Visual 3Dx: Algorithms for quantitative 3-dimensional analysis of ECG signals

Introduction: The 12-lead ECG is useful for cardiac diagnosis but has limited sensitivity and specificity. To address this, we developed the Visual3Dx, a comprehensive method for describing cardiac electrical activity in time and space. The Visual3Dx transforms the ECG input into a time-variable heart vector, and normalizes each lead input to assure equal representation from all cardiac regions. Methods: We compared the Visual3Dx to the standard 12-lead ECG for detection of acute myocardial ischemia (AMI) in 2 clinical models. Model 1 was AMI after 90 s of balloon coronary occlusion in 117 cases. Model 2 was 122 consecutive patients who: (1) presented to an urban emergency department with chest pain; (2) were admitted to coronary care and developed elevated cardiac troponin levels; and (3) had coronary arteriography within 6 hrs. Results: In Model 1, the 12 lead ECG developed ST segment deviation diagnostic of AMI in 78/117 occlusions (67%), whereas using the same input ECG data, the Visual3Dx was diagnostic of AMI in 105/117 occlusions (90%; p<0.001). In Model 2, the first 12 lead ECG was diagnostic of AMI in 80/122 (66%), whereas the Visual3Dx was diagnostic in 103/122 (84%). In both Models, the largest sensitivity gains were seen in left circumflex and right coronary artery occlusions. Conclusions: The Visual3Dx is a promising tool for 3D quantitative analysis of cardiac electrical activity that may improve diagnosis of AMI, especially in electrically remote regions of the heart. Additional studies will define diagnostic specificity and further improve 3D biomarkers of AMI.