Review of Processing Pathological Vectorcardiographic Records for the Detection of Heart Disease

Abstract

Vectorcardiography (VCG) is another useful method that provides us with useful spatial information about the electrical activity of the heart. The use of vectorcardiography in clinical practice is not common nowadays, mainly due to the well-established 12-lead ECG system. However, VCG leads can be derived from standard 12-lead ECG systems using mathematical transformations. These derived or directly measured VCG records have proven to be a useful tool for diagnosing various heart diseases such as myocardial infarction, ventricular hypertrophy, myocardial scars, long QT syndrome, etc., where standard ECG does not achieve reliable accuracy within automated detection. With the development of computer technology in recent years, vectorcardiography is beginning to come to the forefront again. In this review we highlight the analysis of VCG records within the extraction of functional parameters for the detection of heart disease. We focus on methods of processing VCG functionalities and their use in given pathologies. Improving or combining current or developing new advanced signal processing methods can contribute to better and earlier detection of heart disease. We also focus on the most commonly used methods to derive a VCG from 12-lead ECG.

Limits of the spatial ventricular gradient and QRST angles in patients with normal electrocardiograms and no known cardiovascular disease stratified by age, sex, and race

“…Our results differ from prior studies in that they account for a physiologically selected baseline using the TP segment as the true isolelectric/zero voltage and used the Kors transformation matrix to convert 12-lead ECGs into VCGs. The method of VCG construction can have a significant impact on subsequent measurements, 19,20 and data have demonstrated that the Kors transformation matrix, which is based on minimizing error between the 12-lead ECG and VCG rather than anatomic torso modeling, is superior to other transformations. 19,20 Compared to our results, Sur et al reported similar sex differences and similar mean SVG azimuth and elevation in a cohort of healthy patients with mean age ~40 ± 15 years, but the normal limits of SVG magnitude were significantly larger than our observed limits in this age range.…”

“…The method of VCG construction can have a significant impact on subsequent measurements, 19,20 and data have demonstrated that the Kors transformation matrix, which is based on minimizing error between the 12-lead ECG and VCG rather than anatomic torso modeling, is superior to other transformations. 19,20 Compared to our results, Sur et al reported similar sex differences and similar mean SVG azimuth and elevation in a cohort of healthy patients with mean age ~40 ± 15 years, but the normal limits of SVG magnitude were significantly larger than our observed limits in this age range. 18 This may be due to differences in study population and/or signal processing, as the ECGs used for that study were also recorded in the pseudo-orthogonal lead configuration (X, Y, and Z) rather than by transformation from 12-lead ECG and did not appear to undergo physiological baseline correction.…”

“…Our results differ from prior studies in that they account for a physiologically selected baseline using the TP segment as the true isolelectric/zero voltage and used the Kors transformation matrix to convert 12‐lead ECGs into VCGs. The method of VCG construction can have a significant impact on subsequent measurements, 19,20 and data have demonstrated that the Kors transformation matrix, which is based on minimizing error between the 12‐lead ECG and VCG rather than anatomic torso modeling, is superior to other transformations 19,20 …”

“…The influence of age and race on SVG and QRST angle normal limits, however, is unclear. Additionally, there are technical aspects of VCG measurements, primarily related to the manner in which orthogonal X, Y, and Z lead VCGs are created 19,20 and the definition of baseline zero voltage, 21 that can affect these measurements and which complicate direct comparison between studies or previously published normal values. We developed opensource software for automated electrocardiogram (ECG) processing and ECG and VCG measurements, 22 and this study was designed to provide age, sex, and race-specific ranges of SVG components and QRST angles observed in patients with normal ECGs and no evidence of cardiovascular disease as an approximation for "normal values" for reference and use in future studies.…”

Forward problem of electrocardiography based on cardiac source vector orientations

“…VCG is a diagnostic method that provides information about the electrical activity of the heart, representing the vector's spatial orientation and magnitude at every moment [21]. The VCG can be extracted from the standard 12-lead ECG system in clinical applications, employing the VCG transformation matrices [22][23][24]. Kors regression transformation method (KRT), Inverse Dower transformation (IDT), Q Least Square Value Transformation (QLSV), P Least Square Value Transformation (PLSV), and Kors quasi-orthogonal transformation are some of the methods used to extract VCG from the measured ECG signals based on transformation matrices [22,23,25,26].…”