Intra-procedural updating of cardiac digital-twins for automated arrhythmia ablation target guidance using novel electroanatomical system

EPSRC · United Kingdom government procurement

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Closed
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Opportunity Overview

Aim of the PhD Project:
To develop the next generation of cardiac digital twin models which are automatically updated and enhanced using patient intra-procedural imaging and electrophysiological mapping data from the latest novel hybrid electroanatomical mapping-imaging system, facilitated by AI.
Apply our enhanced digital twin models to optimise target identification in ventricular tachycardia ablation.
Project Description:
Clinical Motivation: Ischemic heart disease (IHD) results in the formation of scar tissue in the heart. Scar-related arrhythmias, such as VT, are responsible for ~6 million sudden cardiac deaths annually. Often, the only effective therapy for patients suffering from incessant VT is highly-invasive catheter ablation. However, procedure times and complication rates are high, whilst success rates are punitively low: typically, >50% of patients will present with VT recurrence within 1-year post-procedure. Patient-specific computational simulation provides an exciting opportunity for integrating the wealth of existing imaging and electrical data for more accurate and beneficial pre-procedure and in-procedure planning, increasing success and reducing risk.

State-of-the-art: Computational cardiology will play a leading role in the future of cardiovascular medicine as it allows integrating comprehensive multi-model imaging data and functional measurements through digital twins: in-silico replicas of a patient's heart. Currently, such models are only created pre-procedurally, and then used as static entities during invasive procedures. Automated updating from on-going clinical data acquisition is currently lacking, but is important in order to refine and augment their utility, particularly in progressive diseases such as IHD.

Specific Goal: In this project, we will focus on the development of a new class of digital twins which are automatically updated from data recorded during VT ablation. Increasing the fidelity of the digital twin in this manner...

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Solicitation Details

Issuing agencyEPSRC
CountryUnited Kingdom
CategoryResearch Development
PublishedSeptember 30, 2022
Procurement stageActive solicitation
ClosedClosing date not published
StatusClosed — no longer accepting responses
Official sourceView original notice
Last verifiedOctober 11, 2026

Source: UK Research and Innovation (UKRI) — Open Government Licence v3.0.

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