The clinical profile of SC is considerably broader than reported previously. Cardiovascular magnetic resonance imaging at the time of initial clinical presentation may provide relevant functional and tissue information that might aid in the establishment of the diagnosis of SC.

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations.Design Retrospective pooled analysis of individual patient data.Setting 18 hospitals in Europe and the United States.Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively). Main outcome measuresObstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined. ResultsWe included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory.Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates. IntroductionIn the United States, about 10.2 million people have chest pain complaints each year, 1 and more than 1.1 million diagnostic procedures of catheter based coronary angiography are performed on inpatients each year. 2 In a recent report based on the national cardiovascular data registry of the American College of Cardiology, 3 only 41% of patients undergoing elective procedures of catheter based coronary angiographies are diagnosed with obstructive coronary artery disease. The report's authors concluded that better risk stratification was needed, underlined by decision analyses showing that the choice of further diagnostic investigation in patients with chest pain depends primarily on the pretest probability of coronary artery disease. [4][5][6] The American College of Cardiology/American Heart Associatio...

The aim of our study was to assess the prevalence of variants and anomalies of the coronary artery tree in patients who underwent 64-slice computed tomography coronary angiography (CT-CA) for suspected or known coronary artery disease. A total of 543 patients (389 male, mean age 60.5±10.9) were reviewed for coronary artery variants and anomalies including post-processing tools. The majority of segments were identified according to the American Heart Association scheme. The coronary dominance pattern results were: right, 86.6%; left, 9.2%; balanced, 4.2%. The left main coronary artery had a mean length of 112±55 mm. The intermediate branch was present in the 21.9%. A variable number of diagonals (one, 25%; two, 49.7%; more than two, 24%; none, 1.3%) and marginals (one, 35.2%; two, 46.2%; more than two, 18%; none, 0.6%) was visualized. Furthermore, CT-CA may visualize smaller branches such as the conus branch artery (98%), the sinus node artery (91.6%), and the septal branches (93%). Single or associated coronary anomalies occurred in 18.4% of the patients, with the following distribution: 43 anomalies of origin and course, 68 intrinsic anomalies (59 myocardial bridging, nine aneurisms), three fistulas. In conclusion, 64-slice CT-CA provides optimal visualization of the variable and complex anatomy of coronary arteries because of the improved isotropic spatial resolution and flexible post-processing tool.

No abstract

We assessed the effect of intra-coronary attenuation on diagnostic accuracy using 64-slice computed tomography coronary angiography (CT-CA). We enrolled 170 patients with suspected coronary artery disease who underwent conventional coronary angiography (CA) and 64-slice CT-CA (100 ml of Iomeprol 400 mg I/ml at 4 ml/s). The study population was divided into two groups (85 patients each based on median attenuation of 326 HU) based on mean arterial attenuation; group 1 with low attenuation and group 2 with high attenuation. Diagnostic accuracy for the detection of significant coronary artery stenosis was determined for both groups using CA as reference standard. Overall, 163 significant stenoses were detected in 1,030 assessable coronary artery segments in group 1 compared with 160 significant stenoses in 1,020 assessable segments in group 2. The average intra-coronary attenuation was significantly (P < 0.05) higher for group 2 (388 +/- 46 HU) compared with group 1 (291 +/- 33 HU). The corresponding sensitivity and specificity values for detection of significant coronary artery stenosis were higher for group 2 (96.3% and 97.6%, respectively) than for group 1 (82.8% and 93.2%, respectively) and were more marked in distal coronary segments than in proximal segments. Higher intra-coronary attenuation on CT-CA results in greater diagnostic accuracy for detection of coronary artery stenosis.