Comparison of Different Electrocardiography with Vectorcardiography Transformations.

Area of Science:

• Cardiology
• Biomedical Engineering
• Signal Processing

Background:

• Vectorcardiography (VCG) offers enhanced sensitivity for diagnosing cardiac conditions like myocardial infarction, ischemia, and hypertrophy compared to standard electrocardiography (ECG).
• Clinical adoption of VCG is limited due to the need for additional electrodes; mathematical transformations from 12-lead ECG are commonly used.
• Several transformation methods exist, but a comprehensive comparison of their accuracy against the gold standard (Frank's leads) has been lacking.

Purpose of the Study:

• To implement and compare the accuracy of various mathematical transformations for deriving VCG leads from 12-lead ECG data.
• To evaluate the performance of Kors quasi-orthogonal transformation, inverse Dower transformation, Kors regression transformation, and linear regression-based P wave (PLSV) and QRS complex (QLSV) transformations.
• To assess these methods against the directly measured Frank's leads using metrics like mean squared error (MSE) and correlation coefficient (R).

Main Methods:

• Implementation of four distinct transformation algorithms: Kors quasi-orthogonal, inverse Dower, Kors regression, and linear regression-based (PLSV, QLSV).
• Utilized data from the Physikalisch-Technische Bundesanstalt (PTB) database for comparative analysis.
• Evaluated accuracy using mean squared error (MSE) and correlation coefficient (R) by comparing derived VCG leads with directly measured Frank's leads.

Main Results:

• Kors regression transformation showed statistically significant higher accuracy for deriving the X and Y VCG leads compared to other tested methods.
• No significant differences in accuracy were observed for the Z lead between Kors regression transformation and the PLSV and QLSV methods.
• This study provides a detailed comparison of VCG transformation techniques against the clinical standard Frank's orthogonal lead system.

Conclusions:

• Kors regression transformation is a highly accurate method for deriving X and Y VCG leads from standard ECG.
• For the Z lead, Kors regression, PLSV, and QLSV transformations offer comparable accuracy.
• These findings support the potential of accurate ECG-to-VCG transformations to enhance clinical cardiac diagnostics without additional hardware.