Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models
Lead Research Organisation:
University of Sheffield
Department Name: Computer Science
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Publications
Bernjak A
(2021)
Hypoglycaemia combined with mild hypokalaemia reduces the heart rate and causes abnormal pacemaker activity in a computational model of a human sinoatrial cell
in Journal of The Royal Society Interface
Clayton RH
(2020)
An audit of uncertainty in multi-scale cardiac electrophysiology models.
in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Clayton RH
(2018)
Dispersion of Recovery and Vulnerability to Re-entry in a Model of Human Atrial Tissue With Simulated Diffuse and Focal Patterns of Fibrosis.
in Frontiers in physiology
Corrado C
(2023)
Quantifying the impact of shape uncertainty on predicted arrhythmias.
in Computers in biology and medicine
Corrado C
(2018)
An Algorithm to Sample an Anatomy With Uncertainty
Corrado C
(2020)
Quantifying atrial anatomy uncertainty from clinical data and its impact on electro-physiology simulation predictions.
in Medical image analysis
Coveney S
(2022)
Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds.
in Scientific reports
| Description | We have implemented a novel method that enables us to take a small number of noisy measurements of electrical activation in the heart, and use them to interpolate and extrapolate activation times over the surface of the left atrium. This method is novel because there it accounts for uncertainties in the measurement as well as the interpolation and extrapolation, so the output is a best estimate of local activation time with an associated confidence in the estimate. This method has been extended to estimate the speed of the electrical activation wave across the left atrium in the heart, and we have also assessed how uncertainty and variability in the shape of the left atrium affects speed. We have also undertaken a systematic and detailed analysis of simulation models, so as to identify model parameters that can be identified from routinely available patient data, as well as those that cannot. This work has enabled us to develop a methodology for calibrating personalised models of individual patients, which embeds uncertainties arising from variability and noise in the data, as well as uncertainties that are associated with the methodology. This method has been evaluated using simulated patient data, and we have shown that it can be used to identify pacing protocols that optimise the information that can be obtained in the clinical setting. We have secured further EPSRC funding (EP/W000091/1) to speed up the processing pipeline so that these methods can be deployed in the clinical setting, where decisions need to be made quickly. |
| Exploitation Route | There are many ways that the outcomes of this award could be taken forward. These include the use of these techniques to guide clinical interventions, as well as direct implementation of our methods in medical equipment. We have secured further EPSRC funding to develop the technology further. |
| Sectors | Digital/Communication/Information Technologies (including Software) Healthcare Pharmaceuticals and Medical Biotechnology |
| Description | One of the outcomes from this research was a set of software tools for emulation and sensitivity analysis of complex models. These are now being used widely by academic and industry users. Some of this uptake is as a result of the 'Fickle Heart' work programme organised at the Isaac Newton Institute for Mathematical Sciences in Cambridge (https://www.newton.ac.uk/event/fht/), which included an event aimed at industry (https://gateway.newton.ac.uk/event/OFBW45). |
| First Year Of Impact | 2021 |
| Sector | Digital/Communication/Information Technologies (including Software),Healthcare |
| Impact Types | Societal Economic |
| Description | In-Procedure Personalized Atrial Digital Twin to Predict Outcome of Atrial Fibrillation Ablation |
| Amount | £1,534,181 (GBP) |
| Funding ID | EP/W000091/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 03/2022 |
| End | 03/2025 |
| Description | The SofTMech Statistical Emulation and Translation Hub |
| Amount | £1,225,134 (GBP) |
| Funding ID | EP/T017899/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 03/2021 |
| End | 02/2025 |
| Description | The South Yorkshire Digital Health Hub |
| Amount | £3,211,469 (GBP) |
| Funding ID | EP/X03075X/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2023 |
| End | 08/2026 |
| Description | Atrial UQ |
| Organisation | King's College London |
| Department | Department of Biomedical Engineering |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Sheffield is providing expertise on uncertainty quantification. |
| Collaborator Contribution | King's College London is providing patient data and analysis expertise. |
| Impact | No outputs yet. |
| Start Year | 2017 |
| Title | maGPy |
| Description | Uncertainty and sensitivity analysis using Gaussian process emulators |
| Type Of Technology | Software |
| Year Produced | 2020 |
| Open Source License? | Yes |
| Impact | This software has underpinned a series of publications. |
| URL | https://github.com/samcoveney/maGPy |
| Title | quaLATi -- Quantifying Uncertainty for Local Activation Time Interpolation |
| Description | This package is for Quantifying Uncertainty for Local Activation Time Interpolation. It implements Gaussian Process Manifold Interpolation (GPMI) for doing Gaussian process regression on a manifold represented by a triangle mesh. |
| Type Of Technology | Software |
| Year Produced | 2020 |
| Open Source License? | Yes |
| Impact | This software underpins several publications including https://doi.org/10.1098/rsta.2019.0345 |
| Description | Co-organiser of Fickle Heart workshop: The intersection of UQ, AI and Digital Twins at the Isaac Newton Institute for Mathematical Sciences in Cambridge 3-4 June 2024 |
| 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 | Although the bulk of the preparation work has been done by the 2024 submission deadline in March, the workshop will take place in June 2024, so the outcomes/impact are provisional. It is a follow on from the Fickle Heart programme in 2019, where I was co-organiser. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.newton.ac.uk/event/fhtw02/ |
| Description | Invited presentation at the Isaac Newton Institute |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Presentation entitled "Probabilistic Calibration of Personalised Heart Models from Sparse and Noisy Measurements" invited as part of work programme on "The Role of Uncertainty in Mathematical Modelling of Pandemics" at the Isaac Newton Institute in Cambridge. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://gateway.newton.ac.uk/event/tgm110/programme |
| Description | Invited presentation on Quantitative analysis and comparison of cardiac cell and tissue models using Gaussian process emulators - part of a Special Semester on Mathematical Methods in Medicine at University of Linz 13-17 November 2023 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Participation in Special Semester on Mathematical Methods in Medicine |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://www.ricam.oeaw.ac.at/specsem/specsem2023/workshop2/ |
| Description | Sensitivity analysis and calibration of cardiac models using emulators at the Sixth Soft Tissue Modelling Workshop 7th - 9th June 2023 in Glasgow. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Presentation at the Sixth Soft Tissue Modelling Workshop 7th - 9th June 2023 in Glasgow. |
| Year(s) Of Engagement Activity | 2023 |
| Description | Uncertainty and sensitivity analysis for real-world problems in clinical cardiology at SIAM UQ meeting in Trieste, 27 Feb - 1 March 2024 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Presentation as part of a minisymposium on uncertainty quantification for healthcare and biology. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.siam.org/conferences/cm/conference/uq24 |
| Description | Work Programme at the Isaac Newton Institute |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | This programme took place over a month, and was based at the Isaac Newton Institute in Cambridge. It brought together a small working group of 33 attendees, who were present in Cambridge for between one week and four weeks. During the final week, there was a workshop attended by 81 participants from all over the world, and an industry day that was attended by a range of industry representatives. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://www.newton.ac.uk/event/fht/ |