Dataset Information

Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease.

ABSTRACT:

Background

Myocardial perfusion imaging (MPI) is an accurate noninvasive test for patients with suspected obstructive coronary artery disease (CAD) and coronary artery calcium (CAC) score is known to be a powerful predictor of cardiovascular events. Collection of CAC scores simultaneously with MPI is unexplored.

Aim

We aimed to investigate whether automatically derived CAC scores during myocardial perfusion imaging would further improve the diagnostic accuracy of MPI to detect obstructive CAD.

Methods

We analyzed 150 consecutive patients without a history of coronary revascularization with suspected obstructive CAD who were referred for 82Rb PET/CT and available coronary angiographic data. Myocardial perfusion was evaluated both semi quantitatively as well as quantitatively according to the European guidelines. CAC scores were automatically derived from the low-dose attenuation correction CT scans using previously developed software based on deep learning. Obstructive CAD was defined as stenosis >70% (or >50% in the left main coronary artery) and/or fractional flow reserve (FFR) ≤0.80.

Results

In total 58% of patients had obstructive CAD of which seventy-four percent were male. Addition of CAC scores to MPI and clinical predictors significantly improved the diagnostic accuracy of MPI to detect obstructive CAD. The area under the curve (AUC) increased from 0.87 to 0.91 (p: 0.025). Sensitivity and specificity analysis showed an incremental decrease in false negative tests with our MPI + CAC approach (n = 14 to n = 4), as a consequence an increase in false positive tests was seen (n = 11 to n = 28).

Conclusion

CAC scores collected simultaneously with MPI improve the detection of obstructive coronary artery disease in patients without a history of coronary revascularization.

SUBMITTER: Dekker M

PROVIDER: S-EPMC6872848 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Publications

Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease.

Dekker Mirthe M Waissi Farahnaz F Bank Ingrid E M IEM Lessmann Nikolas N Išgum Ivana I Velthuis Birgitta K BK Scholtens Asbjørn M AM Leenders Geert E GE Pasterkamp Gerard G de Kleijn Dominique P V DPV Timmers Leo L Mosterd Arend A

International journal of cardiology. Heart & vasculature 20191119

<h4>Background</h4>Myocardial perfusion imaging (MPI) is an accurate noninvasive test for patients with suspected obstructive coronary artery disease (CAD) and coronary artery calcium (CAC) score is known to be a powerful predictor of cardiovascular events. Collection of CAC scores simultaneously with MPI is unexplored.<h4>Aim</h4>We aimed to investigate whether automatically derived CAC scores during myocardial perfusion imaging would further improve the diagnostic accuracy of MPI to detect obs ...[more]

PMID: 31768415

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Project description:ObjectivesThis study sought to assess the performance of cardiovascular magnetic resonance (CMR) myocardial perfusion mapping against invasive coronary physiology reference standards for detecting coronary artery disease (CAD, defined by fractional flow reserve [FFR] ≤0.80), microvascular dysfunction (MVD) (defined by index of microcirculatory resistance [IMR] ≥25) and the ability to differentiate between the two.BackgroundDifferentiation of epicardial (CAD) and MVD in patients with stable angina remains challenging. Automated in-line CMR perfusion mapping enables quantification of myocardial blood flow (MBF) to be performed rapidly within a clinical workflow.MethodsFifty patients with stable angina and 15 healthy volunteers underwent adenosine stress CMR at 1.5T with quantification of MBF and myocardial perfusion reserve (MPR). FFR and IMR were measured in 101 coronary arteries during subsequent angiography.ResultsTwenty-seven patients had obstructive CAD and 23 had nonobstructed arteries (7 normal IMR, 16 abnormal IMR). FFR positive (epicardial stenosis) areas had significantly lower stress MBF (1.47 ± 0.48 ml/g/min) and MPR (1.75 ± 0.60) than FFR-negative IMR-positive (MVD) areas (stress MBF: 2.10 ± 0.35 ml/g/min; MPR: 2.41 ± 0.79) and normal areas (stress MBF: 2.47 ± 0.50 ml/g/min; MPR: 2.94 ± 0.81). Stress MBF ≤1.94 ml/g/min accurately detected obstructive CAD on a regional basis (area under the curve: 0.90; p < 0.001). In patients without regional perfusion defects, global stress MBF <1.82 ml/g/min accurately discriminated between obstructive 3-vessel disease and MVD (area under the curve: 0.94; p < 0.001).ConclusionsThis novel automated pixel-wise perfusion mapping technique can be used to detect physiologically significant CAD defined by FFR, MVD defined by IMR, and to differentiate MVD from multivessel coronary disease. A CMR-based diagnostic algorithm using perfusion mapping for detection of epicardial disease and MVD warrants further clinical validation.

Project description:BackgroundThe 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).MethodsWe 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.ResultsObstructive 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.ConclusionsRest-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.

Project description:BackgroundCoronary artery calcium score (CACS) is an anatomic measure of calcified atherosclerosis. Myocardial perfusion defects and reduced myocardial blood flow reserve (MBFR) are physiological measures of ischemia and coronary circulatory health. We aimed to assess the relative prognostic importance of MBFR, perfusion defects, and CACS in patients with suspected coronary artery disease.MethodsA total of 5983 consecutive patients without known history of coronary artery disease or cardiomyopathy, who underwent a CACS and 82Rb positron emission tomography myocardial perfusion imaging between 2010 and 2016, were followed for all-cause death (n=785) over median of 3 years. Prognostic value was assessed using multivariable Cox regression models, and incremental risk discrimination for imaging variables was evaluated by comparing model c-indices after adjusting for clinical risk factors (RF).ResultsMean age was 67.1 years, 60% were female, and 83% were symptomatic. CACS was 0 in 22%, abnormal perfusion in 19%, and MBFR <2 in 53.3%. When added to RF, the model with MBFR had the best fit (c=0.78, P<0.0001). Addition of CACS to model with RF and perfusion (c=0.77) offered modest improvement in discrimination over the model with RF and perfusion (c=0.76, P=0.02). Adding CACS to a model with RF, perfusion, and MBFR did not provide incremental prognostic value (c=0.785 for both, P=0.16). CACS and MBFR both had independent prognostic value in patients with normal and abnormal myocardial perfusion imaging. Even among patients with CACS of 0, MBFR <2 was present in 37.8%, being associated with higher risk of death (hazard ratio per 0.1↓, 1.10 [1.04-1.15]; P<0.001), but perfusion defects were not.ConclusionsUse of anatomic testing such as CACS of 0 to avoid myocardial perfusion imaging in symptomatic patients could lead to missing microvascular dysfunction in 4 out of 10 patients, a finding associated with a high mortality risk. Higher CACS was independently associated with the risk of death but did not provide incremental prognostic value over positron emission tomography with MBFR.

Project description:PurposeMyocardial perfusion imaging (MPI) has limitations in the presence of balanced multivessel disease (MVD) and left main (LM) coronary artery disease, occasionally resulting in false-normal results despite the high cardiovascular risk associated with this condition. The purpose of this study was to assess the incidence of severe coronary artery disease (CAD) in the presence of a very high Agatston coronary artery calcium (CAC) score (>1,000) in stable symptomatic patients without known CAD but with normal MPI results.MethodsA total of 2,659 prospectively acquired consecutive patients were referred for MPI and evaluation of CAC score by CT. Of this patient population, 8 % (222/2,659) had ischemia without myocardial infarction (MI) on MPIand 11 % (298/2,659) had abnormal MPI (MI and/or ischemia). On presentation 1 % of the patients (26/2,659) were symptomatic, had a CAC score >1,000 and normal MPI results. The definition of normal MPI was strict and included a normal hemodynamic response without ischemic ECG changes and normal imaging, particularly absence of transient ischemic dilation. All of these 26 patients with a CAC score >1,000 and normal MPI findings underwent cardiac catheterization.ResultsOf these 26 patients, 58 % (15/26) had severe disease (≥70 % stenosis) leading to revascularization. Of this group, 47 % (7/15) underwent percutaneous intervention, and 53 % (8/15) underwent coronary artery bypass grafting. All of these 15 patients had either MVD (14/15) or LM coronary artery disease (1/15), and represented 0.6 % (15/2,659) of all referred patients (95 % CI 0.3 - 0.9 %). The majority, 90 % (8/9), had severe CAD with typical chest pain.ConclusionA very high CAC score (>1,000) with normal MPI in a small subset of symptomatically stable patients was associated with a moderate incidence of severe CAD (95 % CI 37 - 77 %). Larger studies and/or a meta-analysis of small studies are needed to more precisely estimate the incidence of CAD in this population. This study also supports the concept that a normal MPI result in patients with severe CAD may be due to balanced MVD.

Project description:AimThis study explores the association between Coronary Artery Calcium (CAC) scores and dental pathology such as missing teeth, the (peri-apical) health status and restoration grade of the teeth, and the grade of alveolar bone loss seen on a dental panoramic radiograph (Orthopantomograph-OPG).Materials and methodsIn this retrospective cross-sectional study, data was collected from three hospitals spread in the Netherlands. Patients were included when a CAC score and an OPG were available, both recorded within a maximum period of 365 days from 2009-2017. The CAC score was measured on a CT scan, using the Agatston method. To assess dental pathology, the number of missing teeth, the number of dental implants, alveolar bone loss, caries, endodontic treatments, peri-apical radiolucencies, bone loss at implants, impacted teeth and dental cysts, were determined on the OPG. All observers were calibrated. The electronic health records provided information about: gender, age, smoking, Diabetes Mellitus, hypercholesterolemia, hypertension and Body Mass Index (BMI).Results212 patients were included. We found a statistically significant association between the number of missing teeth and the CAC score. When modeling age, sex, and other well-known risk factors for cardiovascular disease, the significant correlation was no longer present after multivariate correction. Furthermore, the results showed a trend for more teeth with peri-apical lesions and a higher percentage of mean alveolar bone loss in the group with the highest CAC scores.ConclusionThis study showed that being edentulous or missing teeth is correlated to higher CAC scores however failed to be an independent predictor of atherosclerotic cardiovascular diseases. The number of (missing) teeth is an easily accessible marker and could be used as a marker for atherosclerotic cardiovascular disease (ACVD) risk by almost any healthcare worker. The current study needs to be considered as an explorative pilot study and could contribute to the design of further (prospective) studies on the relationship between dental pathology and coronary artery calcification by adding clinical information and extra cardiovascular biomarkers.

Dataset Information

Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease.

Background

Aim

Methods

Results

Conclusion

Publications

Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease.

Similar Datasets

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