title: Map representation and diagnostic performance of the standard 12-lead ECG.
abstract: The diagnostic information contained in the standard 12-lead electrocardiogram was assessed by comparing the classification results produced by the standard leads for various clinical settings, such as normal versus myocardial infarction or versus left ventricular hypertrophy to those achieved by 120-lead data or body surface potential maps (BSPMs). Separately, optimal signal leads were extracted from the BSPM by ranking all leads in function of their capability of reconstructing the BSPM. Ranking was achieved by deriving eigenvalues from the covariance matrix calculated from all leads and corresponding measurements. Thus, while comparing the results from the standard leads (diagnostic leads) to those from the original raw map data, a comparison was also performed with respect to the best signal leads, namely the four best and the eight best. From the results observed for all bi- and multigroup classifications, it appeared that the diagnostic yield of the 12 standard leads matched those obtained with a number of signal leads lying between 4 and 8. This indicated that a large overlap still existed between the leads composing the 12-lead ECG (in fact, only 8 independent leads). Another interesting observation resulted from this investigation: although classifiers (discriminating variables) used for classification were identical, whether they originated from the raw standard leads (derived from the raw maps) or from standard leads reconstructed with four or eight signal leads, reconstructed measurements performed better than original measurements. This paradox can be explained by looking at the respective F values. Indeed, since increased F values result from higher ratios between the difference of group means and the composite variance from the pooled groups, higher differences and/or smaller variances produce larger ratios and hence, better group separations.
authors.affiliation: Free University of Brussels, Belgium.
authors.forename: F
authors.initials: F
authors.lastname: Kornreich
authors.forename: R L
authors.initials: RL
authors.lastname: Lux
authors.forename: R S
authors.initials: RS
authors.lastname: MacLeod
mesh_terms: D018780:Body Surface Potential Mapping / Q000145:classification; D016002:Discriminant Analysis; D004562:Electrocardiography / Q000145:classification / Q000295:instrumentation; D004566:Electrodes; D006321:Heart / Q000502:physiology; D006801:Humans; D017379:Hypertrophy, Left Ventricular / Q000175:diagnosis / Q000503:physiopathology; D007091:Image Processing, Computer-Assisted; D016014:Linear Models; D009203:Myocardial Infarction / Q000175:diagnosis / Q000503:physiopathology; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted