Personalised Model Based Optimal Lead Guidance in Cardiac Resynchronisation Therapy
Lead Research Organisation:
King's College London
Department Name: Imaging & Biomedical Engineering
Abstract
With each heart beat a wave of electrical activation sweeps across the heart stimulating the muscles to contract. In the healthy heart the wave is initiated from many locations across the wall and rapidly activates the whole heart leading to a synchronous, efficient and effective pumping of blood around the body.
In patients suffering dyssynchronous heart failure the activation wave starts on the right hand side of the heart and slowly progresses to the left hand side of the heart. This asynchronous activation pattern causes an asynchronous, inefficient and ineffective pumping of blood. To treat these patients a pacing device is implanted with leads attached to the left and right hand side of the heart. By activating the left and right side of the heart from these two leads the patient's activation pattern can be resynchronised leading to a synchronous and effective contraction. This treatment is referred to as cardiac resynchronisation therapy or CRT.
CRT is an effective treatment in most patients but 30-50% of patients fail to improve or respond to treatment. Due to the invasive nature and cost of the procedure it is undesirable to treat patients who will not respond. Identifying the patients who cannot respond is currently obfuscated by the inability to guarantee optimal treatment in all cases. Hence it is not possible to differentiate from patients that did not respond as they did not receive the optimal treatment from those that were unable to benefit from CRT under any conditions. At present guidelines suggest a "one size fits all" approach to the location of the leads on the patient's heart despite significant evidence that the location of the leads plays a critical role in determining outcome. This indicates that some patients may respond to CRT but only if they receive optimal lead placement.
The aim of this project is to determine the best location to place the pacing lead on the left side of the heart in each individual patient receiving CRT, based on the physiology and pathology of the specific patient's heart. To achieve this aim we propose to use advanced high fidelity and resolution imaging techniques to characterise the shape of the patient's heart, the potential pacing locations, and the location of any dead non-conducting tissue in the heart. We will combine this anatomical information with measurements of electrical activation time to create a biophysical model of the electrical properties of the individual patient's heart.
Using the model we will be able to simulate the activation patterns in the patient's heart for each potential pacing location. In a training data set we will compare the activation patterns at each pacing location with measured pump function, in response to pacing, to identify the activation pattern that best predicts the optimal pacing location.
A prospective clinical study will then be performed where patient specific models will be created for each patient prior to procedure and the optimal pacing site identified. The predictive capacity of the model will then be evaluated when the device is implanted by testing if the model has correctly predicted the optimal pacing location.
The project represents a significant advance for patient specific models - moving from a technique for analysing patient data to a tool for guiding patient treatment. Improving outcomes for CRT patients will reduce morbidity and hospitalisation rates, decrease the financial burden of non-responding patients on the NHS and improve our ability to identify what characteristics determine if a patient will respond to treatment.
In patients suffering dyssynchronous heart failure the activation wave starts on the right hand side of the heart and slowly progresses to the left hand side of the heart. This asynchronous activation pattern causes an asynchronous, inefficient and ineffective pumping of blood. To treat these patients a pacing device is implanted with leads attached to the left and right hand side of the heart. By activating the left and right side of the heart from these two leads the patient's activation pattern can be resynchronised leading to a synchronous and effective contraction. This treatment is referred to as cardiac resynchronisation therapy or CRT.
CRT is an effective treatment in most patients but 30-50% of patients fail to improve or respond to treatment. Due to the invasive nature and cost of the procedure it is undesirable to treat patients who will not respond. Identifying the patients who cannot respond is currently obfuscated by the inability to guarantee optimal treatment in all cases. Hence it is not possible to differentiate from patients that did not respond as they did not receive the optimal treatment from those that were unable to benefit from CRT under any conditions. At present guidelines suggest a "one size fits all" approach to the location of the leads on the patient's heart despite significant evidence that the location of the leads plays a critical role in determining outcome. This indicates that some patients may respond to CRT but only if they receive optimal lead placement.
The aim of this project is to determine the best location to place the pacing lead on the left side of the heart in each individual patient receiving CRT, based on the physiology and pathology of the specific patient's heart. To achieve this aim we propose to use advanced high fidelity and resolution imaging techniques to characterise the shape of the patient's heart, the potential pacing locations, and the location of any dead non-conducting tissue in the heart. We will combine this anatomical information with measurements of electrical activation time to create a biophysical model of the electrical properties of the individual patient's heart.
Using the model we will be able to simulate the activation patterns in the patient's heart for each potential pacing location. In a training data set we will compare the activation patterns at each pacing location with measured pump function, in response to pacing, to identify the activation pattern that best predicts the optimal pacing location.
A prospective clinical study will then be performed where patient specific models will be created for each patient prior to procedure and the optimal pacing site identified. The predictive capacity of the model will then be evaluated when the device is implanted by testing if the model has correctly predicted the optimal pacing location.
The project represents a significant advance for patient specific models - moving from a technique for analysing patient data to a tool for guiding patient treatment. Improving outcomes for CRT patients will reduce morbidity and hospitalisation rates, decrease the financial burden of non-responding patients on the NHS and improve our ability to identify what characteristics determine if a patient will respond to treatment.
Planned Impact
The UK has a long history in developing cardiac electrophysiology models and this proposed research aims to continue this trajectory, moving computational models of cardiac electrophysiology into clinical applications. This project falls within the Clinical Technologies research area and in line with EPSRC guidance is focused heavily on translation to clinical impact and engaging with clinical end users. In light of this, the primary goal of this project is:
To move computational models of the heart from data integration and analysis techniques to predictive tools that directly informs and impacts patient care.
This transformative project will bring computational biophysical models from a position of a novel analysis tool to a clinical application over 4 years. At the end of the project we will have demonstrated the ability of personalised models to guide cardiac resynchronisation therapy (CRT) lead placement. The prospective clinical study, included in this project, will provide the necessary pilot data to underpin the application for funding for the first biophysical patient specific model-guided CRT clinical trial.
Options for delivering CRT are growing with multipolar lead, multi lead pacing, endocardial pacing and combinations of these approaches. Conventional CRT required hundreds of patients to identify the best location to place the lead on average. The identification of activation pattern phenotypes that leads to effective cardiac function will provide an important tool for optimising these novel treatment options.
The ability to predict where to optimally place leads from non-invasive pre-procedural data is expected to improve response to CRT. Increasing the efficacy of CRT will improve patient quality of life and life expectancy while reducing the costs to the NHS of unnecessary implants and increased hospitalisation due to sub-optimal lead positions. Improving response will further isolate the patients that are unable to respond, greatly facilitating the identification of patient phenotypes that prohibit them benefiting from CRT aiding in improved patient selection.
The framework for creating validated patient specific models of cardiac electrophysiology is not limited to informing CRT treatment. Adapting this approach has the potential to be used for modelling the atria to inform atrial arrhythmias, for simulating activation patterns to guide ventricular tachycardia ablations or for interpreting complex activation patterns in congenital heart defect patients.
A by-product of developing patent specific models is the creation of a growing virtual cohort of patients with validated models of activation. We have previously used a model of a single patient case to evaluate pacing strategies and efficacy in the presence of scar for a St. Jude multipolar lead (Niederer et al., 2012) and are currently working with Boston Scientific to evaluate the electrode spacing in their leads. The development of a larger cohort would provide a resource for performing further commercial or clinical studies to evaluate novel lead technologies and pacing strategies characterising both the mean and the variation in the expected response.
To move computational models of the heart from data integration and analysis techniques to predictive tools that directly informs and impacts patient care.
This transformative project will bring computational biophysical models from a position of a novel analysis tool to a clinical application over 4 years. At the end of the project we will have demonstrated the ability of personalised models to guide cardiac resynchronisation therapy (CRT) lead placement. The prospective clinical study, included in this project, will provide the necessary pilot data to underpin the application for funding for the first biophysical patient specific model-guided CRT clinical trial.
Options for delivering CRT are growing with multipolar lead, multi lead pacing, endocardial pacing and combinations of these approaches. Conventional CRT required hundreds of patients to identify the best location to place the lead on average. The identification of activation pattern phenotypes that leads to effective cardiac function will provide an important tool for optimising these novel treatment options.
The ability to predict where to optimally place leads from non-invasive pre-procedural data is expected to improve response to CRT. Increasing the efficacy of CRT will improve patient quality of life and life expectancy while reducing the costs to the NHS of unnecessary implants and increased hospitalisation due to sub-optimal lead positions. Improving response will further isolate the patients that are unable to respond, greatly facilitating the identification of patient phenotypes that prohibit them benefiting from CRT aiding in improved patient selection.
The framework for creating validated patient specific models of cardiac electrophysiology is not limited to informing CRT treatment. Adapting this approach has the potential to be used for modelling the atria to inform atrial arrhythmias, for simulating activation patterns to guide ventricular tachycardia ablations or for interpreting complex activation patterns in congenital heart defect patients.
A by-product of developing patent specific models is the creation of a growing virtual cohort of patients with validated models of activation. We have previously used a model of a single patient case to evaluate pacing strategies and efficacy in the presence of scar for a St. Jude multipolar lead (Niederer et al., 2012) and are currently working with Boston Scientific to evaluate the electrode spacing in their leads. The development of a larger cohort would provide a resource for performing further commercial or clinical studies to evaluate novel lead technologies and pacing strategies characterising both the mean and the variation in the expected response.
Publications
![publication icon](/resources/img/placeholder-60x60.png)
Crozier A
(2016)
Image-Based Personalization of Cardiac Anatomy for Coupled Electromechanical Modeling.
in Annals of biomedical engineering
![publication icon](/resources/img/placeholder-60x60.png)
Roney CH
(2021)
Constructing a Human Atrial Fibre Atlas.
in Annals of biomedical engineering
![publication icon](/resources/img/placeholder-60x60.png)
Kuepfer L
(2017)
A model-based assay design to reproduce in vivo patterns of acute drug-induced toxicity
in Archives of Toxicology
![publication icon](/resources/img/placeholder-60x60.png)
Wijesuriya N
(2023)
Leadless Pacing: Therapy, Challenges and Novelties.
in Arrhythmia & electrophysiology review
![publication icon](/resources/img/placeholder-60x60.png)
Augustin CM
(2020)
The impact of wall thickness and curvature on wall stress in patient-specific electromechanical models of the left atrium.
in Biomechanics and modeling in mechanobiology
![publication icon](/resources/img/placeholder-60x60.png)
Nasopoulou A
(2017)
Improved identifiability of myocardial material parameters by an energy-based cost function.
in Biomechanics and modeling in mechanobiology
![publication icon](/resources/img/placeholder-60x60.png)
Lee AWC
(2019)
Sex-Dependent QRS Guidelines for Cardiac Resynchronization Therapy Using Computer Model Predictions.
in Biophysical journal
![publication icon](/resources/img/placeholder-60x60.png)
Lewalle A
(2019)
Balance of Active, Passive, and Anatomical Cardiac Properties in Doxorubicin-Induced Heart Failure.
in Biophysical journal
![publication icon](/resources/img/placeholder-60x60.png)
Land Sander
(2016)
Investigating Cooperativity using a New Biophysically Detailed Cardiac Contraction Model
in BIOPHYSICAL JOURNAL
![publication icon](/resources/img/placeholder-60x60.png)
Fernandez-Chas M
(2018)
Mechanism of doxorubicin cardiotoxicity evaluated by integrating multiple molecular effects into a biophysical model.
in British journal of pharmacology
![publication icon](/resources/img/placeholder-60x60.png)
Pereira H
(2019)
Comparison of Echocardiographic and Electrocardiographic Mapping for Cardiac Resynchronisation Therapy Optimisation.
in Cardiology research and practice
![publication icon](/resources/img/placeholder-60x60.png)
Pereira H
(2019)
Erratum to "Comparison of Echocardiographic and Electrocardiographic Mapping for Cardiac Resynchronisation Therapy Optimisation".
in Cardiology research and practice
![publication icon](/resources/img/placeholder-60x60.png)
Shattock M
(2017)
Restitution slope is principally determined by steady-state action potential duration
in Cardiovascular Research
![publication icon](/resources/img/placeholder-60x60.png)
Bapat V
(2015)
Factors influencing left ventricular outflow tract obstruction following a mitral valve-in-valve or valve-in-ring procedure, part 1.
in Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
![publication icon](/resources/img/placeholder-60x60.png)
Hyde Eoin R.
(2015)
Early Stimulation of Fast-Conducting Endocardial Tissue Underlies Improvements in Endocardial Pacing
in CIRCULATION
![publication icon](/resources/img/placeholder-60x60.png)
Hyde ER
(2015)
Beneficial Effect on Cardiac Resynchronization From Left Ventricular Endocardial Pacing Is Mediated by Early Access to High Conduction Velocity Tissue: Electrophysiological Simulation Study.
in Circulation. Arrhythmia and electrophysiology
![publication icon](/resources/img/placeholder-60x60.png)
Roney CH
(2022)
Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.
in Circulation. Arrhythmia and electrophysiology
![publication icon](/resources/img/placeholder-60x60.png)
Niederer S
(2015)
The impact of beat-to-beat variability in optimising the acute hemodynamic response in cardiac resynchronisation therapy.
in Clinical trials and regulatory science in cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Solís-Lemus JA
(2023)
Evaluation of an open-source pipeline to create patient-specific left atrial models: A reproducibility study.
in Computers in biology and medicine
![publication icon](/resources/img/placeholder-60x60.png)
Roney CH
(2019)
A technique for measuring anisotropy in atrial conduction to estimate conduction velocity and atrial fibre direction.
in Computers in biology and medicine
![publication icon](/resources/img/placeholder-60x60.png)
Fassina D
(2023)
Assessing the arrhythmogenic risk of engineered heart tissue patches through in silico application on infarcted ventricle models.
in Computers in biology and medicine
![publication icon](/resources/img/placeholder-60x60.png)
Ribba B
(2017)
Methodologies for Quantitative Systems Pharmacology (QSP) Models: Design and Estimation.
in CPT: pharmacometrics & systems pharmacology
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![publication icon](/resources/img/placeholder-60x60.png)
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Aziz W
(2019)
Emerging role of cardiac computed tomography in heart failure.
in ESC heart failure
![publication icon](/resources/img/placeholder-60x60.png)
Williams SE
(2017)
Simultaneous display of multiple three-dimensional electrophysiological datasets (dot mapping).
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Crozier A
(2016)
Analysis of lead placement optimization metrics in cardiac resynchronization therapy with computational modelling.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Roney CH
(2018)
Determinants of new wavefront locations in cholinergic atrial fibrillation.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Williams SE
(2018)
Local activation time sampling density for atrial tachycardia contact mapping: how much is enough?
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Sidhu BS
(2020)
Combined computed tomographic perfusion and mechanics with predicted activation pattern can successfully guide implantation of a wireless endocardial pacing system.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Whitaker J
(2016)
The role of myocardial wall thickness in atrial arrhythmogenesis.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Bishop M
(2016)
Three-dimensional atrial wall thickness maps to inform catheter ablation procedures for atrial fibrillation.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Niederer SA
(2018)
Is the rapidly paced pig the optimal model for endocardial cardiac resynchronization therapy?
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Remme EW
(2016)
Factors determining the magnitude of the pre-ejection leftward septal motion in left bundle branch block.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
Sieniewicz BJ
(2018)
Electrical latency predicts the optimal left ventricular endocardial pacing site: results from a multicentre international registry.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
O'Neill L
(2019)
Pulmonary vein encirclement using an Ablation Index-guided point-by-point workflow: cardiovascular magnetic resonance assessment of left atrial scar formation.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
![publication icon](/resources/img/placeholder-60x60.png)
De Vecchi A.
(2016)
Computational modelling for personalisation of treatment in transcatheter mitral valve replacement
in EUROPEAN HEART JOURNAL
![publication icon](/resources/img/placeholder-60x60.png)
Antoniadis AP
(2017)
A comparison of the different features of quadripolar left ventricular pacing leads to deliver cardiac resynchronization therapy.
in Expert review of medical devices
![publication icon](/resources/img/placeholder-60x60.png)
Sieniewicz BJ
(2018)
Optimal site selection and image fusion guidance technology to facilitate cardiac resynchronization therapy.
in Expert review of medical devices
![publication icon](/resources/img/placeholder-60x60.png)
Dovmark TH
(2018)
Normoxic cells remotely regulate the acid-base balance of cells at the hypoxic core of connexin-coupled tumor growths.
in FASEB journal : official publication of the Federation of American Societies for Experimental Biology
![publication icon](/resources/img/placeholder-60x60.png)
Wijesuriya N
(2023)
The role of conduction system pacing in patients with atrial fibrillation.
in Frontiers in cardiovascular medicine
![publication icon](/resources/img/placeholder-60x60.png)
Mendonca Costa C
(2018)
Modeling the Electrophysiological Properties of the Infarct Border Zone.
in Frontiers in physiology
![publication icon](/resources/img/placeholder-60x60.png)
Roney CH
(2020)
In silico Comparison of Left Atrial Ablation Techniques That Target the Anatomical, Structural, and Electrical Substrates of Atrial Fibrillation.
in Frontiers in physiology
![publication icon](/resources/img/placeholder-60x60.png)
Lewalle A
(2018)
Decreasing Compensatory Ability of Concentric Ventricular Hypertrophy in Aortic-Banded Rat Hearts
in Frontiers in Physiology
![publication icon](/resources/img/placeholder-60x60.png)
Wijesuriya N
(2022)
Leadless Left Bundle Branch Area Pacing in Cardiac Resynchronisation Therapy: Advances, Challenges and Future Directions.
in Frontiers in physiology
![publication icon](/resources/img/placeholder-60x60.png)
![publication icon](/resources/img/placeholder-60x60.png)
![publication icon](/resources/img/placeholder-60x60.png)
![publication icon](/resources/img/placeholder-60x60.png)
Wijesuriya N
(2022)
Leadless left ventricular endocardial pacing for cardiac resynchronization therapy: A systematic review and meta-analysis.
in Heart rhythm
Description | Patients with heart failure can receive devices that pace their heart to improve its output. However, the best location to pace the heart is not known. We have developed a platform that simulates the activation pattern of the heart and how this changes with pacing to work out where best to pace the heart in patients with heart failure. |
Exploitation Route | We have been funded by the NIHR to perform a clinical trial with Siemens. If successful we will discuss licencing options with Siemens. |
Sectors | Healthcare |
Description | Our image analysis and simulation software is being used to identify lead placements in heart failure patients. This may improve patient outcomes. We will know when the trial is completed. Update: We have now completed our pilot clinical trial where we were able to show that CT guidance improved CRT upgrade procedures. |
Sector | Healthcare |
Impact Types | Societal |
Description | Atrial cardiac magnetic resonance imaging in patients with embolic stroke of unknown source without documented atrial fibrillation |
Amount | £184,072 (GBP) |
Organisation | British Heart Foundation (BHF) |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 10/2019 |
End | 10/2021 |
Description | BHF project grant |
Amount | £170,000 (GBP) |
Organisation | British Heart Foundation (BHF) |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 04/2016 |
End | 03/2019 |
Description | Development of a real time, patient-specific computational catheter ablation guidance tool utilising personalised structural and functional measurements |
Amount | £354,064 (GBP) |
Funding ID | 213342/Z/18/Z |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 09/2019 |
End | 09/2022 |
Description | Identifying the optimal location for LV endocardial lead placement in CRT delivery using cardiac magnetic resonance imaging, acute hemodynamic response and non-invasive electro-anatomical mapping |
Amount | £183,756 (GBP) |
Funding ID | PG/16/108/32593 |
Organisation | British Heart Foundation (BHF) |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2017 |
End | 12/2018 |
Description | Image optimization and guidance for next generation wireless endocardial cardiac resynchronisation therapy. |
Amount | £646,103 (GBP) |
Funding ID | II-LB-1116-20001 |
Organisation | National Institute for Health Research |
Sector | Public |
Country | United Kingdom |
Start | 08/2018 |
End | 01/2021 |
Description | Responsive Mode Project Grant |
Amount | £1,200,000 (GBP) |
Funding ID | EP/P01268X/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2017 |
End | 04/2021 |
Description | na |
Amount | £35,000 (GBP) |
Organisation | St. Jude Medical |
Sector | Private |
Country | United States |
Start | 10/2016 |
End | 09/2020 |
Title | A Publicly Available Virtual Cohort of Four-chamber Heart Meshes for Cardiac Electro-mechanics Simulations |
Description | Motivation: Computational models of the heart are increasingly being used in the development of devices, patient diagnosis and therapy guidance. While software techniques have been developed for simulating single hearts, there remain significant challenges in simulating cohorts of virtual hearts from multiple patients. Dataset Description: We present the first database of four-chamber heart models suitable for electro-mechanical simulations. Our database consists of twenty-four four-chamber heart models generated from end-diastolic CT acquired from heart failure patients recruited for cardiac resynchronization therapy upgrade. We also provide a higher resolution version for each of the twenty-four meshes. We segmented end-diastolic CT. The segmentation was then upsampled and smoothed. The final multi-label segmentation was used to generate a tetrahedral mesh. The resulting meshes had an average edge length of 1.1mm. The elements of all the twenty-four meshes are labelled as follows: 1) Left ventricle myocardium 2) Right ventricle myocardium 3) Left atrium myocardium 4) Right atrium myocardium 5) Aorta wall 6) Pulmonary artery wall 7) Left atrium appendage ring 8) Left superior pulmonary vein ring 9) Left inferior pulmonary vein ring 10) Right inferior pulmonary vein ring 11) Right superior pulmonary vein ring 12) Superior vena cava ring 13) Inferior vena cava ring 14) Mitral valve plane 15) Tricuspid valve plane 16) Aortic valve plane 17) Pulmonary valve plane 18) Left atrial appendage valve plane 19) Left superior pulmonary vein valve plane 20) Left inferior pulmonary vein valve plane 21) Right inferior pulmonary vein valve plane 22) Right superior pulmonary vein valve plane 23) Superior vena cava valve plane 24) Inferior vena cava valve plane. Ventricular fibres were generated using a rule-based method, with a fibre orientation varying transmurally from endocardium to epicardium from 80° to -60°, respectively. We defined a system of universal ventricular coordinates on the meshes, see Figure 1B: an apico-basal coordinate varying continuously from 0 at the apex to 1 at the base; a transmural coordinate varying continuously from 0 at the endocardium to 1 at the epicardium; a rotational coordinate varying continuously from - p at the left ventricular free wall, 0 at the septum and then back to + p at the left ventricular free wall; intra-ventricular coordinate defined at -1 at the left ventricle and +1 at the right ventricle. This coordinate system was assigned to the ventricles in the four-chamber meshes and all the other labels were assigned with -100. We also refined each mesh from 1.1mm resolution down to 0.39mm resolution. Each refined mesh has tags defined on its elements (same numbering as described above) and ventricular fibres. Database format: We provide a zipped folder for each mesh. Each folder contains the coarse and the finer versions of the same mesh. All twenty-four 1mm-meshes are supplied in case format, readable with paraview. All binary files containing the meshes data (ens and geo formats) are provided within the zipped folder. Points coordinates are given in mm. Element tags are assigned to the elements of the mesh as well as fibres and sheet directions. Fibres and sheet directions are assigned to the ventricles according to a rule-based method, while non-ventricular elements are assigned with default vectors [1; 0; 0] and [0; 1; 0]. UVCs are assigned to the nodes of the meshes. We also provide the location of the cardiac resynchronisation therapy right-ventricular electrode used to initiate ventricular excitation. This is given as a label on the nodes called electrode endo rv, which is 1 at the stimulated nodes. Finer meshes are provided in vtk format, also readable in paraview. For these meshes, we provide element tags, fibres and sheet directions on the ventricles, all in the same file. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://zenodo.org/record/3890033 |
Title | Constructing a Human Atrial Fibre Atlas, Roney et al. |
Description | Background: Atrial anisotropy affects electrical propagation patterns, anchor locations of atrial reentrant drivers, and atrial mechanics. However, patient-specific atrial fibre fields and anisotropy measurements are not currently available, and consequently assigning fibre fields to atrial models is challenging. We aimed to construct an atrial fibre atlas from a high-resolution DTMRI dataset that optimally reproduces electrophysiology simulation predictions corresponding to patient-specific fibre fields, and to develop a methodology for automatically assigning fibres to patient-specific anatomies. Dataset Description: We include endocardial and epicardial left and right atrial surfaces for each of the 7 anatomies included in our study (Constructing a Human Atrial Fibre Atlas, ABME, 2020), together with their fibre fields. We also include the average fibre field for each of the atrial surfaces displayed on anatomy number 6 (named *_A). For each of the surfaces, we also include universal atrial coordinate fields alpha and beta, which are a lateral-septal coordinate and posterior-anterior coordinate for the LA (IVC-SVC coordinate for the RA). More details on the coordinate construction are given in our manuscript and https://www.ncbi.nlm.nih.gov/pubmed/31026761. These coordinates can be used for registering datasets. These meshes are in vtk format, consisting of the nodes, triangular elements, the atrial coordinate fields defined on the nodes, and the fibre field defined on the elements. We have also included mesh files for the Cardiac Arrhythmia Research Package simulator. These are a list of nodal coordinates (.pts file), a list of triangular elements (.elem file), and a fibre file (.lon). More details on this file format and the carpentry simulator are available at: https://carpentry.medunigraz.at/carputils/index.html. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://zenodo.org/record/3764916 |
Title | Constructing a Human Atrial Fibre Atlas, Roney et al. |
Description | Background: Atrial anisotropy affects electrical propagation patterns, anchor locations of atrial reentrant drivers, and atrial mechanics. However, patient-specific atrial fibre fields and anisotropy measurements are not currently available, and consequently assigning fibre fields to atrial models is challenging. We aimed to construct an atrial fibre atlas from a high-resolution DTMRI dataset that optimally reproduces electrophysiology simulation predictions corresponding to patient-specific fibre fields, and to develop a methodology for automatically assigning fibres to patient-specific anatomies. Dataset Description: We include endocardial and epicardial left and right atrial surfaces for each of the 7 anatomies included in our study (Constructing a Human Atrial Fibre Atlas, ABME, 2020), together with their fibre fields. We also include the average fibre field for each of the atrial surfaces displayed on anatomy number 6 (named *_A). For each of the surfaces, we also include universal atrial coordinate fields alpha and beta, which are a lateral-septal coordinate and posterior-anterior coordinate for the LA (IVC-SVC coordinate for the RA). More details on the coordinate construction are given in our manuscript and https://www.ncbi.nlm.nih.gov/pubmed/31026761. These coordinates can be used for registering datasets. These meshes are in vtk format, consisting of the nodes, triangular elements, the atrial coordinate fields defined on the nodes, and the fibre field defined on the elements. We have also included mesh files for the Cardiac Arrhythmia Research Package simulator. These are a list of nodal coordinates (.pts file), a list of triangular elements (.elem file), and a fibre file (.lon). More details on this file format and the carpentry simulator are available at: https://carpentry.medunigraz.at/carputils/index.html. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://zenodo.org/record/3764917 |
Description | Graz |
Organisation | Medical University of Graz |
Country | Austria |
Sector | Academic/University |
PI Contribution | Technical support and involvement in supervision of PhD Student |
Collaborator Contribution | Development of computer models that are shared for joint projects |
Impact | Joint publications and both partners have been listed as collaborators on respective grants |
Start Year | 2008 |
Description | Graz |
Organisation | Medical University of Graz |
Country | Austria |
Sector | Academic/University |
PI Contribution | Technical support and involvement in supervision of PhD Student |
Collaborator Contribution | Development of computer models that are shared for joint projects |
Impact | Joint publications and both partners have been listed as collaborators on respective grants |
Start Year | 2008 |
Description | Turing |
Organisation | Alan Turing Institute |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We have worked with researchers at the Turing (Professor Chris Oates, Professor Mark Girolami and Jon Cockayne) on this BHF project. |
Collaborator Contribution | They have employed the people we are collaborating with. |
Impact | We received a BHF-Turing grant and a BHF programme grant. We have submitted two conference abstracts and have two papers in draft. |
Start Year | 2018 |
Description | University of Oxford |
Organisation | University of Oxford |
Department | Oxford Hub |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I have worked with Professor Pawel Swietach at the University of Oxford to write grants to Qatar as well as the BHF-Turing program. (these were both funded). |
Collaborator Contribution | We provide modelling advice to Pawel and perform simulations. Pawel provides us with experimental data. |
Impact | we have published papers and written grants gtogether |
Start Year | 2010 |
Title | Image guided CRT upgrade guidance system |
Description | We created a software for measuring ventricle mechanics from cardiac CT and used this guide the location to place pacing leads in a patient undergoing a CRT upgrade procedure. We applied this in a prospective pilot study, where we showed that guidance improved outcomes. We now need to consider how / if to move this forward. We performed a pilot clinical study, this is a clinical trial of sorts but is not a randomized registered clinical trial. |
Type | Diagnostic Tool - Imaging |
Current Stage Of Development | Early clinical assessment |
Year Development Stage Completed | 2018 |
Development Status | On hold |
Impact | We have had attracted additional funding from industry to use the ventricle motion maps created when analysing ventricle motion in these patients in virtual clinical studies evaluating novel devices in a virtual patient cohort. |
Title | CemrgApp: An interactive medical imaging application with image processing, computer vision, and machine learning toolkits for cardiovascular research. |
Description | The Cardiac Electro-Mechanics Research Group Application (CemrgApp) is a platform with custom image processing and computer vision toolkits for applying statistical, machine learning, and simulation approaches to cardiovascular data. CemrgApp provides an integrated environment, where cardiac data visualisation and workflow prototyping are presented through a common user friendly graphical interface. CemrgApp at present supports: |
Type Of Technology | Software |
Year Produced | 2019 |
Open Source License? | Yes |
Impact | CemrgApp has provided a common platform for medical image analysts and cardiologists to cooperate on various applications, with a focus on translation. It has led to a retrospective and now preprocedural planning in a prospective clinical trial (Fire and Ice, Gov Identifier: NCT03706677), provided the foundation for research contracts with industrial partners (Medtronic, EBR, Abbott), and contributed to an EPSRC project grant, NIH R01, ERC fellowship, BHF fellowship, MRC fellowship, BHF programme grant, and Wellcome programme, building a large cohort of patient-specific atrial models for computational modelling studies. The app has also delivered ad hoc solutions to international cardiac research groups based at Stanford's mechanical engineering department, the Catholic University of Louvain in Belgium, the Amsterdam UMC, bioengineers at the University of Washington, cardiologists at the University of Oxford, and the department of medical biophysics at the University of Toronto. Research software from the AI centre has also been planned to become available in the app. Overall, CemrgApp has provided support for more than 30 journal, conference, and abstract publications. |
Description | : A Virtual Cohort of Heart Failure Patients Four-chamber Heart Meshes for Cardiac Electro-mechanics Simulations |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Postgraduate students |
Results and Impact | • Oral presentation: A Virtual Cohort of Heart Failure Patients Four-chamber Heart Meshes for Cardiac Electro-mechanics Simulations. BioMedEng19, Imperial College London, September 5-6, 2019. |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.biomedeng19.com/ |
Description | A Virtual Cohort of Heart Failure Patients Four-chamber Heart Meshes for Cardiac Electro-mechanics Simulations |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | • Poster presentation: A Virtual Cohort of Heart Failure Patients Four-chamber Heart Meshes for Cardiac Electro-mechanics Simulations. COMBINE 2019, Heidelberg, July 15-19, 2019. |
Year(s) Of Engagement Activity | 2019 |
URL | http://co.mbine.org/events/COMBINE_2019 |
Description | A Virtual Cohort of Heart Failure Patients Four-chamber Heart Meshes for Cardiac Electro-mechanics Simulations. Post-graduate divisional symposium, |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | PhD student presentation on CRT modelling |
Year(s) Of Engagement Activity | 2019 |
Description | A Virtual Cohort of Heart Failure Patients Four-chamber Heart Meshes for Cardiac Electro-mechanics Simulations. The Fickle Heart: Uncertanty Quantification for Cardiac Models, |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Postgraduate students |
Results and Impact | • Poster presentation: A Virtual Cohort of Heart Failure Patients Four-chamber Heart Meshes for Cardiac Electro-mechanics Simulations. The Fickle Heart: Uncertanty Quantification for Cardiac Models, Cambridge, June 5-7, 2019. |
Year(s) Of Engagement Activity | 2019 |
Description | Invited talk Roche |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Roche were interested in biophysical models and invited me out to give a presentation |
Year(s) Of Engagement Activity | 2016 |
Description | Isaac Newton Meeting |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Organised meeting and presentation at Isaac Newton Meeting |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.newton.ac.uk/event/fht |
Description | John Hopkins University |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Invited talk John Hopkins University |
Year(s) Of Engagement Activity | 2019 |
URL | https://icm.jhu.edu/events/steven-niederer-kings-college-london-applying-cardiac-modelling-to-study-... |
Description | Kings Christmas lecture to high school students |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | KCL run a series of outreach Christmas lecturers. I was asked to give the presentation this year on modelling the heart. The result was also on twitter and the talk was posted on youtube. |
Year(s) Of Engagement Activity | 2015 |
URL | https://www.youtube.com/watch?v=8Jcr5Ft6OaE |
Description | Lange Symposium |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited presentation at Lange Symposium |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.dhzb.de/fileadmin/user_upload/relaunch/02_medizin_pflege/AHF/Langesymposium/2019/Program... |
Description | MRC Harwell |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | Presented at MRC Harwell seminar series |
Year(s) Of Engagement Activity | 2015 |
Description | Mox invited talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | invited presentation to numerics group in Milan |
Year(s) Of Engagement Activity | 2019 |
URL | https://mox.polimi.it/elenco-seminari/?id_evento=1919&t=763721&ricerca= |
Description | Murdoch Children's Research Institute |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Invited presentation at Murdoch Children's Research Institute, |
Year(s) Of Engagement Activity | 2019 |
Description | Oslo University Hospital |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Invited presentation |
Year(s) Of Engagement Activity | 2020 |
Description | Oxford talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Postgraduate students |
Results and Impact | Invited talk at physiology department oxford |
Year(s) Of Engagement Activity | 2019 |
Description | Pfizer |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Invited talk at Pfizer |
Year(s) Of Engagement Activity | 2019 |
Description | Philips |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Invited talk at Philips to discuss how we are developing digital twins. |
Year(s) Of Engagement Activity | 2019 |
Description | Presentation to Avicenna Alliance |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | The Avicenna is a professional organisation that promotes the use of computer models in clinical and pharmaceutical applications. |
Year(s) Of Engagement Activity | 2016 |
Description | Presentation to staff from UK trade consolutes |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | I gave a presentation on the technology we are developing to model the heart to trade advisor from UK embassies from across the globe |
Year(s) Of Engagement Activity | 2017 |
Description | Prince Alfred Hospital |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited presentation at Prince Alfred Hospital |
Year(s) Of Engagement Activity | 2019 |
Description | Seminar Estonia |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Presented at seminar series |
Year(s) Of Engagement Activity | 2015 |
Description | Simula talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | I gave a presentation at Simula a norwegian research institute to about 40+ researchers. |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.simula.no/simula-seminars-scientific-computing |
Description | St Vincent's Hospital |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited talk at St Vincent's Hospital |
Year(s) Of Engagement Activity | 2019 |
Description | TRM Lugano |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited presentation to biomedical engineering and clinical research workshop. |
Year(s) Of Engagement Activity | 2019 |
Description | UCSD |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Invited presentation at UCSD Biomedical Engineering department |
Year(s) Of Engagement Activity | 2019 |
Description | University of Auckland |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Invited presentation at University of Auckland |
Year(s) Of Engagement Activity | 2019 |
Description | University of Eindhoven Science day |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Annual Science day key note presentation |
Year(s) Of Engagement Activity | 2015 |
Description | Victor Chang Sydney |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Invited presentation at victor chang institute |
Year(s) Of Engagement Activity | 2019 |
Description | Yale |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Invited presentation at the Biomedical Engineering deparmtent in Yale |
Year(s) Of Engagement Activity | 2019 |
Description | Youtube |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | youtube interview for Newton Institute meeting |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.youtube.com/watch?v=MSGaojtXcEA |