1. The 'Digital Twin' to enable the vision of precision cardiology
- Author
-
Pras Pathmanathan, Liesbet Geris, Yingjing Feng, Francesca Margara, Andrew Gilbert, Espen W. Remme, Alfonso Bueno-Orovio, Joao Filipe Fernandes, Mark Potse, Marta Sitges, Blanca Rodriguez, Viatcheslav Gurev, Tammo Delhaas, Tina M. Morrison, Manuel Villegas Martinez, Pablo Lamata, Ali Wajdan, Ada Doltra, Filip Loncaric, Hassaan A. Bukhari, Richard Cornelussen, Paul Leeson, Paolo DiAchille, Frits W. Prinzen, Peter Mortier, Manuel Mayr, Hongxing Luo, Edward J. Vigmond, Mehrdad Shamohammdi, Esther Pueyo, Kristin McLeod, Philip Westphal, Vicente Grau, Jorge Corral-Acero, Ernesto Zacur, Steven A. Niederer, Mariana Sousa Santos, Maciej Marciniak, Cristobal Rodero, Department of Engineering Science [Oxford], Institute of Biomedical Engineering [Oxford] (IBME), University of Oxford [Oxford]-University of Oxford [Oxford], Department of Computer Science [Oxford], University of Oxford [Oxford], King‘s College London, Universitat de Barcelona (UB), Institut de rythmologie et modélisation cardiaque [Pessac] (IHU Liryc), Oslo University Hospital [Oslo], Aragón Institute of Engineering Research [Zaragoza] (I3A), University of Zaragoza - Universidad de Zaragoza [Zaragoza], Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), FEops, Maastricht University [Maastricht], Medtronic Bakken Research Center BV, John Radcliffe Hospital [Oxford University Hospital], IBM Thomas J. Watson Research Center, IBM, Virtual Physiological Human Institute [Leuven] (VPH), U.S. Food and Drug Administration (FDA), Cardiovascular Research Institute Maastricht (CARIM), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Oslo (UiO), GE Vingmed Ultrasound AS, IHU-LIRYC, CHU Bordeaux [Bordeaux]-Université Bordeaux Segalen - Bordeaux 2, Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC, CHU Bordeaux [Bordeaux]-Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Instituto de Salud Carlos III [Madrid] (ISC)-ministerio de ciencia e innovacion, This work was supported by the EU’s Horizon 2020 Marie Sklodowska-Curie ITN Projects (g.a. 764738 and 766082), the EU’s Horizon 2020 research and (g.a. 675451 and 823712), the Wellcome/EPSRC Centre for Medical Engineering (WT 203148/Z/16/Z), the National Research Agency (ANR) (g.a. ANR-10-IAHU-04), theNC3RS (NC/P001076/1) and the British Heart Foundation (RE/13/2/30182, RE/13/1/30181, TG/17/3/33406, PG/16/75/32383, FS/17/22/32644, CH/16/3/21406, RG/16/14/32397). E.Pueyo holds an ERC StartingGrant (g.a. 638284). B. Rodriguez and P. Lamata hold Wellcome TrustSenior Research Fellowships (214290/Z/18/Z, 209450/Z/17/Z)., ANR-10-IAHU-04/10-IAHU-0004,LIRYC,L'Institut de Rythmologie et modélisation Cardiaque(2010), ANR-10-IAHU-0004,LIRYC,L'Institut de Rythmologie et modélisation Cardiaque(2010), Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), University of Oxford-University of Oxford, University of Oxford, Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, and Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-CHU Bordeaux [Bordeaux]
- Subjects
Artificial intelligence ,Cardiac & Cardiovascular Systems ,INFORMATION ,diagnosis ,030204 cardiovascular system & hematology ,0302 clinical medicine ,CHANNEL ,Medicine ,AcademicSubjects/MED00200 ,RISK ,0303 health sciences ,Computational model ,ARTIFICIAL-INTELLIGENCE ,Precision medicine ,twins ,3. Good health ,cardiology ,HEART ,TRIAL ,Cardiology and Cardiovascular Medicine ,Life Sciences & Biomedicine ,Algorithms ,Digital Health and Innovation ,vision ,Boosting (machine learning) ,BIG DATA ,Cardiovascular research ,MEDLINE ,PRESSURE ,03 medical and health sciences ,models ,[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system ,computer simulation ,Extensive data ,State of the Art Review ,Humans ,030304 developmental biology ,Science & Technology ,BLOOD-FLOW ,business.industry ,MEDICINE ,Statistical model ,PERFORMANCE ,CT ANGIOGRAPHY ,Data science ,Digital twin ,Computational modelling ,Cardiovascular System & Cardiology ,Position paper ,precision ,business ,statistical - Abstract
Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine. ispartof: EUROPEAN HEART JOURNAL vol:41 issue:48 pages:4556-+ ispartof: location:England status: published
- Published
- 2020