ECG project UMCU

2020

The correct interpretation of electrocardiograms (ECGs) is crucial for accurately diagnosing cardiac abnormalities. Current methods, both manual by physicians and computerized, have not achieved the level of accuracy comparable to cardiologists in detecting acute cardiac issues. Leveraging advancements in artificial intelligence and big data, particularly deep neural networks, offers promising avenues to improve ECG interpretation where traditional methods have fallen short. The ECG-Project develops deep learning algorithms to automate ECG interpretation, particularly focusing on areas where current methods are inadequate.

Through this research, we aim to revolutionize ECG interpretation, improving diagnostic accuracy, reducing healthcare resource utilization, and ultimately enhancing patient outcomes.

The Research
The project objectives are:

  1. WP1: Creating an algorithm capable of accurately and swiftly triaging ECGs through transfer learning, uncovering features in diseases with unknown ECG characteristics (such as primary arrhythmia syndromes and genetic disorders).
  2. WP2: design a portable multi-lead ecg-device, suitable for use by patients at home and healthcare professionals. This device will enable high-quality ECG acquisitions for rapid diagnosis.

Origin
This project is funded within the Innovative Medical Devices Initiative (IMDI) program 'Heart for Sustainable Care'. The focus of this program is the development of medical technology for the earlier detection, monitoring, and better treatment of cardiovascular diseases to ensure accessible healthcare and sufficient staffing. The program has been developed and funded by the Dutch Heart Foundation, ZonMw and NWO, who collaborate within the Dutch CardioVascular Alliance.

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PREDICT 2

2019
Sudden cardiac arrest (SCA) remains a significant public health challenge, accounting for nearly 20% of all deaths in developed nations and approximately half of all heart disease-related fatalities. A notable subset of SCA cases occurs in individuals without prior heart disease diagnosis, resulting in profound psychosocial impacts on affected families and society. Ventricular fibrillation (VF) is the primary arrhythmia leading to SCA, often occurring outside healthcare settings with survival rates ranging from 5% to 20%. Prevention is crucial, yet gaps in our understanding of SCA causes and mechanisms hinder effective prevention efforts. Various genetic and non-genetic factors, such as gender, age, comorbidities, and lifestyle, likely influence SCA risk, but their specific contributions remain unclear. The Focus The PREDICT2 initiative brings together leading Principal Investigators with expertise in epidemiology, clinical studies, genetics, and functional research to elucidate factors contributing to SCA, uncover underlying mechanisms, and develop strategies for prevention and treatment. The Research Building on foundational work from PREDICT1, which involved extensive patient characterization and preclinical model development, PREDICT2 focuses on inherited arrhythmia syndromes as models to understand the arrhythmogenic substrate in more common cardiac syndromes associated with SCA. Specifically, PREDICT2 aims to: Identify genetic and non-genetic factors that contribute to SCA risk and develop personalized risk prediction algorithms for individual patient assessment. Conduct functional studies to elucidate the mechanisms underlying SCA, enabling the development of novel risk stratification and therapeutic approaches. Implement clinical studies to evaluate risk prediction algorithms and therapeutic interventions, aiming to enhance the treatment and prevention of SCA. Origin This consortium was funded through the Impulse Grant program by the Dutch Heart Foundation.
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Holland Hybrid Heart

2023
In the Netherlands, there are 250,000 patients with heart failure. Half of these patients die within five years. The best treatment: a donor heart. But: there is a great shortage of these. The Holland Hybrid Heart consortium is therefore working on an alternative: a robot heart, made of soft materials. The research We envision the treatment of patients with heart failure (HF) in such a way that the survival and quality of life of HF patients drastically increases. We aim to achieve this by developing a unique bioinspired total artificial heart that integrates soft robotics and tissue engineering (TE). In the long term, we foresee that this pioneering technology allows us to develop and bring to the clinic a full set of artificial motile organs and tissues that seamlessly integrate with the human body. This will be possible as the novel and exciting technologies underlying the artificial heart developed in this project - soft robotics and in situ TE - can be used to generate a broad range of artificial motile organs such as muscle structures (e.g., limbs), bowels or lungs: The motility and flexibility in shape and size of soft robots make them suitable for mimicking motile organs. Actuators can be embedded within the elastomeric matrix of these robots without compromising their malleable properties. In addition, embodied intelligence provides direct feedback on shape and force, enabling natural behaviour. Biocompatibility of these artificial organs is provided by TE inside the body (in situ) using biodegradable coatings or scaffolds. Such TE scaffolds are cell-free synthetic bio-resorbable implants or linings that can recruit or interact with cells from the bloodstream, leading to gradual replacement of the scaffold by fully endogenous, and thus biocompatible, tissue. Importantly, the cell-free and thus off-the-shelf availability of these scaffolds avoids the high costs and complex logistics inherent to pre-implantation in vitro TE. The Holland Hybrid Heart (HHH) consortium will push the development of these newly emerging technologies forward and combines soft robotics and in situ TE to generate the first biocompatible, soft actuated heart. This project will deliver Proof-of-Principle for full in vivo cardiac functionality of the artificial HHH in large animals. If successful, the HHH will be available for translation to the clinic as an effective treatment for advanced HF in patients and a valid alternative for moderately effective current HF therapies. This is a quantum leap forward in the treatment of HF. Origin A photo in the newspaper inspired Rotterdam heart specialist Jolanda Kluin to develop a robot heart. Kluin immediately contacted the interviewee in the article, Bas Overvelde, head of the Soft Robotic Matter group at Amolf, which develops soft robots. Could he perhaps also make a heart using soft robot techniques? Overvelde believed in it and a collaboration was born. Five years ago, they received a European subsidy of more than 3 million euros. This grant started the previous EU consortium, the EU Hybrid Heart. Last December (2023), Kluin received another 11 million euros from the Dutch government to continue the Holland hybrid heart project. The Holland Hybrid Heart has pivoted to meet the demands of that new grant and now only contains 15 Dutch consortium partners. The consortium is funded by NWA-ORC and the Dutch Heart Foundation. In-kind contributions are also provided by the DCVA, the Dutch Heart Foundation, TrailBlazers, SBMC, EVOS and EE-Labels. The executing academic partners are Erasmus MC, Amolf, TU Eindhoven, University of Twente, TU Delft and Saxion Applied University. This research is driven by patient needs and the Harteraad and Stichting Pulmonale Hypertensie will provide the connections to these patients.
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