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Autocorrelation maps for optimal setting in cardiac resynchronization therapy
Anna Přibilová1, Jana Švehlíková1, Michal Šašov2
1Institute of Measurement Science, Department of Biomeasurements, Slovak Academy of Sciences, Bratislava, Slovakia.
Background And Objective:
Patients with chronic heart failure are treated with implanted devices artificially stimulating the ventricular myocardium to support the ventricular activation propagation dynamics. The criterion for stimulation/pacing timing is a shortening of the QRS duration in the ECG signal. The study suggests additional ECG parameters that could be helpful in cardiac resynchronization therapy (CRT) device pacing settings.
Methods:
This issue was approached by computing and evaluating autocorrelation maps derived from body surface potential maps during the QRS complex. The autocorrelation maps were calculated from the body surface potential maps of seventeen patients, fourteen of whom were diagnosed with the left bundle branch block (LBBB) and three with the right bundle branch block (RBBB). Eleven of the LBBB patients were responders, and all three RBBB patients and three LBBB patient were non-responders. The body surface potential maps were measured during their spontaneous heart rhythm and optimal CRT setting. The patients' autocorrelation maps were compared with the autocorrelation maps of a control group of 33 healthy persons using two-sample Kolmogorov-Smirnov and Wilcoxon rank-sum statistical tests.
Results:
The autocorrelation maps from spontaneous rhythm were significantly different (p < 0.00008) in healthy and LBBB groups, which was shown on 19 parameters extracted from the autocorrelation maps by both the statistical tests of equality. In the optimal CRT setting in the LBBB responders, four of the studied parameters (Shannon entropy of the histogram of the autocorrelation map's values, and mean, standard deviation, and geometrical mean of the autocorrelation map's positive values) were not significantly different from the parameters of the healthy subjects (p > 0.19).
Conclusions:
Selected parameters of autocorrelation maps can be used as additional parameters for optimal CRT pacing settings, leading to patients' positive responses to the treatment.
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