Towards cardiac and respiratory motion characterization from electrophysiology data for improved real time MR-integration
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KeywordsVentricular Tachycardia Late Gadolinium Enhancement Respiratory Motion Cardiac Motion Inter Patient Variability
Electro-anatomical voltage mapping (EAM) is an invasive technique used for the identification of ventricular tachycardia (VT) substrate and subsequent guidance of VT ablation . The mapping of VT substrate is very time-consuming procedure, requires highly skilled electrophysiologist, is associated with patient risk and is an invasive procedure. Late gadolinium enhancement (LGE) MRI allows non-invasive evaluation of 3D structure of scar. Therefore, LGE has the potential to identify the VT substrate and can now be integrated in the current clinical platform for guidance of VT ablation as a roadmap. However, fusion of the two imaging modality is very challenging due to respiratory and cardiac motion during the mapping which results in large errors in data fusion. Our aim in this study is to develop a novel algorithm to detect the respiratory and cardiac-induced motion of the mapping catheter during the VT ablation to facilitate integration of LGE MRI to EAM data.
The cardiac and respiratory motion can be extracted from 3D catheter location through time. Further studies to integrate the calculated motion to correct for fusion of LGE and MRI are warranted to evaluate the improvement achieved for fusion of the two imaging modalities.
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