title: The derivation of the spatial QRS-T angle and the spatial ventricular gradient using the Mason-Likar 12-lead electrocardiogram.
abstract: Research has shown that the 'spatial QRS-T angle' (SA) and the 'spatial ventricular gradient' (SVG) have clinical value in a number of different applications. The determination of the SA and the SVG requires vectorcardiographic data. Such data is seldom recorded in clinical practice. The SA and the SVG are therefore frequently derived from 12-lead electrocardiogram (ECG) data using linear lead transformation matrices. This research compares the performance of two previously published linear lead transformation matrices (Kors and ML2VCG) in deriving the SA and the SVG from Mason-Likar (ML) 12-lead ECG data. This comparison was performed through an analysis of the estimation errors that are made when deriving the SA and the SVG for all 181 subjects in the study population. The estimation errors were quantified as the systematic error (mean difference) and the random error (span of the Bland-Altman 95% limits of agreement). The random error was found to be the dominating error component for both the Kors and the ML2VCG matrix. The random error [ML2VCG; Kors; result of the paired, two-sided Pitman-Morgan test for statistical significance of differences in the error variance between ML2VCG and Kors] for the vectorcardiographic parameters SA, magnitude of the SVG, elevation of the SVG and azimuth of the SVG were found to be [37.33°; 50.52°; p<0.001], [30.17mVms; 39.09mVms; p<0.001], [36.77°; 47.62°; p=0.001] and [63.45°; 80.32°; p<0.001] respectively. The findings of this research indicate that in comparison to the Kors matrix the ML2VCG provides greater precision for estimating the SA and SVG from ML 12-lead ECG data.
authors.affiliation: Ulster University, Belfast, United Kingdom. Electronic address: guldenring-d2@email.ulster.ac.uk.
authors.forename: Daniel
authors.initials: D
authors.lastname: Guldenring
authors.affiliation: Ulster University, Belfast, United Kingdom.
authors.forename: Dewar D
authors.initials: DD
authors.lastname: Finlay
authors.affiliation: Ulster University, Belfast, United Kingdom.
authors.forename: Raymond R
authors.initials: RR
authors.lastname: Bond
authors.affiliation: Ulster University, Belfast, United Kingdom.
authors.forename: Alan
authors.initials: A
authors.lastname: Kennedy
authors.affiliation: Ulster University, Belfast, United Kingdom.
authors.forename: James
authors.initials: J
authors.lastname: McLaughlin
authors.affiliation: Office of Science and Engineering Laboratories, CDRH, US FDA, Silver Spring, MD, USA.
authors.forename: Loriano
authors.initials: L
authors.lastname: Galeotti
authors.affiliation: Office of Science and Engineering Laboratories, CDRH, US FDA, Silver Spring, MD, USA.
authors.forename: David G
authors.initials: DG
authors.lastname: Strauss
mesh_terms: D001145:Arrhythmias, Cardiac / Q000175:diagnosis* / Q000503:physiopathology*; D018780:Body Surface Potential Mapping / Q000379:methods*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006329:Heart Conduction System / Q000503:physiopathology*; D006352:Heart Ventricles / Q000503:physiopathology*; D006801:Humans; D008955:Models, Cardiovascular; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D062211:Spatio-Temporal Analysis
keywords: Derivation of the Frank VCG; Estimation of the Frank VCG; Linear lead transformations; Mason–Likar 12-lead ECG; Spatial QRS-T angle; Spatial ventricular gradient