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. 2014 Jul;25(7):774-80.
doi: 10.1111/jce.12444. Epub 2014 May 30.

Sensitivity and specificity of substrate mapping: an in silico framework for the evaluation of electroanatomical substrate mapping strategies

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Sensitivity and specificity of substrate mapping: an in silico framework for the evaluation of electroanatomical substrate mapping strategies

Joshua J E Blauer et al. J Cardiovasc Electrophysiol. 2014 Jul.

Abstract

Background: Voltage mapping is an important tool for characterizing proarrhythmic electrophysiological substrate, yet it is subject to geometric factors that influence bipolar amplitudes and thus compromise performance. The aim of this study was to characterize the impact of catheter orientation on the ability of bipolar amplitudes to accurately discriminate between healthy and diseased tissues.

Methods and results: We constructed a 3-dimensional, in silico, bidomain model of cardiac tissue containing transmural lesions of varying diameter. A planar excitation wave was stimulated and electrograms were sampled with a realistic catheter model at multiple positions and orientations. We carried out validation studies in animal experiments of acute ablation lesions mapped with a clinical mapping system. Bipolar electrograms sampled at higher inclination angles of the catheter with respect to the tissue demonstrated improvements in both sensitivity and specificity of lesion detection. Removing low-voltage electrograms with concurrent activation of both electrodes, suggesting false attenuation of the bipolar electrogram due to alignment with the excitation wavefront, had little effect on the accuracy of voltage mapping.

Conclusions: Our results demonstrate possible mechanisms for the impact of catheter orientation on voltage mapping accuracy. Moreover, results from our simulations suggest that mapping accuracy may be improved by selectively controlling the inclination of the catheter to record at higher angles with respect to the tissue.

Keywords: bipolar electrogram; computer-based model; electroanatomical mapping; voltage mapping.

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Figures

Figure 1
Figure 1
In silico model of electroanatomical substrate mapping. A. 3-dimensional slab model with activation wave propagating from right to left and extracellular potentials displayed with color on the mesh. The white spheres show randomly selected points on the surface where the catheter tip was positioned for the recording of EGMs. The catheter, displayed at an inclination of ≈ 30 degrees, is representative of devices used clinically(8 F, 4 mm tip, 2 mm spacing). B. Illustration of the catheter positions used to sample electrograms. White spheres represent 116 transformations of the proximal electrode around the surface point. C. Representative electrograms acquired from same location in model before (L), and after simulated lesions were included in the model (R). EAM - electroanatomical map, EGMs - electrograms, PhiE - extracellular potential, M1 and M2 - unipolar signals from distal and proximal electrodes, respectively.
Figure 2
Figure 2
Mean of 116 BPAs recorded at each mapping site. Bipolar amplitudes were recorded at 928 locations (colored spheres) on the lesion model (normal tissue is colored light gray and lesions are black). The mean of all bipolar amplitudes recorded at each of 928 sites (n = 116) determines sphere color.
Figure 3
Figure 3
Baseline evaluation of lesion detection accuracy. Top: Baseline TPR and FPR of lesion detection for the in vivo and in silico models were calculated at voltage cutoffs ranging from 0.25 to 3.0 mV. Bottom: MCC plotted as a function of the low voltage cutoff illustrates the performance of substrate mapping in each model at a given voltage. TPR = True Positive Ratio, FPR = False Positive Ratio, MCC = Matthews Correlation Coefficient.
Figure 4
Figure 4
Effect of inclination angle on in silico voltage mapping accuracy. The upper panel contains ROC curves that demonstrate the sensitivity and specificity of voltage mapping as BPAs recorded at low inclination angles are removed by increments of 15 degrees. The lower panel contains plots of Matthews correlation coefficient which show the effect of progressively removing low inclination recordings on the performance of voltage mapping as a function of the low voltage threshold. The blue curves, marked with circles, indicate the baseline conditions shown in the previous figure.
Figure 5
Figure 5
Effect of simultaneous electrode activation on the accuracy of voltage mapping in silico (left column) and in vivo (right column). The top panels in both columns contain ROC curves from which EGMs with low ΔLAT values, indicating perpendicular alignment of the wavefront direction and the bipolar axis, were removed. The lower panels contain Matthews correlation coefficient as a function of low voltage threshold for the same EGMs

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