H2020Индивидуална стипендия2022–2023

PhyNeTouch · Multiphysics modelling and neural networks synergy to enhance the outcome of robotic catheter ablation for the treatment of atrial fibrillation

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2022-01-01 → 2023-12-31
Финансиране от ЕС: 212 934 €
Участници: 1
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Компютърни модели и невронни мрежи се използват за по-точно разпределяне на топлината при роботизирана катетерна аблация за лечение на предсърдно мъждене. Това помага за повишаване на успеха на процедурата и намаляване на риска от усложнения и инсулти.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Multiphysics modelling and neural networks synergy to enhance the outcome of robotic catheter ablation for the treatment of atrial fibrillation

This Marie Sklodowska Curie Action (MSCA) is titled “Multiphysics modelling and neural networks synergy to enhance the outcome of robotic catheter ablation for the treatment of atrial fibrillation”. This project aims to propose novel computational methods to assist the improved delivery of cardiac radiofrequency ablation for the treatment of atrial fibrilation. This is an important topic for society because atrial fibrillation is the most common cardiac arrhythmia and a major risk factor for ischemic stroke with serious health and socioeconomic implications for EU. Despite the superior outcome of catheter ablation, its success rate remains limited, and the complication risk significant. To address this challenge, the objectives of this project are: (1) to predict bioheat distribution in tissue with high accuracy, and (2) to achieve real-time feedback through Neural Networks.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Atrial fibrillation is the most common cardiac arrhythmia affecting more than 7.6 million people in Europe, while future projections estimate a worldwide increase by over 60%. Catheter ablation has evolved over the last decades to an important therapeutic modality for patients with atrial fibrillation. Despite the fact that modern robotic ablation systems made precise catheter navigation possible, the success rate remains limited and the risk for complications is significant. As a result, atrial fibrillation remains a serious health issue, influencing the quality of life, and the source of very important socioeconomic problems.The vision of PhyNeTouch project (reads: fine-touch) is to capitalize on the recent advancements in computational modelling and artificial intelligence in order to enhance the safety of robotic catheter ablation procedure and improve its success rate. Novel multiphysics modelling techniques based on meshfree methods will be combined for the first time with physics-informed neural networks to advance the state-of-the-art and produce accurate bioheat distribution maps in real-time which currently are not available in the clinical setting.Predicting bioheat distribution in the tissue during the operation will assist the decision making and will allow improving the outcome of robotic catheter ablation. In this way, PhyNeTouch aims to contribute to the healthy ageing of citizens of EU and the rest of the world, as well as to reduce the socioeconomic burden, by reducing the complexity of this procedure and making it accessible to a wider public.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSITY COLLEGE LONDON · LondonКоординаторОбединеното кралство