Suspected Coronary Artery Disease Patients Research Articles

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

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

Technetium-99m Methoxyisobutyl Isonitrile Stress MPI in Suspected Coronary Artery Disease Patients: A Prospective Study to Evaluate Clinical Significance of Adenosine-induced ECG Changes

Purpose: The purpose of this study is to evaluate the adenosine pharmacological stress-induced electrocardiogram (ECG) changes and their association with stress-induced ischemic defects on myocardial perfusion scintigraphy (MPS) in the evaluation of coronary artery disease (CAD) and to evaluate event-free survival among patients with positive and negative ECG/MPS image findings. Methods: A total of 100 patients were examined using stress MPS from March 2020 to August 2021. Stress-induced ECG changes during adenosine infusion were evaluated. The summed stress score (SSS) was evaluated to identify ischemic defects in myocardium. Association of stress ECG changes and scintigraphic results was evaluated. Results: Out of 100 patients, stress ECG changes during adenosine infusion were seen among 34 patients, whereas 66 patients had normal ECG findings. Positive stress MPS findings with SSS >3 were seen in 22 patients, whereas 78 patients had SSS ≤3. There was no agreement between stress ECG changes and MPS findings with Cohen’s kappa coefficient (κ) = −0.023, whereas there was mild agreement between stress ECG changes and SSS >7 with κ = 0.105. Median follow-up of 11 months showed more events among patients with positive ECG changes than negative ECG changes. Conclusion: Adenosine, pharmacological stress is safe to use, but few patients might experience some minor and transient symptoms. Adenosine may induce ECG changes in patients with or without positive MPS findings. Patients with concordant positive findings need aggressive cardiac care, whereas patients with small or no defects on MPS need close monitoring.

Prognostic value of CT-derived fractional flow reserve and fat attenuation index in patients with suspected coronary artery disease: a sex-disaggregated analyses

BackgroundThere are sex differences in many risk factors associated with coronary artery disease (CAD). CT-derived fractional flow reserve (CT-FFR) and fat attenuation index (FAI) have been shown to independently predict cardiovascular events. We aimed to examine the impact of sex on the prognostic value of CT-FFR and FAI in suspected CAD patients, and to examine the incremental prognostic value of FAI over CT-FFR in both sex.MethodsA total of 1334 consecutive suspected CAD subjects who underwent coronary computed tomographic angiography (CCTA) were retrospectively collected. We divided the patients into males and females and calculated CT-FFR and FAI data from CCTA images. Kaplan-Meier analysis was used to assess the risk of major adverse cardiovascular events (MACE) stratified by CT-FFR and FAI in both sex. Cox regression models were used to assess the incremental prognostic value of FAI by adding the variable to a model that included CT-FFR and clinical variables.ResultsDuring a median follow-up of 2.08 years, 212 patients had MACE. CT-FFR ≤ 0.80 was significantly associated with MACE in both sex. FAI value of left anterior descending artery (FAI[LAD]) and FAI value of left circumflex (FAI[LCX]) ≥ 70.1 were significantly associated with MACE in females. FAI[LCX] added incremental prognostic value over clinical and CT-FFR variables in females, with hazard ratio (HR) 3.230 (1.982–5.265, P = 0.000), Harrel’s C 0.669 (P < 0.001), net reclassification improvement (NRI) 0.161 (0.073–0.260, P < 0.001), and integrated discrimination index (IDI) 0.036 (0.008–0.090, P = 0.010). FAI[LAD] did not enhance risk prediction in females (Harrel’s C 0.643, P = 0.054; NRI 0.041, P = 0.189; IDI 0.005, P = 0.259). The decision curve analysis demonstrated that the model including FAI[LCX] resulted in the highest net benefit.ConclusionsIn suspected CAD patients, the prognostic value of CT-FFR is not significantly biased by sex. The prognostic value of FAI[LAD] and FAI[LCX] were significantly associated with MACE in females, but not males. FAI[LCX], not FAI[LAD], added incremental prognostic value over CT-FFR and might enhance CT-FFR risk stratification in females.

Association Between Telomere G-Tail Length and Coronary Artery Disease or Statin Treatment in Patients With Cardiovascular Risks - A Cross-Sectional Study.

Background: The utility of telomere G-tail length to predict coronary artery disease (CAD) remains controversial. CAD results from coronary artery narrowing due to cholesterol and lipid accumulation, augmented by inflammatory cells and other factors. This study explored the significance of telomere G-tail length in suspected CAD patients. Methods and Results: In all, 95 patients with suspected CAD or ≥1 cardiac risk factor underwent coronary computed tomography angiography (CCTA). We measured leukocyte telomere length and G-tail length using a hybrid protection method, and diagnosed the presence of CAD using CCTA. Associations between G-tail length and the presence of CAD, the number of stenosed coronary arteries, and brachial-ankle pulse wave velocity (baPWV) were analyzed. No significant difference was observed in G-tail length when comparing groups with or without CAD or statin treatment. However, in the non-statin group, G-tail length was significantly shorter in patients with 3-vessel disease compared with 1-vessel disease. Dividing the group using a baPWV of 1,300 cm/s, telomere G-tail length was significantly shorter in the high-risk (baPWV ≥1,300 cm/s) group. Conclusions: The clinical utility of telomere G-tail length as a CAD risk indicator seems limited. There was a trend for longer telomere G-tail length in the statin-treated group. Moreover, telomere G-tail length was reduced in patients at high-risk of cardiovascular events, aligning with the trend of a shortening in telomere G-tail length with CAD severity.

Association between monocyte to high-density lipoprotein cholesterol ratio and multi-vessel coronary artery disease: a cross-sectional study

BackgroundPatients with multi-vessel coronary artery disease (MV-CAD) have poorer clinical outcomes than those with single-vessel coronary artery disease (SV-CAD). Solid evidence underlines that high-density lipoprotein cholesterol (HDL-C) plays a protective role and monocyte plays a negative role in coronary artery disease (CAD). However, the monocyte to high-density lipoprotein ratio (MHR) has not been studied in relation to MV-CAD.MethodsIn this study, 640 patients underwent coronary angiography, of whom 225 had severe coronary artery disease. Then divide the above two groups of patients into three groups based on the MHR tertiles, respectively. Logistic regression and subgroup analysis were carried out to estimate the association between MHR and MV-CAD. The receiver operating characteristic (ROC) curve analysis was constructed by combining classic CAD risk factors with MHR in response to MV-CAD. In addition, the mediating effect of MHR between smoking and MV-CAD in suspected CAD Patients was analyzed.ResultsAmong the three MHR groups, a statistically discrepant was observed in the number of patients with CAD, Severe-CAD and MV-CAD (PCAD < 0.001; PSevere-CAD < 0.001; PMV-CAD = 0.001) in suspected CAD patients. Furthermore, the number of patients with MV-CAD (P < 0.001) was different in Severe-CAD patients among three MHR groups. Non-CAD and CAD patients showed statistically discrepant in MHR levels (P < 0.001), and this difference also was observed between SV-CAD and MV-CAD patients (P < 0.001). In the analysis of suspected CAD patients, a significantly positive relationship was found between MHR and CAD, Severe-CAD, and MV-CAD (P for trend < 0.001). The effect of MHR on MV-CAD was consistent across all subgroups, with no significant randomized factor-by-subgroup interaction (P-interaction = 0.17–0.89). ROC analysis showed that the model constructed with MHR and classic influencing factors of CAD was superior to the model constructed solely based on classic influencing factors of CAD (0.742 vs.0.682, P = 0.002). In the analysis of Severe-CAD patients, patients with higher MHR levels had a higher risk of MV-CAD [OR (95%CI): 2.90 (1.49, 5.62), P for trend = 0.002] compared to patients with lower MHR. The trends persisted after adjusting for demographic (P for trend = 0.004) and classic influencing factors of CAD (P for trend = 0.009). All subgroup factors for patients with MV-CAD had no interaction with MHR (P-interaction = 0.15–0.86). ROC analysis showed that the model combining MHR and classic influencing factors of CAD was superior to the one including only the classic influencing factors of CAD (0.716 vs.0.650, P = 0.046). Assuming that MHR played a mediating effect between smoking and MV-CAD in suspected CAD patients. The results indicated that MHR played a partial mediating effect of 0.48 (P < 0.001).ConclusionA higher MHR was mainly associated with multi-vessel coronary artery disease and MHR partially mediated the association between smoking and MV-CAD.

ECG-based cardiodynamicsgram can reflect anomalous functional information in coronary artery disease.

The cardiodynamicsgram (CDG), a novel noninvasive method, extracts dynamic ST-T segment information from an electrocardiogram (ECG) through deterministic learning. The CDG can reflect anomalous functional information in coronary artery disease (CAD). We retrospectively enrolled 456 patients with suspected CAD who underwent coronary computed tomography angiography (CCTA) from January 2020 to 2022, followed immediately by standard 12-lead ECG acquisition. Positivity for CAD were defined as CCTA ≥ 50% or CT-derived fractional flow reserve (CT-FFR) ≤ 0.8. A CDG value <0 was considered negative; otherwise, it was considered positive. We also evaluated the diagnostic performance of the CDG in the ECG-diagnosis-negative subgroup and in patients who had undergone invasive coronary angiography (ICA) after CCTA. Of 362 patients, 168 (46.41%) were positive for CAD, and 178 (49.17%) were men. The median age was 59 (52-66) years. The accuracy of the CDG in the diagnosis of CAD was 79.56%, with a sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) of 75.60%, 82.99%, and 0.836 (95% CI: 0.794-0.878), respectively. Similarly, in the ECG-diagnosis-negative subgroup (n = 223), the accuracy of the CDG was 80.27%, with an AUC of 0.842 (95% CI: 0.790-0.895). Among the 11 patients with CAD confirmed by ICA, 10 were diagnosed positive by the CDG. Furthermore, the CDG values and CT-FFR were correlated (r = -.395; p < .001). The ECG-based CDG has relatively high specificity and accuracy for the diagnosis of CAD and reflects functional cardiac information to some extent. It has the potential to be used as a screening tool for suspected CAD patients before CCTA.

Clinical Evaluation of the Automatic Coronary Artery Disease Reporting and Data System (CAD-RADS) in Coronary Computed Tomography Angiography Using Convolutional Neural Networks.

The coronary artery disease reporting and data system (CAD-RADS™) was recently introduced to standardise reporting. We aimed to evaluate the utility of an automatic postprocessing and reporting system based on CAD-RADS™ in suspected coronary artery disease (CAD) patients. Clinical evaluation was performed in 346 patients who underwent coronary computed tomography angiography (CCTA). We compared deep learning (DL)-based CCTA with human readers for evaluation of CAD-RADS™ with commercially-available automated segmentation and manual postprocessing in a retrospective validation cohort. Compared with invasive coronary angiography, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the DL model for diagnosis of CAD were 79.02%, 86.52%, 89.50%, 73.94%, and 82.08%, respectively. There was no significant difference between the DL-based and the reader-based CAD-RADS™ grading of CCTA results. Consistency testing showed that the Kappa value between the model and the readers was 0.775 (95% confidence interval [CI]: 0.728-0.823, p < 0.001), 0.802 (95% CI: 0.756-0.847, p < 0.001), and 0.796 (95% CI: 0.750-0.843, p < 0.001), respectively. This system reduces the time taken from 14.97 ± 1.80 min to 5.02 ± 0.8 min (p < 0.001). The standardised reporting of DL-based CAD-RADS™ in CCTA can accurately and rapidly evaluate suspected CAD patients, and has good consistency with grading by radiologists.

Detecting obstructive coronary artery disease with machine learning: rest-only gated single photon emission computed tomography myocardial perfusion imaging combined with coronary artery calcium score and cardiovascular risk factors.

The rest-only single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has low diagnostic performance for obstructive coronary artery disease (CAD). Coronary artery calcium score (CACS) is strongly associated with obstructive CAD. The aim of this study was to investigate the performance of rest-only gated SPECT MPI combined with CACS and cardiovascular risk factors in diagnosing obstructive CAD through machine learning (ML). We enrolled 253 suspected CAD patients who underwent the 1-stop rest-only SPECT MPI and computed tomography (CT) scan due to stress test-related contraindications. Myocardial perfusion and wall motion were assessed using quantitative perfusion SPECT + quantitative gated SPECT (QPS + QGS) automated quantification software. The Agatston algorithm was used to calculate CACS. The clinical data of patients, including cardiovascular risk factors, were collected. Based on feature selection and clinical experience, 8 factors were identified as modeling variables. Subsequently, patients were divided randomly into 2 groups: the training (70%) and test (30%) groups. The performance of 8 supervised ML algorithms was evaluated in the training and test groups. Obstructive CAD was diagnosed by coronary angiography in 94 (37.2%, 94/253) patients. In the training group, the area under the receiver operator characteristic (ROC) curve (AUC) of the random forest was the highest, and the AUCs of Logistic, extreme gradient boosting (XGBoost), support vector machine (SVM), and adaptive boosting (AdaBoost) were all above 0.9. In the test group, the AUC of recursive partitioning and regression trees (Rpart) was the highest (0.911). Rpart and Naïve Bayes had the highest accuracy (0.840). Rpart had a sensitivity and specificity of 0.851 and 0.821, respectively; Naïve Bayes had a sensitivity and specificity of 0.809 and 0.893, respectively. Next was Logistic, with an accuracy of 0.827, a sensitivity of 0.872, and a specificity of 0.750. The random forest and XGBoost algorithms also had high accuracy, which was 0.813 for each algorithm. Rest-only SPECT MPI combined with CACS and cardiovascular risk factors using an ML algorithm to detect obstructive CAD is feasible. Among the algorithms validated in the test group, Rpart, Naïve Bayes, XGBoost, Logistic, and random forest are all highly accurate for diagnosing obstructive CAD. The application of ML in resting MPI and CACS may be used for screening obstructive CAD.

Correlation of Epicardial Fat Thickness with Angiographic Severity and LDL Cholesterol Level in CAD

Background: Epicardial fat is independently related to coronary artery disease (CAD). Clinical imaging research has established a robust direct correlation between epicardial fat and abdominal visceral adiposity. This study aimed to assess the association of epicardial fat thickness (EFT) with CAD in patients. Objective: To find the association between EFT, Low-density lipoprotein (LDL) cholesterol levels, and angiographic severity by SYNTAX score. Methods: This prospective observational study involved 321 patients with suspected CAD patients undergoing catheter coronary angiography. Epicardial fat thickness was measured by means of transthoracic echocardiography within 90 days after coronary angiography. The severity of coronary atherosclerotic lesions become evaluated from at least 3 projections in all of the sufferers. The angiographic characteristics of the coronary atherosclerotic lesion have been defined using the SYNTAX score. Results: 321 patients took part in this study; the sex distribution has 259 male subjects (80.7%) and 62 female subjects (19.3%). LDL cholesterol levels &lt;100 mg/dl are present in 75.1% (241 subjects) of the study population. The categories and variables were analyzed, and they show a significant correlation between epicardial fat thickness and SYNTAX score with a p-value of &lt;0.0001. A significant correlation has been observed between LDL cholesterol levels and the angiographic severity of CAD by the SYNTAX score. Conclusion: This study suggests that there is a significant correlation between LDL cholesterol levels, EFT and angiographic severity, and complexity of the coronary lesions by the SYNTAX score. Keywords: Body Fat; Coronary Artery Disease; Epicardial Fat Thickness; CAD

A clinical strategy to improve the diagnostic performance of 3T non-contrast coronary MRA and noninvasively evaluate coronary distensibility: combination of diastole and systole imaging

BackgroundThe clinical application of coronary MR angiography (MRA) combining diastole and systole imaging has never been described comprehensively in coronary artery disease (CAD) patients. We aimed to design an optimal non-contrast coronary MRA scan protocol combining diastolic and systolic imaging and to (1) evaluate its diagnostic performance for detecting significant coronary stenosis; (2) evaluate the feasibility of this protocol to noninvasively measure the coronary distensibility index (CDI). MethodsFrom June 2021 to May 2022, 33 healthy volunteers and 91 suspected CAD patients scheduled for X-ray coronary angiography (CAG) were prospectively enrolled. 3T non-contrast water-fat coronary MRA was carried out twice at diastole and systole. Significant coronary stenosis was defined as a luminal diameter reduction of ≥ 50% using CAG as the reference and was evaluated as follows: (1) by coronary MRA in diastole alone; (2) by coronary MRA in systole alone; (3) by combined coronary MRA in diastole and systole. According to CAG, the patients were divided into significant CAD patients and non-significant CAD patients. The difference in CDI among participants was evaluated. ResultsCombined coronary MRA was completed in 31 volunteers and 76 patients. The per-patient sensitivity, specificity, and accuracy of combined coronary MRA were 97.5%, 83.3%, and 90.8%, respectively. Compared with single diastolic mode, combined coronary MRA showed equally high sensitivity but improved specificity on a per-patient basis (83.3% vs. 63.9%, adjusted P = 0.013). The CDI tested by coronary MRA decreased incrementally from healthy volunteers to non-significant and significant CAD patients. ConclusionCompared with single-phase mode, 3 T non-contrast combined coronary MRA significantly improved specificity and may have potential to be a simple noninvasive method to measure CDI.

The value of regional and global CACS combined with SPECT MPI in detecting obstructive CAD: a retrospective real-world comparative study

ObjectivePrevious studies have shown that global coronary artery calcium score (CACS) can improve single photon emission computerized tomography (SPECT) myocardial perfusion imaging (MPI) to detect obstructive coronary artery disease (CAD). Whether regional CACS can improve SPECT MPI to detect obstructive CAD remains unclear. The aim of this study was to verify whether regional CACS has additional diagnostic value for obstructive CAD in suspected patients, compared to SPECT MPI and global CACS.MethodsThe study included 321 suspected CAD patients who underwent one-stop rest-stress SPECT MPI and low-dose computed tomography (CT) scan. All patients underwent coronary angiography within one month after examination. MPI images were visually analyzed by 2 experienced nuclear cardiologists. The regional CACS of left anterior descending coronary artery (LAD), left circumflex coronary artery (LCX), right coronary artery (RCA) and global CACS were calculated. Obstructive CAD was defined as ≥ 70% narrowing of the inner diameter of the LAD, LCX, RCA or their main branches and ≥ 50% narrowing of the left main coronary artery (LM).ResultsAmong the 321 patients, 86 (26.8%, 86/321) had obstructive CAD. With the increased in global and regional CACS, there was an increasing trend of patients with obstructive CAD (P for trend < 0.001). Regional CACS had a better diagnostic performance in RCA territories (AUC 0.856, P < 0.001) compared with LAD, LCX territories (AUC 0.690, 0.674, respectively). The AUC of combined regional CACS and MPI was significantly higher than that of MPI alone (0.735 vs. 0.600, P < 0.001). However, based on MPI, the AUC of combined regional CACS was not significantly higher than that of global CACS (0.735 vs. 0.732, P = 0.898). The sensitivity and specificity of regional CACS combined with MPI for detecting obstructive CAD were 64.0% and 72.8%, respectively.ConclusionsRegional CACS was effective in detecting obstructive CAD in RCA territory. Based on SPECT MPI, regional CACS improved the detection of obstructive CAD, but was not superior to global CACS.

A model combining rest-only ECG-gated SPECT myocardial perfusion imaging and cardiovascular risk factors can effectively predict obstructive coronary artery disease

ObjectiveThe rest-only single photon emission computerized tomography (SPECT) myocardial perfusion imaging (MPI) had low sensitivity in diagnosing obstructive coronary artery disease (CAD). Improving the efficacy of resting MPI in diagnosing CAD has important clinical significance for patients with contraindications to stress. The purpose of this study was to develop and validate a model predicting obstructive CAD in suspected CAD patients, based on rest-only MPI and cardiovascular risk factors.MethodsA consecutive retrospective cohort of 260 suspected CAD patients who underwent rest-only gated SPECT MPI and coronary angiography was constructed. All enrolled patients had stress MPI contraindications. Clinical data such as age and gender were collected. Automated quantitative analysis software QPS and QGS were used to evaluate myocardial perfusion and function parameters. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the variables and build the prediction model.ResultsAmong the enrolled 260 patients with suspected CAD, there were 95 (36.5%, 95/260) patients with obstructive CAD. The prediction model was presented in the form of a nomogram and developed based on selected predictors, including age, sex, SRS ≥ 4, SMS ≥ 2, STS ≥ 2, hypertension, diabetes, and hyperlipidemia. The AUC of the prediction model was 0.795 (95% CI: 0.741–0.843), which was better than the traditional models. The AUC calculated by enhanced bootstrapping validation (500 bootstrap resamples) was 0.785. Subsequently, the calibration curve (intercept = − 0.106; slope = 0.843) showed a good calibration of the model. The decision curve analysis (DCA) shows that the constructed clinical prediction model had good clinical applications.ConclusionsIn patients with suspected CAD and contraindications to stress MPI, a prediction model based on rest-only ECG-gated SPECT MPI and cardiovascular risk factors have been developed and validated to predict obstructive CAD effectively.

Machine Learning Models to Predict Exercise Stress Test Results: Optimising the Diagnostic Test Selection Strategy and Reducing Wastage in Suspected CAD Patients

Cardiac exercise stress test (EST) is a commonly used investigation in the management of patients with suspected coronary artery disease (CAD). However, up to 30% EST results are either inconclusive or non-diagnostic, which results in significant resource wastage.

Prognostic value of CAD-RADS classification by coronary CTA in patients with suspected CAD

BackgroundThe study sought to compare Coronary Artery Disease Reporting and Data System (CAD-RADS) classification with traditional coronary artery disease (CAD) classifications and Duke Prognostic CAD Index for predicting the risk of all-cause mortality in patients with suspected CAD.Methods9625 consecutive suspected CAD patients were assessed by coronary CTA for CAD-RADS classification, traditional CAD classifications and Duke Prognostic CAD Index. Kaplan–Meier and multivariable Cox models were used to estimate all-cause mortality. Discriminatory ability of classifications was assessed using time dependent receiver-operating characteristic (ROC) curves and The Hosmer–Lemeshow goodness-of-fit test was employed to evaluate calibration.ResultsA total of 540 patients died from all causes with a median follow-up of 4.3 ± 2.1 years. Kaplan–Meier survival curves showed the cumulative events increased significantly associated with CAD-RADS, three traditional CAD classifications and Duke Prognostic CAD Index. In multivariate Cox regressions, the risk for the all-cause death increased from HR 0.861 (95% CI 0.420–1.764) for CAD-RADS 1 to HR 2.761 (95% CI 1.961–3.887) for CAD-RADS 4B&5, using CAD-RADS 0 as the reference group. The relative HRs for all-cause death increased proportionally with the grades of the three traditional CAD classifications and Duke Prognostic CAD Index. The area under the time dependent ROC curve for prediction of all-cause death was 0.7917, 0.7805, 0.7991for CAD-RADS in 1 year, 3 year, 5 year, respectively, which was non-inferior to the traditional CAD classifications and Duke Prognostic CAD Index.ConclusionsThe CAD-RADS classification provided important prognostic information for patients with suspected CAD with noninvasive evaluation, which was non-inferior than Duke Prognostic CAD Index and traditional stenosis-based grading schemes in prognostic value of all-cause mortality. Traditional and simplest CAD classification should be preferable, given the more number of groups and complexity of CAD-RADS and Duke prognostic index, without using more time consuming classification.

Predictive Added Value of Selected Plasma Lipids to a Re-estimated Minimal Risk Tool.

Background: Lipidomics is emerging for biomarker discovery in cardiovascular disease, and circulating lipids are increasingly incorporated in risk models to predict cardiovascular events. Moreover, specific classes of lipids, such as sphingomyelins, ceramides, and triglycerides, have been related to coronary artery disease (CAD) severity and plaque characteristics. To avoid unnecessary testing, it is important to identify individuals at low CAD risk. The only pretest model available so far to rule out the presence of coronary atherosclerosis in patients with chest pain, but normal coronary arteries, is the minimal risk tool (MRT).Aim: Using state-of-the-art statistical methods, we aim to verify the additive predictive value of a set of lipids, derived from targeted plasma lipidomics of suspected CAD patients, to a re-estimated version of the MRT for ruling out the presence of coronary atherosclerosis assessed by coronary CT angiography (CCTA).Methods: Two hundred and fifty-six subjects with suspected stable CAD recruited from five European countries within H2020-SMARTool, undergoing CCTA and blood sampling for clinical biochemistry and lipidomics, were selected. The MRT was validated by regression methods and then re-estimated (reMRT). The reMRT was used as a baseline model in a likelihood ratio test approach to assess the added predictive value of each lipid from 13 among ceramides, triglycerides, and sphingomyelins. Except for one lipid, the analysis was carried out on more than 240 subjects for each lipid. A sensitivity analysis was carried out by considering two alternative models developed on the cohort as baseline models.Results: In 205 subjects, coronary atherosclerosis ranged from minimal lesions to overt obstructive CAD, while in 51 subjects (19.9%) the coronary arteries were intact. Four triglycerides and seven sphingomyelins were significantly (p < 0.05) and differentially expressed in the two groups and, at a lesser extent, one ceramide (p = 0.067). The probability of being at minimal risk was significantly better estimated by adding either Cer(d18:1/16:0) (p = 0.01), SM(40:2) (p = 0.04), or SM(41:1) at a lesser extent (p = 0.052) to reMRT than by applying the reMRT alone. The sensitivity analysis confirmed the relevance of these lipids. Furthermore, the addition of SM(34:1), SM(38:2), SM(41:2), and SM(42:4) improved the predictive performance of at least one of the other baseline models. None of the selected triglycerides was found to provide an added value.Conclusions: Plasma lipidomics can be a promising source of diagnostic and prognostic biomarkers in cardiovascular disease, exploitable not only to assess the risk of adverse events but also to identify subjects without coronary atherosclerosis, thus reducing unnecessary further testing in normal subjects.

Diagnostic Accuracy of 128-Slice Dual Source CT Coronary Angiography with Invasive Catheter Coronary Angiography in a Tertiary Care Teaching Hospital

Background: Coronary artery disease (CAD) morbidity and mortality increasing day by day in India as well as worldwide. Coronary arteries visualization by using invasive catheterization angiography is still using as a front-line diagnostic tool to evaluate the patients with CAD. 128 slice dual source CT improves the cardiac imaging such as high scanning speed, good temporal resolution and low radiation dose. Objective: To assess the diagnostic accuracy of 128-slice dual source CT cardiac angiography with conventional catheter angiography to find common arteries involved in CAD. Methods: This is a prospective, comparative, cross sectional study conducted at cardiology OPD. Patients with complaint of chest pain and suspected CAD were evaluated by CT and conventional coronary angiography and results were compared. Serum creatinine and ECG status were analyzed before the angiography. SIEMENS 128-slice Dual Source Flash Definition CT Scanner was used as a CT coronary angiography. Severity distribution of coronary artery disease, artery wise distribution of non-significant, significant lesions and coronary artery dominance pattern were analyzed and compared. Results: A total of 70 suspected CAD patients were selected and analyzed. American Heart Association (AHA) model of 17-segment was used to assess the coronary arteries. Normal angiograms reported in 15.71% patients and 58.57% had significant disease. A total of 356 lesions were identified from 690 out of 720 segments. Right coronary artery (RCA) is the most common location of significant lesions which contributes 33.5% (n=55/164). Coronary circulation of right-sided dominance was most commonly reported (70.0%). CT angiography showed 96.13% of an overall sensitivity, 96.28% specificity, 89.72% positive predictive value and 98.49% negative predictive value. Conclusion: 128-slice dual source CT scanner has showed high accuracy and act as non-invasive assessment of coronary arteries in patients with CAD Keywords: Cardiac angiography, Catheter coronary angiography, CT coronary angiography, 128-slice MDCT, Conventional angiography

ATHEROSCLEROTIC CORONARY ARTERY DISEASE IN PATIENTS WITH CARDIOMETABOLIC SYNDROME: FROM THREE FUKUOKA UNIVERSITY REGISTRY IN JAPAN

Abstract Objective: Major coronary risk factors were included in aging, gender, family history, hypertension, diabetes, high cholesterol and smoking. Metabolic syndrome includes abdominal obesity, high blood pressure, high triglyceride (TG) and/or low high-density lipoprotein cholesterol (HDL-C) and diabetes. We determined the critical risk factors for the onset and progression of coronary artery disease (CAD). Design and method: We have been going on three Fukuoka University Registry in Japan to define the risk factors for primary and secondary prevention of atherosclerotic CAD: Coronary Computed Tomography Angiography (FU-CCTA) Registry, Coronary Intravascular Ultrasound (FU-IVUS) Registry and Quantitative Coronary Angiography (FU-QCA) Registry. We analyzed the data from three Registry. Results: First, HDL-C levels were most closely associated with the presence of CAD from the FU-CCTA registry, and we need to perform CCTA for suspected CAD patients with lower HDL-C levels under statin treatment. In addition, in the five groups classified according to the number of metabolic factors, the number of significantly coronary stenosed vessels was significantly increased as the number of metabolic factors increased. Second, we found that among CAD patients treated with statins, TG levels were associated with lipid-rich coronary plaques in females, but not in males according to the FU-IVUS Registry. TG levels may be more important indicators of residual risk after statin treatment in females than in males. Lastly, HDL-C &lt; 40 mg/dl and low-density lipoprotein cholesterol (LDL-C) equal to or more than 100 mg/dl were even more strongly related to major adverse cardiac events in female patients, whereas the combination of LDL-C and HDL-C was not related to MACEs in male patients on the FU-QCA Registry. Conclusions: Although an increased metabolic factors induces more severe CAD and lower HDL-C and higher LDL-C induce the onset and progression of CAD, there may be gender differences in the significance of lipid profiles.

Impaired coronary flow reserve evaluated by phase-contrast cine magnetic resonance imaging in patients with atrial fibrillations.

Myocardial perfusion and perfusion reserve are diminished in patients with atrial fibrillation (AF). Phase-contrast (PC) cine magnetic resonance imaging (MRI) of the coronary sinus serves as a non-invasive means of quantifying coronary flow reserve (CFR) without any radioactive tracer. The present study aimed to evaluate the utility of PC cine MRI of the coronary sinus for assessing decreased CFR in patients with AF. We studied 362 patients with known or suspected coronary artery disease (CAD) [age 72 ± 9years; 267 (74%) male; 90 (25%) had AF] and 20 age- and gender-matched control subjects [age 72 ± 9years, 14 (70%) male]. Using a 1.5-T MR scanner and cardiac coils, blood flow of the coronary sinus (CBF) was quantified by PC cine MRI. CFR was calculated as CBF during adenosine triphosphate infusion divided by CBF at rest. CFR was significantly lower in patients with AF than in those without AF among all patients (n = 362) (2.45 ± 0.42 vs. 2.71 ± 0.58, p < 0.001), in patients with known CAD (n = 155) (2.40 ± 0.46 vs. 2.72 ± 0.58, p = 0.002), and in those with suspected CAD (n = 207) (2.49 ± 0.40 vs. 2.72 ± 0.59, p = 0.007). Significant differences in CFR were found between controls and patients without AF (3.12 ± 0.52 vs. 2.71 ± 0.58, p < 0.001). AF was independently associated with CFR in both known CAD patients [β = - 0.248, 95% confidence interval (CI): - 0.561 to - 0.119, p = 0.003) and suspected CAD patients (β = - 0.154, 95% CI - 0.353 to - 0.034, p = 0.018). The presence of AF was related to impaired CFR in both known and suspected CAD patients. PC cine MRI of the coronary sinus can be useful for detecting impaired CFR in patients with AF.

Incremental value of regional wall motion abnormalities for detecting obstructive coronary artery disease by rest-only electrocardiogram-gated single-photon emission computerized tomography myocardial perfusion imaging in suspected coronary artery disease patients.

The purpose of this study was to determine whether regional wall motion (WM) abnormalities by rest-only 99mtechnetium-sestamibi (99mTc-MIBI) electrocardiogram (ECG)-gated single-photon emission computerized tomography (SPECT) myocardial perfusion imaging (MPI) had incremental diagnostic value for detecting obstructive coronary artery disease (CAD) in suspected CAD patients. This study retrospectively studied 255 consecutive suspected CAD patients who underwent rest-only ECG-gated SPECT MPI and were performed coronary angiography within 3 months. Obstructive CAD was defined as ≥70% narrowing of the inner diameter of the left anterior descending coronary artery, left circumflex coronary artery and right coronary artery or their main branches and ≥50% narrowing of the left main coronary artery. QPS and QGS were used to assess rest perfusion and WM. Summed rest score ≥4 and summed motion score ≥2 exhibited in two consecutive segments in one territory was considered abnormal. The sensitivity of the combination of perfusion and regional WM abnormalities was significantly higher than perfusion alone for detecting obstructive CAD (46.8% vs. 30.9%; P < 0.001), with similar specificity (91.9% vs. 95.0; P = 0.063). The global chi-square value of combination of perfusion and WM increased from 31.40 to 50.71 (P < 0.001) compared to perfusion. The sensitivity of combination of perfusion and WM for detecting obstructive CAD in patients with multivessel disease was higher than single-vessel disease (56.1% vs. 25.0%; P < 0.001), with similar specificity. Regional WM abnormalities at rest, as shown by rest-only 99mTc-MIBI ECG-gated SPECT MPI, have additional diagnostic value over perfusion alone for detecting obstructive CAD in suspected CAD patients.

Detection of coronary artery disease using multi-modal feature fusion and hybrid feature selection

Objective: Coronary artery disease (CAD) is a common fatal disease. At present, an accurate method to screen CAD is urgently needed. This study aims to provide optimal detection models for suspected CAD detection according to the differences in medical conditions, so as to assist physicians to make accurate judgments on suspected CAD patients. Approach: Electrocardiogram (ECG) and phonocardiogram (PCG) signals of 32 CAD patients and 30 patients with chest pain and normal coronary angiograms (CPNCA) were simultaneously collected for this paper. For each subject, the ECG and PCG multi-domain features were extracted, and the results of Holter monitoring, echocardiography (ECHO), and biomarker levels (BIO) were obtained to construct a multi-modal feature set. Then, a hybrid feature selection (HFS) method was developed using mutual information, recursive feature elimination, random forest, and weight of support vector machine to obtain the optimal feature subset. A support vector machine with nested cross-validation was used for classification. Main results: Results showed that the Holter model achieved the best performance as a single-modal feature model with an accuracy of 82.67%. In terms of multi-modal feature models, PCG-Holter, PCG-Holter-ECHO, PCG-Holter-ECHO-BIO, and ECG-PCG-Holter-ECHO-BIO were the optimal bimodal, three-modal, four-modal, and five-modal models, with accuracies of 90.38%, 91.92%, 95.25%, and 96.67%, respectively. Among them, the ECG-PCG-Holter-ECHO-BIO model, which was constructed by combining ECG and PCG signals features with Holter, ECHO, and BIO examination results, achieved the best classification results with an average accuracy, sensitivity, specificity, and F1-measure of 96.67%, 96.67%, 96.67%, and 96.64%, respectively. Significance: The study indicated that multi-modal feature fusion and HFS can obtain more effective information for CAD detection and provide a reference for physicians to diagnose CAD patients.