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Body surface maps in left bundle branch block uncomplicated or complicated by myocardial infarction, left ventricular
Insights
Body surface maps (BSM) can help identify left bundle branch block (LBBB) with or without complications like myocardial infarction (MI) or left ventricular hypertrophy (LVH). This study shows BSM analysis accurately differentiates these conditions.
Area of Science:
- Cardiology
- Medical Imaging
- Electrophysiology
Background:
- Left bundle branch block (LBBB) presents unique challenges in electrocardiographic diagnosis.
- Body surface mapping (BSM) offers a detailed view of cardiac electrical activity.
- Complicating conditions like myocardial infarction (MI) and left ventricular hypertrophy (LVH) can alter LBBB presentation.
Purpose of the Study:
- To characterize body surface maps (BSM) during the QRST interval in patients with LBBB.
- To evaluate the impact of complicating conditions (MI, LVH, IS) on BSM patterns.
- To develop and validate BSM-based models for discriminating LBBB with and without MI and classifying different LBBB subtypes.
Main Methods:
- Topographic and quantitative analysis of BSM during the QRST interval.
- Inclusion of 7 uncomplicated LBBB and 31 complicated LBBB patients (MI, LVH, IS, MI+LVH, LVH+IS).
- Application of stepwise discriminant analysis to 77 voltage-related BSM variables for classification.
Main Results:
- Abnormal BSM configurations were consistently observed in all LBBB patients.
- Surface voltages were decreased by MI and IS, and increased by LVH.
- A discriminant model correctly classified >90% of LBBB patients with/without MI.
- A four-group classification model achieved ~80% accuracy for pure LBBB, LBBB+MI, LBBB+LVH, and LBBB+IS.
Conclusions:
- BSM provides valuable topographic and quantitative data in LBBB.
- BSM analysis shows potential for differentiating LBBB with and without MI.
- BSM can aid in classifying LBBB patients with co-existing cardiac conditions.
Abstract:
We provided a topographic and quantitative description of body surface maps (BSM) during the entire QRST interval in seven uncomplicated LBBBs and 31 LBBBs complicated by: myocardial infarction (MI, seven cases), left ventricular hypertrophy (LVH, eight cases), myocardial ischemia (IS, seven cases), MI + LVH (six cases) and LVH + IS (three cases). In all patients we observed abnormal map configurations attributable to the LBBB. We were unable to identify consistent effects of the complicating heart condition(s) on the general pattern of chest potentials. Conversely, the surface voltages were generally decreased by MI and IS and increased by LVH. By considering the 38 patients as a preliminary learning set we applied a stepwise discriminant analysis to 77 voltage-related variables derived from BSM to produce a model for discriminating between LBBBs with and without MI. We properly allocated more than 90% of the patients. We also attempted to classify the patients into four groups: pure LBBB, LBBB + MI, LBBB + LVH and LBBB + IS, with a percentage of correct classification of about 80%. The two classifying procedures were applied to ten new LBBB patients with results similar to those obtained in the 38 of the study group.