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The Nottingham Ischaemic Cardiovascular Magnetic Resonance resource (NotIs CMR): a prospective paired clinical and imaging scar database-protocol.

Authors :
Jathanna N
Strachan K
Erhayiem B
Kamaruddin H
Swoboda P
Auer D
Chen X
Jamil-Copley S
Source :
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance [J Cardiovasc Magn Reson] 2023 Nov 27; Vol. 25 (1), pp. 69. Date of Electronic Publication: 2023 Nov 27.
Publication Year :
2023

Abstract

Introduction: Research utilising artificial intelligence (AI) and cardiovascular magnetic resonance (CMR) is rapidly evolving with various objectives, however AI model development, generalisation and performance may be hindered by availability of robust training datasets including contrast enhanced images.<br />Methods: NotIs CMR is a large UK, prospective, multicentre, observational cohort study to guide the development of a biventricular AI scar model. Patients with ischaemic heart disease undergoing clinically indicated contrast-enhanced cardiac magnetic resonance imaging will be recruited at Nottingham University Hospitals NHS Trust and Mid-Yorkshire Hospital NHS Trust. Baseline assessment will include cardiac magnetic resonance imaging, demographic data, medical history, electrocardiographic and serum biomarkers. Participants will undergo monitoring for a minimum of 5 years to document any major cardiovascular adverse events. The main objectives include (1) AI training, validation and testing to improve the performance, applicability and adaptability of an AI biventricular scar segmentation model being developed by the authors and (2) develop a curated, disease-specific imaging database to support future research and collaborations and, (3) to explore associations in clinical outcome for future risk prediction modelling studies.<br />Conclusion: NotIs CMR will collect and curate disease-specific, paired imaging and clinical datasets to develop an AI biventricular scar model whilst providing a database to support future research and collaboration in Artificial Intelligence and ischaemic heart disease.<br /> (© 2023. The Author(s).)

Details

Language :
English
ISSN :
1532-429X
Volume :
25
Issue :
1
Database :
MEDLINE
Journal :
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Publication Type :
Academic Journal
Accession number :
38008732
Full Text :
https://doi.org/10.1186/s12968-023-00978-1