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Treatment Planning for Atrial Fibrillation Using Patient-Specific Models Showing the Importance of Fibrillatory-Areas

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Abstract

Computational models have made it possible to study the effect of fibrosis and scar on atrial fibrillation (AF) and plan future personalized treatments. Here, we study the effect of area available for fibrillatory waves to sustain AF. Then we use it to plan for AF ablation to improve procedural outcomes. CARPentry was used to create patient-specific models to determine the association between the size of residual contiguous areas available for AF wavefronts to propagate and sustain AF [fibrillatory area (FA)] after ablation with procedural outcomes. The FA was quantified in a novel manner accounting for gaps in ablation lines. We selected 30 persistent AF patients with known ablation outcomes. We divided the atrial surface into five areas based on ablation scar pattern and anatomical landmarks and calculated the FAs. We validated the models based on clinical outcomes and suggested future ablation lines that minimize the FAs and terminate rotor activities in simulations. We also simulated the effects of three common antiarrhythmic drugs. In the patient-specific models, the predicted arrhythmias matched the clinical outcomes in 25 of 30 patients (accuracy 83.33%). The average largest FA (FAmax) in the recurrence group was 8517 ± 1444 vs. 6772 ± 1531 mm2 in the no recurrence group (p < 0.004). The final FAs after adding the suggested ablation lines in the AF recurrence group reduced the average FAmax from 8517 ± 1444 to 6168 ± 1358 mm2 (p < 0.001) and stopped the sustained rotor activity. Simulations also correctly anticipated the effect of antiarrhythmic drugs in 5 out of 6 patients who used drug therapy post unsuccessful ablation (accuracy 83.33%). Sizes of FAs available for AF wavefronts to propagate are important determinants for ablation outcomes. FA size in combination with computational simulations can be used to direct ablation in persistent AF to minimize the critical mass required to sustain recurrent AF.

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Abbreviations

AF:

Atrial fibrillation

LGE:

Late gadolinium enhancement

MRI:

Magnetic resonance imaging

FA:

Fibrillatory area

RF:

Radiofrequency

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Funding

RR is or reently has been a consultant to Abbott, Biosense Webster and Medtronic. The University of Utah has research grants from Biosense Webster and Abbott with RR as the PI. JB has research grants from Boehringer Ingelheim, Boston Scientific, Altathera. The remaining authors have nothing to disclose. RR is currently supported by NHLBI R01 HL142913.

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Author notes

  1. Roya Kamali

    Present address: Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA

Authors and Affiliations

  1. Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA

    Roya Kamali, Devaki Abhijit Abhyankar, Derek J. Dosdall, Rob S. Macleod & Ravi Ranjan

  2. Division of Cardiovascular Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA

    Roya Kamali, Derek J. Dosdall, T. Jared Bunch & Ravi Ranjan

  3. Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT, USA

    Roya Kamali, Derek J. Dosdall, Rob S. Macleod & Ravi Ranjan

  4. Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA

    Jess Tate

  5. Institute of Biophysics, Medical University of Graz, Graz, Austria

    Karli Gillete & Gernot Plank

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Correspondence to Ravi Ranjan.

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Kamali, R., Gillete, K., Tate, J. et al. Treatment Planning for Atrial Fibrillation Using Patient-Specific Models Showing the Importance of Fibrillatory-Areas. Ann Biomed Eng 51, 329–342 (2023). https://doi.org/10.1007/s10439-022-03029-5

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