Alabed, S. orcid.org/0000-0002-9960-7587, Alandejani, F., Dwivedi, K. et al. (21 more authors) (2022) Validation of artificial intelligence cardiac MRI measurements: relationship to heart catheterization and mortality prediction. Radiology, 305 (1). ISSN 0033-8419
Abstract
Background
Cardiac MRI measurements have diagnostic and prognostic value in the evaluation of cardiopulmonary disease. Artificial intelligence approaches to automate cardiac MRI segmentation are emerging but require clinical testing.
Purpose
To develop and evaluate a deep learning tool for quantitative evaluation of cardiac MRI functional studies and assess its use for prognosis in patients suspected of having pulmonary hypertension.
Materials and Methods
A retrospective multicenter and multivendor data set was used to develop a deep learning–based cardiac MRI contouring model using a cohort of patients suspected of having cardiopulmonary disease from multiple pathologic causes. Correlation with same-day right heart catheterization (RHC) and scan-rescan repeatability was assessed in prospectively recruited participants. Prognostic impact was assessed using Cox proportional hazard regression analysis of 3487 patients from the ASPIRE (Assessing the Severity of Pulmonary Hypertension In a Pulmonary Hypertension Referral Centre) registry, including a subset of 920 patients with pulmonary arterial hypertension. The generalizability of the automatic assessment was evaluated in 40 multivendor studies from 32 centers.
Results
The training data set included 539 patients (mean age, 54 years ± 20 [SD]; 315 women). Automatic cardiac MRI measurements were better correlated with RHC parameters than were manual measurements, including left ventricular stroke volume (r = 0.72 vs 0.68; P = .03). Interstudy repeatability of cardiac MRI measurements was high for all automatic measurements (intraclass correlation coefficient range, 0.79–0.99) and similarly repeatable to manual measurements (all paired t test P > .05). Automated right ventricle and left ventricle cardiac MRI measurements were associated with mortality in patients suspected of having pulmonary hypertension.
Conclusion
An automatic cardiac MRI measurement approach was developed and tested in a large cohort of patients, including a broad spectrum of right ventricular and left ventricular conditions, with internal and external testing. Fully automatic cardiac MRI assessment correlated strongly with invasive hemodynamics, had prognostic value, were highly repeatable, and showed excellent generalizability.
Clinical trial registration no. NCT03841344
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s). Published under a CC BY 4.0 license. (http://creativecommons.org/licenses/by/4.0). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > The Medical School (Sheffield) > Academic Unit of Medical Education (Sheffield) The University of Sheffield > Sheffield Teaching Hospitals |
Funding Information: | Funder Grant number DEPARTMENT OF HEALTH AND SOCIAL CARE AI_AWARD01706 WELLCOME TRUST (THE) 205188/Z/16/Z Academy of Medical Sciences None-SGL015\1023 National Institute for Health Research AI_AWARD01706 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Sep 2022 13:21 |
Last Modified: | 27 Jan 2023 11:31 |
Status: | Published |
Publisher: | Radiological Society of North America (RSNA) |
Refereed: | Yes |
Identification Number: | 10.1148/radiol.212929 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:190536 |