Long-term prognosis for individuals with hypertension undergoing coronary artery calcium scoring

To examine the performance of coronary artery calcification (CAC) for stratifying long-term risk of death in asymptomatic hypertensive patients

Aggregate Plaque Volume by Coronary Computed Tomography Angiography Is Superior and Incremental to Luminal Narrowing for Diagnosis of Ischemic Lesions of Intermediate Stenosis Severity

ObjectivesThis study examined the performance of percent aggregate plaque volume (%APV), which represents cumulative plaque volume as a function of total vessel volume, by coronary computed tomography angiography (CTA) for identification of ischemic lesions of intermediate stenosis severity.BackgroundCoronary lesions of intermediate stenosis demonstrate significant rates of ischemia. Coronary CTA enables quantification of luminal narrowing and %APV.MethodsWe identified 58 patients with intermediate lesions (30% to 69% diameter stenosis) who underwent invasive angiography and fractional flow reserve. Coronary CTA measures included diameter stenosis, area stenosis, minimal lumen diameter (MLD), minimal lumen area (MLA) and %APV. %APV was defined as the sum of plaque volume divided by the sum of vessel volume from the ostium to the distal portion of the lesion. Fractional flow reserve ≤0.80 was considered diagnostic of lesion-specific ischemia. Area under the receiver operating characteristic curve and net reclassification improvement (NRI) were also evaluated.ResultsTwenty-two of 58 lesions (38%) caused ischemia. Compared with nonischemic lesions, ischemic lesions had smaller MLD (1.3 vs. 1.7 mm, p = 0.01), smaller MLA (2.5 vs. 3.8 mm2, p = 0.01), and greater %APV (48.9% vs. 39.3%, p < 0.0001). Area under the receiver operating characteristic curve was highest for %APV (0.85) compared with diameter stenosis (0.68), area stenosis (0.66), MLD (0.75), or MLA (0.78). Addition of %APV to other measures showed significant reclassification over diameter stenosis (NRI 0.77, p < 0.001), area stenosis (NRI 0.63, p = 0.002), MLD (NRI 0.62, p = 0.001), and MLA (NRI 0.43, p = 0.01).ConclusionsCompared with diameter stenosis, area stenosis, MLD, and MLA, %APV by coronary CTA improves identification, discrimination, and reclassification of ischemic lesions of intermediate stenosis severity

Thoracic Aortic Calcium Versus Coronary Artery Calcium for the Prediction of Coronary Heart Disease and Cardiovascular Disease Events

ObjectivesThis study compared the ability of coronary artery calcium (CAC) and thoracic aortic calcium (TAC) to predict coronary heart disease (CHD) and cardiovascular disease (CVD) events.BackgroundCoronary artery calcium has been shown to strongly predict CHD and CVD events, but it is unknown whether TAC, also measured within a single cardiac computed tomography (CT) scan, is of further value in predicting events.MethodsA total of 2,303 asymptomatic adults (mean age 55.7 years, 38% female) with CT scans were followed up for 4.4 years for CHD (myocardial infarction, cardiac death, or late revascularizations) and CVD (CHD plus stroke). Cox regression, adjusted for Framingham risk score (FRS), examined the relation of Agatston CAC and TAC categories, and log-transformed CAC and TAC with the incidence of CHD and CVD events and receiver-operator characteristic (ROC) curves tested whether TAC improved prediction of events over CAC and FRS.ResultsA total of 53% of subjects had Agatston CAC scores of 0; 8% 1 to 9; 19% 10 to 99; 12% 100 to 399; and 8% ≥400. For TAC, proportions were 69%, 5%, 12%, 8%, and 7%, respectively; 41 subjects (1.8%) experienced CHD and 47 (2.0%) CVD events. The FRS-adjusted hazard ratios (HR) across increasing CAC groups (relative to <10) ranged from 3.7 (p = 0.04) to 19.6 (p < 0.001) for CHD and from 2.8 (p = 0.07) to 13.1 (p < 0.001) for CVD events; only TAC scores of 100 to 399 predicted CHD and CVD (HR: 3.0, p = 0.008, and HR: 2.3, p = 0.04, respectively); these risks were attenuated after accounting for CAC. Findings were consistent when using log-transformed CAC and TAC Agatston and volume scores. The ROC curve analyses showed CAC predicted CHD and CVD events over FRS alone (p < 0.01); however, TAC did not further add to predicting events over FRS or CAC.ConclusionsThis study found that CAC, but not TAC, is strongly related to CHD and CVD events. Moreover, TAC does not further improve event prediction over CAC

Assessment of the relationship between stenosis severity and distribution of coronary artery stenoses on multislice computed tomographic angiography and myocardial ischemia detected by single photon emission computed tomography

The relationship between luminal stenosis measured by coronary CT angiography (CCTA) and severity of stress-induced ischemia seen on single photon emission computed tomographic myocardial perfusion imaging (SPECT-MPI) is not clearly defined. We sought to evaluate the relationship between stenosis severity assessed by CCTA and ischemia on SPECT-MPI. ECG-gated CCTA (64 slice dual source CT) and SPECT-MPI were performed within 6 months in 292 patients (ages 26-91, 73% male) with no prior history of coronary artery disease. Maximal coronary luminal narrowing, graded as 0, ≥25%, 50%, 70%, or 90% visual diameter reduction, was consensually assessed by two expert readers. Perfusion defect on SPECT-MPI was assessed by computer-assisted visual interpretation by an expert reader using the standard 17 segment, 5 point-scoring model (stress perfusion defect of ≥5% = abnormal). By SPECT-MPI, abnormal perfusion was seen in 46/292 patients. With increasing stenosis severity, positive predictive value (PPV) increased (42%, 51%, and 74%, P = .01) and negative predictive value was relatively unchanged (97%, 95%, and 91%) in detecting perfusion abnormalities on SPECT-MPI. In a receiver operator curve analysis, stenosis of 50% and 70% were equally effective in differentiating between the presence and absence of ischemia. In a multivariate analysis that included stenosis severity, multivessel disease, plaque composition, and presence of serial stenoses in a coronary artery, the strongest predictors of ischemia were stenosis of 50-89%, odds ratio (OR) 7.31, P = .001, stenosis ≥90%, OR 34.05, P = .0001, and serial stenosis ≥50% OR of 3.55, P = .006. The PPV of CCTA for ischemia by SPECT-MPI rises as stenosis severity increases. Luminal stenosis ≥90% on CCTA strongly predicts ischemia, while &lt;50% stenosis strongly predicts the absence of ischemia. Serial stenosis of ≥50% in a vessel may offer incremental value in addition to stenosis severity in predicting ischemia

Simplified Approach to Predicting Obstructive Coronary Disease With Integration of Coronary Calcium: Development and External Validation

BACKGROUND The Diamond-Forrester model was used extensively to predict obstructive coronary artery disease (CAD) but overestimates probability in current populations. Coronary artery calcium (CAC) is a useful marker of CAD, which is not routinely integrated with other features. We derived simple likelihood tables, integrating CAC with age, sex, and cardiac chest pain to predict obstructive CAD. METHODS AND RESULTS The training population included patients from 3 multinational sites (n=2055), with 2 sites for external testing (n=3321). We determined associations between age, sex, cardiac chest pain, and CAC with the presence of obstructive CAD, defined as any stenosis ≥50% on coronary computed tomography angiography. Prediction performance was assessed using area under the receiver-operating characteristic curves (AUCs) and compared with the CAD Consortium models with and without CAC, which require detailed calculations, and the updated Diamond-Forrester model. In external testing, the proposed likelihood tables had higher AUC (0.875 [95% CI, 0.862-0.889]) than the CAD Consortium clinical+CAC score (AUC, 0.868 [95% CI, 0.855-0.881]; P=0.030) and the updated Diamond-Forrester model (AUC, 0.679 [95% CI, 0.658-0.699]; P<0.001). The calibration for the likelihood tables was better than the CAD Consortium model (Brier score, 0.116 versus 0.121; P=0.005). CONCLUSIONS We have developed and externally validated simple likelihood tables to integrate CAC with age, sex, and cardiac chest pain, demonstrating improved prediction performance compared with other risk models. Our tool affords physicians with the opportunity to rapidly and easily integrate a small number of important features to estimate a patient's likelihood of obstructive CAD as an aid to clinical management

The accuracy of coronary CT angiography in patients with coronary calcium score above 1000 Agatston Units:Comparison with quantitative coronary angiography: Coronary CT Angiography in High Coronary Calcium

BACKGROUND: High amounts of coronary artery calcium (CAC) pose challenges in interpretation of coronary CT angiography (CCTA). The accuracy of stenosis assessment by CCTA in patients with very extensive CAC is uncertain. METHODS: Retrospective study was performed including patients who underwent clinically directed CCTA with CAC score >1000 and invasive coronary angiography within 90 days. Segmental stenosis on CCTA was graded by visual inspection with two-observer consensus using categories of 0%, 1–24%, 25–49%, 50–69%, 70–99%, 100% stenosis, or uninterpretable. Blinded quantitative coronary angiography (QCA) was performed on all segments with stenosis ≥25% by CCTA. The primary outcome was vessel-based agreement between CCTA and QCA, using significant stenosis defined by diameter stenosis ≥ 70%. Secondary analyses on a per-patient basis and inclusive of uninterpretable segments were performed. RESULTS: 726 segments with stenosis ≥25% in 346 vessels within 119 patients were analyzed. Median coronary calcium score was 1616 (1221–2118). CCTA identification of QCA-based stenosis resulted in a per-vessel sensitivity of 79%, specificity of 75%, positive predictive value (PPV) of 45%, negative predictive value (NPV) of 93%, and accuracy 76% (68 false positive and 15 false negative). Per-patient analysis had sensitivity 94%, specificity 55%, PPV 63%, NPV 92%, and accuracy 72% (30 false-positive and 3 false-negative). Inclusion of uninterpretable segments had variable effect on sensitivity and specificity, depending on whether they are considered as significant or non-significant stenosis. CONCLUSIONS: In patients with very extensive CAC (>1000 Agatston units), CCTA retained a negative predictive value > 90% to identify lack of significant stenosis on a per-vessel and per-patient level, but frequently overestimated stenosis

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P&lt;0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP

Clinical risk factors and atherosclerotic plaque extent to define risk for major events in patients without obstructive coronary artery disease: the long-term coronary computed tomography angiography CONFIRM registry.

AimsIn patients without obstructive coronary artery disease (CAD), we examined the prognostic value of risk factors and atherosclerotic extent.Methods and resultsPatients from the long-term CONFIRM registry without prior CAD and without obstructive (≥50%) stenosis were included. Within the groups of normal coronary computed tomography angiography (CCTA) (N = 1849) and non-obstructive CAD (N = 1698), the prognostic value of traditional clinical risk factors and atherosclerotic extent (segment involvement score, SIS) was assessed with Cox models. Major adverse cardiac events (MACE) were defined as all-cause mortality, non-fatal myocardial infarction, or late revascularization. In total, 3547 patients were included (age 57.9 ± 12.1 years, 57.8% male), experiencing 460 MACE during 5.4 years of follow-up. Age, body mass index, hypertension, and diabetes were the clinical variables associated with increased MACE risk, but the magnitude of risk was higher for CCTA defined atherosclerotic extent; adjusted hazard ratio (HR) for SIS &gt;5 was 3.4 (95% confidence interval [CI] 2.3-4.9) while HR for diabetes and hypertension were 1.7 (95% CI 1.3-2.2) and 1.4 (95% CI 1.1-1.7), respectively. Exclusion of revascularization as endpoint did not modify the results. In normal CCTA, presence of ≥1 traditional risk factors did not worsen prognosis (log-rank P = 0.248), while it did in non-obstructive CAD (log-rank P = 0.025). Adjusted for SIS, hypertension and diabetes predicted MACE risk in non-obstructive CAD, while diabetes did not increase risk in absence of CAD (P-interaction = 0.004).ConclusionAmong patients without obstructive CAD, the extent of CAD provides more prognostic information for MACE than traditional cardiovascular risk factors. An interaction was observed between risk factors and CAD burden, suggesting synergistic effects of both

Coronary atherosclerosis scoring with semiquantitative CCTA risk scores for prediction of major adverse cardiac events: Propensity score-based analysis of diabetic and non-diabetic patients.

AIMS:We aimed to compare semiquantitative coronary computed tomography angiography (CCTA) risk scores - which score presence, extent, composition, stenosis and/or location of coronary artery disease (CAD) - and their prognostic value between patients with and without diabetes mellitus (DM). Risk scores derived from general chest-pain populations are often challenging to apply in DM patients, because of numerous confounders. METHODS:Out of a combined cohort from the Leiden University Medical Center and the CONFIRM registry with 5-year follow-up data, we performed a secondary analysis in diabetic patients with suspected CAD who were clinically referred for CCTA. A total of 732 DM patients was 1:1 propensity-matched with 732 non-DM patients by age, sex and cardiovascular risk factors. A subset of 7 semiquantitative CCTA risk scores was compared between groups: 1) any stenosis ≥50%, 2) any stenosis ≥70%, 3) stenosis-severity component of the coronary artery disease-reporting and data system (CAD-RADS), 4) segment involvement score (SIS), 5) segment stenosis score (SSS), 6) CT-adapted Leaman score (CT-LeSc), and 7) Leiden CCTA risk score. Cox-regression analysis was performed to assess the association between the scores and the primary endpoint of all-cause death and non-fatal myocardial infarction. Also, area under the receiver-operating characteristics curves were compared to evaluate discriminatory ability. RESULTS:A total of 1,464 DM and non-DM patients (mean age 58 ± 12 years, 40% women) underwent CCTA and 155 (11%) events were documented after median follow-up of 5.1 years. In DM patients, the 7 semiquantitative CCTA risk scores were significantly more prevalent or higher as compared to non-DM patients (p ≤ 0.022). All scores were independently associated with the primary endpoint in both patients with and without DM (p ≤ 0.020), with non-significant interaction between the scores and diabetes (interaction p ≥ 0.109). Discriminatory ability of the Leiden CCTA risk score in DM patients was significantly better than any stenosis ≥50% and ≥70% (p = 0.003 and p = 0.007, respectively), but comparable to the CAD-RADS, SIS, SSS and CT-LeSc that also focus on the extent of CAD (p ≥ 0.265). CONCLUSION:Coronary atherosclerosis scoring with semiquantitative CCTA risk scores incorporating the total extent of CAD discriminate major adverse cardiac events well, and might be useful for risk stratification of patients with DM beyond the binary evaluation of obstructive stenosis alone