Quantitative evaluation of body surface potential mapping of heart electrical field in ischaemic heart disease.

New possibilities of quantitative evaluation of body surface potential mapping were studied in 78 patients with ischaemic heart disease. Integral maps of the Q wave, QRS and ST-T intervals were plotted and isochronous maps of ventricular activation time and maps of asynchronous potential minima of the Q wave were determined. Minimum and maximum potential values and their time relations were evaluated in the maps. Left ventricular contraction abnormality detected by left ventricular angiography was determined by a point score and expressed as an index of asynergy. The number of coronary artery branches with significant narrowing was assessed and the extent of coronary artery damage was evaluated by an arbitrary defined index. Using quantitative parameters from the maps, multiple stepwise linear regression was performed. The relationship between map parameters and index of asynergy corresponded to multiple correlation coefficient r = 0.69 (p = 0.01) in the whole group of patients. In the group of patients with left ventricular contraction abnormality the relationship between these parameters was found to be r = 0.87 (p = 0.01). The relationship between map parameters and the number of coronary artery branches with significant stenosis was r = 0.60 (p = 0.01) in the group of patients with positive coronary angiography. In the same group of patients the relationship between map parameters and the index evaluating coronary artery damage was equal to r = 0.63 (p = 0.01). The data obtained from body surface integral maps enable to quantify cardiac ischaemic damage.

Body surface potential mapping (BSPM) before and after percutaneous transluminal coronary angioplasty (PTCA).

The departure index area of departure maps before and after the PTCA procedure was evaluated in 10 randomly chosen patients with clinically significant ischaemic heart disease. The body surface mapping system CARDIAG 128.1, (ZPA Prague-Cakovice) was used. The departure index was calculated using Kubota's formula. The departure indexes of the ST-T interval and departure maps of 36 ms and 80 ms intervals from the J point were followed. A decrease of the departure index area was considered as a sign of successful PTCA. A correct classification was made in 6 patients out of 9 (66%) with successfully performed PTCA. The identification of one patient with unsuccessful PTCA procedure was also correctly determined. The overall correlation between the effect of PTCA and the departure index area change was 7 out of 10 (70%). The authors consider this method to be a useful non-invasive method for identifying of successful or unsuccessful PTCA in patients with coronary artery disease.

Cardiac micropotentials reached from one systole as non-dipolar residue by singular value decomposition.

Cardiac micropotentials are considered to have a predictive value in critical ventricular tachycardia or sudden death. These micropotentials are obtained by numeric filtration of the result of sequential averaging of about 200 systoles (i.e. of measurement at about 3 min interval) which is significantly influenced by known intraindividual ECG variability. It follows from our previous studies that the non-dipolar residue (i.e. the sum of all components of an equivalent source of the heart electrical field with the exception of the first three dominant dipolar components) corresponds by its nature to the cardiac micropotentials, i.e. to late potentials. Verification of this hypothesis utilizing singular value decomposition and replacing the sequential averaging by "surface" averaging of the matrix of synchronously measured ECGs is the aim of this project. The results of the present study can be considered as a confirmation of this hypothesis. These results provide a better understanding of the structure of the body surface potential distribution and for clinical purposes they make it possible to attain cardiac micropotentials (late potentials) from one systole.

Comparison of discriminant analysis and probabilistic expert system in VCG data classification.

Our previous studies (Valová et al. 1992) have dealt with the possibilities of expert system utilization for electrocardiologic data interpretation. The results obtained in these studies provided evidence that the selected probabilistic expert system is suitable for the solution of VCG data interpretation problems. The aim of this paper was to compare the results obtained by stepwise discriminant analysis with that obtained by a probabilistic expert system. These classification methods were applied to VCG data measured by Frank's lead system. Five groups of patients were investigated: 76 healthy subjects, 36 patients with angina pectoris, 112 patients with old posterior myocardial infarction, 107 patients with old anterior myocardial infarction and 35 patients with old anteroseptal myocardial infarction. The classification was carried out by the leaving-one-out technique. Results of the classification obtained in five groups by a probabilistic expert system are evidently better than those obtained by stepwise discriminant analysis.