Coronary Calcium Characteristics as Predictors of Major Adverse Cardiac Events in Symptomatic Patients: Insights From the CORE 320 Multinational Study

Evaluating atherosclerosis prevalence via coronary calcium in executives with normal LDL levels in the US: a cohort study-the clear protocol

INTRODUCTION

The coronary artery calcium (CAC) scan serves as a crucial tool in assessing the risk of coronary atherosclerosis in patients with hyperlipidaemia, particularly when there is ambiguity surrounding pharmacotherapy decisions. In addition to CAC, advanced glycation end products (AGEs), glycated proteins and lipids involved in ageing are emerging as markers for atherosclerosis. However, the relationship between AGEs score and CAC scores has not been evaluated to date. Our primary objective is to evaluate abnormal CAC scores in patients with low and borderline ASCVD risk and normal low-density lipoprotein cholesterol (LDL-C) levels ≤100 mg/dL. The secondary objective is to explore potential associations between CAC and AGEs scores.

METHODS AND ANALYSIS

We will retrospectively review health records of adult patients seen at the General Internal Medicine Executive Health Program (Mayo Clinic; Rochester, Minnesota) between 1 September 2023 and 31 March 2024, where all patients were offered the option of a baseline CAC scan. For our primary aim, we will determine the percentage of patients with low and borderline 10-year Atherosclerotic Cardiovascular Disease (ASCVD) risk, not receiving pharmacotherapy for hyperlipidaemia, who have LDL-C levels ≤100 mg/dL and have an abnormal CAC score. For our secondary aim, we will examine potential associations between CAC and AGEs scores.

ETHICS AND DISSEMINATION

This study was determined to be exempt from institutional review board approval (ID 24-0 03 921; 45 CFR 46.104d, category/subcategory 4(iii)) at the Mayo Clinic, Rochester. The findings of this study will be published in a peer-reviewed journal.

Opportunistic assessment of abdominal aortic calcification using artificial intelligence (AI) predicts coronary artery disease and cardiovascular events

BACKGROUND

Abdominal computed tomography (CT) is commonly performed in adults. Abdominal aortic calcification (AAC) can be visualized and quantified using artificial intelligence (AI) on CTs performed for other clinical purposes (opportunistic CT). We sought to investigate the value of AI-enabled AAC quantification as a predictor of coronary artery disease and its association with cardiovascular events.

METHODS

A fully automated AI algorithm to quantify AAC from the diaphragm to aortic bifurcation using the Agatston score was retrospectively applied to a cohort of patient that underwent both noncontrast abdominal CT for routine clinical care and cardiac CT for coronary artery calcification (CAC) assessment. Subjects were followed for a median of 36 months for major adverse cardiovascular events (MACE, composite of death, myocardial infarction [MI], ischemic stroke, coronary revascularization) and major coronary events (MCE, MI or coronary revascularization). The 10-year Predicting Risk of cardiovascular disease EVENTs (PREVENT) cardiovascular risk score was calculated.

RESULTS

Our cohort included 3599 patients (median age 61 years, 49% female, 73% white) with an evaluable abdominal and cardiac CT. There was a positive correlation between presence and severity of AAC and CAC (r = 0.56, P < .001). AAC showed excellent discriminatory power for detecting or ruling out any CAC (AUC for PREVENT risk score 0.701 [0.683-0.718]; AUC for PREVENT plus AAC 0.782 [0.767-0.797]; P < .001). There were 324 MACE, of which 246 were MCE. Following adjustment for the PREVENT score, the presence of AAC was associated with a significant risk of MACE (adjHR 2.26, 95% CI 1.67-3.07, P < .001) and MCE (adjHR 2.58, 95% CI 1.80-3.71, P < .001). A doubling of the AAC score resulted in an 11% increase in the risk of MACE and a 13% increase in the risk of MCE.

CONCLUSIONS

Using opportunistic abdominal CTs, assessment of AAC using a fully automated AI algorithm, predicted CAC and was independently associated with cardiovascular events. These data support the use of opportunistic imaging for cardiovascular risk assessment. Future studies should investigate whether opportunistic imaging can help guide appropriate cardiovascular prevention strategies.

Progression of coronary artery calcium density and major adverse cardiovascular events

BACKGROUND AND AIMS

We aimed to investigate the relationship between coronary artery calcium (CAC) density progression and major adverse cardiovascular events (MACE), and the prognostic value of CAC density progression.

METHODS

Patients with serial CAC scans were enrolled in this study. CAC density was directly measured in calcified lesions. Change and rate of progression of CAC density were calculated. Cox proportional hazard regression was utilized to estimate hazard ratios (HRs) for time to MACE regarding CAC density. The incremental prognostic value and the reclassification ability of CAC density progression were evaluated using the C-index and continuous net reclassification index (NRI).

RESULTS

304 patients (57.86 ± 9.47 years, 69.4 % male) were included. There were 47 MACE over a follow-up period of 76.00 (56.00-95.00) months. After adjustment for risk factors and CAC volume, the change of CAC density was inversely associated with MACE (per 10HU: HR: 0.956, 95 % confidence interval: 0.920-0.992, p = 0.018). Adding the change of CAC density to risk factors and baseline CAC density improved the C-index (0.694 vs. 0.678, p = 0.026). Adding the change of CAC density improved reclassification of MACE compared with risk factors and baseline CAC density [NRI = 0.432 (0.016-0.789)].

CONCLUSIONS

CAC density progression is inversely associated with MACE. The addition of the change of CAC density improves prognostic value compared to baseline risk factors and CAC density and optimizes risk reclassification.

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.

Coronary artery calcification burden, atherogenic index of plasma, and risk of adverse cardiovascular events in the general population: evidence from a mediation analysis

BACKGROUND

Dyslipidemia and abnormal cholesterol metabolism are closely related to coronary artery calcification (CAC) and are also critical factors in cardiovascular disease death. In recent years, the atherogenic index of plasma (AIP) has been widely used to evaluate vascular sclerosis. This study aimed to investigate the potential association of AIP between CAC and major adverse cardiovascular events (MACEs).

METHODS

This study included 1,121 participants whose CACs were measured by multislice spiral CT. Participants' CAC Agatston score, CAC mass, CAC volume, and number of vessels with CACs were assessed. AIP is defined as the base 10 logarithm of the ratio of triglyceride (TG) concentration to high-density lipoprotein-cholesterol (HDL-C) concentration. We investigated the multivariate-adjusted associations between AIP, CAC, and MACEs. The mediating role of the AIP in CAC and MACEs was subsequently discussed.

RESULTS

During a median follow-up of 31 months, 74 MACEs were identified. For each additional unit of log-converted CAC, the MACE risk increased by 48% (HR 1.48 [95% CI 1.32-1.65]). For each additional unit of the AIP (multiplied by 10), the MACEs risk increased by 19%. Causal mediation analysis revealed that the AIP played a partial mediating role between CAC (CAC Agatston score, CAC mass) and MACEs, and the mediating proportions were 8.16% and 16.5%, respectively. However, the mediating effect of CAC volume tended to be nonsignificant (P = 0.137).

CONCLUSIONS

An increased AIP can be a risk factor for CAC and MACEs. Biomarkers based on lipid ratios are a readily available and low-cost strategy for identifying MACEs and mediating the association between CAC and MACEs. These findings provide a new perspective on CAC treatment, early diagnosis, and prevention of MACEs.

Plaque Characteristics Derived from Intravascular Optical Coherence Tomography That Predict Cardiovascular Death

This study aimed to investigate whether plaque characteristics derived from intravascular optical coherence tomography (IVOCT) could predict a long-term cardiovascular (CV) death. This study was a single-center, retrospective study on 104 patients who had undergone IVOCT-guided percutaneous coronary intervention. Plaque characterization was performed using Optical Coherence TOmography PlaqUe and Stent (OCTOPUS) software developed by our group. A total of 31 plaque features, including lesion length, lumen, calcium, fibrous cap (FC), and vulnerable plaque features (e.g., microchannel), were computed from the baseline IVOCT images. The discriminatory power for predicting CV death was determined using univariate/multivariate logistic regressions. Of 104 patients, CV death was identified in 24 patients (23.1%). Univariate logistic regression revealed that lesion length, calcium angle, calcium thickness, FC angle, FC area, and FC surface area were significantly associated with CV death (p < 0.05). In the multivariate logistic analysis, only the FC surface area (OR 2.38, CI 0.98-5.83, p < 0.05) was identified as a significant determinant for CV death, highlighting the importance of the 3D lesion analysis. The AUC of FC surface area for predicting CV death was 0.851 (95% CI 0.800-0.927, p < 0.05). Patients with CV death had distinct plaque characteristics (i.e., large FC surface area) in IVOCT. Studies such as this one might someday lead to recommendations for pharmaceutical and interventional approaches.

Coronary artery calcium quantification technique using dual energy material decomposition: a simulation study

Coronary artery calcification is a significant predictor of cardiovascular disease, with current detection methods like Agatston scoring having limitations in sensitivity. This study aimed to evaluate the effectiveness of a novel CAC quantification method using dual-energy material decomposition, particularly its ability to detect low-density calcium and microcalcifications. A simulation study was conducted comparing the dual-energy material decomposition technique against the established Agatston scoring method and the newer volume fraction calcium mass technique. Detection accuracy and calcium mass measurement were the primary evaluation metrics. The dual-energy material decomposition technique demonstrated fewer false negatives than both Agatston scoring and volume fraction calcium mass, indicating higher sensitivity. In low-density phantom measurements, material decomposition resulted in only 7.41% false-negative (CAC = 0) measurements compared to 83.95% for Agatston scoring. For high-density phantoms, false negatives were removed (0.0%) compared to 20.99% in Agatston scoring. The dual-energy material decomposition technique presents a more sensitive and reliable method for CAC quantification.

Physical activity and the heart: from well-established cardiovascular benefits to possible adverse effects

The favorable effects of physical activity on the cardiovascular system have been well described in scientific literature. Physical activity reduces cardiovascular morbidity and mortality in both healthy subjects and in patients with cardiovascular disease. However, different intensity levels of physical activity have a different impact on the cardiovascular system. Some data support the hypothesis of a "physical activity paradox": repetitive exposure to vigorous physical activity may induce biological effects that counteract the benefits of moderate intensity levels of physical activity. In this review, we report the main effects of acute and chronic physical activity on the cardiovascular system and we summarize the biochemical mechanisms that may explain these effects.

Machine learning algorithms to predict major adverse cardiovascular events in patients with diabetes

BACKGROUND

Major Adverse Cardiovascular Events (MACE) are common complications of type 2 diabetes mellitus (T2DM) that include myocardial infarction (MI), stroke, and heart failure (HF). The objective of the current study was to predict MACE among T2DM patients.

METHODS

Type 2 diabetes mellitus patients above 18 years old were recruited for the study from the All of Us Research Program. Eligible participants were those who took sodium-glucose cotransporter 2 inhibitors. Different Machine learning algorithms: including RandomForest (RF), XGBoost, logistic regression (LR), and weighted ensemble model (WEM) were employed. Clinical attributes, electrolytes and biomarkers were explored in predicting MACE. The feature importance was determined using mean decrease accuracy.

RESULTS

Overall, 9, 059 subjects were included in the analyses, of which 5197 (57.4%) were females. The XGBoost Model demonstrated a prediction accuracy of 0.80 [0.78-0.82], which is higher as compared to the RF 0.78[0.76-0.80], the LR model 0.65 [0.62-0.67], and the WEM 0.75 [0.73-0.76], respectively. The classification accuracy of the models for stroke was more than 95%, which was higher than prediction accuracy for MI (∼85%), and HF (∼80%). Phosphate, blood urea nitrogen and troponin levels were the major predictors of MACE.

CONCLUSION

The ML models had shown acceptable performance in predicting MACE in T2DM patients, except the LR model. Phosphate, blood urea nitrogen, and other electrolytes were important predictors of MACE, which is consistent between the individual components of MACE, such as stroke, MI, and HF. These parameters can be calibrated as prognostic parameters of MACE events in T2DM patients.

Integrated intensity-based technique for coronary artery calcium mass measurement: A phantom study

BACKGROUND

Agatston scoring, the traditional method for measuring coronary artery calcium, is limited in its ability to accurately quantify low-density calcifications, among other things. The inaccuracy of Agatston scoring is likely due partly to the arbitrary thresholding requirement of Agatston scoring.

PURPOSE

A calcium quantification technique that removes the need for arbitrary thresholding and is more accurate, sensitive, reproducible, and robust is needed. Improvements to calcium scoring will likely improve patient risk stratification and outcome.

METHODS

The integrated Hounsfield technique was adapted for calcium scoring (integrated calcium mass). Integrated calcium mass requires no thresholding and includes all calcium information within an image. This study utilized phantom images acquired by G van Praagh et al., with calcium hydroxyapatite (HA) densities in the range of 200-800 mgHAcm-3 to measure calcium according to integrated calcium mass and Agatston scoring. The calcium mass was known, which allowed for accuracy, reproducibility, sensitivity, and robustness comparisons between integrated calcium mass and Agatston scoring. Multiple CT vendors (Canon, GE, Philips, Siemens) were used during the image acquisition phase, which provided a more robust comparison between the two calcium scoring techniques. Three calcification inserts of different diameters (1, 3, and 5 mm) and different HA densities (200, 400, and 800 mgHAcm-3 ) were placed within the phantom. The effect of motion was also analyzed using a dynamic phantom. All dynamic phantom calcium inserts were 5.0 ± 0.1 mm in diameter with a length of 10.0 ± 0.1 mm. The four different densities were 196 ± 3, 380 ± 2, 408 ± 2, and 800 ± 2 mgHAcm-3 .

RESULTS

Integrated calcium mass was more accurate than Agatston scoring for stationary scans (R M S E I n t e g r a t e d = 2.87 $RMS{E}_{Integrated} = 2.87$ ,R M S E A g a t s o n = 4.07 $RMS{E}_{Agatson} = 4.07$ ) and motion affected scans (R M S E I n t e g r a t e d = 9.70 $RMS{E}_{Integrated} = 9.70$ ,R M S E A g a t s o n = 19.98 $RMS{E}_{Agatson} = 19.98$ ). On average, integrated calcium mass was more reproducible than Agatston scoring for two of the CT vendors. The percentage of false-negative and false-positive calcium scores were lower for integrated calcium mass (15.00%, 0.00%) than Agatston scoring (28.33%, 6.67%). Integrated calcium mass was more robust to changes in scan parameters than Agatston scoring.

CONCLUSIONS

The results of this study indicate that integrated calcium mass is more accurate, reproducible, and sensitive than Agatston scoring on a variety of different CT vendors. The substantial reduction in false-negative scores for integrated calcium mass is likely to improve risk-stratification for patients undergoing calcium scoring and their potential outcome.

The novel H2VK-65 clinical risk assessment tool predicts high coronary artery calcium score in symptomatic patients referred for coronary computed tomography angiography

Background

Coronary computed tomographic angiography (CCTA) has emerged as a powerful imaging modality for the detection and prognostication of individuals with suspected coronary artery disease (CAD). High amounts of coronary artery calcium (CAC) significantly obscure the interpretation of CCTA. Clinical risk assessment tools and data specific to predictors of high CAC in symptomatic patients are limited.

Methods

Consecutive patients who underwent CAC scan and CCTA to diagnose CAD during 2016-2020 were included. A high CAC score was defined as >400 by Agatston method. Univariate and multivariate analyses were performed to determine the predictors of high CAC. The clinical risk score was derived from factors independently associated with high CAC. The derivation cohort was composed of 465 patients; this score was validated in 98 patients.

Results

The mean age was 63 ± 11 years, 53% were female, and 15.9% had high CAC scores. The independent predictors of high CAC scores were age >65 years (odds ratio [OR] 3.02, 95% confidence interval (95%CI) 1.56-5.85, p = 0.001), chronic kidney disease (CKD) (OR 11.09, 95%CI 3.38-36.38, p < 0.001), heart failure (OR 6.52, 95%CI 2.23-19.09, p = 0.001), hypertension (OR 26.44, 95%CI 9.02-77.44, p < 0.001), and vascular diseases, including ischemic stroke/transient ischemic attack and peripheral arterial disease (OR 20.96, 95%CI 4.19-104.86, p < 0.001). The H₂VK-65 (Hypertension, Heart failure, Vascular diseases, CKD, and Age > 65) score allocates 1 point for age >65, 2 points for CKD or heart failure, and 3 points for hypertension or vascular diseases. Using a threshold of ≥4 points, the sensitivity and specificity to detect high CAC was 81% and 80%, respectively. The area under the curve was 0.88 and 0.85 in the derivation and validation cohorts, respectively.

Conclusion

The novel H₂VK-65 score demonstrated good performance for predicting high CAC scores in symptomatic patients referred for CCTA.

Coronary artery calcium mass measurement based on integrated intensity and volume fraction techniques

Purpose

Agatston scoring does not detect all the calcium present in computed tomography scans of the heart. A technique that removes the need for thresholding and quantifies calcium mass more accurately and reproducibly is needed.

Approach

Integrated intensity and volume fraction techniques were evaluated for accurate quantification of calcium mass. Integrated intensity calcium mass, volume fraction calcium mass, Agatston scoring, and spatially weighted calcium scoring were compared with known calcium mass in simulated and physical phantoms. The simulation was created to match a 320-slice CT scanner. Fat rings were added to the simulated phantoms, which resulted in small (30 × 20    cm 2 ), medium (35 × 25    cm 2 ), and large (40 × 30    cm 2 ) phantoms. Three calcification inserts of different diameters and hydroxyapatite densities were placed within the phantoms. All the calcium mass measurements were repeated across different beam energies, patient sizes, insert sizes, and densities. Physical phantom images from a previously reported study were then used to evaluate the accuracy and reproducibility of the techniques.

Results

Both integrated intensity calcium mass and volume fraction calcium mass yielded lower root mean squared error (RMSE) and deviation (RMSD) values than Agatston scoring in all the measurements in the simulated phantoms. Specifically, integrated calcium mass (RMSE: 0.49 mg, RMSD: 0.49 mg) and volume fraction calcium mass (RMSE: 0.58 mg, RMSD: 0.57 mg) were more accurate for the low-density stationary calcium measurements than Agatston scoring (RMSE: 3.70 mg, RMSD: 2.30 mg). Similarly, integrated calcium mass (15.74%) and volume fraction calcium mass (20.37%) had fewer false-negative (CAC = 0) measurements than Agatston scoring (75.00%) and spatially weighted calcium scoring (26.85%), on the low-density stationary calcium measurements.

Conclusion

The integrated calcium mass and volume fraction calcium mass techniques can potentially improve risk stratification for patients undergoing calcium scoring and further improve risk assessment compared with Agatston scoring.

Automated cardiovascular risk categorization through AI-driven coronary calcium quantification in cardiac PET acquired attenuation correction CT

BACKGROUND

We present an automatic method for coronary artery calcium (CAC) quantification and cardiovascular risk categorization in CT attenuation correction (CTAC) scans acquired at rest and stress during cardiac PET/CT. The method segments CAC according to visual assessment rather than the commonly used CT-number threshold.

METHODS

The method decomposes an image containing CAC into a synthetic image without CAC and an image showing only CAC. Extensive evaluation was performed in a set of 98 patients, each having rest and stress CTAC scans and a dedicated calcium scoring CT (CSCT). Standard manual calcium scoring in CSCT provided the reference standard.

RESULTS

The interscan reproducibility of CAC quantification computed as average absolute relative differences between CTAC and CSCT scan pairs was 75% and 85% at rest and stress using the automatic method compared to 121% and 114% using clinical calcium scoring. Agreement between automatic risk assessment in CTAC and clinical risk categorization in CSCT resulted in linearly weighted kappa of 0.65 compared to 0.40 between CTAC and CSCT using clinically used calcium scoring.

CONCLUSION

The increased interscan reproducibility achieved by our method may allow routine cardiovascular risk assessment in CTAC, potentially relieving the need for dedicated CSCT.

Can Serum Fetuin-A be Used as a Marker for Cardiovascular Involvement in Psoriatic Patients?

Background

Psoriasis is a systemic inflammatory disorder. It is associated with increased risk of developing other chronic health diseases such cardiovascular disorders. Fetuin A is a glycoprotein that is present in blood serum. It may prevent vascular calcification by forming calciprotien particles; which are formed from their attachment with phosphate and calcium complexes.

Aim

The aim of this study was to measure serum Fetuin A in Psoriatic patients and correlate its level with cardiac events and risks in these patients using CT calcium (Ca) scoring.

Patients and Methods

24 psoriatic patients (healthy without apparent cardiac risks to detect subclinical events if present) and 24 age and sex matched controls were tested for serum Fetuin A and underwent coronary calcium scoring by multidetector computed tomography (CT) scan. Psoriasis area and severity index (PASI) score for each patient was measured and was correlated with serum Fetuin A and CT calcium (Ca) scoring. Serum Fetuin A was compared between cases and controls and was correlated with coronary calcium score.

Results

There was highly statistically significant decrease in serum Fetuin A level in psoriatic group compared to control group (P-value < .001). There was highly statistically significant negative correlation between calcium score and the level of serum Fetuin A (P-value < .001). No statistically significant correlation was found between the serum level of Fetuin A and the psoriasis severity.

Conclusion

Serum Fetuin A is a simple, easy diagnostic tool to evaluate subclinical atherosclerosis in psoriatic patients.

Performance of visual, manual, and automatic coronary calcium scoring of cardiac 13N-ammonia PET/low dose CT

BACKGROUND

Coronary artery calcium is a well-known predictor of major adverse cardiac events and is usually scored manually from dedicated, ECG-triggered calcium scoring CT (CSCT) scans. In clinical practice, a myocardial perfusion PET scan is accompanied by a non-ECG triggered low dose CT (LDCT) scan. In this study, we investigated the accuracy of patients' cardiovascular risk categorisation based on manual, visual, and automatic AI calcium scoring using the LDCT scan.

METHODS

We retrospectively enrolled 213 patients. Each patient received a 13N-ammonia PET scan, an LDCT scan, and a CSCT scan as the gold standard. All LDCT and CSCT scans were scored manually, visually, and automatically. For the manual scoring, we used vendor recommended software (Syngo.via, Siemens). For visual scoring a 6-points risk scale was used (0; 1-10; 11-100; 101-400; 401-100; > 1 000 Agatston score). The automatic scoring was performed with deep learning software (Syngo.via, Siemens). All manual and automatic Agatston scores were converted to the 6-point risk scale. Manual CSCT scoring was used as a reference.

RESULTS

The agreement of manual and automatic LDCT scoring with the reference was low [weighted kappa 0.59 (95% CI 0.53-0.65); 0.50 (95% CI 0.44-0.56), respectively], but the agreement of visual LDCT scoring was strong [0.82 (95% CI 0.77-0.86)].

CONCLUSIONS

Compared with the gold standard manual CSCT scoring, visual LDCT scoring outperformed manual LDCT and automatic LDCT scoring.

Myocardial Fibrosis and Coronary Calcifications Caused by Endurance Exercise? Insights from Former Professional Cyclists

PURPOSE

This study aimed to compare the prevalence of myocardial fibrosis and coronary calcification in individuals who have performed very high levels of strenuous endurance exercise (SEE; former male professional cyclists) and sex/age-matched controls.

METHODS

We used a retrospective cohort study design, where cases were former finishers of ≥1 Grand Tour (Tour de France, Giro d' Italia or Vuelta a España) and controls were untrained individuals free of cardiovascular risk. All participants underwent cardiac magnetic resonance and cardiac computer tomography in the same center during years 2020-2021 to detect myocardial fibrosis (late gadolinium enhancement) and to quantify coronary calcium, respectively.

RESULTS

Twenty-three cases (age, 46 ± 6 yr) and 59 controls (47 ± 7 yr) were studied. Fibrotic patches were evidenced only in the left ventricle, with a higher prevalence in cases (23% vs 2% in controls, P = 0.006). However, fibrotic tissue was nonischemic and of low extension (0.6% ± 0.4% of left ventricle mass), and no significant differences were found between cases and controls for native T1 or T2 values. No between-group differences were found for coronary calcium indicators, including Agatston or density scores. Subanalyses revealed no differences attending to whether cases were still performing regular SEE ( n = 8) or not ( n = 15) after professional retirement.

CONCLUSIONS

Although former professional cyclists seemed to show a greater prevalence of myocardial fibrosis, the extension of fibrotic tissue was minimal and no alterations were found in coronary calcification indicators. While keeping in mind the low sample size of the cases' group, our results do not support evidence for major cardiac maladaptations with long-term exposure to SEE, at least in middle-age adults.

Association between plaque localization in proximal coronary segments and MACE outcomes in patients with mild CAC: Results from the EISNER study

Objective

Coronary artery calcium score (CAC) is a validated tool to predict and reclassify cardiovascular risk. Additional metrics such as regional distribution and extent of CAC over Agatston CAC score may allow further risk stratification. In this study, we evaluate the prognostic significance of proximal CAC involvement in asymptomatic population from the prospective EISNER (Early-Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) registry, focusing on patients with mild CAC (score 1-99).

Methods

This study included a total of 2,047 adult asymptomatic subject who underwent baseline CAC scan and 14-year follow-up for MACE, defined as myocardial infarction, late revascularization, or cardiac death. Proximal involvement was defined as presence of CAC in the LM, proximal LAD, LCX or RCA. CAC was categorized as 0, 1-99, and ≥100.

Results

1,090 (53.2%) subjects had no CAC, 576 (28.1%) had CAC 1-99, and 381 (18.7%) had CAC ≥100. Proximal involvement was seen in 67.2% of subjects with CAC 1-99 and 97.3% of subjects with CAC ≥100. In the CAC 1-99 category, the presence of proximal CAC was associated with increased MACE risk after adjustment for CAC score, CAC extent and conventional risk factors compared to those without proximal CAC (HR: 2.84 95% CI: 1.29-6.25, p=0.009).

Conclusion

In asymptomatic subjects with CAC scores of 1-99, the presence and extent of proximal CAC plaques provides strong independent prognostic information in predicting MACE

Evolving Role of Calcium Density in Coronary Artery Calcium Scoring and Atherosclerotic Cardiovascular Disease Risk

Coronary artery calcium (CAC) is a specific marker of coronary atherosclerosis that can be used to measure calcified subclinical atherosclerotic burden. The Agatston method is the most widely used scoring algorithm for quantifying CAC and is expressed as the product of total calcium area and a quantized peak calcium density weighting factor defined by the calcification attenuation in HU on noncontrast computed tomography. Calcium density has emerged as an important area of inquiry because the Agatston score is upweighted based on the assumption that peak calcium density and atherosclerotic cardiovascular disease (ASCVD) risk are positively correlated. However, recent evidence demonstrates that calcium density is inversely associated with lesion vulnerability and ASCVD risk in population-based cohorts when accounting for age and plaque area. Here, we review calcium density by focusing on 3 main areas: 1) CAC scan acquisition parameters; 2) pathophysiology of calcified plaques; and 3) epidemiologic evidence relating calcium density to ASCVD outcomes. Through this process, we hope to provide further insight into the evolution of CAC scoring on noncontrast computed tomography.

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.

Long-Term Clinical Outcomes of New-Generation Drug-Eluting Stents in Coronary Artery Disease: A Real-World Observational Study

BACKGROUND

Treating vessels with a very small reference vessel diameter (RVD) in coronary artery disease is challenging.

OBJECTIVE

Long-term evaluation of new-generation drug-eluting stents (DESs) for the treatment of coronary lesions with different RVDs.

METHODS

From April 2009 to March 2019, 780 patients who underwent single coronary stenting were divided into ≤ 2.25 (very small), 2.5-3.0 (small), and ≥ 3.5 mm (large) DES groups after 1:2:2 propensity score matching. The primary endpoint was target lesion failure (TLF), and the secondary endpoints were major adverse cardiac events (MACEs) and stent thrombosis (ST).

RESULTS

During 3 years after new-generation DES implantation, TLF and MACE rates were significantly lower in the very small DES group. The risk of TLF was significantly lower in the very small DES group compared to the small DES group [very small vs. small: TLF, adjusted hazard ratio (HR) = 0.282, p = 0.040]. The risks of MACEs and all-cause mortality were significantly lower in the very small DES group compared to the small DES group (very small vs. small: MACEs, adjusted HR = 0.215, p = 0.001; all-cause mortality, adjusted HR = 0.181, p = 0.005). The cumulative incidence rates of TLF-free (log-rank test p = 0.001) and MACE-free (log-rank test p < 0.001) survival were significantly different among the groups, and the very small DES group had a high event-free survival rate. No cases of ST occurred in any group.

CONCLUSIONS

Our results indicate that the use of new-generation DESs for treating coronary lesions in very small vessels is safe and effective.

Coronary artery calcium score above 250 confirms the presence of significant stenosis in coronary CT angiography of symptomatic patients

OBJECTIVES

Evaluation of coronary artery calcium score (CACS) at multiple low and high cutoff values for the detection of significant coronary stenosis at two different cutoffs (50 and 70%) in a large number of symptomatic patients was not investigated previously in one study. This study aims to investigate if there are a correlation and statistical significance between different CACS cutoffs and the severity of coronary artery stenosis by coronary CT angiography (CCTA) in symptomatic patients.

METHODS

This is a retrospective study that included all symptomatic patients who had CCTA in a tertiary care hospital over a period of 7 years.

RESULTS

CCTA of 502 patients was evaluated (406 included, mean age 56.2 years); 230 were males (56.7%). The prevalence of stenosis at any percentage was 53.7%, ≥50% was 26.6% and ≥70% was 12.3%. The mean CACS was 84.5 (range 0-1860), for males was 124.5 and for females was 32.1. Patients with CACS of zero (59%) and CACS of ≥1 (41%) had a mean stenosis of 8.9% (range 0-75%) and 52.6% (range 0-100%), respectively. All patients with a CACS of ≥250 were found to have ≥50% stenosis (100% specificity and positive predictive value, 35.2% sensitivity, 81% negative predictive value and 82.6% accuracy). The percentage of stenosis increased as CACS increased with strong statistical significance (P value < 0.0001) and a positive correlation (r = 0.58).

CONCLUSIONS

CACS is a valuable diagnostic tool to predict the severity of coronary artery stenosis. A cutoff value of 250 confirmed the presence of at least 50% stenosis in symptomatic patients.

Cervicocephalic Spotty Calcium for the Prediction of Coronary Atherosclerosis in Patients With Acute Ischemic Stroke

Purpose: To investigate the characteristics of cervicocephalic spotty calcium (SC) and coronary atherosclerosis in patients with acute ischemic stroke (AIS) and to assess the predictive value of SC for coronary atherosclerosis using combined coronary and cervicocephalic CTA.

Materials and Methods: Patients with AIS (n = 70) confirmed by brain MRI or CT and patients with asymptomatic carotid atherosclerosis (n = 58) confirmed by carotid ultrasonography were enrolled in our study. Subjects in both groups underwent combined coronary and cervicocephalic CTA. SC was used to evaluate cervicocephalic atherosclerosis. Coronary artery stenosis (CAS) ≥ 50% by segment and coronary artery calcium score (CACS) were used to evaluate coronary atherosclerosis. The SC frequency and the difference in coronary atherosclerosis between the two groups were compared, and the correlation between SC and coronary atherosclerosis was analyzed. Independent factors for CAS ≥ 50% were assessed via logistic regression analysis. Receiver operating characteristic curve analysis was performed to evaluate the added value of SC for predicting CAS ≥ 50%.

Results: Both SC and the CACS were significantly higher in the Stroke group than in the Control group (total SC count: 6.83 ± 4.34 vs. 2.98 ± 2.87, P < 0.05; CACS: 477.04 ± 798.01 vs. 136.31 ± 205.65, P < 0.05). There were significant differences in the presence of CAS ≥ 50% (61.4 vs. 27.6%, P < 0.001). SC and coronary atherosclerosis were significantly correlated for both the CACS and CAS ≥ 50% (r = 0.746 and 0.715, respectively; P < 0.001). SC was an independent predictor for CAS ≥ 50%.

Conclusion: SC correlates significantly with the CACS and could serve as an independent predictor of CAS ≥ 50% in patients with AIS, which suggests that combined cerebrovascular and cardiovascular assessments are of importance for such patients.

Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications

OBJECTIVES

To develop a fully automatic multiview shape constraint framework for comprehensive coronary artery calcium scores (CACS) quantification via deep learning on nonenhanced cardiac CT images.

METHODS

In this retrospective single-centre study, a multi-task deep learning framework was proposed to detect and quantify coronary artery calcification from CT images collected between October 2018 and March 2019. A total of 232 non-contrast cardiac-gated CT scans were retrieved and studied (80 % for model training and 20 % for testing). CACS results of testing datasets (n = 46), including Agatston score, calcium volume score, calcium mass score, were calculated fully automatically and manually at total and vessel-specific levels, respectively.

RESULTS

No significant differences were found in CACS quantification obtained using automatic or manual methods at total and vessel-specific levels (Agatston score: automatic 535.3 vs. manual 542.0, P = 0.993; calcium volume score: automatic 454.2 vs. manual 460.6, P = 0.990; calcium mass score: automatic 128.9 vs. manual 129.5, P = 0.992). Compared to the ground truth, the number of calcified vessels can be accurate recognized automatically (total: automatic 107 vs. manual 102, P = 0.125; left main artery: automatic 15 vs. manual 14, P = 1.000 ; left ascending artery: automatic 37 vs. manual 37, P = 1.000; left circumflex artery: automatic 22 vs. manual 20, P = 0.625; right coronary artery: automatic 33 vs. manual 31, P = 0.500). At the patient's level, there was no statistic difference existed in the classification of Agatston scoring (P = 0.317) and the number of calcified vessels (P = 0.102) between the automatic and manual results.

CONCLUSIONS

The proposed framework can achieve reliable and comprehensive quantification for the CACS, including the calcified extent and distribution indicators at both total and vessel-specific levels.

Urolithiasis, Independent of Uric Acid, Increased Risk of Coronary Artery and Carotid Atherosclerosis: A Meta-Analysis of Observational Studies

Background and Aims

Recent epidemiological evidence indicates an association between urolithiasis and atherosclerosis; however, results are incongruous. Our aim is to summarize the association between urolithiasis and arteriosclerosis risk through a detailed meta-analysis.

Methods

Relevant studies published before April 2019 were identified by searching OVID, EMBASE, PubMed, Web of Science database, and Cochrane Library. The relationship between urolithiasis and the risk of atherosclerosis was assessed by using odds ratio (OR) values and the corresponding 95% confidence intervals (CIs), and the selection of fixed- or random-effects model based on heterogeneity.

Results

The meta-analysis includes 8 observational studies that contained 70,716 samples. Pooled results showed that urolithiasis was associated with an increased adjusted and unadjusted risk estimated for atherosclerosis (P=0.017 and P=0.017 and n = 65,751/70,716) with serum uric acid levels less than 6.0 mg/dl, it still showed that urolithiasis was associated with a higher risk of atherosclerosis (P=0.017 and I² = 0.0%, P=0.017 and P=0.017 and P=0.017 and

Conclusions

Urolithiasis is associated with an increased risk for atherosclerosis, especially in coronary artery and carotid atherosclerosis. Urolithiasis may be another potential risk factor of atherosclerosis, which is independent of serum uric acid levels.

The significance of coronary artery calcium score as a predictor of coronary artery stenosis in individuals referred for CT angiography

Introduction: Cardiovascular diseases, including coronary artery disease (CAD), are among the most common causes of death in the elderly population. Recent studies have found that coronary artery calcium score (CACS) is a strong independent predictor of CAD. Here we aimed to investigate the association between CACS and demographic, clinical, laboratory, and CT angiographic findings inpatients with suspected CAD. Methods: From June 2008 to August 2018, we retrospectively reviewed 219 consecutive patients suspected with CAD who were referred for CT angiography in Rajaie Cardiovascular, Medical, and Research Center. Medical records were reviewed, and relevant demographic, clinical, laboratory and imaging were collected. Results: A total of 219 patients with an average age of 62.64±12.39 were included. Twelve patients(5.5%) had normal coronary angiography, and 50.2% had mild CAD. An obstructive CAD was found in97 patients (44.3%). The median CACS was 76.4 (IQR, 13.0-289.1). The frequency of obstructive CAD was 28.1% in the CACS <100 group, and 67.0% in CACS >100 group (P < 0.001). On multiple logistic regression analysis, age (OR=1.04 [1.01-1.07], P = 0.006), CACS (OR= 4.31 [2.33-7.98], P < 0.001), and neutrophil to lymphocyte ratio (NLR) (OR = 0.82 [0.68-0.98], P = 0.027) were independent predictors of obstructive CAD. Conclusion: We found a direct association between higher CACS and obstructive patterns in coronary CT angiography. Our findings indicate that the possibility of the presence of obstructive CAD was higher among symptomatic patients with older age, lower NLR, and CACS >100.

Coronary Calcium Characteristics as Predictors of Major Adverse Cardiac Events in Symptomatic Patients: Insights From the CORE 320 Multinational Study

Background

The predictive value of coronary artery calcium (CAC) has been widely studied; however, little is known about specific characteristics of CAC that are most predictive. We aimed to determine the independent associations of Agatston score, CAC volume, CAC area, CAC mass, and CAC density score with major adverse cardiac events in patients with suspected coronary artery disease.

Methods and Results

A total of 379 symptomatic participants, aged 45 to 85 years, referred for invasive coronary angiography, who underwent coronary calcium scanning and computed tomography angiography as part of the CORE320 (Combined Noninvasive Coronary Angiography and Myocardial Perfusion Imaging Using 320 Detector Computed Tomography) study, were included. Agatston score, CAC volume, area, mass, and density were computed on noncontrast images. Stenosis measurements were made on contrast‐enhanced images. The primary outcome of 2‐year major adverse cardiac events (30 revascularizations [>182 days of index catheterization], 5 myocardial infarctions, 1 cardiac death, 9 hospitalizations, and 1 arrhythmia) occurred in 32 patients (8.4%). Associations were estimated using multivariable proportional means models. Median age was 62 (interquartile range, 56–68) years, 34% were women, and 56% were white. In separate models, the Agatston, volume, and density scores were all significantly associated with higher risk of major adverse cardiac events after adjustment for age, sex, race, and statin use; density was the strongest predictor in all CAC models. CAC density did not provide incremental value over Agatston score after adjustment for diameter stenosis, age, sex, and race.

Conclusions

In symptomatic patients, CAC density was the strongest independent predictor of major adverse cardiac events among CAC scores, but it did not provide incremental value beyond the Agatston score after adjustment for diameter stenosis.