The MAESTRIA programme is divided in eight work-packages (WP1-8), five scientific (WP1-5), one “outreach” (WP6) and two dedicated to project coordination and management (WP7) and Ethics issues (WP8). All work packages are tightly integrated so that data, samples, technical and computing expertise are available and shared throughout the wider collaborative programme such as data generated in one WP informing the other research and innovation activities. WP1-3 form the research task force of MAESTRIA to define new biomarkers using Machine Learning (ML) algorithms that will feed the platform: WP1 is orientated towards atrial imaging; WP2 focuses on electrical parameters and WP3 investigates molecular complexity.WP4 is clinically oriented, focussing on the development of validation datasets for ML algorithms through the retrospective analysis of cohorts from AFNET and the development of a novel specific prospective cohort. WP5 serves as an integrative analysis and data hub by providing the ML algorithms and biomarkers developed in WP1-3 with the annotated datasets assembled in WP4.WP6 conducts Dissemination, Exploitation & Valorisation of the MAESTRIA Demonstrator diagnostic platform. WP7 provides overall project management, ensuring that MAESTRIA is delivered on budget, in time and on target.
WP4 is clinically oriented, focussing on the development of validation datasets for ML algorithms through the retrospective analysis of cohorts from AFNET and the development of a novel specific prospective cohort. WP5 serves as an integrative analysis and data hub by providing the ML algorithms and biomarkers developed in WP1-3 with the annotated datasets assembled in WP4.
MAESTRIA-AFNET 10 study
MAESTRIA-AFNET 10 study is a research project conducted in several European countries. A total of 600 persons are planned to participate. The study is organised by Kompetenznetz Vorhofflimmern e.V. who run the Atrial Fibrillation Network – AFNET and who are a partner in the larger MAESTRIA Study. The study is funded by the EU programme “Horizon 2020” (EU grant number 965286).
Participation in this study is entirely voluntary and requires written consent. Non-participation or withdrawal from the study at a later stage will not result in any disadvantages.
Our interest in conducting this study is the improvement of clinical diagnostics (the detection of disease) for better patient care. The study initiator does not have commercial interests.
The aim of the MAESTRIA-AFNET 10 study is to develop a digital diagnostic platform for the common condition of atrial fibrillation (AF) – the most common heart-beat disorder. This platform should enable improved diagnostic accuracy, which will increase the effectiveness and efficiency of treatments and prevent complications of AF, the most common of which is stroke.
| Title | Machine Learning and Artificial Intelligence for Early Detection of Stroke and Atrial Fibrillation (MAESTRIA) |
| Chief investigator | Professor Dr. Andreas Goette St. Vincenz-Krankenhaus GmbH Am Busdorf 2 33098 Paderborn Germany |
| Sponsor | Kompetenznetz Vorhofflimmern e.V. / Atrial Fibrillation NETwork (AFNET) Represented by Professor Dr. Stephan Willems, member of the board of directors Mendelstraße 11 48149 Münster Germany Phone: +49 251 980 1330 Fax: +49 251 980 1349 Website: https://www.af-net.eu |
| Data controllers | Several entities are working together to conduct the MAESTRIA-AFNET 10 study. The following parties are jointly responsible for processing your data in compliance with data protection laws :
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| Background and rationale | Atrial fibrillation (AF) and stroke are major health care problems in Europe. They are most often the clinical expressionof atrial cardiomyopathy, which is underestimated due to the lack of specific diagnostic tools. Multidisciplinary researchand stratified approaches are urgently needed to prevent, diagnose, and treat AF and stroke and preempt the AF-related threat to healthy ageing in Europe.
MAESTRIA is a European consortium of 18 clinicians, scientists and pharma industry partners who are at the forefront of research and medical care of AF and stroke patients funded by the EU Horizon 2020 programme (grant number 965286). The Atrial Fibrillation Network (AFNET) is one of the 18 partner institutions in this European consortium. MAESTRIA will create multi-parametric digital tools based on a new generation of biomarkers that integrate artificialintelligence (AI) processing and big data from cutting edge imaging, electrocardiography and omics technologies. It willdevelop novel biomarkers, diagnostic tools and personalized therapies for atrial cardiomyopathy. The MAESTRIA-AFNET 10 Study is an integral part of the MAESTRIA project. The study will collect relevant clinical parameters for AF from patients, this includes ECGs, cardiac CTs, MRIs andechocardiograms. Dedicated core labs will collect and homogenize the clinical data. For atrial arrhythmias (AA) and vascular stiffness index (VSI) recording, patients will be provided with a measuring bracelet for continuous monitoring of heart rhythm with a photoplethysmographic (PPG) sensor coupled with a smartphone app and the Preventicus Heartbeats® analytic service (Class IIa, CE marked), approved as consumerdevice. Preventicus is ISO 13485 certified. |
| Study objective(s) | – Enrolment of a representative cross-section of AF patients in Europe. – Detailed analysis of clinical and relevant parameters (ECG, cardiac imaging, blood biomarkers) that could be used during clinical practice for the diagnosis of atrial cardiomyopathy and patient outcome. – The data sets will be assessed including but not limited to AI algorithms to characterize specific subgroups of AF or define novel outcome predictors. |
| List of recipients of data and types of forwarded data | Purpose: Development of the Artificial Intelligence (AI) process Recipients: – University of Maastricht – IDOVEN – Oxford University – Sorbonne University Type of data: – Routine ECG – Digital ECG – Computerized tomography (CT) imaging – Echocardiogram (Echo) – Magnetic Resonance Image (MRI) Data retention period : 2 years after completion of research |
| Date of study start | Study started in Germany in November 2022 |
| Period of patients recruitment | Patients are recruited for 24 months |
| Duration of patients’ follow up | Follow up duration is 12 months |
| Data retention period | The total duration of the MAESTRIA project is five years then archiving for 15 years, including storage in an active database for the duration of the project + 2 years |
| Project reference | NCT05855538 |
The MAESTRIA-AFNET 10 study was approved:
– In Germany by the Ethik Kommission of Munster on October 4, 2022
– In Spain by the Comité de Ética de la Investigación con Medicamentos de hospital clinic San Carlos (Madrid) on January 25, 2023
– In France by the Comité de Protection des Personnes (CPP) Ouest II on June 15, 2023
– In the Netherlands by the medisch ethische toetsingscommisie (METC) of Maastricht University on December 8, 2023
How can the use of data be objected to?
To object to participation in one or more research studies conducted as part of MAESTRRIA-AFNET 10, it’s possible to contact the doctor associated with the study during the hospital stay where recruitment occurred..
For assistance in exercising rights, the Data Protection Officer of the recruiting hospital (as indicated on the signed consent form) can be contacted. They can provide information about available remedies throughthe CNIL.
What are the results of this study?
The first results of the MAESTRIA-AFNET 10 project will be available soon on the MAESTRIA website.
What further studies will the data be used for?
The study is in its early stages, and no further use is envisaged as yet. Updates about new studies requiring reuse of the data and samples will be provided regularly
Biobank samples
The biobank will received approval from local regulatory authority
With agreement to optional biobank sampling (second signed ethics committee (EC) approved informed consent form), an additional blood volume will be collected during routine blood collection.
Pseudonymized samples will then be shipped in batches from recruiting sites and stored in an ISO9001 and NF S96-900 accredited Biobank at SU ICAN (Paris, France).
At the end of the MAESTRIA-AFNET 10 study, researchers from the European Union and outside the European Union will have access to the samples stored in the central MAESTRIA biobank (SU ICAN) in order to carry out their own analyses.
| Title | Machine Learning and Artificial Intelligence for Early Detection of Stroke and Atrial Fibrillation (MAESTRIA) |
| Chief investigator | Professor Dr. Andreas Goette St. Vincenz-Krankenhaus GmbH Am Busdorf 2 33098 Paderborn Germany |
| Sponsor | Kompetenznetz Vorhofflimmern e.V. / Atrial Fibrillation NETwork (AFNET) Represented by Professor Dr. Stephan Willems, member of the board of directors Mendelstraße 11 48149 Münster Germany Phone: +49 251 980 1330 Fax: +49 251 980 1349 Website: https://www.af-net.eu |
| Data controllers |
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| Study objective(s) | Biobank are used to advance medical research. To this end, the biological samples collected and the associated data will be preserved over the long term and made available for future studies aimed at preventing, diagnosing and treating disease. |
| List of recipients of data and types of forwarded data | Purpose: Advance medical research Recipient : SU ICAN Type of data : – Blood samples (serum and plasma) – Associated data : (year of birth, date of blood sample collection, research ID) Data retention period : 10 years maximum |
| Date of study start | Study started in Germany in November 2022 |
| Period of patients recruitment | Patients are recruited for 24 months |
| Duration of patients’ follow up | Follow up duration is 12 months |
| Data retention period | 10 years |