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Using machine learning to identify local cellular properties that support re-entrant activation in patient-specific models of atrial fibrillation
- Source :
- Europace
- Publication Year :
- 2021
- Publisher :
- Oxford University Press, 2021.
-
Abstract
- AimsAtrial fibrillation (AF) is sustained by re-entrant activation patterns. Ablation strategies have been proposed that target regions of tissue that may support re-entrant activation patterns. We aimed to characterize the tissue properties associated with regions that tether re-entrant activation patterns in a validated virtual patient cohort.Methods and resultsAtrial fibrillation patient-specific models (seven paroxysmal and three persistent) were generated and validated against local activation time (LAT) measurements during an S1–S2 pacing protocol from the coronary sinus and high right atrium, respectively. Atrial models were stimulated with burst pacing from three locations in the proximity of each pulmonary vein to initiate re-entrant activation patterns. Five atria exhibited sustained activation patterns for at least 80 s. Models with short maximum action potential durations (APDs) were associated with sustained activation. Phase singularities were mapped across the atria sustained activation patterns. Regions with a low maximum conduction velocity (CV) were associated with tethering of phase singularities. A support vector machine (SVM) was trained on maximum local conduction velocity and action potential duration to identify regions that tether phase singularities. The SVM identified regions of tissue that could support tethering with 91% accuracy. This accuracy increased to 95% when the SVM was also trained on surface area.ConclusionIn a virtual patient cohort, local tissue properties, that can be measured (CV) or estimated (APD; using effective refractory period as a surrogate) clinically, identified regions of tissue that tether phase singularities. Combing CV and APD with atrial surface area further improved the accuracy in identifying regions that tether phase singularities.
- Subjects :
- medicine.medical_specialty
Support vector machine
medicine.medical_treatment
Action Potentials
030204 cardiovascular system & hematology
Nerve conduction velocity
Pulmonary vein
Machine Learning
03 medical and health sciences
0302 clinical medicine
Physiology (medical)
Internal medicine
Atrial Fibrillation
medicine
Humans
AcademicSubjects/MED00200
Heart Atria
Coronary sinus
Phase singularity map
Atrium (architecture)
business.industry
Tethering
Effective refractory period
Atrial fibrillation
Ablation
medicine.disease
Supplement Papers
Cardiology
cardiovascular system
Patient-specific model
Cardiology and Cardiovascular Medicine
business
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- ISSN :
- 15322092 and 10995129
- Volume :
- 23
- Issue :
- Suppl 1
- Database :
- OpenAIRE
- Journal :
- Europace
- Accession number :
- edsair.doi.dedup.....e4a839c4a10b703f54f27c3947dfdd7e