Abstract 2333: Coronary Magnetic Resonance Angiography with Whole Heart Coverage for The Detection of Coronary Arery Stenoses: A Multicenter Study

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Yasutaka Ichikawa ◽  
Hajime Sakuma ◽  
Yasuyuki Kobayashi ◽  
Masaki Ishida ◽  
Kazuhiro Katahira ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Negative Predictive Value ◽  
Multicenter Study ◽  
Predictive Value ◽  
X Ray ◽  
Coronary Mra ◽  
Coronary Magnetic Resonance ◽  
High Negative Predictive Value ◽  
Artery Disease ◽  
Whole Heart

Background: Previous single center studies demonstrated that coronary magnetic resonance angiography (MRA) with whole heart coverage allows for noninvasive detection of coronary artery disease. In this prospective, multicenter study, we investigated the accuracy of whole heart coronary MRA in patients with suspected coronary disease. Methods: The subjects were recruited from five institutions. Free-breathing coronary MRA covering the entire heart were obtained in fifty eight patients by using a 3-dimensional, segmented steady-state free precession sequence without contrast injection. Coronary MRA was interpreted by 3 independent observers. Conventional X-ray coronary angiography was analyzed by a separate blinded reviewer. The diagnostic accuracy of coronary MRA was determined in all segments with reference diameter of 2 mm or more on X-ray coronary angiography regardless of the image quality of MRA. Results: Acquisition of coronary MRA was completed in all patients with an averaged imaging time of 9.8 ± 4.8 min. On patient based analysis, coronary MRA showed the sensitivity of 79.4% (range 64.7–88.2%), the specificity of 70.1% (65.9–80.5%), and the negative predictive value of 89.6% (84.6–93.1%). The sensitivity, specificity and negative predictive value in the segmental analysis were 60.6% (53.8–65.4%), 95.5% (94.2–97.6%) and 97.7% (97.4–98.1%). Conclusions: Coronary MRA with whole heart coverage can provide detection of luminal narrowing of the coronary artery with moderate sensitivity, high specificity and high negative predictive value. The high negative predictive value observed in this multicenter study indicates that noninvasive MRA approach is useful in ruling out significant coronary artery disease.

Abstract 2805: Assessment of Coronary Artery Disease Using Magnetic Resonance Coronary Angiography: A Multicenter Trial

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Shingo Kato ◽  
Hajime Sakuma ◽  
Nanaka Ishida ◽  
Masaki Ishida ◽  
Motonori Nagata ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Magnetic Resonance ◽  
Coronary Angiography ◽  
Multicenter Study ◽  
Sublingual Administration ◽  
X Ray ◽  
Coronary Mra ◽  
Artery Disease ◽  
Roc Area

Background: CT coronary angiography is widely used to assess the presence of significant coronary artery disease (CAD). However, CT approach is associated with low but nonnegligible cancer risk. The purpose of this prospective multicenter study was to evaluate the diagnostic performance of coronary magnetic resonance angiography (MRA) in the ability to identify patients with significant CAD compared with coronary angiography. Materials and Methods: The subjects were recruited from 7 institutions. Free breathing coronary MR angiograms covering the entire coronary artery tree were obtained in 138 patients who were suspicious of CAD. Non-contrast enhanced images were acquired with a commercial 1.5T MR imager and five-element cardiac coils after sublingual administration of isosorbide dinitrate. Conventional X-ray coronary angiography was performed within 4 weeks after coronary MRA. MR and X-ray angiograms were sent to a core laboratory for blinded interpretation. Coronary MR angiograms were evaluated by two experienced investigators by using sliding partial MIP reconstruction. Quantitative X-ray coronary angiography analysis was performed with significant CAD defined as luminal narrowing of at least 50% of the diameter. Results: The mean imaging time of coronary MRA was 9.5 ± 4.9 minutes. The prevalence of significant disease on X-ray angiography was 45% (62/138). On a vessel-based analysis, the area under receiver operating characteristic (ROC) curve for the MRA compared with X-ray angiography was 0.90 (95% CI; 0.86 to 0.93). On a patient based analysis, the ROC area was 0.88 (95% CI; 0.81– 0.93). The sensitivity, specificity, positive and negative predictive values of coronary MRA by vessel analysis were 78% (95% CI; 68 – 86%), 86% (82–90%), 60% (51– 69%), 94% (90–96%). These values by patient analysis were 87% (95% CI; 76–94%), 71% (59 – 81%), 71% (59 – 81%), 87% (76–94%). Conclusions: In the current multicenter study using commercial 1.5T MR imagers and sliding partial MIP reconstruction, the diagnostic accuracy of coronary MRA compared to quantitative coronary angiography is good, reflected by an ROC area of 0.88 on patient-based analysis. High negative predictive value indicates that coronary MRA can be used for screening CAD.

Computed tomography myocardial perfusion

ESC CardioMed ◽  
2018 ◽  
pp. 556-560
Author(s):  
Amita Singh ◽  
Noreen Nazir ◽  
Victor Mor-Avi ◽  
Amit R. Patel
Keyword(s):  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Myocardial Perfusion ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Single Photon ◽  
Photon Emission ◽  
High Negative Predictive Value ◽  
Artery Disease

Coronary computed tomography angiography (CTA) has been widely adopted as a non-invasive tool for the evaluation of coronary artery disease. Given its high negative predictive value, it is an accurate modality to rule out obstructive coronary artery disease in the setting of chest pain. While the sensitivity and derived negative predictive value of coronary CTA are excellent, the specificity and positive predictive value are lower due to the difficult image interpretation in the presence of heavy coronary calcification, stents, coronary bypass grafts, motion artefacts, and arrhythmias. Vasodilator computed tomography myocardial perfusion (CTP) is an emerging technique with the ability to identify myocardial segments perfused by haemodynamically significant coronary stenoses. A growing number of studies have demonstrated the feasibility and diagnostic accuracy of CTP in comparison to a number of reference standards, including single-photon emission computed tomography, cardiovascular magnetic resonance imaging, and invasive coronary angiography with and without fractional flow reserve testing. This chapter summarizes the current state of CTP.

Abstract 5803: Optimal Threshold for Multi Detector Computer Tomography to Detect Physiologically Significant Stenosis in Patients with Ischemic Heart Disease

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Takashi Yamano ◽  
Atsushi Tanaka ◽  
Takashi Tanimoto ◽  
Shigeho Takarada ◽  
Hiroki Kitabata ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Coronary Angiography ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Optimal Threshold ◽  
Fractional Flow ◽  
Significant Stenosis ◽  
Artery Disease

PURPOSE: Sixty-four multi detector computed tomography angiography (64-MDCT) has emerged as a rapidly developing method for the noninvasive detection of coronary artery disease with high negative predictive value and relatively low positive predictive value, especially in patients with intermediate-severity coronary artery disease (ISCAD). There are, however, few studies regarding with optimal threshold for detection of physiologically significant stenosis in 64-MDCT. The purpose of this study was to investigate the optimal threshold for 64-MDCT to detect physiologically significant stenosis using fractional flow reserve of the myocardium (FFRmyo) in patients with ISCAD. METHODS: We enrolled single lesions detected by 64-MDCT of 64 ISCAD patients (age, 68.3 +/− 10.2 years; 78% male). FFRmyo </= 0.75 measured by a 0.014-inch pressure wire was used as the gold standard for presence of physiologically significant stenosis. The area stenosis (%AS) in 64-MDCT were compared with the results of FFRmyo and percent diameter stenosis (%DS) in quantitative coronary angiography (QCA) during elective coronary angiography. Using receiver operating characteristic (ROC) analysis, the optimum threshold for percent area stenosis (%AS) in 64-MDCT was determined in the prediction of FFRmyo </= 0.75. RESULTS: There was an inverse correlation between %AS in 64-MDCT and FFRmyo (65 +/− 20 % and 0.71 +/− 0.16, respectively; r = −0.67; p < 0.01). Furthermore, there was a positive correlation between %AS in 64-MDCT and %DS in QCA (65 +/− 20 % and 63 +/− 19 %, respectively; r = 0.69; p < 0.01). Using a cutoff of 62 %AS in 64-MDCT, ROC curve analysis shows 79 % sensitivity, 85 % specificity, 82% positive predictive value, 83% negative predictive value and 83% accuracy for detecting physiologically significant stenosis. CONCLUSION: > 62 %AS in 64-MDCT could predict the physiologically significant coronary stenosis in patients with ISCAD. Applying an alternative threshold to detect physiologically significant stenosis might contribute to improve the diagnostic accuracy for 64-MDCT in patients with ISCAD.

Abstract 2806: Whole Heart Coronary Magnetic Resonance Angiography Using 32-Channel Cardiac Coils and High Parallel Imaging Factor

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Motonori Nagata ◽  
Hajime Sakuma ◽  
Nanaka Ishida ◽  
Hiroshi Nakajima ◽  
Masaki Ishida ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Coronary Angiography ◽  
Parallel Imaging ◽  
Noninvasive Detection ◽  
Acquisition Time ◽  
Luminal Diameter ◽  
X Ray ◽  
Coronary Mra ◽  
Imaging Time ◽  
Whole Heart

PURPOSE Coronary MRA provides noninvasive detection of coronary artery disease (CAD) without administration of contrast medium or exposing the patient to radiation. However, use of coronary MRA in excluding patients with CAD has been limited due to lengthy imaging time. The purpose of this study was to reduce acquisition time of coronary MRA by using 32 channel cardiac coils and high parallel imaging factor, and to evaluate diagnostic performance of this method in detecting significant CAD. METHOD AND MATERIALS Sixty-two patients with suspected CAD were studied. Free-breathing coronary MRA encompassing the entire heart was acquired by using 32-channel coils and SENSE factor of 4. After monitoring motion of the coronary artery on cine MRI, MR angiograms were acquired during diastole in 46 patients (acquisition window 82±57ms) and during systole in 16 patients (50±19ms). Coronary MRA images were interpreted by 2 observers by employing a sliding SLAB MIP method. All patients underwent X-ray coronary angiography within 4 weeks from MRA, and significant CAD was defined as a luminal diameter reduction of 50% or more by QCA. All lesions with a reference diameter of 2mm or more on X-ray angiography were included when determining the accuracy of coronary MRA. RESULTS Acquisition of MRA was completed in all 62 patients, with the averaged imaging time of 6.1±2.6min. High SENSE factor achieved by 32-channel coils resulted in substantial reduction of imaging time by factor of >2, with the image quality score (4.6±0.2) at least equivalent to that by conventional 5-channel coils and SENSE factor of 2 (4.5±0.2). Significant CAD was observed on X-ray coronary angiography in 39 patients. MRA detected 33(85%) of 39 patients having CAD, with high specificity of 96%(22/23). All 16 patients with double- or triple-vessel diseases were detected by MRA. On a vessel based analysis, Whole-heart coronary MRA demonstrated sensitivity of 83%(49/59), specificity of 94%(119/127) and NPV of 92%(119/129). CONCLUSION Whole-heart coronary MRA with 1.5T MR imager and 32-chennel coils permits noninvasive detection of CAD with substantially reduced imaging time and high study success rate. High NPV (>90%) indicated the value of this approach in ruling out significant CAD.

Abstract 15233: The Lesion Length Gives a Better Effect on the Fractional Flow Reserve Than the Minimal Luminal Area in the Intermediate Coronary Artery Lesion

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Yoon Juneyoung ◽  
Xiongjie Jin ◽  
Kyong-Woo Seo ◽  
Jin-sun Park ◽  
Hyoung-Mo Yang ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Lesion Length ◽  
Visual Estimation ◽  
Luminal Area ◽  
Artery Disease

Introduction: The pressure gradient of the circulation fluid in a stenosis area depends on minimal luminal area (MLA) of the stenosis, lesion length (LL), and the fluid velocity. However, the correlation of the LL and the MLA; the cutoff values are uncertain. Hypothesis: LL and MLA differently influences the FFR. Methods: We studied 117 patients with intermediate coronary artery disease who underwent FFR and IVUS measurement out of 302 patients in FAVOR study. This study was a prospective, 1:1 randomized, open label multicenter trial to demonstrate the clinical outcomes between FFR and IVUS-guided PCI. Inclusion criteria were as follows: 1)Angina or documented silent ischemia 2) De novo intermediate coronary artery disease (30-70% diameter stenosis) by visual estimation, 3) Reference vessel diameter ≥ 3.0mm by visual estimation. We excluded left main disease, MI, EF< 40%, and graft vessel. There were no significant differences in baseline clinical characteristics. The mean values are the QCA (54.3±14.0 %), MLA (3.6±1.4 mm2) and LL (20.6±1.4mm), respectively. We were performed the path analysis using AMOS 18, and estimated the ROC curve in SPSS 18. Results: Standardized estimates were the LL -0.47,QCA -0.28 and MLA -0.21 (R2=0.594, p<0.000) in path analysis. The model is recursive and statistically significant. The FFR was ≤0.80 in 47 lesions (31%). The optimal LL for an FFR of ≤0.80 was 15.8mm (90% sensitivity, 50% specificity, 44% positive predictive value, 87% negative predictive value, area under the curve: 0.75, 95% CI: 0.66 to 0.85; p < 0.001) and MLA 3.9mm (sensitivity 86%, specificity 59%, 35% positive predictive value , 94% negative predictive value, area under the curve: 0.78, 95% CI: 0.67 to 0.85; p < 0.001) Conclusions: The lesion length influenced more the FFR than MLA. The lesion length ≥ 15.8mm and MLA ≤ 3.9mm are risk zones, which need to be confirm the functional status with FFR because of the low positive predictive value

Abstract 587: Absence of Coronary Calcium on Non-contrast Enhanced, Non ECG-gated CT Correlates with Non-obstructive Coronary Artery Disease. A Retrospective Data Analysis of Liver Transplant Recipients

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Hilda M Gonzalez-Bonilla ◽  
Akanksha Thakkar ◽  
Antonio Duran ◽  
Alpana Senapati ◽  
Nakul Gupta ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Liver Transplant ◽  
Negative Predictive Value ◽  
Sensitivity And Specificity ◽  
Predictive Value ◽  
Chest Ct ◽  
Transplant Recipients ◽  
Artery Disease ◽  
Liver Transplant Recipients

Background: Coronary angiography (CAG) remains the gold standard to diagnose coronary artery disease (CAD). However, it is associated with multiple risks and its utility is not well defined in the liver transplant population. Alternatives to evaluate for CAD such as coronary artery calcium score (CACS) are being increasingly investigated. Hypothesis: To determine if the absence of coronary arterial calcium (CACS=0) on non-contrast, non-ECG gated chest CT scan can exclude obstructive CAD in liver transplant patients. Methods: We performed a retrospective analysis of data collected from liver transplant recipients. We included patients who had a CT chest without contrast and CAG less than one year apart. Agatston score was derived from non-IV contrast, non-ECG gated chest CT’s utilizing the syngo.via platform (Siemens Healthcare). CACS was compared against CAG. Patients with coronary stents were excluded. We determined NPV, PPV, sensitivity and specificity of using CACS = 0 as predictor of the absence of obstructive CAD. Results: Mean age at date of transplant was 59.03 and males accounted for 68.8% of our population. The negative predictive value for CACS=0 as a predictor of non-obstructive CAD was 100%. Positive predictive value for CACS≥1 was 6.8%. Sensitivity and specificity for the correlation between CACS and CAD were 100% and 33% respectively (Figure 1). CACS was stratified into four subgroups based severity, and we found that all patients with obstructive CAD had scores >400 (Figure 2). Conclusion: The absence of coronary arterial calcium (CACS=0) on non-contrast, non ECG gated chest CT has a high negative predictive value and can exclude the presence of obstructive CAD.

MDCT and detection of coronary artery disease

2015 ◽  
pp. 271-285
Author(s):  
Stephan Achenbach
Keyword(s):  
Coronary Artery ◽  
Predictive Value ◽  
Acute Chest Pain ◽  
Intermediate Risk ◽  
Coronary Cta ◽  
Improve Risk Stratification ◽  
Coronary Atherosclerotic Plaque ◽  
High Negative Predictive Value ◽  
Artery Disease ◽  
Asymptomatic Individuals

Coronary CT angiography (coronary CTA) with multi-detector row CT (MDCT) systems permits visualization of the coronary arteries and detection of stenoses. Image quality depends on a low and stable heart rate, so patients need to be selected and adequately prepared. Due to a very high negative predictive value, coronary CTA is useful to rule out coronary artery stenosis, especially in low-to-intermediate risk patients with stable or acute chest pain. Imaging of patients with coronary artery stents and patients after bypass surgery is challenging and only in selected situations considered appropriate. Coronary CTA can visualize non-stenotic coronary atherosclerotic plaque, the presence and extent of which is associated with cardiovascular events, but there is no indication to perform coronary CTA for screening of asymptomatic individuals at low-intermediate risk. Coronary calcium, on the other hand, has a well-established predictive value and can be considered to improve risk stratification in asymptomatic individuals with a low to intermediate cardiovascular risk profile.

scholarly journals Diagnostic performance of deep learning-based vascular extraction and stenosis detection technique for coronary artery disease

2020 ◽  
Vol 93 (1113) ◽  
pp. 20191028 ◽  
Author(s):  
Meng Chen ◽  
Ximing Wang ◽  
Guangyu Hao ◽  
Xujie Cheng ◽  
Chune Ma ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Deep Learning ◽  
Coronary Artery ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Operating Characteristics ◽  
Stenosis Detection ◽  
Artery Disease

Objective: To investigate the diagnostic performance of deep learning (DL)-based vascular extraction and stenosis detection technology in assessing coronary artery disease (CAD). Methods: The diagnostic performance of DL technology was evaluated by retrospective analysis of coronary computed tomography angiography in 124 suspected CAD patients, using invasive coronary angiography as reference standard. Lumen diameter stenosis ≥50% was considered obstructive, and the diagnostic performances were evaluated at per-patient, per-vessel and per-segment levels. The diagnostic performances between DL model and reader model were compared by the areas under the receiver operating characteristics curves (AUCs). Results: In patient-based analysis, AUC of 0.78 was obtained by DL model to detect obstructive CAD [sensitivity of 94%, specificity of 63%, positive predictive value of 94%, and negative predictive value of 59%], While AUC by reader model was 0.74 (sensitivity of 97%, specificity of 50%, positive predictive value of 93%, negative predictive value of 73%). In vessel-based analysis, the AUCs of DL model and reader model were 0.87 and 0.89 respectively. In segment-based analysis, the AUCs of 0.84 and 0.89 were obtained by DL model and reader model respectively. It took 0.47 min to analyze all segments per patient by DL model, which is significantly less than reader model (29.65 min) (p < 0.001). Conclusion: The DL technology can accurately and effectively identify obstructive CAD, with less time-consuming, and it could be a reliable diagnostic tool to detect CAD. Advances in knowledge: The DL technology has valuable prospect with the diagnostic ability to detect CAD.

scholarly journals Development and Validation of a Predictive Model for Coronary Artery Disease Using Machine Learning

2021 ◽  
Vol 8 ◽  
Author(s):  
Chen Wang ◽  
Yue Zhao ◽  
Bingyu Jin ◽  
Xuedong Gan ◽  
Bin Liang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Random Forest ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Validation Cohort ◽  
Random Forest Algorithm ◽  
Artery Disease

Early identification of coronary artery disease (CAD) can prevent the progress of CAD and effectually lower the mortality rate, so we intended to construct and validate a machine learning model to predict the risk of CAD based on conventional risk factors and lab test data. There were 3,112 CAD patients and 3,182 controls enrolled from three centers in China. We compared the baseline and clinical characteristics between two groups. Then, Random Forest algorithm was used to construct a model to predict CAD and the model was assessed by receiver operating characteristic (ROC) curve. In the development cohort, the Random Forest model showed a good AUC 0.948 (95%CI: 0.941–0.954) to identify CAD patients from controls, with a sensitivity of 90%, a specificity of 85.4%, a positive predictive value of 0.863 and a negative predictive value of 0.894. Validation of the model also yielded a favorable discriminatory ability with the AUC, sensitivity, specificity, positive predictive value, and negative predictive value of 0.944 (95%CI: 0.934–0.955), 89.5%, 85.8%, 0.868, and 0.886 in the validation cohort 1, respectively, and 0.940 (95%CI: 0.922–0.960), 79.5%, 94.3%, 0.932, and 0.823 in the validation cohort 2, respectively. An easy-to-use tool that combined 15 indexes to assess the CAD risk was constructed and validated using Random Forest algorithm, which showed favorable predictive capability (http://45.32.120.149:3000/randomforest). Our model is extremely valuable for clinical practice, which will be helpful for the management and primary prevention of CAD patients.

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