euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling

Author:

Smith Nic12,de Vecchi Adelaide1,McCormick Matthew2,Nordsletten David1,Camara Oscar34,Frangi Alejandro F.345,Delingette Hervé6,Sermesant Maxime6,Relan Jatin6,Ayache Nicholas6,Krueger Martin W.7,Schulze Walther H. W.7,Hose Rod8,Valverde Israel1,Beerbaum Philipp1,Staicu Cristina8,Siebes Maria9,Spaan Jos9,Hunter Peter10,Weese Juergen11,Lehmann Helko11,Chapelle Dominique12,Rezavi Reza1

Affiliation:

1. Imaging Sciences and Biomedical Engineering Division, St Thomas' Hospital, King's College London, London, UK

2. Computing Laboratory, University of Oxford, Oxford, UK

3. Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra, Barcelona, Spain

4. Networking Biomedical Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain

5. Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain

6. INRIA Sophia-Antipolis, Sophia Antipolis Cedex, France

7. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

8. Department of Cardiovascular Science, University of Sheffield, Sheffield, UK

9. Academic Medical Center Amsterdam, Amsterdam, The Netherlands

10. Bioengineering Institute, University of Auckland, Auckland, New Zealand

11. Philips Research Laboratories, Eindhoven, The Netherlands

12. INRIA Paris-Rocquencourt, Paris, France

Abstract

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.

Publisher

The Royal Society

Subject

Biomedical Engineering,Biomaterials,Biochemistry,Bioengineering,Biophysics,Biotechnology

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