Samenvatting
The infarct, 15% in size, was found to reduce stroke work by 30% compared to the healthy heart. This disproportional loss was attributed to unfavourable mechanical interactions in healthy tissue, adjacent to the infarction. The effect of the patch was investigated for a circumferential, an oblique, and a longitudinal orientation. In its most favourable oblique configuration, the cardiac patch was able to recover 6% of stroke work lost. This specific configuration was found to best restore the transmission of active force, that was lost due to the myocardial infarction.
| Originele taal-2 | Engels |
|---|---|
| Titel | Functional Imaging and Modeling of the Heart |
| Subtitel | 12th International Conference, FIMH 2023, Lyon, France, June 19–22, 2023, Proceedings |
| Redacteuren | Olivier Bernard, Patrick Clarysse, Nicolas Duchateau, Jacques Ohayon, Magalie Viallon |
| Uitgeverij | Springer |
| Pagina's | 594-603 |
| Aantal pagina's | 10 |
| ISBN van elektronische versie | 978-3-031-35302-4 |
| ISBN van geprinte versie | 978-3-031-35301-7 |
| DOI's | |
| Status | Gepubliceerd - jun. 2023 |
Publicatie series
| Naam | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 13958 LNCS |
| ISSN van geprinte versie | 0302-9743 |
| ISSN van elektronische versie | 1611-3349 |
Financiering
Acknowledegments. This work was supported by the British Heart Foundation Centre of Research Excellence at Imperial College London (RE/18/4/34215). K. Vimalesvaran and S. Zaman were supported by UKRI Centre for Doctoral Training in AI for Healthcare grant number EP/S023283/1. The project was partly supported by a Rosetrees Interdisciplinary Award. Acknowledgements. The study was approved by the Ethics Committee of the University Medical Center Ljubljana, Slovenia, under 0120-133/2021/3 and 0120-312/2022/3, and supported by the Slovenian Research Agency (ARRS) under grants J2-4453 and P2-0232, and by the University Medical Center Ljubljana, Slovenia, under grant 20190174. Acknowledgements. This work has been supported by the French government through the National Research Agency (ANR) Investments in the Future with 3IA Côte d’Azur (ANR-19-P3IA-0002) and by Inria PhD funding. The authors are grateful to the OPAL infrastructure from Université Côte d’Azur for providing resources and support. Acknowledgements. The authors thank the Stanford Research Computing Center for computational resources (Sherlock HPC Cluster). This work is funded by a National Science Foundation Graduate Research Fellowship (DGE-1656518) to PJN and by the Stanford Maternal and Child Health Research Institute (award K99HL161313) to MRP. gen, Germany, for providing the 4D flow work-in-progress package. Malak Sabry is supported by a PhD educational grant from Siemens Healthineers and the Magdi Yacoub Foundation. Acknowledgements. This work is funded by a EPSRC grant (EP/X023826/1). The study was also supported by the Wellcome/EPSRC Centre for Medical Engineering (WT203148/Z/16/Z) and the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Acknowledgements. This work has been performed under FI 2022 grant number 00237, awarded by the Agency for Management of University and Research Grants (AGAUR), Generalitat de Catalunya. It has been partially funded by European Union-NextGenerationEU, Ministry of Universities and Recovery, Transformation and Resilience Plan, through a call from Pompeu Fabra University (Barcelona). Acknowledgments. This Project has received funding from the European Unions Horizon research and innovation programme under the Marie Skodowska-Curie grant agreement No. 860974 and by the French National Research Agency, grant references ANR-10-IAHU04-LIRYC and ANR-11-EQPX-0030. The study was carried out as part of the PersonalizeAF project in collaboration with EP-Solutions SA. Youth and Sports of the Czech Republic under the OP RDE grants number CZ2.11/0/0/16 019/0000765 and by the Ministry of Health of the Czech Republic project No. NV19-08-00071. This work was also supported by the Inria-UTSW Associated Team TOFMOD. Acknowledgements. This material is based upon work supported, in part, by American Heart Association Grant 19IPLOI34760294 (to D.B.E.) and National Heart, Lung, and Blood Institute Grants R01-HL131823 (to D.B.E.), R01-HL152256 (to D.B.E.), and K25-HL135408 (to L.E.P.) and by the National Science Foundation under Grants 2205043 (to L.E.P.) and 2205103 (to D.B.E.). Acknowledgement. The authors gratefully acknowledge support from the French Agence Nationale de la Recherche (ANR) (grant ANR-22-CE45-0014-01, project MIRE4VTach), from the Atrial Fibrillation Chair of the IHU Liryc, from the Fon-dation Bordeaux Université, from the Fondation Lefoulon-Delalande, and from the French Federation of Cardiology - Grands projets - 2022 (project DIELECTRIC). Acknowledgments. This work was funded by British Heart Foundation Grants RE/13/4/30184 and RG/19/1/34160. Acknowledgements. We are grateful for the funding provided by the British Heart Foundation (ref: PG/22/10930), and the UK Engineering and Physical Sciences Research Council (EP/S030875, EP/S020950/1, EP/S014284/1, EP/R511705/1). Science Foundation under Grant Number 2205043. Ethical Considerations and Acknowledgements. This virtual study was carried out using computer simulations which did not require ethical approval. This research has been conducted using the UK Biobank Resource under Application Number 40161. The authors express no conflict of interest. This work was funded by an Engineering and Physical Sciences Research Council doctoral award, a Wellcome Trust Fellowship in Basic Biomedical Sciences (214290/Z/18/Z), the CompBioMed2 Centre of Excellence in Computational Biomedicine (European Commission Horizon 2020 research and innovation programme, grant agreement No. 823712). The computation costs were incurred through a PRACE ICEI project (icp019), which provided access to Piz Daint at the Swiss National Supercomputing Centre, Switzerland. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) public copyright license to any Author Accepted Manuscript (AAM) version arising from this submission. supported by NSF 2205103 and NIH R01 Acknowledgements. The authors acknowledge the support from the French ANR (LABEX PRIMES of Univ. Lyon [ANR-11-LABX-0063], the JCJC project “MICMAC” [ANR-19-CE45-0005]), and the European Union - NextGenerationEU, Ministry of Universities and Recovery, Transformation and Resilience Plan, through a call from Pompeu Fabra University (Barcelona). They are also grateful to P. Moceri (CHU Nice, France) for providing the imaging data related to the studied population, and to M. Sermesant (INRIA Epione, Sophia Antipolis, France) for initial discussions on this topic. Acknowledgments. This work was supported by the European High-Performance Computing Joint Undertaking EuroHPC under grant agreement No 955495 (MICROCARD) co-funded by the Horizon 2020 programme of the European Union (EU) and the Swiss State Secretariat for Education, Research and Innovation. Acknowledgement. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement, No 101016496 (SimCardioTest). Acknowledgements. Jelmer M. Wolterink was supported by the NWO domain Applied and Engineering Sciences VENI grant (18192). Acknowledgements. This work was supported by TUBITAK (grant no: 120N200), SAS (grant no: 536057), and VEGA (grant no: 2/0109/22). Acknowledgements. The authors acknowledge the support from the European Union - NextGenerationEU, Ministry of Universities and Recovery, Transformation Acknowledgements. This work was supported by the Ministry of Education, Research reported in this publication was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institute of Health under award number R01EB027774. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The concepts and information Acknowledgements. This research was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research innovation programme under grant agreement no. 874827 (BRAV ). Acknowledgments. This work was supported by the British Heart Foundation Centre of Research Excellence at Imperial College London (RE/18/4/34215). The authors would like to thank Abhishek Roy, Tommy Chen and Krithika Balaji for their contributions. Acknowledgements. We gratefully acknowledge the financial support from the Health Research Council of New Zealand (17/608). We also acknowledge the important roles of our research nurses Mariska Oakester Bals, Jane Hannah, Anna Taylor, and Gracie Hoskin for their invaluable assistance in participant recruitment and data collection. Acknowledgements. The authors would like to thank Michel Ovize, Thomas Bocha-ton, and Nathan Mewton for sharing in-vivo data from the HIBISCUS cohort. We also thank Circle Cardiovascular Imaging (Calgary, Canada) for making the CVI42 software package available for research purposes. We acknowledge the support of the French Agence Nationale de la Recherche (ANR) under grants ANR-19-CE45-0020 (SIMR project), ANR-11-LABX-0063 (LABEX PRIMES of Univ. Lyon), and ANR-19-CE45-0005 (MIC-MAC project), and the Fédération Francaise de Cardiologie (MI-MIX project, Allocation René Foudon). Acknowledgements. This material is based upon work supported by the National Institutes of Health grants HL129077, HL119297 to MSS and RCG, and an American Heart Association pre-doctoral fellowship to NTS. Acknowledgements. This work is funded by EPSRC Centre for Doctoral Training in Smart Medical Imaging (EP/S022104/1), by a Program Grant from the British Heart Foundation (RG/19/1/34160), and Siemens Healthineers. This work was supported by the National Institute of Health (NIH R01-HL131823). Acknowledgements. This research was supported by the Innovate UK (104691) London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, the USA National Institutes of Health R01HL121754, and core funding from the Wellcome/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z]. SCOT-HEART was funded by The Chief Scientist Office of the Scottish Government Health and Social Care Directorates (CZH/4/588), with supplementary awards from Edinburgh and Lothian’s Health Foundation Trust and the Heart Diseases Research Fund. MCW was supported by the British Heart Foundation FS/ICRF/20/26002 and CH/09/002. SEW is supported by the British Heart Foundation (FS/20/26/34952). The authors acknowledge the support of the British Heart Foundation Centre for Research Excellence Award III (RE/18/5/34216). Acknowledgements. We thank and acknowledge VINNOVA (2022-00849), Digital Futures, and the Digital platform of KTH for their financial support; Dr. Marianne Schmid Daners and Dr. Thomas Gwosch at ETH Zurich for sharing their know-how in replicating the hybrid mock circulation loop and provision of the colacino-model implementation; Sara Mettler for the electrical support; Peter Arfert for the mechanical design; Laura Andersson, and Roxanne Rais for their experimental support. Acknowledgment. Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award No. R35GM128877 and by the Office of Advanced Cyberinfrastructure of the National Science Foundation under Award No. 1808530 and Award No. 1808553. Acknowledgments. This work was financially supported by the Theo Rossi di Mon-telera Foundation, the Metis Foundation Sergio Mantegazza, the Fidinam Foundation, and the Horten Foundation to the Center for CCMC. SP also acknowledges the CSCS-Swiss National Supercomputing Centre (No. s1074). Finally, this work was supported by the European High-Performance Computing Joint Undertaking EuroHPC under grant agreement No. 955495 (MICROCARD) co-funded by the Horizon 2020 programme of the European Union (EU) and the Swiss State Secretariat for Education, Research and Innovation. Acknowledgements. This work is funded in part by the 4TU Precision Medicine programme supported by High Tech for a Sustainable Future, a framework commissioned by the four Universities of Technology of the Netherlands. Jelmer M. Wolterink was supported by the NWO domain Applied and Engineering Sciences VENI grant (18192). This work made use of the Dutch national e-infrastructure with the support of the SURF Cooperative using grant no. EINF-2675. Acknowledgements. Chinese Heilongjiang Postdoctoral Grant (LBH-Z22184), National Natural Science Foundation of China (no. 52075133) and Metislab (Medical Engineering and Theory in Imaging and Signal Laboratory), CNRS LIA no.1124, INSA Lyon supported this work. This work was also performed within the framework of the LABEX PRIMES (ANR-11-LABX-0063) of Université de Lyon, within the program “Investissements d’Avenir” (ANR-11-IDEX-0007) operated by the French National Research Agency (ANR). The FIMH 2023 conference was certified by the MICCAI society and the French Society of Biomechanics (with financial support). Acknowledgements. This work was funded by Generalitat Valenciana Grant AICO/2021/318 (Consolidables 2021) and Grant PID2020-114291RB-I00 funded by MCIN/https://doi.org/10. 13039/501100011033 and by “ERDF A way of making Europe”. Acknowledgement. This work was supported in part by the British Heart Foundation, UK (Grant no. RG/F/22/110059). J Jevsikov is supported by the Vice Chancellor’s Scholarship at the University of West London. We are grateful to the following experts for their invaluable input in labelling images: Arjun Ghosh, Maysaa Zetani, Mahmoud Tawil, Luxy Ananthan, Camelia Demetrescu, Amar Singh, Sanjeev Bhattacharyya, Joban Sehmi, Kavitha Vimalesvaran, Abdallah Al-Mohammad, Bushra Rana, Tiffany Ng. Acknowledgements. This work was supported by the H2020 EU SimCardioTest project (Digital transformation in Health and Care SC1-DTH-06-2020; grant agreement number 101016496). This study received financial support from the French Government as part of the “Investments of the Future” program managed by the National Research Agency (ANR), Grant reference ANR-10-IAHU-04. Experiments presented in this paper were partially carried out using the PlaFRIM experimental testbed, supported by Inria, CNRS (LABRI and IMB), Université de Bordeaux, Bordeaux INP and Conseil Régional d’Aquitaine. Acknowledgement. This research has been conducted using the UK Biobank Resource under Application Number ‘40161’. The authors express no conflict of interest. This work was funded by the CompBioMed 2 Centre of Excellence in Computational Biomedicine (European Commission Horizon 2020 research and innovation programme, grant agreement No. 823712). L. Li was partially supported by the SJTU 2021 Outstanding Doctoral Graduate Development Scholarship. A. Banerjee is a Royal Society University Research Fellow and is supported by the Royal Society Grant No. URF\R1\221314. The work of A. Banerjee and V. Grau was partially supported by the British Heart Foundation (BHF) Project under Grant PG/20/21/35082. Acknowledgements and Funding. All staff from LIRYC and CHU Bordeaux involved in the Human donor program CADENCE and HARMONICA project are gratefully acknowledged for their valuable contributions. This work received financial support from the French National Investments for the Future Programs: ANR-10-IAHU-04. HD figures are available at: https://github.com/ valeryozenne/Cardiac-Structure-Database/tree/master/Article-4.
| Financiers | Financiernummer |
|---|---|
| British Heart Foundation Centre for Research Excellence Award III | RE/18/5/34216 |
| Imperial College London | RE/18/4/34215 |
| Center for CCMC | |
| European Union’s Horizon Europe research and innovation programme | 823712 |
| European High-Performance Computing Joint Undertaking EuroHPC | 955495 |
| European Union-NextGenerationEU | |
| European Union’s Horizon Europe research and innovation programme | |
| European Union’s Horizon Europe research and innovation programme | 874827 |
| Fidinam Foundation | |
| Fondation Bordeaux Université | |
| Fondation Lefoulon-Delalande | |
| French Government | |
| French National Investments for the Future Programs | |
| French Society of Biomechanics | |
| French Government | |
| European Union H2020 | |
| Heart Diseases Research Fund | |
| Horten Foundation | |
| Magdi Yacoub Foundation | |
| H2020 Marie Skłodowska-Curie Actions | 860974 |
| Metis Foundation Sergio Mantegazza | |
| Ministry of Universities and Recovery | |
| SJTU 2021 Outstanding Doctoral Graduate Development Scholarship | |
| Surf, Stichting | EINF-2675 |
| Theo Rossi di Mon-telera Foundation | |
| University Medical Center Ljubljana | 0120-312/2022/3, 0120-133/2021/3 |
| National Science Foundation(NSF) | DGE-1656518, 2205103, 1808553, 1808530, 2205043 |
| National Institutes of Health, NIH | R01EB027774, R01, R35GM128877, HL119297, HL129077, R01HL121754 |
| National Heart, Lung, and Blood Institute | R01-HL131823, K25-HL135408, R01-HL152256 |
| National Institute of General Medical Sciences | |
| National Institute of Biomedical Imaging and Bioengineering | |
| Office of Advanced Cyberinfrastructure | |
| American Heart Association | 19IPLOI34760294 |
| Indian National Science Academy | |
| King's College London | |
| Society for Anthropological Sciences | 536057 |
| University of West London | |
| Wellcome Trust | 214290/Z/18/Z |
| European Union’s Horizon Europe research and innovation programme | 101016496 |
| INRIA Institut National de Recherche en Informatique et en Automatique | |
| UK Research and Innovation | EP/S023283/1 |
| Chief Scientist Office, Scottish Government Health and Social Care Directorate | CZH/4/588 |
| Stanford Maternal and Child Health Research Institute | K99HL161313 |
| Universitat Pompeu Fabra | |
| Digital Futures | |
| Engineering and Physical Sciences Research Council | EP/S030875, EP/S022104/1, EP/S014284/1, EP/R511705/1, EP/S020950/1, EP/X023826/1 |
| National Institute for Health and Care Research | |
| British Heart Foundation | CH/09/002, PG/22/10930, RG/19/1/34160, RG/F/22/110059, PG/20/21/35082, FS/20/26/34952, FS/ICRF/20/26002, RE/13/4/30184 |
| Royal Society | URF\R1\221314 |
| European Commission | |
| European Research Council | |
| Health Research Council of New Zealand | 17/608 |
| Agence Nationale de la Recherche (ANR) | ANR-19-CE45-0020, ANR-10-IAHU04-LIRYC, ANR-11-LABX-0063, ANR-22-CE45-0014-01, ANR-11-EQPX-0030, ANR-10-IAHU-04, ANR-19-P3IA-0002, MIRE4VTach |
| National Natural Science Foundation of China | 52075133 |
| VINNOVA | 2022-00849 |
| Ministry of Education | |
| Generalitat de Catalunya | |
| ETH Zurich | |
| Agència de Gestió d'Ajuts Universitaris i de Recerca | |
| Ministerstvo Zdravotnictví Ceské Republiky | NV19-08-00071 |
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek | 18192 |
| Generalitat Valenciana | AICO/2021/318, PID2020-114291RB-I00 |
| Kungliga Tekniska Högskolan | |
| Javna Agencija za Raziskovalno Dejavnost RS | J2-4453, 20190174, P2-0232 |
| Türkiye Bilimsel ve Teknolojik Araştırma Kurumu | 120N200 |
| CNRS | 1124 |
| Guy's and St Thomas' NHS Foundation Trust | |
| Innovate UK | 104691 |
| Vedecká Grantová Agentúra MŠVVaŠ SR a SAV | 2/0109/22 |
| Universite de Bordeaux | |
| Russian Science Foundation | |
| Staatssekretariat für Bildung, Forschung und Innovation | |
| Conseil Régional Aquitaine | |
| Université de Lyon | ANR-11-IDEX-0007 |
| Siemens Healthineers | |
| Wellcome EPSRC Centre for Medical Engineering | WT203148/Z/16/Z |
| Institut Polytechnique de Bordeaux |