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Effects of Resting Magnetocardio-graphic Imaging on diagnosis of Coronary Artery Disease. Yuanlu Chen, Xiaocheng Liu, Xiangqian Qi, Yi Lian, Yu Song, TEDA International Cardiovascular Hospital, Tianjin, China; Kirsten Tolstrup, Cedars-Sinai Medical Center, Los Angeles, CA;. Background:
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Effects of Resting Magnetocardio-graphic Imaging on diagnosis of Coronary Artery Disease Yuanlu Chen, Xiaocheng Liu, Xiangqian Qi, Yi Lian, Yu Song, TEDA InternationalCardiovascular Hospital,Tianjin, China; Kirsten Tolstrup, Cedars-Sinai Medical Center, Los Angeles, CA;
Background: Magnetocardiographic (MCG) imaging is a new noninvasive mapping technique that measures and records cardiac electric activity. It has been suggested that the MCG provides independent information for the detection of myocardial ischemia. We evaluated the utility of MCG for the diagnosis of coronary artery disease (CAD) in patients with chronic ischemic heart disease.
Methods: We studied 76 patients (55 male, 21 female,mean age 58 ±9.4 years old) with CAD confirmed by coronary angiography (≥70% stenosis in ≥ one branch of main coronary arteries). 34 case with 3 branch, 20 case with 2 branch, 22 with one branch(19 LAD, 1 LCX, 2 RCA). Patients with concomitant hypertension, left ventricular hypertrophy, bundle branch block, complex rhythm disturbances and NYHA functional class III and IV were excluded.
Methods: The control group consisted of 36 healthy subjects (12 male, 24 female mean age 31 ± 10 years) who all underwent 12-lead ECG, stress testing, transthoracic echocardiography, and Electron Beam-CT.
Methods All MCG images were acquired with a 9-channel MCG system (CardioMag Imaging, Schenectady, New York), in an unshielded location. The scans were performed at rest with an acquisition time of 6 minutes. Ventricular repolarization was analyzed using 7 parameters set by an automated software program, and scores for normal and abnormal were obtained.
Results table 1. Comparison of magnetocardiographic paramemters between CAD group and normal group(X±S) parameter normal(n=36) CAD(n=76) t p DML 5.58±1.68 60.76±34.24 9.412 〈0.001 PDML * 5.72±11.89 64.48±32.67 10.637 〈0.001 Ad * 7.55±12.31 37.14±65.37 3.268 〈0.002 Dd 6.75±4.21 17.77±114.37 5.453 〈0.001 Rd 0.144±0.103 0.369±0.316 5.007 〈0.001 DML:Dipole machine learning score,DQIS: Dipole quantitative integral score,PDML:Plain data machine learning score,Ad:Angle dynamics,Dd:Distance dynamic Rd:Ratio dynamics.
table 2. Sensitivity,specificity and accuracy of magnetocardiographic paramemters on diagnosis of coronary heart disease(%) parameter sensitivity specificity accuracy likelihood DML 71.7 91.6 77.6 8.5 DQIS 71.4 86.1 76.1 5.2 PDML 71.1 97.2 79.6 26.4 Ae 56.0 100 66.4 ≥20.7 Ad 20.7 97.2 45.1 7.7 Dd 29.9 97.2 51.3 11.1 Rd 46.7 94.4 61.9 8.5 The sensitivity of each of the parameters for the diagnosis of CAD was 68.0%, 84.0%, 76.0%, 36.0%, 40.0%, 56.0% and 56.0%, respectively.The corresponding specificities were 91.6%, 86.1%, 97.2%, 97.2%, 97.2%,94.4% and 100%, respectively. The accuracy of the scan was 72% to 89% depending on the chosen parameter.
Table 3.Comparison between CAD and subjects groups in positive rate of Dipole quantitative integral score X2=29.665, P<0.001
Table 4.Comparison between CAD and subjects groups in positive rate of angle extrema X2=26.165, P<0.001
table 5. Sensitivity, specificity and accuracy of numbers of positive MCG parameters for diagnosing CAD(%) positive sensitivity specificity accuracy likelihood parameter 1 90.9 75.0 85.8 3.6 2 75.3 91.6 80.5 9.1 3 70.1 97.2 78.7 25.9 4 58.4 100 71.6 21.6 5 38.1 100 57.5 14.1 6 23.3 100 47.7 8.6 7 9.1 100 38.0 3.4 With ≥ 3 parameters positive, the specificity of the test was ≥ 97% and the accuracy was 85%-88%. A positive MCG scan increased the likelihood of CAD up to 27 times.
Table6. Comparison between MCG and ECG for diagnosing CAD X2=11.711, P<0.005
Conclusion Resting MCG imaging is an accurate and rapid test for the detection of obstructive coronary artery disease in patients with chronic ischemic heart disease.MCG is more sensitive than ECG in diagnosis of CAD.