Key result
Spline, Laplacian, and Hardy interpolation methods performed better than the nearest-neighbor method for reconstructing activation-time values in simulated cardiac mapping.
Why the study?
Determining values at unmeasured sites in catheter-based cardiac mapping requires effective interpolation methods, and the use of spline interpolation had not been previously introduced or compared.
Spline interpolation is a viable and potentially superior method for estimating unmeasured activation times in catheter-based cardiac mapping compared to nearest-neighbor approaches.
Spline interpolation may refine simulated cardiac mapping; leaves open clinical translation pending in vivo validation.
Due to their minimal invasiveness catheters are highly preferred incardiacmapping techniques used in the source localization of rhythm disturbances in the heart. In cardiac mapping, standard steerable catheters and multielectrode basket catheters are the two alternatives for the characterization of the underlying tissue on the inner (endocardium) and outer (epicardium) surfaces of the heart. As with any discrete sampling technique, an important question for catheter-based cardiac mapping is how to determine values at locations from which direct measurements are not available. Interpolation is the most common approach for providing values at unmeasured sites using the available measurements. In this study, the usage of spline interpolation technique in catheter-based cardiac mapping was introduced for the first time in the literature and compared with the existing approaches such as the nearest-neighbor, Laplacian, and Hardy’s interpolation techniques.For different sampling resolutions on the endocardium and epicardium, we reconstructed the activation-time values on unmeasured sites using measured values. To provide quantitative validation, we have applied thesemethods to high resolution simulated activation-time values from a realistic heart model using Aliev-Panfilov mathematical modeling approach. The results show that spline, Laplacian, and Hardy interpolation methods performed successfully and also better than nearest-neighbor method. Among all interpolation schemes exceptfor the nearest-neighbor method the average correlation coefficient (CC) values were greater than
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Abdurasulova Dilnoza Botirali Qizi (2020) studied Cardiac rhythm disturbances. Spline interpolation technique vs. Nearest-neighbor, Laplacian, and Hardy's interpolation techniques was evaluated on Average correlation coefficient (CC) for reconstructed activation-time values. Spline, Laplacian, and Hardy interpolation methods performed better than the nearest-neighbor method for reconstructing activation-time values in simulated cardiac mapping.
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