A whole-heart model of multiscale soft tissue mechanics and fluid structure interaction for clinical applications (Whole-Heart-FSI)

Lead Research Organisation: University of Glasgow
Department Name: School of Mathematics & Statistics

Abstract

Heart disease is the leading cause of disability and death in the UK and worldwide, resulting in enormous health care costs. Risk prediction on an individual patient basis is imperfect. Advanced medical development has already saved many lives, particularly in systolic heart failure. However, there is currently no treatment option for diastolic heart failure (with preserved ejection fraction) due to its complexity of multiple mechanisms and co-modality. Structural heart diseases, such as myocardial infarction (MI- commonly known as heart attack) and mitral regurgitation (MR, a leakage of blood through the mitral valve to left atrium in systole), where biomechanical factors are crucial, are often precursors to heart failure. MI can eventually lead to dilated heart failure despite immediate treatments post-MI. MR can induce pulmonary hypertension and oedema and subsequently, right heart overload and heart failure. The grand challenge is for these situations the heart simply cannot be modelled as an isolated left ventricle (as in most of the current studies); flow-structure interaction (FSI), heart-valve interaction, multiscale soft tissue mechanics, and tissue growth and remodelling (G&R) all play important roles in the progression of the structural diseases.

This project is set up to meet this challenge by delivering a multiscale computational framework to include Whole-Heart FSI with G&R. Making use of the novel mathematical tools (constitutive laws, G&R, upscaling and statistical inference) developed by SofTMech, I will build a realistic four-chamber heart model that include heart-valve, chamber-chamber, heart-blood, and heart-circulation interactions, which will be powerful enough to model MI, MR and their pathological consequences. This work will be in close collaboration with my clinical, industrial and academic collaborators. The model will quantify which factors lead to adverse G&R and what variations are to be expected as the disease progresses. We will also identify significant biomechanical markers (e.g. constitutive parameters, energy indices, stress/strain evolution). The predictive values of these biomechanical parameters will be assessed against other established predictors of adverse remodellings, such as duration of ischaemia, final coronary flow grade after a primary percutaneous coronary intervention, and microvascular obstruction revealed by MRI. Thus, this project will generate new testable hypotheses and will be a significant step up towards more consistent decision-support for clinicians, since increasingly the pace and complexity of medical advances outstrip the ability of individual clinicians to cope with. Due to the statistical emulation and uncertainty quantification built into the project, the model predictions will be fast and quantified with error bounds on the outcome of alternative treatments. Consequently, we will also address the critical aspect of convincing clinicians that information obtained from simulations will be correct and relevant to their daily practice. The proposed research is right within the Healthcare Technologies "Optimising Treatment" and "Developing Future Therapies" priority areas, as well as targeting "New Connections from Mathematical Sciences", and "Statistics and Applied Probability" of Mathematical Sciences.

Planned Impact

Academic impact: This research, combining whole-heart multiscale modelling and fast emulation, will lead to a translational framework that scientists, engineers, and clinicians one day can use to plan and develop new intervention strategies. The work will also generate a valuable database of key classifiers in geometry and material properties associated with disease progression and identify how various interactions (chamber-chamber, chamber- valve, chamber-circulation) affect the heart function and stress/strain distributions, what drives the growth law, which parameters are strongly associated with eventual heart failure, and where we should focus our attention on in terms of treatment and prevention. For example, this heuristic approach will enable clinical scientists to study the effects of abnormalities of remote vessels of the circulation networks (which may be easier to monitor) to the heart function, and vice versa, or for companies to design better grafts that will reduce the compliance mismatch between the aorta and the heart. The energy budget analysis of the FSI within the heart will provide useful scalar measures for the complex 3D dynamic fluid fields, and thus, quantify interventions associated with the minimum energy dissipation. Importantly, we will build novel emulators to speed up the modelling process and assess model uncertainties, and move towards real-time clinical-support systems. This project will broaden the research base of SofTMech by both implementing and expanding the models developed for the left ventricle and provide multidisciplinary training for two RAs, as well as for PhD students.

Socio-Economic impact: The project will improve the quality of healthcare in the UK and beyond, and enhance the UK's global competitiveness by addressing the most important healthcare problems. Heart disease is the leading killer in the world, responsible for 30% of all deaths each year. MI is a leading cause of premature morbidity and mortality worldwide. Determining which patients will experience heart failure and sudden cardiac death after an acute MI is notoriously difficult for clinicians. The occurrence of MR increases with age (up to 10% of the population aged over 75), the burden of MR is likely to increase significantly in the future due to the ageing population. Severe MR leads to dilatation and failure of the left ventricle (LV), enlargement of the left atrium (LA), atrial fibrillation, pulmonary hypertension, stroke and even sudden death. This poses severe economic and medical challenges for the UK healthcare system. The research will generate a range of new mathematical and computational models for studying some common heart diseases. For example, developing predictive and quantitative models of healing processes post-MI will facilitate translational medical research to enhance diagnosis, treatment, and prevention. By developing test- and data-based modelling, we will examine how mitral dysfunction affects the function of the heart through FSI and the energy budget, and which parameters are strongly associated with adverse remodelling due to MR leading to heart failure. This fundamental research will significantly advance our understanding of disease pathogenesis, diagnosis and responses to therapy, and hence move clinical research forward.

Whole-Heart FSI will be directly supported by Terumo Aortic, GSK, Dassault Systemes Simulia, NHS Scotland, Scottish Health Innovations Ltd, hospitals (Berry and Danton), SofTMech, the Medical University of Graz, Kings College of London, and Ecole Polytechnique. It will embark on extensive networking activities and expand cutting-edge heart research in the UK.

Publications

10 25 50
 
Description 1. We developed a new theory that allows the growth tensor to be defined in the current, loaded configuration and were able to produce a residual strain that is consistent with experimental observations. We also estimated the growth tensor from imaging of an infarcted human heart in a first natural history of the disease. These results are published in BMMB (Zhuan & Luo 2021) and CBM (Li et al. 2021).
2. We extended the left ventricle model to include the mitral valve model, and then added the left atrium model, linked with the pulmonary circulation. In collaboration with Mark Danton (consultant cardiac surgeon), we obtained interesting new results about these sub-systems of the heart, that has been presented at various conferences, workshops, and published in BMMB (Feng et al. 2021).
3. We modelled cardiac perfusion with improved numerical efficiency. The computational framework we developed is published in IJNMBE (Richardson et al. 2021), we also developed novel numerical methods applicable for perfusion modelling. In addition to collaboration with Colin Berry the cardiologist, Boyce Griffith from the University of North Carolina at Chapel Hill, and Mette Olufsen from NC State University, we also established a new collaboration with Jack Lee from UCL.
4. We studied the effects of myofibre architecture on ventricular pump function by using a neonatal porcine heart model: from DT-MRI to rule-based methods and discovered that realistic fibre dispersion of the heart could be suitably modelled using a rule-based method.
5. We carried out a detailed energy budget analysis of FSI. The model has first been applied to flow through a collapsible channel, a prototypical system for investigating FSI, that exhibits fascinating physical behaviour including multiple steady and oscillatory solutions. We have revealed an entirely new mechanism for self-excited oscillation from an inflated basic state, which may have relevance to aneurysms. These studies are published in JFM and IJAM (Wang et al. 2021, 2022).
6. We improved the modelling of the myocardium by adding details of the cellular level. The heart muscle cells (myocytes) in the myocardium and the scaffold (collagen network) have very delicate structures to maximize the pumping function. Existing studies usually consider main features (i.e. average muscle orientations), but missed features like dispersion. In this work, both the passive and active heart muscle models include the myocyte and collagen dispersions, and the work is published in JEM (Guan et al. 2021).
7. To make a heart model work requires lengthy computational time since the mathematical model needs to be run thousands of times as part of an optimisation algorithm to match the patient data. To overcome those obstacles, we must make use of advanced statistical inference approaches and artificial intelligence to accelerate the clinical translation of models. In a series of past studies, we have demonstrated that a computationally cheap statistical surrogate model can be derived from the computationally expensive mathematical model can be replaced by without compromising the accuracy. In this project, led by Dirk, we have successfully adapted "deep learning" techniques based on convolutional neural networks to learn heart geometry directly from the heart scans without manual interventions and published in AIM (Romaszko et al. 2021). We have observed three orders of magnitude acceleration when inferring heart muscle stiffness using surrogate modelling, reducing the computational time to less than 15 mins.
Exploitation Route Journal publications, conference presentations, and open-source software uploaded in Github
Sectors Education,Healthcare

URL http://www.softmech.org/currentgrants/whole-heart-fsi/
 
Description Heart disease is the leading cause of disability and death in the UK and worldwide, resulting in enormous health care costs. There is currently no treatment option for diastolic heart failure (with preserved ejection fraction) due to its complexity of multiple mechanisms and co-modality. This project works on delivering a multiscale computational framework to include Whole-Heart Fluid-Structure Interaction (FSI) with tissue Growth and Remodelling (G&R). Making use of the novel mathematical tools (constitutive laws, G&R, upscaling and statistical inference) developed by SofTMech, the objective is to build a realistic four-chamber heart model that includes heart-valve, chamber-chamber, heart-blood, and heart-circulation interactions, which is powerful enough to model mitral infarction, mitral regurgitation and their pathological consequences. This work is in close collaboration with clinical, industrial and academic collaborators. The model aims to quantify which factors lead to adverse G&R and what variations are to be expected as the disease progresses. This project is generating new testable hypotheses and will be a significant step up towards more consistent decision-support for clinicians, since increasingly the pace and complexity of medical advances outstrip the ability of individual clinicians to cope with. Due to the statistical emulation and uncertainty quantification built into the project, the model predictions will be fast and quantified with error bounds on the outcome of alternative treatments.
First Year Of Impact 2020
Sector Digital/Communication/Information Technologies (including Software),Education,Healthcare,Manufacturing, including Industrial Biotechology
Impact Types Economic

 
Description EPSRC IAA project "Cardiac endotypes in COVID-19: quantification and mechanisms of cardiac injury"
Amount £109,400 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 01/2020 
End 12/2020
 
Title Cardiac Modelling with dispersed myofibre and collagen structures 
Description It is the accompanying dataset and model the paper "modelling of fibre dispersion and its effects on cardiac mechanics from diastole to systole", accepted in the Journal of Engineering Mathematics. It implements two different fibre dispersion models within two ventricular finite element models: a bi-ventricular rabbit heart and a human left ventricular model. 
Type Of Material Computer model/algorithm 
Year Produced 2021 
Provided To Others? Yes  
Impact This study highlights the importance of fibre dispersion in cardiac mechanics, and for the first time to investigate how to incorporate a complex fibre dispersion distribution into a cardiac mechanics model. This work has been presented in the Living Heart Project Seminar, and we are working with the Virtual Human Team from Dassault System to implement it in the Living Heart Project. 
URL https://github.com/HaoGao/DispersedFibresMyocardiumModelling
 
Title Energetics of a collapsible channel flow with a nonlinear fluid-beam model 
Description Data for figures in 'Energetics of a collapsible channel flow with a nonlinear fluid-beam model' 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL http://researchdata.gla.ac.uk/id/eprint/1112
 
Title Fibre Dispersion Myocardial Mechanics 
Description It contains the computational models for the following two papers 1. Guan, D., Mei, Y., Xu, L., Cai, L., Luo, X., & Gao, H. (2022). Effects of dispersed fibres in myocardial mechanics, Part I: passive response. Mathematical Biosciences and Engineering, 19(4), 3972-3993. 2. Guan, D., Wang, Y., Xu, L., Cai, L., Luo, X., & Gao, H. (2022). Effects of dispersed fibres in myocardial mechanics, Part II: active response. Mathematical Biosciences and Engineering, 19(4), 4101-4119. Published Year: 2022 
Type Of Material Computer model/algorithm 
Year Produced 2022 
Provided To Others? Yes  
Impact This work has attracted interest from the Virtual Human Team from Dassault System. It will further improve the cardiac modelling by including detailed fibre dispersion, in particular in fibrosis modelling. 
URL https://github.com/HaoGao/FibreDispersionMyocardialMechanics
 
Title FibreGeneration-LDDMM 
Description We develop a procedure to map an ex vivo DT-MRI dataset into a porcine bi-ventricle model, all model data and algorithms are included. The companion paper is being accepted in Royal Society Open Science (http://eprints.gla.ac.uk/211485/). 
Type Of Material Computer model/algorithm 
Year Produced 2019 
Provided To Others? Yes  
Impact The Abaqus LivingHeart Team was very interested in this approach and has been trying to deploy the framework within the LivingHeart Project. 
URL https://github.com/HaoGao/FibreGeneration-LDDMM
 
Title GlasgowHeart: A Magnetic Resonance Imaging-derived 'virtual twin' cardiac mechanics platform 
Description A personalized biomechanical cardiac modelling framework, aimed at the mechanistic understanding of individual patients' cardiac remodelling in the longer-term and risk-stratification. Our long-term aim is to be able to revolutionise clinical practice through accurate risk-stratification and virtual testing. Four modules are currently available in GlasgowHeart: 1) image processing, 2) biomechanics modelling, 3) personalization, inference and machine learning of left ventricular (LV) mechanics and 4) statistical emulation as shown in Figure 1. Modules 1, 2 and 3 have been developed in MATLAB by the co-authors, and module 4 is programmed in Python using Tensor Flow, Scikit-learn, XGBoost to use advanced machine-learning methods. For computational modelling in module 2, we further use LibMesh, IBAMR, Fenics for solving nonlinear systems, Visit and Paraview for 3D visualization. Module 2 can also work with other commercial packages for biomechanics simulations (ABAQUS, FEAP). 
Type Of Material Computer model/algorithm 
Year Produced 2021 
Provided To Others? Yes  
Impact This framework has been developed over the last ten years and contributed to various projects and funding applications. Recently it was presented in SCMR 2021 conference in the open-source software demo session. 
URL https://github.com/HaoGao/GlasgowHeart
 
Title Multiple Steady and Oscillatory Solutions in a Collapsible Channel Flow 
Description  
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL http://researchdata.gla.ac.uk/id/eprint/1165
 
Description New academic collabration 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution Collaboration with Dr. Jack Lee on heart perfusion modelling enables us to make use of their detailed coronary circulation model and expertise.
Collaborator Contribution Expertise and data
Impact Collaboration is still ongoing. No output yet.
Start Year 2021
 
Title GlasgowHeart 
Description GlasgowHeart platform for personalized modelling of the human heart. It is organized into 4 modules, and each can be run separately. Currently, MatLab is the main programming language and using scripts for run, this will require certain knowledge of Matlab. In the future, we will develop a GUI package for easy use. The four modules are image processing, biomechanics modelling, personalization, and parameter inference of left ventricular (LV) mechanics and statistical emulation. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact The package is actively being used by the researchers from the SofTMech Centre and supports a few cardiac research projects. 
 
Description BAMC minisymposium on Soft Tissue Growth and Remodelling 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact I organized a BAMC mini-symposium on Soft Tissue Growth and Remodelling with colleagues, which has attracted more than 50 audience
Year(s) Of Engagement Activity 2022
 
Description Computationally efficient parameter estimation and uncertainty quantification in complex physiological systems 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited keynote lecture given at the 2nd International Conference on Statistics:
Theory and Applications (ICSTA'20),
held as a virtual conference via Zoom, 19-21 August 2020.
Year(s) Of Engagement Activity 2021
URL https://2020.icsta.net/program/
 
Description Interview for BBC Scotland News, 12th November 2020: Colin Berry 
Form Of Engagement Activity A broadcast e.g. TV/radio/film/podcast (other than news/press)
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Colin Berry discussing the effects of long COVID on BBC News on the 12th November, 2020. The purpose was to make the general public aware that some people who become infected with COVID suffer long lasting effects.
Year(s) Of Engagement Activity 2020
URL https://twitter.com/UofGMVLS/status/1326844312525606914
 
Description Plenary talk at the International Forum on coompuational heart modelling 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Up to 100 people attended this event, organized by the North-West Polytechnic University
Year(s) Of Engagement Activity 2021
URL http://xygg.nwpu.edu.cn
 
Description Presentation of GlasgowHeart Platform in SCMR 2021 meeting 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact This is the first time to present the Glasgow heart modelling framework to clinicians in one of the largest meetings in the cardiac magnetic resonance imaging community, SCMR 2021. The audiences consist of clinicians, imaging experts, industry partners, etc. The presentation was given in the first software demo session of the SCMR meeting, which brings the mechanic model one step closer to clinicians. The meeting committee believes that biomechanical biomarkers shall be included in the diagnosis guideline, and encourage more open-source software within the society of cardiac magnetic resonance.
Year(s) Of Engagement Activity 2021
URL https://scmr2021.process.y-congress.com/scientificProcess/Schedule/?setLng=en
 
Description Research visits and seminars at the University of Auckland, Auckland Bioengineering Institute, and Department of Maths, University of Canterbury, Christchurch 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Both students and researchers, including other international visitors, attended the talks during the visits, which sparkled questions and discussion afterwards, and laid the foundation for future collaborations.
Year(s) Of Engagement Activity 2020
 
Description Statistical inference in cardiac mechanics 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact Talk given to the Royal Statistical Society local Glasgow group on 12th March 2020, which sparked questions and discussions afterwards, both over coffee and via follow-up emails.
Year(s) Of Engagement Activity 2020
URL https://sites.google.com/site/rssglasgow/events
 
Description Statistical inference in cardiovascular modelling 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact Three of Dirk Husmeier's PhD students and postdocs gave talks at an event organised by the Royal Statistical Society Glasgow local group on 9 February 2021, with the following titles:
Mihaela Paun
The importance of allowing for model mismatch in cardiovascular modelling
Alan Lazarus
Improving cardio-mechanic parameter estimation by including prior knowledge derived from ex-vivo data
Agnieszka Borowska
Bayesian optimisation for improving accuracy and efficiency of cardio-mechanic parameter estimation
The event was delivered via ZOOM, and lead to a stimulating discussion between speakers and participants (also via Zoom).
Year(s) Of Engagement Activity 2021
URL https://rss.org.uk/training-events/events/statistical-inference-in-cardiovascular-modelling/#eventov...
 
Description Talk at 9th International Biofluid Mechanics And Vascular Mechanobiology Symposium 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Maintain the tradition of excellence and the spirit of the International Bio-fluid Mechanics and Vascular Mechano-Biology Symposia that have evolved to be a unique opportunity for reviewing recent major milestones and achievements in all areas of biofluid mechanics, experimental and computational, from molecule and cell to organ levels and corresponding mechano-biological processes, therapeutics, and cardiovascular devices.

The event gathered scientists, clinicians, and practitioners from around the world to explore and assess the latest frontiers of Bio-Fluid Mechanics and Vascular Mechano-Biology, and set important directions for further research and development, and education. The symposium provided an opportunity for investigators to interact with peers, young and seniors, for development of new collaborations, as well as enhancement of existing ones.
Year(s) Of Engagement Activity 2020
URL https://9thbiofluids.com/
 
Description Twitter Account 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact SofTMech Twitter Account which covers a number of SofTMech and SofTMech related grants. Main purpose to give information on research activities, event including social, advertise job opportunities to a wide audience, and announce graduations, prizes and achievements of the group. in addition to use the re-tweet feature of Twitter to advertise information from partner groups or groups the SofTMech Twitter Account follows. The account has 174 followers and follows 157 other Twitter Account. Impacts arising from the account are quick dissemination of material
Year(s) Of Engagement Activity 2019,2020,2021
URL https://twitter.com/SofTMech