Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

Journal: Circulation. Arrhythmia and electrophysiology
PMID: 35089057

Abstract

BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while patient-specific models in small cohorts primarily explain acute response to ablation. We aimed to predict long-term atrial fibrillation recurrence after ablation in large cohorts, by using machine learning to complement biophysical simulations by encoding more interindividual variability.

Authors

  • Caroline H Roney
    King's College London, London, United Kingdom.
  • Iain Sim
    Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.).
  • Jin Yu
    School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (C.H.R., I.S., J.Y., M.B., A.M., J.A.S.-L., I.K., J.W., C.C., O.R., M.O., S.E.W., S.A.N.).
  • Marianne Beach
    School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (C.H.R., I.S., J.Y., M.B., A.M., J.A.S.-L., I.K., J.W., C.C., O.R., M.O., S.E.W., S.A.N.).
  • Arihant Mehta
    School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (C.H.R., I.S., J.Y., M.B., A.M., J.A.S.-L., I.K., J.W., C.C., O.R., M.O., S.E.W., S.A.N.).
  • Jose Alonso Solis-Lemus
    School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (C.H.R., I.S., J.Y., M.B., A.M., J.A.S.-L., I.K., J.W., C.C., O.R., M.O., S.E.W., S.A.N.).
  • Irum Kotadia
    School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (C.H.R., I.S., J.Y., M.B., A.M., J.A.S.-L., I.K., J.W., C.C., O.R., M.O., S.E.W., S.A.N.).
  • John Whitaker
    Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.).
  • Cesare Corrado
    King's College London, London, United Kingdom.
  • Orod Razeghi
    King's College London, London, United Kingdom.
  • Edward Vigmond
    IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, France (E.V.).
  • Sanjiv M Narayan
    Biomedical Informatics Training Program (L.H., S.M.N.), Stanford University, CA.
  • Mark O'Neill
    Division of Cardiovascular Medicine, Guys and St Thomas' NHS Foundation Trust, King's College London, London, United Kingdom.
  • Steven E Williams
    Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom (O.R., I.S., C.H.R., R.K., H.C., J.W., L.O., R.M., M.O., S.E.W., S.N.).
  • Steven A Niederer
    Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom.

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