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Image Computing and Computational Modelling (pre-2019)

Imaging and computational tools for catheter ablation treatment of atrial fibrillation

Project ID: 2015_304

Student: Aditi Roy

1st supervisor: Oleg Aslanidi, King’s College London
2nd supervisor: Tobias Schaeffter, King’s College London

Disease: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. The disease is associated with high morbidity rates and increased risks of heart failure, stroke and sudden death. AF is often chronic and progressive, exhibiting a self-sustained and treatment-resistant nature. Hence, success rates of AF treatments are suboptimal, with 30-50% long-term recurrence rates. Poor clinical outcomes suggest a pressing need to develop novel tools and improve treatments for this costly healthcare problem.

Challenges: The genesis of AF is strongly linked with self-sustained sources of abnormal excitations in the atria – electrical rotors. Catheter ablation treatment is based on the elimination of such sources in AF patients, by destroying the underlying atrial tissue substrate using a localised radiofrequency (RF) energy delivery. Suboptimal long-term success rates of ablation can be due to several reasons: 1) insufficient RF energy delivery to a thick atrial wall can result in quick tissue reconnection and AF recurrence, 2) delivery of excessive RF energy to a thin wall can cause serious complications such as atrio-esophageal fistulae, 3) empirical ablation of “usual suspect” rotor locations is performed without a knowledge of the actual rotor locations in a given patient.

Imaging: Knowledge of atrial wall thickness can help select an adequate amount of RF energy, but clinical imaging does not currently provide adequate wall thickness data for AF patients. Therefore, this project will develop and apply novel MR imaging protocols to reconstruct the whole-atria geometry from AF patients. Such a protocol (black-blood PSIR with a T2-preparation) is currently being developed to produce good contrast between the atrial wall and surrounding lung and blood, as well as suitable image resolution (1.4 mm isotropic voxels) and acquisition time (10-20 minutes). The protocol has already been successfully applied to reconstruct the whole atria from 10 healthy volunteers. The data is currently being used to generate subject-specific atrial wall thickness maps.
The protocol will be translated to allow data acquisition from AF patients undergoing pre-ablation MRI scans. The MRI protocol for patients will be adapted to take advantage of the improved contrast between the wall and blood due to injection of gadolinium. This will enable reducing the acquisition time from the patient. Gadolinium-enhanced MRI will also provide information on atrial fibrosis.

Modelling: Reconstructed 3D atrial geometries will be linked with the electrical function using biophysically detailed models of the human atria, which are being developed in our group. Integration of the MR imaging data into the models with produce patient-specific atrial models. Animal experiments suggest that electrical rotors can reside in regions of the atria with the largest gradient of the atrial wall thickness. The project will test this hypothesis using the 3D atria models. The 3D atrial geometries will also be coupled with the Pennes bioheat equation to investigate the effects of atrial wall thickness on the amount of RF energy required for ablation. The electrical and thermal models will then be combined to simulate efficient patient-specific ablation of the rotors.

[1] Camm AJ, et al. Eur Heart J. 2010; 31: 2369-29.
[2] Kolbitsch C, et al. Magn Reson Med. 2012 ; 68: 205-13.
[3] Aslanidi OV, et al. Prog Biophys Mol Biol 2011; 107: 156-68.
[4] Colman MA, et al. J Physiol. 2013; 591: 4249-72.
[5] Yamazaki M, et al. Cardiovasc Res. 2012; 94: 48-57.
[6] Berjano E, et al. IEEE Trans Biomed Eng. 2004; 51: 1348-57.

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