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Detection of arrhythmogenic substrates in prior myocardial infarction patients with complete right bundle branch
Hiroshige Murata1, Toshihiko Ohara, Yoshinori Kobayashi
1Division of Cardiology, Hepatology, Geriatrics, and Integrated Medicine, Department of Internal Medicine, Graduate School of Medicine, Nippon Medical School. s7086@nms.ac.jp
Insights
Wavelet-transformed ECG (WTECG) effectively identifies dangerous heart rhythms in myocardial infarction (MI) survivors with complete right bundle branch block (CRBBB). This novel method shows high accuracy in detecting arrhythmogenic substrates, improving patient follow-up.
Area of Science:
- Cardiology
- Biomedical Engineering
- Signal Processing
Background:
- Post-myocardial infarction (MI) patients require follow-up for life-threatening arrhythmias.
- Conventional methods like signal-averaged ECG (SAECG) have limitations in detecting ventricular tachycardia (VT) in patients with complete right bundle branch block (CRBBB).
- Wavelet transform offers superior time-frequency analysis for detecting abnormal high-frequency components (HFCs) indicative of myocardial conduction abnormalities.
Purpose of the Study:
- To evaluate the predictive value of wavelet-transformed ECG (WTECG) for identifying arrhythmogenic substrates in MI patients with CRBBB.
- To compare the efficacy of WTECG against SAECG in this specific patient population.
Main Methods:
- WTECG and SAECG were assessed in 22 subjects with CRBBB (10 controls, 7 non-VT MI, 5 VT MI).
- A 12-lead ECG was recorded, and QRS complexes were analyzed using Gabor wavelet transform (40-280 Hz).
- Abnormal high-frequency components (AHFC) were defined by specific power percentages (e.g., P150/40 ≥ 50%), and the number of leads with AHFC (NL-AHFC) was counted.
Main Results:
- SAECG showed no significant differences among groups.
- WTECG revealed significantly higher HFCs in Non-VT MI patients compared to controls.
- NL-AHFC (P150/40) was significantly higher in the VT group than the Non-VT group (3.2 vs. 1.4, P=0.001).
- Defining abnormal as NL-AHFC (P150/40) ≥ 3 yielded 100% sensitivity and 85.7% specificity for VT detection in MI patients with CRBBB.
Conclusions:
- WTECG demonstrates significant potential as a novel non-invasive method for detecting arrhythmogenic substrates.
- This technique is particularly promising for risk stratification in MI patients with CRBBB.
- WTECG may offer improved diagnostic capabilities compared to conventional methods like SAECG in this challenging patient group.
Background:
It is important to follow up patients surviving acute myocardial infarction (MI), to detect the presence of any life-threatening arrhythmias. Various non-invasive examinations, such as signal-averaged ECG (SAECG), have been reported to predict the fatal ventricular tachycardia (VT); however, these conventional methods have limitations in detecting VT occurring in patients with complete right bundle branch block (CRBBB) QRS. Wavelet transform has been increasingly reported as a superior time-frequency analysis on the surface ECG in detecting abnormal high-frequency components (HFCs), thus suggesting abnormal myocardial conductions; however, it remains unclear whether wavelet-transformed ECG (WTECG) is useful in patients with CRBBB.
Objective:
The purpose of this study is to assess the predictive value of WTECG for detecting arrhythmogenic substrates in MI patients with CRBBB.
Methods:
Both the WTECG and SAECG were evaluated in 22 subjects with CRBBB, including 10 subjects without cardiovascular diseases (control group), 7 prior MI patients without VT (Non-VT group), and 5 prior MI patients with sustained VT (VT group). A 12-lead ECG (10 kHz sampling) was recorded and the representative QRS complex (300 ms) was transformed at a frequency range of 40-280 Hz using the Gabor function as the analyzing wavelet. In the power curve along a time course, the percentages of the peak power values at each frequency (60, 80, 120, 150, and 200 Hz) in the corresponding power values at 40 Hz (P60/40, P80/40, P120/40, P150/40, and P200/40, respectively) were calculated. 'The power percentages (P120/40, P150/40, or P200/40) > or =50%' was defined as an abnormal HFC (AHFC), and the number of the leads in which an AHFC was detected (NL-AHFC) of 8 leads (I, aV(F), V1-V6) was counted for comparison of the two MI groups.
Results:
There was no significant difference among the three groups in the SAECG recording. The power percentages of HFCs (P120/40, P150/40, and P200/40) in Non-VT group were significantly higher than those in control group (48.2 +/- 36.5 vs. 30.6 +/- 7.7, P<0.001; 47.8 +/- 35.5 vs. 26.9 +/- 7.1, P<0.001; 47.3 +/- 39.4 vs. 24.9 +/- 7.6, P<0.001; respectively). NL-AHFC (P150/40) in VT group significantly increased more than in Non-VT group (3.2 +/- 0.4 vs. 1.4 +/- 0.8, P=0.001). When 'NL-AHFC (P150/40) > or =3' was defined as abnormal, the sensitivity, specificity, positive and negative predictive values for detection of VT in MI patients with CRBBB was 100, 85.7, 83.3, and 100%, respectively.
Conclusion:
WTECG might be a novel non-invasive method to detect arrhythmogenic substrates in MI patients with CRBBB.
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