Endocardial motion estimation from electro-anatomical data

Porras, Antonio R.; Piella, Gemma; Hoogendoorn, Corné; Andreu, David; Berruezo, Antonio; Frangi, Alejandro F.

doi:10.1109/isbi.2012.6235539

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…This method could be used intraoperatively together with an EAM system for guidance during the intervention. This is an extended version of [14], which was limited to qualitative results on four subjects. This study also provides quantification of the results, the validation of the proposed methodology and application to more clinical cases.…”

Section: A State Of the Artmentioning

confidence: 99%

Interventional Endocardial Motion Estimation from Electroanatomical Mapping Data: Application to Scar Characterization

Porras

Piella

Berruezo

et al. 2013

IEEE Trans. Biomed. Eng.

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Scar presence and its characteristics play a fundamental role in several cardiac pathologies. To accurately define the extent and location of the scar is essential for a successful ventricular tachycardia ablation procedure. Nowadays, a set of widely accepted electrical voltage thresholds applied to local electrograms recorded are used intraoperatively to locate the scar. Information about cardiac mechanics could be considered to characterize tissues with different viability properties. We propose a novel method to estimate endocardial motion from data obtained with an electroanatomical mapping system together with the endocardial geometry segmented from preoperative 3-D magnetic resonance images, using a statistical atlas constructed with bilinear models. The method was validated using synthetic data generated from ultrasound images of nine volunteers and was then applied to seven ventricular tachycardia patients. Maximum bipolar voltages, commonly used to intraoperatively locate scar tissue, were compared to endocardial wall displacement and strain for all the patients. The results show that the proposed method allows endocardial motion and strain estimation and that areas with low-voltage electrograms also present low strain values.

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Section: A State Of the Artmentioning

confidence: 99%

Interventional Endocardial Motion Estimation from Electroanatomical Mapping Data: Application to Scar Characterization

Porras

Piella

Berruezo

et al. 2013

IEEE Trans. Biomed. Eng.

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Characterization of Respiratory and Cardiac Motion from Electro-Anatomical Mapping Data for Improved Fusion of MRI to Left Ventricular Electrograms

et al. 2013

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Accurate fusion of late gadolinium enhancement magnetic resonance imaging (MRI) and electro-anatomical voltage mapping (EAM) is required to evaluate the potential of MRI to identify the substrate of ventricular tachycardia. However, both datasets are not acquired at the same cardiac phase and EAM data is corrupted with respiratory motion limiting the accuracy of current rigid fusion techniques. Knowledge of cardiac and respiratory motion during EAM is thus required to enhance the fusion process. In this study, we propose a novel approach to characterize both cardiac and respiratory motion from EAM data using the temporal evolution of the 3D catheter location recorded from clinical EAM systems. Cardiac and respiratory motion components are extracted from the recorded catheter location using multi-band filters. Filters are calibrated for each EAM point using estimates of heart rate and respiratory rate. The method was first evaluated in numerical simulations using 3D models of cardiac and respiratory motions of the heart generated from real time MRI data acquired in 5 healthy subjects. An accuracy of 0.6–0.7 mm was found for both cardiac and respiratory motion estimates in numerical simulations. Cardiac and respiratory motions were then characterized in 27 patients who underwent LV mapping for treatment of ventricular tachycardia. Mean maximum amplitude of cardiac and respiratory motion was 10.2±2.7 mm (min = 5.5, max = 16.9) and 8.8±2.3 mm (min = 4.3, max = 14.8), respectively. 3D Cardiac and respiratory motions could be estimated from the recorded catheter location and the method does not rely on additional imaging modality such as X-ray fluoroscopy and can be used in conventional electrophysiology laboratory setting.

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Endocardial motion estimation from electro-anatomical data

Cited by 2 publications

References 9 publications

Interventional Endocardial Motion Estimation from Electroanatomical Mapping Data: Application to Scar Characterization

Interventional Endocardial Motion Estimation from Electroanatomical Mapping Data: Application to Scar Characterization

Characterization of Respiratory and Cardiac Motion from Electro-Anatomical Mapping Data for Improved Fusion of MRI to Left Ventricular Electrograms

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