Non-invasive estimation of QLV from the standard 12-lead ECG in patients with left bundle branch block

Jacob Melgaard1, Peter M van Dam2,3, Anders Sommer4

  • 1CardioTech Research Group, Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg, Denmark.

Frontiers in Physiology
|October 10, 2022
PubMed

Insights

A new non-invasive method estimates left ventricular lead (LV) timing (QLV) using standard ECGs, improving cardiac resynchronization therapy (CRT) planning. This technique helps optimize LV lead placement for better heart failure treatment outcomes.

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Medical Imaging

Background:

  • Cardiac resynchronization therapy (CRT) treats heart failure with electrical dyssynchrony, often indicated by a left bundle branch block (LBBB) pattern on ECG.
  • Optimal CRT outcomes depend on precise left ventricular (LV) lead placement in the latest activated region, measured by QLV.
  • Current limitations include unpredictable coronary venous anatomy and inability to non-invasively measure QLV pre-implantation.

Purpose of the Study:

  • To develop and validate a novel non-invasive method for estimating QLV from standard 12-lead ECGs in sinus rhythm.
  • To assess the accuracy of this method in predicting optimal LV lead positioning for CRT.

Main Methods:

  • A cohort of 135 CRT recipients provided 12-lead ECGs, LV electrograms, and LV lead positions.
  • A computational heart model was used to iteratively fit the electrical activation pattern to match measured ECGs.
  • QLV was non-invasively estimated by calculating the time difference between ECG Q-wave onset and calculated LV activation time.

Main Results:

  • The non-invasive QLV estimation showed no significant difference compared to measured QLV.
  • The median distance between the actual and estimated LV pacing sites was 18.6 mm, indicating good spatial accuracy.

Conclusions:

  • Standard 12-lead ECGs and a generic heart model can accurately estimate QLV.
  • This non-invasive method holds potential for improving patient selection, optimizing CRT implant procedures, and simulating stimulation parameters.

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