Transformations for estimating body surface potential maps from the standard 12-lead electrocardiogram

The aim of this study was to compare general and patient-specific transformations for estimating body surface potential maps (BSPMs) from the standard 12-lead electrocardiogram (ECG). The design set for deriving the general transformation consisted of 120-lead BSPMs of Dalhousie Superset (n = 892); as a test set for comparing patient-specific and general transformations we used 120-lead BSPMs from the Dalhousie database of patients (n = 88) who underwent elective percutaneous coronary intervention (PCI). From these two datasets we derived the desired transformations by regression analysis. The estimated BSPMs were assessed by 3 goodness-of-fit measures: similarity coefficient (SC), root-mean-square error, and relative error (RE). Results show that BSPMs can be estimated from the 12-lead ECG by using general transformation with (mean ± SD) SC (%) = 92.4 ± 3.5 and RE (%) = 42.2 ± 9.2; patient-specific transformations yielded significantly better (P < 0.0001) estimates, achieving SC (%) = 96.6 ± 4.3 and RE (%) = 22.4 ± 10.7. Thus, in conclusion, BSPMs of our particular test set could be estimated from the standard 12-lead ECG with a very good accuracy by means of general transformation. With patient-specific transformations, accuracy was further improved. In patient monitoring and some clinical interventional procedures (e.g., elective PCI, catheter ablation), a pre-procedure BSPM recording can be used to derive patient-specific lead transformation that can subsequently enhance utility of the 12-lead ECG during the procedure.