Why the study?
Combining pre-procedural cardiac imaging and electro-anatomical mapping (EAM) can potentially help locate new ablation targets, prompting the development of a fully automated alignment technique.
Does an iterative closest plane-to-plane algorithm accurately align pre-procedural cardiac MRI/CT images with electro-anatomical mapping anatomies in patients undergoing pulmonary vein isolation?
Does an iterative closest plane-to-plane algorithm accurately align pre-procedural cardiac MRI/CT images with electro-anatomical mapping anatomies in patients undergoing pulmonary vein isolation?
An automated iterative closest plane-to-plane algorithm provides reliable alignment of pre-procedural CT/MRI images with intra-procedural electro-anatomical mapping, potentially aiding in identifying ablation targets.
Automated LA registration may aid ablation targeting; leaves open impact on procedural success or outcomes.
Background: The combination of information obtained from pre-procedural cardiac imaging and electro-anatomical mapping (EAM) can potentially help to locate new ablation targets. In this study we developed and evaluated a fully automated technique to align left atrial (LA) anatomies obtained from CT- and MRI-scans with LA anatomies obtained from EAM. Methods: Twenty-one patients scheduled for a pulmonary vein (PV) isolation with a pre-procedural MRI were enrolled. Additionally, a recent computed tomography (CT) scan was available in 12 patients. LA anatomies were segmented from MRI-scans using ADAS-AF (Galgo Medical, Barcelona) and from the CT-scans using Slicer3D. MRI and CT anatomies were aligned with the EAM anatomy using an iterative closest plane-to-plane algorithm. Initially, the algorithm included the PVs, LA appendage and mitral valve anulus as they are the most distinctive landmarks. Subsequently, the algorithm was applied again, excluding these structures, with only three iterative steps to refine the alignment of the true LA surface. The result of the alignments was quantified by the Euclidian distance between the aligned anatomies after excluding PVs, LA appendage and mitral anulus. Results: Our algorithm successfully aligned 20/21 MRI anatomies and 11/12 CT anatomies with the corresponding EAM anatomies. The average median residual distances were 1.9 ± 0.6 mm and 2.5 ± 0.8 mm for MRI and CT anatomies respectively. The average LA surface with a residual distance less than 5.00 mm was 89 ± 9% and 89 ± 10% for MRI and CT anatomies respectively. Conclusion: An iterative closest plane-to-plane algorithm is a reliable method to automatically align pre-procedural cardiac images with anatomies acquired during ablation procedures.
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Hermans et al. (2023) studied this question.
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