Effects of torso mesh density and electrode distribution on the accuracy of electrocardiographic imaging during atrial fibrillation

Figures

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  FIGURE 1. Example of torso models with different number of nodes and node distribution. The electrodes relocated appear in blue and the original locations in red. (A) illustrates torsos with irregular mesh distribution, (B) with homogeneous distribution and (C) torsos maintaining the electrodes in the original position.

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  FIGURE 2. Mean value and standard deviation of torso model properties of the geometries used in the simulation study represented. (A). Mean number of nodes depending on the model. (B). Mean area of the faces. (C). Variability of the area of the faces. (D). Mean distance between nodes of the same triangle.

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  FIGURE 3. Mean value and standard deviation of torso model properties of the geometries used in the real patient’s study. (A). Mean number of nodes depending on the model. (B). Mean area of the faces. (C). Variability of the area of the faces. (D). Mean distance between nodes of the same triangle.

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  FIGURE 4. (A). Example of 1 s of inverse computed electrograms obtained with different torso models and the same simulation signals for torsos without electrode relocation. Signal in black was obtained with the reference 4000-node torso, red and blue signals correspond to the ones obtained with torsos of 2000 and 100 nodes respectively. (B). Pearson’s correlation coefficient (CC), (C). relative measurement (RDM*) and (D). mean absolute difference between the reference dominant frequencies (DF) between torso models and from 100 to 2000 nodes. Points in black represent the mean value of the metrics torsos in which the distribution of the nodes is homogeneous and white points represent the torso with nodes heterogeneously placed. Whiskers represent the standard deviation.

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  FIGURE 5. Time metrics obtained comparing the inverse computed electrograms 25 atrial fibrillation patients of the reference and the signals obtained with different torso models without electrode relocation. Points in black represent the torsos in which the distribution of the nodes is homogeneous and white points represent the torso with nodes heterogeneously placed. (A). Pearson’s correlation coefficient (CC) and (B). Relative difference measurement (RDM*). (C). Mean absolute difference between the reference dominant frequencies (DF) between torso models and from 100 to 1,000 nodes.

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  FIGURE 6. (A). Example of 1 s of inverse computed electrograms obtained with different torso models and the same simulation signals for torsos with the node of the electrode displaced by the remeshing. Signal in black was obtained with the reference 4000-node torso, red and blue signals correspond to the ones obtained with torsos of 2000 and 100 nodes respectively. (B). Pearson’s correlation coefficient (CC), (C). relative measurement (RDM*) and (D). mean absolute difference between the reference DF between torso models and from 100 to 2000 nodes. Points in black represent the mean value of the metrics torsos in which the distribution of the nodes is homogeneous and white points represent the torso with nodes heterogeneously placed. Whiskers represent the standard deviation.

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  FIGURE 7. Time metrics obtained comparing the inverse computed electrograms 25 atrial fibrillation patients of the reference and the signals obtained with different torso models with the node of the electrode displaced by the remeshing. Points in black represent the torsos in which the distribution of the nodes is homogeneous and white points represent the torso with nodes heterogeneously placed. (A). Pearson’s correlation coefficient (CC) and (B). Relative difference measurement (RDM*). (C). Mean absolute difference between the reference DF between torso models and from 100 to 1,000 nodes.

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  FIGURE 8. Dominant frequency maps obtained with different torso models for one real patient case.