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Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics.

Chabiniok R, Wang VY, Hadjicharalambous M, Asner L, Lee J, Sermesant M, Kuhl E, Young AA, Moireau P, Nash MP, Chapelle D, Nordsletten DA - Interface Focus (2016)

Bottom Line: Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation.Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart.Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice.

View Article: PubMed Central - PubMed

Affiliation: Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas' Hospital, London SE1 7EH, UK; Inria and Paris-Saclay University, Bâtiment Alan Turing, 1 rue Honoré d'Estienne d'Orves, Campus de l'Ecole Polytechnique, Palaiseau 91120, France.

ABSTRACT
With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.

No MeSH data available.


Related in: MedlinePlus

TCM pathway, illustrating the formative steps of model-based analysis. The driver for TCM efforts starts with the clinical question, informing the selection of an application-specific model that brings together the appropriate data and model components. Data–model fusion is then required, personalizing the model with sufficient data (either patient-specific or population average data) to address the clinical need. Once formulated, modelling can be executed and used to generate specific clinically relevant outcomes, informing diagnosis, treatment optimization or treatment planning.
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RSFS20150083F4: TCM pathway, illustrating the formative steps of model-based analysis. The driver for TCM efforts starts with the clinical question, informing the selection of an application-specific model that brings together the appropriate data and model components. Data–model fusion is then required, personalizing the model with sufficient data (either patient-specific or population average data) to address the clinical need. Once formulated, modelling can be executed and used to generate specific clinically relevant outcomes, informing diagnosis, treatment optimization or treatment planning.

Mentions: The advancements made in modelling, imaging, image processing and data assimilation provide an impressively diverse range of tools and data. Extending these developments beyond academic and research realms and into the hospital requires careful consideration of specific clinical questions and the requirements of the end-user. The specific clinical application and desired outcome, in turn, guide the selection of required models and data, influencing the necessary processing and assimilation tools, theoretical considerations, etc. (figure 4). The pathways for TCM to make an impact clinically are numerous. In this section, we highlight some of these active TCM efforts.Figure 4.


Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics.

Chabiniok R, Wang VY, Hadjicharalambous M, Asner L, Lee J, Sermesant M, Kuhl E, Young AA, Moireau P, Nash MP, Chapelle D, Nordsletten DA - Interface Focus (2016)

TCM pathway, illustrating the formative steps of model-based analysis. The driver for TCM efforts starts with the clinical question, informing the selection of an application-specific model that brings together the appropriate data and model components. Data–model fusion is then required, personalizing the model with sufficient data (either patient-specific or population average data) to address the clinical need. Once formulated, modelling can be executed and used to generate specific clinically relevant outcomes, informing diagnosis, treatment optimization or treatment planning.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4759748&req=5

RSFS20150083F4: TCM pathway, illustrating the formative steps of model-based analysis. The driver for TCM efforts starts with the clinical question, informing the selection of an application-specific model that brings together the appropriate data and model components. Data–model fusion is then required, personalizing the model with sufficient data (either patient-specific or population average data) to address the clinical need. Once formulated, modelling can be executed and used to generate specific clinically relevant outcomes, informing diagnosis, treatment optimization or treatment planning.
Mentions: The advancements made in modelling, imaging, image processing and data assimilation provide an impressively diverse range of tools and data. Extending these developments beyond academic and research realms and into the hospital requires careful consideration of specific clinical questions and the requirements of the end-user. The specific clinical application and desired outcome, in turn, guide the selection of required models and data, influencing the necessary processing and assimilation tools, theoretical considerations, etc. (figure 4). The pathways for TCM to make an impact clinically are numerous. In this section, we highlight some of these active TCM efforts.Figure 4.

Bottom Line: Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation.Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart.Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice.

View Article: PubMed Central - PubMed

Affiliation: Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas' Hospital, London SE1 7EH, UK; Inria and Paris-Saclay University, Bâtiment Alan Turing, 1 rue Honoré d'Estienne d'Orves, Campus de l'Ecole Polytechnique, Palaiseau 91120, France.

ABSTRACT
With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.

No MeSH data available.


Related in: MedlinePlus