Personalised thermal-fluid models for planning catheter ablation therapy for atrial arrhythmia

Lead Research Organisation: King's College London
Department Name: Imaging & Biomedical Engineering

Abstract

In recent years, significant advances in clinical imaging have provided a wealth of detailed information on the internal function and anatomy of the human body. Fundamental questions on the progression of diseases and on their treatment can be addressed using this information. A highly promising avenue for the exploitation of this potential is the creation of biophysical computer models of the organs based on these state-of-the-art data. These models combine the available clinical information in a consistent mathematical framework that can be tailored to the specific characteristics of the individual patient. They can be used to predict the complex internal dynamics of a working organ, as well as its diseases' mechanisms, providing a powerful tool to personalise treatment.

This project will create a toolbox to generate personalised models of flow and temperature in the heart. Specifically, this platform will be designed to simulate atrial fibrillation, a disease that commonly affects one chamber of the heart (the left atrium), and its treatment, known as catheter ablation. When the left atrium is in fibrillation, the wall stops contracting and starts quivering. This behavior is triggered by abnormal electrical impulses at a specific site, called the driver site. As a result, the motion of the blood flow in the atrium is weakened. This abnormal behavior can reduce the supply of blood to the body. Catheter ablation consists in burning the driver site in the atrial wall by applying heat via a catheter, in order to suppress the abnormal electrical impulses and restore contraction. However, patient outcomes are suboptimal and reoccurrence of fibrillation after a single procedure is high. This is due to the strong dependence of this treatment effectiveness on patient-specific factors that are difficult to quantify from the imaging data alone.

The proposed research will focus on improving outcomes using personalised computer models. Previous pilot work has proven the potential of this type of approach in predicting the size of the lesion caused by ablation. The overall goal of this project is to create physiologically accurate, personalised models to inform the choice of the ablation parameters such as the catheter voltage and the ablation time. This modelling toolbox will then be applied to a cohort of patients with the aim of increasing significantly the clinical impact of the approach. The research will be undertaken at St Thomas' Hospital, one of the biggest UK referral centres for atrial fibrillation. Given the multi-disciplinary aspect of the project, internal collaborations have been set up with groups within different areas of expertise. Clinical guidance and patient datasets will be provided by Dr M. O'Neill and his team, the Cardiac Arrhythmia Research Group, while Dr O. Aslanidi and Dr D. Nordsletten will provide expertise in scar and blood flow modelling, respectively. This work will therefore generate impact in different areas, from clinical research to mathematical modelling. Ultimately, however, the beneficiaries of the proposed project are the patients themselves, who will benefit from a personalised and more efficient approach to catheter ablation.

Planned Impact

The main goal of the proposed project is to create and apply an integrated imaging-modelling toolbox to improve ablation therapy in atrial arrhythmias. In the first part of the project, the focus will be on developing and testing personalised models of the thermal and fluid dynamics in the left atrium. In the second stage, the validated models will be applied to a cohort of patients to improve our understanding of the pathophysiology of a common atrial arrhythmia, i.e. atrial fibrillation, and of its treatment. In particular, we will simulate the effect of radiofrequency catheter ablation therapy for each individual patient in their personal clinical context. We envisage that this work will have a strong potential to benefit end-users such as clinicians, patients and the NHS, as well as the research community.
For the clinician, placing the focus on a patient-specific approach is a fundamental advance in the clinical decision-making process: it allows to improve significantly the diagnosis potential in diseases like atrial fibrillation, where the heterogeneity of patient outcomes has been demonstrated to be highly dependent on patient-specific factors. The proposed research will inform the choice of ablation strategy by providing insight into the effect of settings such as catheter voltage and contact time on the treatment outcomes.
For the patient, a customised treatment strategy will primarily contribute to enhance the quality and quantity of life by addressing specific needs. These include reducing the incidence of re-interventions from inaccurate patient assessments and thus the re-hospitalisation incidence. Developing more effective ablation stretegies will also put less strain on the patient. Further, improvements in home monitoring and care have been demonstrated to help increasing the event-free survival rates: a better awareness of the disease's dynamics, and of its potentially fatal consequences will therefore benefit a wider public, including the patients themselves and their families, and has the potential to make a social impact.
For the NHS, faster procedures will mean more efficient use of time and infrastructures, enabling improved scheduling and effectiveness of service. Reduced re-intervention rates will also have a direct economic impact. Further, a more complete understanding of the diseases' mechanisms will facilitate and speed up new clinical research and, consequently, improve the level of specialists training.
The proposed research will also benefit the research community by placing emphasis on the synergy between different scientific areas, from computing to imaging sciences. Computer modelling relies on the quality of the clinical imaging datasets: to achieve impact it is essential that the patient data are collected following standardised procedures and organised in databases that can be easily accessed by both the modelling and the clinical community. The models and the imaging protocols used throughout this project will be made publicly available via the King's College database (http://amdb.isd.kcl.ac.uk) to raise clinical awareness of this matter, paving the way for future exploitation of the data and progression of research.
 
Description Atrial fibrillation (AF) is the most common cardiac arrhythmia and carries high risks of stroke due to abnormal blood flow conditions that are prone to thrombus formation. The treatment of choice for patients who do not respond to antiarrhythmic drug therapy is radiofrequency catheter ablation (RCA), which burns the tissue areas where the arrhythmia originates to isolate them and restore sinus rhythm (SR). Our EPSRC project developed personalised biophysical models of blood flow in the left atrium (LA) to study the effects of RCA settings (site, temperature, time) on the lesion formation, to improve procedural outcomes.
The project successfully delivered on the proposed objectives: (1) creation of an image-based modelling toolbox for patient-specific simulations of flow and temperature in the LA; (2) its application to model AF patients pre- and post- RCA.
Our modelling toolbox has been developed to include:
a) Advanced image processing for model personalisation by deriving patient-specific anatomy and flow boundary conditions from Cine MRI and Doppler ultrasound data.
b) Whole-cavity 3D blood flow modelling using a finite-element based Navier-Stokes solver.
c) Temperature modelling in blood and tissue during RCA, using the modified Pennes bioheat equation with an added convection term to account for the blood flow.
d) Particle tracking algorithm to track blood particles during the cardiac cycle and classify them into four components based on their residence time in the LA.
The models were then applied to a cohort of patients. While focusing on lesion formation for varying atrial wall thickness (AWT), this study also showed that varying the RCA site position can lead to increases in the maximum blood temperature of up to 31%. This is particularly relevant in regions with low blood velocity such as the Left Atrial Appendage (LAA), which is predominantly occupied by flow with high residence time in the cavity, even after RCA, and is thus prone to prothrombotic blood stasis. Specifically, when RCA is done near this critical region, the blood temperature reaches the threshold for plasma aggregation in stationary blood inside the LAA and the coagulation risk threshold near the RCA site. High residence times and blood temperatures and low flow velocities are all strong predisposing factors to thrombus formation. This key result prompted clinical questions on the potentially deleterious effects of RCA on the already highly thrombogenic substrate of AF, whose mechanisms are also incompletely understood.
Exploitation Route As the prevalence of AF is predicted to rise substantially in the next years, alongside with the number of patients receiving RCA, the associated stroke risks will carry a significant burden on the healthcare system. The results from our study can be taken forward to address the clinical need for a better stroke risk stratification for AF patients, which inevitably relies on a better understanding of the patient-specific dynamics of blood flow and thrombus formation to help determine the best course of action for antithrombotic therapy. This is particularly relevant to patients who might be inaccurately considered at low stroke risk after RCA and not be prescribed anticoagulants. To address this issue, our current technlogy can be further developed to include a mathematical model of thrombus formation. This enhanced toolbox may then be applied to AF patients to understand the mechanistic links between blood flow dynamics and a prothrombotic state, both in AF before RCA and in normal rhythm after RCA
Sectors Healthcare,Pharmaceuticals and Medical Biotechnology

 
Description As the project is still ongoing the findings have not been used yet. However, Abbott Laboratories, a multinational healthcare company has recently started collaborating with one of our collaborators (Dr Oleg Aslanidi) on the integration of the novel information generated by the personalised models into their EnSite Precision™ Cardiac Mapping System, one of the most common guidance systems for catheter ablation procedures, which is used in the clinics worldwide. The aim of this integration is to use the modelling data to assess the ablation injury, provide thrombus location maps, and update stroke scores on a patient-specific basis. If successful, this integration will benefit both clinicians and patients the short-medium term. In the longer term it will also have potential to impact the NHS by improving the routine patient management .
First Year Of Impact 2018
Sector Healthcare,Pharmaceuticals and Medical Biotechnology
Impact Types Economic

 
Title Modelling database 
Description This database includes all the modelling data underpinning our publications connected to this grant. 
Type Of Material Computer model/algorithm 
Year Produced 2018 
Provided To Others? Yes  
Impact The data was used to produce two peer-reviewed publications. 
URL http://dx.doi.org/10.18742/RDM01-423
 
Title Personalised models of left atrium 
Description A total of 43 patient dataset was acquired, with 35 in sinus rhythm and 7 in atrial fibrillation at the time of initial scan. Of these latter group of patients, 6 exhibited sinus rhythm in the follow up scan. A total of 20 models were generated from these datasets. These included anatomy, blood flow dynamics (flow velocity, pressure and temperature), and wall motion. As this is an ongoing project the total number is likely to increase before the end of the grant. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? No  
Impact The continued model development will be of significant interest to researchers seeking to apply numerical simulations to clinically relevant problems. Despite the wealth of available data, a standardised procedure for benchmarking and validation of models from different methodological approaches is still lacking. To facilitate impact in this pathway, the models will be shared within the research community using the King's College Database, which is will take over from the previous web-based management system AMDB (Kerfoot et al. Med Biol Eng Comput. 2013;51(11):1181-90). This approach will allow model reuse and benchmarking, broadly benefitting the modelling community outside of our group. The models are currently stored locally at King's College London and will be made accessible at the end of the project via our database. 
 
Title Cheart, a scientific software application for simulating the physics of the human heart. 
Description CHeart is a modelling platform used to simulate the mechanical physics, fluid dynamics, and electrophysiology of the heart. The software is based on finite element methods for the Navier-Stokes equations in flow solver and quasi-static finite elasticity equations in the solid mechanics solver. 
Type Of Technology Software 
Year Produced 2017 
Impact This project developed an additional functionality within CHeart that allowed to model a three-dimensional temperature distribution in the blood flow, for example following heat delivery during radio frequency catheter ablation of atrial fibrillation. This is achieved by incorporating reaction-diffusion equations into the flow solver embedded in CHeart. 
URL http://cheart.co.uk
 
Description Heart in Your Hands Exhibition 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Heart in your Hands is an initiative created by the collaboration between researchers at King's College London, robotic art and design studio Rusty Squid, the Royal Academy of Engineers and the British Heart Foundation. It was presented at the Royal Society Summer Exhibition (https://royalsociety.org/science-events-and-lectures/2017/summer-science-exhibition/exhibits/heart-in-your-hands/) and aimed at engaging the general public on how the beating heart works, how disease can influence your heart, and how computational modelling and medical imaging are providing new avenues for personalised and predictive medicine. The exhibit received nationwide attention and featured on BBC Click and Health Check (https://www.bbc.co.uk/programmes/p0574spr).
Year(s) Of Engagement Activity 2017
URL http://cheart.co.uk/heart-in-your-hands/
 
Description Press release EPSRC 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact The funder, EPSRC, issued a press release on the work carried out during this grant. It was released on the front page of their website on the 27 November 2018. After its release I have been contacted by other researchers in the field and as a result I have submitted a funding application as PI on a 3-year research consortium project together with Bilbao Centre for Applied Mathematics and Barcelona Hospital de la Santa Creu i Sant Pau.
Year(s) Of Engagement Activity 2018
URL https://epsrc.ukri.org/newsevents/news/personalisedheartmodels/