score ≥ 100 at low risk of bleeding, the benefits of aspirin use may outweigh the risk of bleeding. Other applications of CAC scoring include risk estimation on non-contrast CT scans of the chest, risk prediction in younger patients (< 40 years of age), its value as a gatekeeper for the decision to perform nuclear stress testing, and to aid in risk stratification in patients presenting with low-risk chest pain. There is a correlation between extra-coronary calcification (e.g., breast arterial calcification, aortic calcification, and aortic valve calcification) and incident ASCVD events. However, its role in informing lipid management remains unclear. Identification of coronary calcium in selected patients is the single best non-invasive imaging modality to identify future ASCVD risk and inform lipid-lowering therapy decision-making.

Evaluation of Clinical Applicability of Coronary Artery Calcium Assessment on Non-Gated Chest Computed Tomography, Compared With the Classic Agatston Score on Cardiac Computed Tomography

Given current pretest probability (PTP) estimations tend to overestimate patients' risk for obstructive coronary artery disease, evaluation of patients' coronary artery calcium (CAC) is more precise. The value of CAC assessment with the Agatston score on cardiac computed tomography (CT) for risk estimation has been well indicated in patients with stable chest pain. CAC can be equally well assessed on routine non-gated chest CT, which is often available. This study aims to determine the clinical applicability of CAC assessment on non-gated CT in patients with stable chest pain compared with the classic Agatston score on gated CT. Consecutive patients referred for evaluation of the Agatston score, who had a previously performed non-gated chest CT for evaluation of noncardiac diseases, were included. CAC on non-gated CT was ordinally scored. Subsequently, patients were stratified according to CAC severity and PTP. The agreement and correlation between the classic Agatston score and CAC on non-gated CT were evaluated. The discriminative power for risk reclassification of both CAC assessment methods was assessed. Invasive coronary angiography was used as the gold standard, when available. A total of 140 patients aged between 30 and 88 years were included. The agreement between ordinally scored CAC and the Agatston score was excellent (κ = 0.82) and the correlation strong (r = 0.94). Most patients (80%) with an intermediate PTP had no or mild CAC on non-gated CT. They were reclassified at low risk with 100% accuracy compared with invasive coronary angiography. Similarly, 86% of patients had an Agatston score <300. These patients were reclassified with 98% accuracy. In patients with high PTP, the accuracy remained substantial and comparable, 94% and 89%, respectively. In conclusion, we believe this is the first study to assess the clinical applicability of CAC on non-gated CT in patients with stable chest pain, compared with the classic Agatston score. The agreement between methods was excellent and the correlation strong. Furthermore, CAC assessment on non-gated CT could reclassify patients' risk for obstructive coronary artery disease as accurately as could the classic Agatston score.

Recent advances in artificial intelligence for cardiac CT: Enhancing diagnosis and prognosis prediction

Recent advances in artificial intelligence (AI) for cardiac computed tomography (CT) have shown great potential in enhancing diagnosis and prognosis prediction in patients with cardiovascular disease. Deep learning, a type of machine learning, has revolutionized radiology by enabling automatic feature extraction and learning from large datasets, particularly in image-based applications. Thus, AI-driven techniques have enabled a faster analysis of cardiac CT examinations than when they are analyzed by humans, while maintaining reproducibility. However, further research and validation are required to fully assess the diagnostic performance, radiation dose-reduction capabilities, and clinical correctness of these AI-driven techniques in cardiac CT. This review article presents recent advances of AI in the field of cardiac CT, including deep-learning-based image reconstruction, coronary artery motion correction, automatic calcium scoring, automatic epicardial fat measurement, coronary artery stenosis diagnosis, fractional flow reserve prediction, and prognosis prediction, analyzes current limitations of these techniques and discusses future challenges.

Assessing cardiovascular risk with mammography and non-contrast chest CT: A review of the literature and clinical implications

Coronary artery disease (CAD) is the leading cause of mortality and disability globally. In the United States, about 7.2% of adults aged 20 and older are affected by CAD. However, due to its progression over decades, CAD is often undetected and unnoticed until plaque ruptures. This leads to partial or complete artery blockage, resulting in myocardial infarction. Thus, new screening methods for early detection of CAD are needed to prevent and minimize the morbidity and mortality from CAD. Vascular calcifications seen on mammography and non-contrast chest CT (NCCT) can be used for the early detection of CAD and are an accurate predictor of cardiovascular risk. This paper aims to review the basic epidemiology, pathophysiology, imaging findings, and correlation of long-term cardiovascular outcomes with vascular calcifications on mammography and NCCT.

Radiomics analysis of pericoronary adipose tissue based on plain CT for preliminary screening of coronary artery disease in patients with type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus (T2DM) is associated with a markedly increased prevalence of coronary artery disease (CAD). Radiomics features of pericoronary adipose tissue (PCAT) were correlated with inflammation, which may have potential value in the prediction of CAD.

PURPOSE

To determine whether radiomics analysis of PCAT captured by plain computed tomography (CT) could predict obstructive CAD in patients with T2DM.

MATERIAL AND METHODS

The study included 155 patients with T2DM with suspected CAD between January 2020 and December 2021. Volumes of right coronary artery of 10-50 mm were delineated in the plain CT to extract radiomics features and PCAT CT attenuation (PCATa). Least absolute shrinkage and selection operator was used to select the useful radiomics features to calculate the radiomics score (Rad-score). Univariate and multivariable logistic regression were applied to select independent predictors. The predictive performance was evaluated by the area under the receiver operating characteristics curve (AUC).

RESULTS

Rad-score (per 0.1 increments: odds ratio [OR] = 1.297; P < 0.001), coronary artery calcium score (CACS) (OR = 1.003; P = 0.037), and sex (OR = 3.245; P = 0.026) were identified as independent predictors for obstructive CAD. Rad-score (AUC = 0.835) outperformed CACS (AUC = 0.780), sex (AUC = 0.665), and PCATa (AUC = 0.550) in predicting obstructive CAD (P = 0.017 and 0.003 for Rad-score vs. sex and PCATa, respectively); however, the improvement between Rad-score and CACS had no statistical significance (P = 0.490).

CONCLUSION

Plain CT-derived Rad-score may be used as a preliminary screening tool for obstructive CAD in patients with T2DM.

Artificial intelligence using a deep learning versus expert computed tomography human reading in calcium score and coronary artery calcium data and reporting system classification

BACKGROUND

Artificial intelligence (AI) applied to cardiac imaging may provide improved processing, reading precision and advantages of automation. Coronary artery calcium (CAC) score testing is a standard stratification tool that is rapid and highly reproducible. We analyzed CAC results of 100 studies in order to determine the accuracy and correlation between the AI software (Coreline AVIEW, Seoul, South Korea) and expert level-3 computed tomography (CT) human CAC interpretation and its performance when coronary artery disease data and reporting system (coronary artery calcium data and reporting system) classification is applied.

METHODS

A total of 100 non-contrast calcium score images were selected by blinded randomization and processed with the AI software versus human level-3 CT reading. The results were compared and the Pearson correlation index was calculated. The CAC-DRS classification system was applied, and the cause of category reclassification was determined using an anatomical qualitative description by the readers.

RESULTS

The mean age was age 64.5 years, with 48% female. The absolute CAC scores between AI versus human reading demonstrated a highly significant correlation (Pearson coefficient R  = 0.996); however, despite these minimal CAC score differences, 14% of the patients had their CAC-DRS category reclassified. The main source of reclassification was observed in CAC-DRS 0-1, where 13 were recategorized, particularly between studies having a CAC Agatston score of 0 versus 1. Qualitative description of the errors showed that the main cause of misclassification was AI underestimation of right coronary calcium, AI overestimation of right ventricle densities and human underestimation of right coronary artery calcium.

CONCLUSION

Correlation between AI and human values is excellent with absolute numbers. When the CAC-DRS classification system was adopted, there was a strong correlation in the respective categories. Misclassified were predominantly in the category of CAC = 0, most often with minimal values of calcium volume. Additional algorithm optimization with enhanced sensitivity and specificity for low values of calcium volume will be required to enhance AI CAC score utilization for minimal disease. Over a broad range of calcium scores, AI software for calcium scoring had an excellent correlation compared to human expert reading and in rare cases determined calcium missed by human interpretation.

Cardiac Virtual Noncontrast Images for Calcium Quantification with Photon-counting Detector CT

Purpose

To assess the accuracy of aortic valve calcium (AVC), mitral annular calcium (MAC), and coronary artery calcium (CAC) quantification and risk stratification using virtual noncontrast (VNC) images from late enhancement photon-counting detector CT as compared with true noncontrast images.

Materials and Methods

This retrospective, institutional review board-approved study evaluated patients undergoing photon-counting detector CT between January and September 2022. VNC images were reconstructed from late enhancement cardiac scans at 60, 70, 80, and 90 keV using quantum iterative reconstruction (QIR) strengths of 2-4. AVC, MAC, and CAC were quantified on VNC images and compared with quantification of AVC, MAC, and CAC on true noncontrast images using Bland-Altman analyses, regression models, intraclass correlation coefficients (ICC), and Wilcoxon tests. Agreement between severe aortic stenosis likelihood categories and CAC risk categories determined from VNC and true noncontrast images was assessed by weighted κ analysis.

Results

Ninety patients were included (mean age, 80 years ± 8 [SD]; 49 male patients). Scores were similar on true noncontrast images and VNC images at 80 keV for AVC and MAC, regardless of QIR strengths, and VNC images at 70 keV with QIR 4 for CAC (all P > .05). The best results were achieved using VNC images at 80 keV with QIR 4 for AVC (mean difference, 3; ICC = 0.992; r = 0.98) and MAC (mean difference, 6; ICC = 0.998; r = 0.99), and VNC images at 70 keV with QIR 4 for CAC (mean difference, 28; ICC = 0.996; r = 0.99). Agreement between calcification categories was excellent on VNC images at 80 keV for AVC (κ = 0.974) and on VNC images at 70 keV for CAC (κ = 0.967).

Conclusion

VNC images from cardiac photon-counting detector CT enables patient risk stratification and accurate quantification of AVC, MAC, and CAC.Keywords: Coronary Arteries, Aortic Valve, Mitral Valve, Aortic Stenosis, Calcifications, Photon-counting Detector CT Supplemental material is available for this article © RSNA, 2023.

Significance of coronary artery calcification for predicting major adverse cardiovascular events: results from the NADESICO study in Japan

BACKGROUND

We aimed to determine the usefulness and sex differences of assessment of coronary artery calcification (CAC) with cardiovascular risk factors and major adverse cardiovascular events (MACE) in Japanese patients.

METHODS

In a nationwide, multicenter, prospective cohort study, 1187 patients with suspected coronary artery disease who underwent coronary computed tomography were enrolled. MACE included cardiovascular death, myocardial infarction, stroke, revascularization, and hospitalization for unstable angina, heart failure, or aortic disease. The concordance (C)-statistics were used to assess the relationships among the Suita risk score, CAC score, and incident MACE, with emphasis on sex differences.

RESULTS

The final analysis included 982 patients (mean age, 64.7 ± 6.6 years; 53.9 % male patients). MACE developed in 65 male and 21 female patients during a median follow-up of 1480 days. The C-statistics calculated using Suita score for MACE were 0.650, 0.633, and 0.569 in overall, male, and female patients, respectively. In overall patients, the C-statistic significantly increased in combined models of Agatston CAC scores of ≥100, 200, 300, or 400 and the Suita score. In each sex, the C-statistics significantly increased in the model that added an Agatston CAC score of ≥100 and ≥ 200 (+0.049 and + 0.057) in male patients, and ≥ 400 (+0.119) in females, respectively.

CONCLUSIONS

Adding assessment of Agatston CAC scores to Suita score was useful to improve the predictive ability for future MACE in Japanese patients. Agatston CAC scores of ≥100 or 200 in male and ≥ 400 in female patients in addition to Suita score improved the MACE risk prediction.

Computed tomographic angiography in coronary artery disease

Coronary computed tomographic angiography (CCTA) is becoming the first-line investigation for establishing the presence of coronary artery disease and, with fractional flow reserve (FFRCT), its haemodynamic significance. In patients without significant epicardial obstruction, its role is either to rule out atherosclerosis or to detect subclinical plaque that should be monitored for plaque progression/regression following prevention therapy and provide risk classification. Ischaemic non-obstructive coronary arteries are also expected to be assessed by non-invasive imaging, including CCTA. In patients with significant epicardial obstruction, CCTA can assist in planning revascularisation by determining the disease complexity, vessel size, lesion length and tissue composition of the atherosclerotic plaque, as well as the best fluoroscopic viewing angle; it may also help in selecting adjunctive percutaneous devices (e.g., rotational atherectomy) and in determining the best landing zone for stents or bypass grafts.

Role of plaque imaging for identification of vulnerable patients beyond the stage of myocardial ischemia

Chronic coronary syndrome (CCS) is a progressive disease, which often first manifests as acute coronary syndrome (ACS). Imaging modalities are clinically useful in making decisions about the management of patients with CCS. Accumulating evidence has demonstrated that myocardial ischemia is a surrogate marker for CCS management; however, its ability to predict cardiovascular death or nonfatal myocardial infarction is limited. Herein, we present a review that highlights the latest knowledge available on coronary syndromes and discuss the role and limitations of imaging modalities in the diagnosis and management of patients with coronary artery disease. This review covers the essential aspects of the role of imaging in assessing myocardial ischemia and coronary plaque burden and composition. Furthermore, recent clinical trials on lipid-lowering and anti-inflammatory therapies have been discussed. Additionally, it provides a comprehensive overview of intracoronary and noninvasive cardiovascular imaging modalities and an understanding of ACS and CCS, with a focus on histopathology and pathophysiology.

Coronary Artery Calcium Dispersion and Cause-Specific Mortality

Coronary artery calcium (CAC) measures subclinical atherosclerosis and improves risk stratification. CAC characteristics-including vessel(s) involved, number of vessels, volume, and density-have been shown to differentially impact risk. We assessed how dispersion-either the number of calcified vessels or CAC phenotype (diffuse, normal, and concentrated)-impacted cause-specific mortality. The CAC Consortium is a retrospective cohort of 66,636 participants without coronary heart disease (CHD) who underwent CAC scoring. This study included patients with CAC >0 (n = 28,147). CAC area, CAC density, and CAC phenotypes (derived from the index of diffusion = 1 - [CAC in most concentrated vessel/total Agatston score]) were calculated. The associations between CAC characteristics and cause-specific mortality were assessed. The participant details included (n = 28,147): mean age 58.3 years, 25% female, 89.6% White, and 66% had 2+ calcified vessels. Diabetes, hypertension, and hyperlipidemia were predictors of multivessel involvement (p <0.001). After controlling for the overall CAC score, those with 4-vessel CAC involvement had more CAC area and less dense calcifications than those with 1-vessel. There was a graded increase in all-cause and cardiovascular disease (CVD)- and CHD-specific mortality as the number of calcified vessels increased. Among those with ≥2 vessels involved (n = 18,516), a diffuse phenotype was associated with a higher CVD-specific mortality and had a trend toward higher all-cause and CHD-specific mortality than a concentrated CAC phenotype. Diffuse CAC involvement was characterized by less dense calcification, more CAC area, multiple coronary vessel involvement, and presence of certain traditional risk factors. There is a graded increase in all-cause and CVD- and CHD-specific mortality with increasing CAC dispersion.

The journal of cardiovascular computed tomography: A year in review: 2022

This review aims to summarize key articles published in the Journal of Cardiovascular Computed Tomography (JCCT) in 2022, focusing on those that had the most scientific and educational impact. The JCCT continues to expand; the number of submissions, published manuscripts, cited articles, article downloads, social media presence, and impact factor continues to grow. The articles selected by the Editorial Board of the JCCT in this review highlight the role of cardiovascular computed tomography (CCT) to detect subclinical atherosclerosis, assess the functional relevance of stenoses, and plan invasive coronary and valve procedures. A section is dedicated to CCT in infants and other patients with congenital heart disease, in women, and to the importance of training in CT. In addition, we highlight key consensus documents and guidelines published in JCCT last year. The Journal values the tremendous work by authors, reviewers, and editors to accomplish these contributions.

Obstructive Sleep Apnea as a Predictor of a Higher Risk of Significant Coronary Artery Disease Assessed Non-Invasively Using the Calcium Score

The aim of this study was to assess the coronary artery calcium score in patients with obstructive sleep apnea (OSA). The study group (group A) consisted of 62 patients with diagnosed obstructive sleep apnea (mean age: 59.12 ± 9.09 years, mean AHI index in polysomnography: 20.44 ± 13.22/h), and 62 people without diagnosed obstructive sleep apnea (mean age 59.50 ± 10.74 years) constituted the control group (group B). The risk of significant coronary artery disease was assessed in all patients, based on the measurement of the coronary artery calcium score (CACS) using computed tomography. The following cut-off points were used to assess the risk of significant coronary artery disease: CACS = 0—no risk, CACS 1–10—minimal risk, CACS 11–100—low risk, CACS 101–400—moderate risk, and CACS > 400—high risk. Group A was characterized by statistically significantly higher CACS than group B (550.25 ± 817.76 vs. 92.59 ± 164.56, p < 0.05). No risk of significant coronary artery disease was statistically significantly less frequent in group A than in group B (0.0% vs. 51.6%, p < 0.05). A high risk of significant coronary artery disease was statistically significantly more frequent in group A than in group B (40.3% vs. 4.8%, p < 0.05). In group A, patients with severe OSA and patients with moderate OSA had statistically significantly higher CACS than patients with mild OSA (910.04 ± 746.31, 833.35 ± 1129.87, 201.66 ± 192.04, p < 0.05). A statistically significant positive correlation was found between the AHI and CACS (r = 0.34, p < 0.05). The regression analysis showed that OSA, male gender, older age, type 2 diabetes, peripheral arterial disease, and smoking were independent risk factors for higher CACS values. AHI ≥ 14.9 was shown to be a predictor of a high risk of significant coronary artery disease with a sensitivity and specificity of 62.2% and 80.0%, respectively. In summary, obstructive sleep apnea should be considered an independent predictive factor of a high risk of significant coronary artery disease (based on the coronary artery calcium score).

2022 use of coronary computed tomographic angiography for patients presenting with acute chest pain to the emergency department: An expert consensus document of the Society of cardiovascular computed tomography (SCCT): Endorsed by the American College of Radiology (ACR) and North American Society for cardiovascular Imaging (NASCI)

Coronary computed tomography angiography (CTA) improves the quality of care for patients presenting with acute chest pain (ACP) to the emergency department (ED), particularly in patients with low to intermediate likelihood of acute coronary syndrome (ACS). The Society of Cardiovascular Computed Tomography Guidelines Committee was formed to develop recommendations for acquiring, interpreting, and reporting of coronary CTA to ensure appropriate, safe, and efficient use of this modality. Because of the increasing use of coronary CTA testing for the evaluation of ACP patients, the Committee has been charged with the development of the present document to assist physicians and technologists. These recommendations were produced as an educational tool for practitioners evaluating acute chest pain patients in the ED, in the interest of developing systematic standards of practice for coronary CTA based on the best available data or broad expert consensus. Due to the highly variable nature of medical care, approaches to patient selection, preparation, protocol selection, interpretation or reporting that differs from these guidelines may represent an appropriate variation based on a legitimate assessment of an individual patient's needs.

Coronary calcium scoring using virtual non-contrast reconstructions on a dual-layer spectral CT system: Feasibility in the clinical practice

PURPOSE

To evaluate the clinical applicability of a prototype virtual non-contrast (VNC) reconstruction algorithm based on coronary CT angiography (cCTA) to assess calcified coronary plaques by calcium scoring (CACS).

METHODS

Eighty consecutive patients suspected of coronary artery disease were retrospectively included. All patients underwent a cardiac CT using a dual-layer spectral-detector CT system. The standardized acquisition protocol included unenhanced CACS and cCTA. Datasets were acquired using 120 keV. VNC-reconstructions were calculated from the cCTA images at 2.5 mm (VNC group 1), 2.5 of 0.9 mm (group 2), and 0.9 mm (group 3) slice thickness. We compared the Agatston score and Coronary Artery Calcium Data and Reporting System (CAC-DRS) of all VNC reconstructions with the true non-contrast (TNC)-dataset as the gold standard.

RESULTS

In total, 73 patients were evaluated. Fifty patients (68.5 %) had a CACS > 0 based on TNC. We found a significant difference in the Agatston score comparing all VNC-reconstructions (1: 1.35, 2: 3.7, 3: 10.4) with the TNC dataset (3.8) (p < 0.001). Correlation analysis of the datasets showed an excellent correlation of the TNC results with the different VNC-reconstructions (r = 0.904-0.974, p < 0.001) with a slope of 1.89-2.53. Mean differences and limits of agreement by Bland-Altman analysis between TNC and group 1 were 83 and -196 to 362, respectively. By using the VNC-reconstructions, in group 1 23 patients (31.5 %), in group 2 10 (13.7 %), and in group 3 23 (31.5 %) were reclassified according to CAC-DRS compared to TNC. Classification according to CAC-DRS revealed a significant difference between TNC and group 1 (p = 0.024) and no significance compared to groups 2 and 3 (p = 0.670 and 0.273).

CONCLUSION

The investigated VNC reconstruction algorithm of routine cCTA allows the detection and evaluation of coronary calcium burden without the requirement for an additional acquisition of an unenhanced CT scan for CACS and, therefore, a reduction of radiation exposure.

German Radiological Society and the Professional Association of German Radiologists Position Paper on Coronary computed tomography: Clinical Evidence and Quality of Patient Care in Chronic Coronary Syndrome

This position paper is a joint statement of the German Radiological Society (DRG) and the Professional Association of German Radiologists (BDR), which reflects the current state of knowledge about coronary computed tomography. It is based on preclinical and clinical studies that have investigated the clinical relevance as well as the technical requirements and fundamentals of cardiac computed tomography. CITATION FORMAT: · Langenbach MC, Sandstede J, Sieren M et al. DRG and BDR Position Paper on Coronary CT: Clinical Evidence and Quality of Patient Care in Chronic Coronary Syndrome. Fortschr Röntgenstr 2023; 195: 115 - 133.

[German Radiological Society and the Professional Association of German Radiologists position paper on coronary computed tomography: clinical evidence and quality of patient care in chronic coronary syndrome]

This position paper is a joint statement of the German Radiological Society (DRG) and the Professional Association of German Radiologists (BDR), which reflects the current state of knowledge about coronary computed tomography (CT). It is based on preclinical and clinical studies that have investigated the clinical relevance as well as the technical requirements and fundamentals of cardiac computed tomography.

Benign incidental cardiac findings in chest and cardiac CT imaging

With the continuous expansion of the disease scope of chest CT and cardiac CT, the number of these CT examinations has increased rapidly. In addition to their common indications, many incidental cardiac findings can be observed when carefully evaluating the coronary arteries, valves, pericardium, ventricles, and large vessels. These findings may have clinical significance or risk of complications, but they are sometimes overlooked or may not be described in the final reports. Although most of the incidental findings are benign, timely detection and treatment can improve the management of chronic diseases or reduce the possibility of severe complications. In this review, we summarized the imaging findings, incidence rate, and clinical relevance of some benign cardiac findings such as coronary artery calcification, aortic and mitral valve calcification, aortic calcification, cardiac thrombus, myocardial bridge, aortic dilation, cardiac myxoma, pericardial cyst, and coronary artery fistula. Reporting incidental cardiac findings will help reduce the risk of severe complications or disease deterioration and contribute to the recovery of patients.

Incidental coronary artery calcification on non-gated CT thorax correlates with risk of cardiovascular events and death

OBJECTIVES

To assess coronary artery calcification (CAC) on non-contrast non-ECG-gated CT thorax (NC-NECG-CTT) and to evaluate its correlation with short-term risk of cardiovascular disease (CVD) events and death.

METHODS

Single-institution retrospective study including all patients 40-70 years old who underwent NC-NECG-CTT over a period of 6 months. Individuals with known CVD were excluded. The presence of CAC was assessed and quantified by the Agatston score (CACS). CAC severity was defined as mild (< 100), moderate (100-400), or severe (> 400). CVD events (including CVD death, myocardial infarction, revascularisation procedures, ischaemic stroke, acute peripheral atherosclerotic ischaemia), and all-cause mortality over a median of 3.5 years were recorded. Cox proportional-hazards regression modelling was performed including CACS, age, gender and CVD risk factors (smoking, hypertension, diabetes mellitus, dyslipidaemia, and family history of CVD).

RESULTS

Of the total 717 eligible cases, 325 (45%) had CAC. In patients without CAC, there was only one CVD event, compared to 26 CVD events including 5 deaths in patients with CAC. The presence and severity of CAC correlated with CVD events (p < 0.001). A CACS > 100 was significantly associated with both CVD events, hazard ratio (HR) 5.74, 95% confidence interval: 2.19-15.02; p < 0.001, and all-cause mortality, HR 1.7, 95% CI: 1.08-2.66; p = 0.02. Ever-smokers with CAC had a significantly higher risk for all-cause mortality compared to never-smokers (p = 0.03), but smoking status was not an independent predictor for CVD events in any subgroup category of CAC severity.

CONCLUSIONS

The presence and severity of CAC assessed on NC-NECG-CTT correlates with short-term cardiovascular events and death.

KEY POINTS

• Patients aged 40-70 years old without known CVD but with CAC on NC-NECG-CTT have a higher risk of CVD events compared to those without CAC. • CAC (Agatston) score above 100 confers a 5.7-fold increase in the risk of short-term CVD events in these patients. • The presence and severity of CAC on NC-NECG-CTT may have prognostic and therapeutic implications.

Extent of coronary atherosclerosis is associated with deterioration of left ventricular global longitudinal strain in patients with preserved ejection fraction undergoing coronary computed tomography angiography

Background

This study aimed to investigate the association between the extent and severity of coronary atherosclerosis, epicardial adipose tissue (EAT) accumulation, and left ventricular (LV) global longitudinal strain (GLS) in patients with preserved LV ejection fraction (LVEF) and without LV regional wall motion abnormalities.

Methods

This study included 169 preserved LVEF patients without LV wall motion abnormalities who underwent coronary computed tomography (CT) angiography for the assessment of suspected coronary artery disease (CAD). The segment stenosis score (SSS) and segment involvement score (SIS) were calculated to evaluate CAD extent. The EAT volume was defined as CT attenuation values ranging from -250 to -30 HU within the pericardial sac. LVGLS was measured using echocardiography to assess subclinical LV dysfunction.

Results

All patients had preserved LVEF of ≥50%, and the mean LVGLS was -18.7% (-20.5% to -16.9%). Mean SSS and SIS were 2.0 (0-5) and 4.0 (0-36), respectively, while mean EAT volume was 116.1 mL (22.9-282.5 mL). Multivariate analysis using linear regression model demonstrated that LVEF (β, -17.0; 95% CI, -20.9 - -13.1), LV mass index (β, 0.03; 95% CI, 0.01-0.06), and EAT volume (β, 0.010; 95% CI, 0.0020-0.0195) were independently associated with LVGLS; however, obstructive CAD was not. The multivariate models demonstrated that SSS (Î, 0.12; 95% CI, 0.05-0.18) and SIS (Î, 0.27; 95% CI, 0.10-0.44) were correlated with deterioration of LVGLS, independent of other parameters.

Conclusion

This study demonstrates that EAT volume and CAD extent are associated with the deterioration of LVGLS in this population.

Fully automated calcium scoring predicts all-cause mortality at 12 years in the MILD lung cancer screening trial

Coronary artery calcium (CAC) is a known risk factor for cardiovascular (CV) events and mortality but is not yet routinely evaluated in low-dose computed tomography (LDCT)-based lung cancer screening (LCS). The present analysis explored the capacity of a fully automated CAC scoring to predict 12-year mortality in the Multicentric Italian Lung Detection (MILD) LCS trial. The study included 2239 volunteers of the MILD trial who underwent a baseline LDCT from September 2005 to January 2011, with a median follow-up of 190 months. The CAC score was measured by a commercially available fully automated artificial intelligence (AI) software and stratified into five strata: 0, 1-10, 11-100, 101-400, and > 400. Twelve-year all-cause mortality was 8.5% (191/2239) overall, 3.2% with CAC = 0, 4.9% with CAC = 1-10, 8.0% with CAC = 11-100, 11.5% with CAC = 101-400, and 17% with CAC > 400. In Cox proportional hazards regression analysis, CAC > 400 was associated with a higher 12-year all-cause mortality both in a univariate model (hazard ratio, HR, 5.75 [95% confidence interval, CI, 2.08-15.92] compared to CAC = 0) and after adjustment for baseline confounders (HR, 3.80 [95%CI, 1.35-10.74] compared to CAC = 0). All-cause mortality significantly increased with increasing CAC (7% in CAC ≤ 400 vs. 17% in CAC > 400, Log-Rank p-value <0.001). Non-cancer at 12 years mortality was 3% (67/2239) overall, 0.8% with CAC = 0, 1.0% with CAC = 1-10, 2.9% with CAC = 11-100, 3.6% with CAC = 101-400, and 8.2% with CAC > 400 (Grey's test p < 0.001). In Fine and Gray's competing risk model, CAC > 400 predicted 12-year non-cancer mortality in a univariate model (sub-distribution hazard ratio, SHR, 10.62 [95% confidence interval, CI, 1.43-78.98] compared to CAC = 0), but the association was no longer significant after adjustment for baseline confounders. In conclusion, fully automated CAC scoring was effective in predicting all-cause mortality at 12 years in a LCS setting.

Cardiac computed tomographic imaging in cardio-oncology: An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT). Endorsed by the International Cardio-Oncology Society (ICOS)

Cardio-Oncology is a rapidly growing sub-specialty of medicine, however, there is very limited guidance on the use of cardiac CT (CCT) in the care of Cardio-Oncology patients. In order to fill in the existing gaps, this Expert Consensus statement comprised of a multidisciplinary collaboration of experts in Cardiology, Radiology, Cardiovascular Multimodality Imaging, Cardio-Oncology, Oncology and Radiation Oncology aims to summarize current evidence for CCT applications in Cardio-Oncology and provide practice recommendations for clinicians.

Coronary Artery Calcium Data and Reporting System (CAC-DRS): A Primer

The Coronary Artery Calcium Data and Reporting System (CAC-DRS) is a standardized reporting method for calcium scoring on computed tomography. CAC-DRS is applied on a per-patient basis and represents the total calcium score with the number of vessels involved. There are 4 risk categories ranging from CAC-DRS 0 to CAC-DRS 3. CAC-DRS also provides risk prediction and treatment recommendations for each category. The main strengths of CAC-DRS include a detailed and meaningful representation of CAC, improved communication between physicians, risk stratification, appropriate treatment recommendations, and uniform data collection, which provides a framework for education and research. The major limitations of CAC-DRS include a few missing components, an overly simple visual approach without any standard reference, and treatment recommendations lacking a basis in clinical trials. This consistent yet straightforward method has the potential to systemize CAC scoring in both gated and non-gated scans.

Cardiac adipose tissue volume assessed by computed tomography is a specific and independent predictor of early mortality and critical illness in COVID-19 in type 2-diabetic patients

BACKGROUND

Patients with type 2-diabetes mellitus (T2D), are characterized by visceral and ectopic adipose tissue expansion, leading to systemic chronic low-grade inflammation. As visceral adiposity is associated with severe COVID-19 irrespective of obesity, we aimed to evaluate and compare the predictive value for early intensive care or death of three fat depots (cardiac, visceral and subcutaneous) using computed tomography (CT) at admission for COVID-19 in consecutive patients with and without T2D.

METHODS

Two hundred and two patients admitted for COVID-19 were retrospectively included between February and June 2020 and distributed in two groups: T2D or non-diabetic controls. Chest CT with cardiac (CATi), visceral (VATi) and subcutaneous adipose tissue (SATi) volume measurements were performed at admission. The primary endpoint was a composite outcome criteria including death or ICU admission at day 21 after admission. Threshold values of adipose tissue components predicting adverse outcome were determined.

RESULTS

One hundred and eight controls [median age: 76(IQR:59-83), 61% male, median BMI: 24(22-27)] and ninety-four T2D patients [median age: 70(IQR:61-77), 70% male, median BMI: 27(24-31)], were enrolled in this study. At day 21 after admission, 42 patients (21%) had died from COVID-19, 48 (24%) required intensive care and 112 (55%) were admitted to a conventional care unit (CMU). In T2D, CATi was associated with early death or ICU independently from age, sex, BMI, dyslipidemia, CRP and coronary calcium (CAC). (p = 0.005). Concerning T2D patients, the cut-point for CATi was  > 100 mL/m² with a sensitivity of 0.83 and a specificity of 0.50 (AUC = 0.67, p = 0.004) and an OR of 4.71 for early ICU admission or mortality (p = 0.002) in the fully adjusted model. Other adipose tissues SATi or VATi were not significantly associated with early adverse outcomes. In control patients, age and male sex (OR = 1.03, p = 0.04) were the only predictors of ICU or death.

CONCLUSIONS

Cardiac adipose tissue volume measured in CT at admission was independently predictive of early intensive care or death in T2D patients with COVID-19 but not in non-diabetics. Such automated CT measurement could be used in routine in diabetic patients presenting with moderate to severe COVID-19 illness to optimize individual management and prevent critical evolution.