Simultaneous display of multiple three-dimensional electrophysiological datasets (dot mapping)
Abstract
Aims
Complex ablation procedures are supported by accurate representation of an increasing variety of electrophysiological and imaging data within electroanatomic mapping systems (EMS). This study aims to develop a novel method for representing multiple complementary datasets on a single cardiac chamber model. Validation of the system and its application to both atrial and ventricular arrhythmias is examined.
Methods and results
Dot mapping was conceived to display multiple datasets by utilizing quantitative surface shading to represent one dataset and finely spaced dots to represent others. Dot positions are randomized within triangular (surface meshes) or tetrahedral (volumetric meshes) simplices making the approach directly transferrable to contemporary EMS. Test data representing uniform electrical activation (n = 10) and focal scarring (n = 10) were used to test dot mapping data perception accuracy. User experience of dot mapping with atrial and ventricular clinical data is evaluated. Dot mapping ensured constant screen dot density for regions of uniform dataset values, regardless of user manipulation of the cardiac chamber. Perception accuracy of dot mapping was equivalent to colour mapping for both propagation direction (1.5 ± 1.8 vs. 4.8 ± 5.3°, P = 0.24) and focal source localization (1.1 ± 0.7 vs. 1.4 ± 0.5 mm, P = 0.88). User acceptance testing revealed equivalent diagnostic accuracy and display fidelity when compared with colour mapping.
Conclusion
Dot mapping provides the unique ability to display multiple datasets from multiple sources on a single cardiac chamber model. The visual combination of multiple datasets may facilitate interpretation of complex electrophysiological and imaging data.
Electroanatomic mapping, Atrial fibrillation, Ventricular tachycardia, Substrate mapping, Data representation
What's new?
This study develops a novel technology capable of displaying multiple parameters simultaneously on a single cardiac chamber model.
A combination of colour and monochrome dots allows multiple datasets to be overlaid.
Examples of both atrial and ventricular datasets are presented for surface and volumetric cardiac chamber models.
Introduction
Substrate-based ablation strategies underpin the treatment of multiple atrial and ventricular arrhythmias. In identifying arrhythmia substrates, a variety of physiological parameters are proposed, for example late or decrement evoked potentials in ventricular tachycardia (VT)1,2 and complex fractionated electrograms (CFE) or low-voltage areas (LVAs) in atrial fibrillation (AF).3,4 In certain situations, combinations of datasets become especially valuable, for example bipolar voltage combined with local activation time in macro-re-entrant atrial tachycardia and VT mapping. Furthermore, emerging technologies such as non-invasive body surface mapping5 and contact rotor mapping6 may provide new physiological information describing the arrhythmia substrate. In addition to these electrical parameters, pre-procedural assessment with atrial and ventricular imaging aims to identify areas of scar,7 fibrosis,8 or adiposity,9 which may be crucial to arrhythmogenesis. Despite this array of complimentary clinical datasets, no contemporary electroanatomic mapping technology is widely available to statically display more than one dataset on a single cardiac chamber model. We therefore aimed to devise a method to represent multiple scalar datasets within a single spatial domain whilst minimizing (1) loss of fidelity in the original datasets and (2) operator-dependent manual segmentation or threshold selection of either dataset. This study demonstrates the application of this system to data representation for both atrial and ventricular arrhythmias.
Methods Dot mapping
Dot mapping displays multiple datasets on a single cardiac chamber model by representing one dataset with chamber surface shading (colour map), and further datasets by closely spaced dots (dot map) drawn within the same spatial domain. For surface models, dots are drawn over the underlying coloured surface (Figure 1A), and for volumetric models, dots are distributed throughout the volume being represented (Figure 1B). Dots are related to the dataset in two ways: (i) the location of the dots represents the location of the dataset being represented, and (ii) the density of the dots is proportional to the underlying dataset values. Examples of datasets that might be represented with dot mapping include late gadolinium signal intensity from cardiac magnetic resonance (CMR) imaging or bipolar voltage from electroanatomic mapping. Importantly, since only a fraction of available screen space is used to represent the dataset with dots, it remains possible to ‘see through’ the dots in order to continue to perceive the dataset represented by surface colour shading.
Figure 1
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Dot mapping algorithm. (A) The dot mapping algorithm as applied to 3D (...truncated)