PURPOSE: To develop a method to determine significant stenosis at whole-heart coronary magnetic resonance (MR) angiography and to evaluate the accuracy and reproducibility of this approach. MATERIALS AND METHODS: The institutional review board approved the study, and all participants provided written informed consent. Sixty-two patients who were suspected of having coronary artery disease (CAD) and were scheduled for conventional coronary angiography were included. Coronary MR angiography was performed by using a 1.5-T imager with 32-channel coils. Luminal narrowing was evaluated with quantitative analysis (QA) of coronary MR angiograms on the basis of the signal intensity profile along the vessel. Percentage stenosis with QA of coronary MR angiograms was calculated as [1 - (SI(min)/SI(ref))] × 100, where SI(min) is minimal signal intensity and SI(ref) is corresponding reference signal intensity. Diagnostic performance of QA of coronary MR angiograms for predicting at least a 50% reduction in diameter was evaluated by using quantitative coronary angiography (QCA), with conventional angiography findings serving as the reference standard. Receiver operating characteristic (ROC) analysis, Spearman rank correlation, Bland-Altman analysis, and Cohen κ analysis were used. RESULTS: The areas under the ROC curve in a segment-based analysis for detecting significant CAD were 0.96 (95% confidence interval [CI]: 0.94, 0.98) with QA of coronary MR angiograms and 0.93 (95% CI: 0.88, 0.98) with visual assessment. The correlation coefficients between percentage stenosis with QA of coronary MR angiograms and percentage stenosis with QCA were 0.84 (P < .001), 0.80 (P < .001), and 0.66 (P < .001) in the patient-, vessel-, and segment-based analyses, respectively. CONCLUSION: QA of coronary MR angiograms with use of a signal intensity profile along the vessel permits detection of CAD. This method had a diagnostic performance approximately equal to that of visual analysis of coronary MR angiograms with high inter- and intraobserver reliability, allowing for more objective interpretation of coronary MR angiography findings.
PURPOSE: To develop a method to determine significant stenosis at whole-heart coronary magnetic resonance (MR) angiography and to evaluate the accuracy and reproducibility of this approach. MATERIALS AND METHODS: The institutional review board approved the study, and all participants provided written informed consent. Sixty-two patients who were suspected of having coronary artery disease (CAD) and were scheduled for conventional coronary angiography were included. Coronary MR angiography was performed by using a 1.5-T imager with 32-channel coils. Luminal narrowing was evaluated with quantitative analysis (QA) of coronary MR angiograms on the basis of the signal intensity profile along the vessel. Percentage stenosis with QA of coronary MR angiograms was calculated as [1 - (SI(min)/SI(ref))] × 100, where SI(min) is minimal signal intensity and SI(ref) is corresponding reference signal intensity. Diagnostic performance of QA of coronary MR angiograms for predicting at least a 50% reduction in diameter was evaluated by using quantitative coronary angiography (QCA), with conventional angiography findings serving as the reference standard. Receiver operating characteristic (ROC) analysis, Spearman rank correlation, Bland-Altman analysis, and Cohen κ analysis were used. RESULTS: The areas under the ROC curve in a segment-based analysis for detecting significant CAD were 0.96 (95% confidence interval [CI]: 0.94, 0.98) with QA of coronary MR angiograms and 0.93 (95% CI: 0.88, 0.98) with visual assessment. The correlation coefficients between percentage stenosis with QA of coronary MR angiograms and percentage stenosis with QCA were 0.84 (P < .001), 0.80 (P < .001), and 0.66 (P < .001) in the patient-, vessel-, and segment-based analyses, respectively. CONCLUSION: QA of coronary MR angiograms with use of a signal intensity profile along the vessel permits detection of CAD. This method had a diagnostic performance approximately equal to that of visual analysis of coronary MR angiograms with high inter- and intraobserver reliability, allowing for more objective interpretation of coronary MR angiography findings.
Authors: Marc R Dweck; Michelle C Williams; Alastair J Moss; David E Newby; Zahi A Fayad Journal: J Am Coll Cardiol Date: 2016-11-15 Impact factor: 24.094
Authors: Nataliya V Mushenkova; Volha I Summerhill; Dongwei Zhang; Elena B Romanenko; Andrey V Grechko; Alexander N Orekhov Journal: Int J Mol Sci Date: 2020-04-23 Impact factor: 5.923
Authors: Aryan Zahergivar; Madison Kocher; Jeffrey Waltz; Ismail Kabakus; Jordan Chamberlin; Selcuk Akkaya; Ali M Agha; U Joseph Schoepf; Jeremy R Burt Journal: Heliyon Date: 2021-03-18
Authors: Marc R Dweck; Mhairi K Doris; Manish Motwani; Philip D Adamson; Piotr Slomka; Damini Dey; Zahi A Fayad; David E Newby; Daniel Berman Journal: Nat Rev Cardiol Date: 2016-05-26 Impact factor: 32.419