W. Bob Meijboom

Diagnostic accuracy of 64-slice computed tomography coronary angiography: a prospective, multicenter, multivendor study.

OBJECTIVES This study sought to determine the diagnostic accuracy of 64-slice computed tomographic coronary angiography (CTCA) to detect or rule out significant coronary artery disease (CAD). BACKGROUND CTCA is emerging as a noninvasive technique to detect coronary atherosclerosis. METHODS We conducted a prospective, multicenter, multivendor study involving 360 symptomatic patients with acute and stable anginal syndromes who were between 50 and 70 years of age and were referred for diagnostic conventional coronary angiography (CCA) from September 2004 through June 2006. All patients underwent a nonenhanced calcium scan and a CTCA, which was compared with CCA. No patients or segments were excluded because of impaired image quality attributable to either coronary motion or calcifications. Patient-, vessel-, and segment-based sensitivities and specificities were calculated to detect or rule out significant CAD, defined as >or=50% lumen diameter reduction. RESULTS The prevalence among patients of having at least 1 significant stenosis was 68%. In a patient-based analysis, the sensitivity for detecting patients with significant CAD was 99% (95% confidence interval [CI]: 98% to 100%), specificity was 64% (95% CI: 55% to 73%), positive predictive value was 86% (95% CI: 82% to 90%), and negative predictive value was 97% (95% CI: 94% to 100%). In a segment-based analysis, the sensitivity was 88% (95% CI: 85% to 91%), specificity was 90% (95% CI: 89% to 92%), positive predictive value was 47% (95% CI: 44% to 51%), and negative predictive value was 99% (95% CI: 98% to 99%). CONCLUSIONS Among patients in whom a decision had already been made to obtain CCA, 64-slice CTCA was reliable for ruling out significant CAD in patients with stable and unstable anginal syndromes. A positive 64-slice CTCA scan often overestimates the severity of atherosclerotic obstructions and requires further testing to guide patient management.

Comprehensive Assessment of Coronary Artery Stenoses: Computed Tomography Coronary Angiography Versus Conventional Coronary Angiography and Correlation With Fractional Flow Reserve in Patients With Stable Angina

OBJECTIVES We sought to determine the diagnostic accuracy of noninvasive visual (computed tomography coronary angiography [CTCA]) and quantitative computed tomography coronary angiography (QCT) to predict the hemodynamic significance of a coronary stenosis, using intracoronary fractional flow reserve (FFR) as the reference standard. BACKGROUND It has been demonstrated that CTCA provides excellent diagnostic sensitivity for identifying coronary stenoses, but may lack accurate delineation of the hemodynamic significance. METHODS We investigated 79 patients with stable angina pectoris who underwent both 64-slice or dual-source CTCA and FFR measurement of discrete coronary stenoses. CTCA and conventional coronary angiography (CCA), and QCT and quantitative coronary angiography (QCA), were performed to determine the severity of a stenosis that was compared with FFR measurements. A significant anatomical or functional stenosis was defined as >/=50% diameter stenosis or an FFR <0.75. Stented segments and bypass grafts were not included in the analysis. RESULTS A total of 89 stenoses were evaluated of which 18% (16 of 89) had an FFR <0.75. The diagnostic accuracy of CTCA, QCT, CCA, and QCA to detect a hemodynamically significant coronary lesion was 49%, 71%, 61%, and 67%, respectively. Correlation between QCT and QCA with FFR measurement was weak (R values of -0.32 and -0.30, respectively). Correlation between QCT and QCA was significant, but only moderate (R = 0.53; p < 0.0001). CONCLUSIONS The anatomical assessment of the hemodynamic significance of coronary stenoses determined by visual CTCA, CCA, or QCT or QCA does not correlate well with the functional assessment of FFR. Determining the hemodynamic significance of an angiographically intermediate stenosis remains relevant before referral for revascularization treatment.

A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension

AIMS The aim was to validate, update, and extend the Diamond-Forrester model for estimating the probability of obstructive coronary artery disease (CAD) in a contemporary cohort. METHODS AND RESULTS Prospectively collected data from 14 hospitals on patients with chest pain without a history of CAD and referred for conventional coronary angiography (CCA) were used. Primary outcome was obstructive CAD, defined as ≥ 50% stenosis in one or more vessels on CCA. The validity of the Diamond-Forrester model was assessed using calibration plots, calibration-in-the-large, and recalibration in logistic regression. The model was subsequently updated and extended by revising the predictive value of age, sex, and type of chest pain. Diagnostic performance was assessed by calculating the area under the receiver operating characteristic curve (c-statistic) and reclassification was determined. We included 2260 patients, of whom 1319 had obstructive CAD on CCA. Validation demonstrated an overestimation of the CAD probability, especially in women. The updated and extended models demonstrated a c-statistic of 0.79 (95% CI 0.77-0.81) and 0.82 (95% CI 0.80-0.84), respectively. Sixteen per cent of men and 64% of women were correctly reclassified. The predicted probability of obstructive CAD ranged from 10% for 50-year-old females with non-specific chest pain to 91% for 80-year-old males with typical chest pain. Predictions varied across hospitals due to differences in disease prevalence. CONCLUSION Our results suggest that the Diamond-Forrester model overestimates the probability of CAD especially in women. We updated the predictive effects of age, sex, type of chest pain, and hospital setting which improved model performance and we extended it to include patients of 70 years and older.

CT coronary angiography in patients suspected of having coronary artery disease: decision making from various perspectives in the face of uncertainty.

PURPOSE To determine the cost-effectiveness of computed tomographic (CT) coronary angiography as a triage test, performed prior to conventional coronary angiography, by using a Markov model. MATERIALS AND METHODS A Markov model was used to analyze the cost-effectiveness of CT coronary angiography performed as a triage test prior to conventional coronary angiography from the perspective of the patient, physician, hospital, health care system, and society by using recommendations from the United Kingdom, the United States, and the Netherlands for cost-effectiveness analyses. For CT coronary angiography, a range of sensitivities (79%-100%) and specificities (63%-94%) were used to help diagnose significant coronary artery disease (CAD). Optimization criteria (ie, outcomes considered) were: revised posttest probability of CAD, life-years, quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). Extensive sensitivity analysis was performed. RESULTS For a prior probability of CAD of less than 40%, the probability of CAD after CT coronary angiography with negative results was less than 1%. The Markov model calculations from the patient/physician perspective suggest that CT coronary angiography maximizes life-years respectively in 60-year-old men and women at a prior probability of less than 38% and 24% and maximizes QALYs at a prior probability of less than 17% and 11%. From the hospital/health care perspective, CT coronary angiography helps reduce health care and direct nonhealth care-related costs (according to UK/U.S. recommendations), regardless of prior probability, and lowers all costs, including production losses (Netherlands recommendations) at a prior probability of less than 87%-92%. Analysis performed from a societal perspective by using a willingness-to-pay threshold level of euro 80,000/QALY suggests that CT coronary angiography is cost-effective when the prior probability is lower than 44% and 37% in men and women, respectively. Sensitivity analyses showed that results changed across the reported range of sensitivity of CT coronary angiography. CONCLUSION The optimal diagnostic work-up depends on the optimization criterion, prior probability of CAD, and the diagnostic performance of CT coronary angiography.

Quantitative Computed Tomographic Coronary Angiography Does It Predict Functionally Significant Coronary Stenoses

Background—Coronary lesions with a diameter narrowing ≥50% on visual computed tomographic coronary angiography (CTCA) are generally considered for referral to invasive coronary angiography. However, similar to invasive coronary angiography, visual CTCA is often inaccurate in detecting functionally significant coronary lesions. We sought to compare the diagnostic performance of quantitative CTCA with visual CTCA for the detection of functionally significant coronary lesions using fractional flow reserve (FFR) as the reference standard. Methods and Results—CTCA and FFR measurements were obtained in 99 symptomatic patients. In total, 144 coronary lesions detected on CTCA were visually graded for stenosis severity. Quantitative CTCA measurements included lesion length, minimal area diameter, % area stenosis, minimal lumen diameter, % diameter stenosis, and plaque burden [(vessel area−lumen area)/vessel area×100]. Optimal cutoff values of CTCA-derived parameters were determined, and their diagnostic accuracy for the detection of flow-limiting coronary lesions (FFR ⩽0.80) was compared with visual CTCA. FFR was ⩽0.80 in 54 of 144 (38%) coronary lesions. Optimal cutoff values to predict flow-limiting coronary lesion were 10 mm for lesion length, 1.8 mm2 for minimal area diameter, 73% for % area stenosis, 1.5 mm for minimal lumen diameter, 48% for % diameter stenosis, and 76% for plaque burden. No significant difference in sensitivity was found between visual CTCA and quantitative CTCA parameters (P>0.05). The specificity of visual CTCA (42%; 95% confidence interval [CI], 31%–54%) was lower than that of minimal area diameter (68%; 95% CI, 57%–77%; P=0.001), % area stenosis (76%; 95% CI, 65%–84%; P<0.001), minimal lumen diameter (67%; 95% CI, 55%–76%; P=0.001), % diameter stenosis (72%; 95% CI, 62%–80%; P<0.001), and plaque burden (63%; 95% CI, 52%–73%; P=0.004). The specificity of lesion length was comparable with that of visual CTCA. Conclusions—Quantitative CTCA improves the prediction of functionally significant coronary lesions compared with visual CTCA assessment but remains insufficient. Functional assessment is still required in lesions of moderate stenosis to accurately detect impaired FFR.

Quantitative CT Coronary Angiography: Does It Predict Functionally Significant Coronary Stenoses?

Background—Coronary lesions with a diameter narrowing ≥50% on visual computed tomographic coronary angiography (CTCA) are generally considered for referral to invasive coronary angiography. However, similar to invasive coronary angiography, visual CTCA is often inaccurate in detecting functionally significant coronary lesions. We sought to compare the diagnostic performance of quantitative CTCA with visual CTCA for the detection of functionally significant coronary lesions using fractional flow reserve (FFR) as the reference standard. Methods and Results—CTCA and FFR measurements were obtained in 99 symptomatic patients. In total, 144 coronary lesions detected on CTCA were visually graded for stenosis severity. Quantitative CTCA measurements included lesion length, minimal area diameter, % area stenosis, minimal lumen diameter, % diameter stenosis, and plaque burden [(vessel area−lumen area)/vessel area×100]. Optimal cutoff values of CTCA-derived parameters were determined, and their diagnostic accuracy for the detection of flow-limiting coronary lesions (FFR ⩽0.80) was compared with visual CTCA. FFR was ⩽0.80 in 54 of 144 (38%) coronary lesions. Optimal cutoff values to predict flow-limiting coronary lesion were 10 mm for lesion length, 1.8 mm2 for minimal area diameter, 73% for % area stenosis, 1.5 mm for minimal lumen diameter, 48% for % diameter stenosis, and 76% for plaque burden. No significant difference in sensitivity was found between visual CTCA and quantitative CTCA parameters (P>0.05). The specificity of visual CTCA (42%; 95% confidence interval [CI], 31%–54%) was lower than that of minimal area diameter (68%; 95% CI, 57%–77%; P=0.001), % area stenosis (76%; 95% CI, 65%–84%; P<0.001), minimal lumen diameter (67%; 95% CI, 55%–76%; P=0.001), % diameter stenosis (72%; 95% CI, 62%–80%; P<0.001), and plaque burden (63%; 95% CI, 52%–73%; P=0.004). The specificity of lesion length was comparable with that of visual CTCA. Conclusions—Quantitative CTCA improves the prediction of functionally significant coronary lesions compared with visual CTCA assessment but remains insufficient. Functional assessment is still required in lesions of moderate stenosis to accurately detect impaired FFR.

Non-invasive visualization of coronary atherosclerosis: State-of-art

Coronary artery disease remains the leading cause of death in the Western world. Non-invasive coronary artery imaging challenges any diagnostic modality because the coronary arteries are small and tortuous, whereas cardiac contraction and respiration cause motion artifacts. Therefore, non-invasive coronary imaging requires high spatial and temporal resolution. This review discusses the feasible applications in coronary imaging of magnetic resonance imaging and multi-slice computed tomography (MSCT), which are currently the only non-invasive diagnostic modalities for direct coronary atherosclerosis imaging. Particular attention and focus is devoted to the potential indications and clinical impact of MSCT due to its fast development and the robust results recently reported. MSCT of the coronary arteries is a promising imaging modality for the assessment of the coronary lumen and wall.

Incremental value of the CT coronary calcium score for the prediction of coronary artery disease

Objectives:To validate published prediction models for the presence of obstructive coronary artery disease (CAD) in patients with new onset stable typical or atypical angina pectoris and to assess the incremental value of the CT coronary calcium score (CTCS).Methods:We searched the literature for clinical prediction rules for the diagnosis of obstructive CAD, defined as ≥50% stenosis in at least one vessel on conventional coronary angiography. Significant variables were re-analysed in our dataset of 254 patients with logistic regression. CTCS was subsequently included in the models. The area under the receiver operating characteristic curve (AUC) was calculated to assess diagnostic performance.Results:Re-analysing the variables used by Diamond & Forrester yielded an AUC of 0.798, which increased to 0.890 by adding CTCS. For Pryor, Morise 1994, Morise 1997 and Shaw the AUC increased from 0.838 to 0.901, 0.831 to 0.899, 0.840 to 0.898 and 0.833 to 0.899. CTCS significantly improved model performance in each model.Conclusions:Validation demonstrated good diagnostic performance across all models. CTCS improves the prediction of the presence of obstructive CAD, independent of clinical predictors, and should be considered in its diagnostic work-up.

Computed tomography coronary imaging as a gatekeeper for invasive coronary angiography in patients with newly diagnosed heart failure of unknown aetiology.

To evaluate the accuracy of cardiac computed tomography (CT) in distinguishing CAD and non‐CAD heart failure (HF) and its effectiveness as a gatekeeper for invasive coronary angiography (ICA).