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- Title
Prognostic impact of artificial intelligence-based fully automated global circumferential strain in patients undergoing stress CMR.
- Authors
Pezel, Théo; Garot, Philippe; Toupin, Solenn; Hovasse, Thomas; Sanguineti, Francesca; Champagne, Stéphane; Morisset, Stéphane; Chitiboi, Teodora; Jacob, Athira J; Sharma, Puneet; Unterseeh, Thierry; Garot, Jérôme
- Abstract
Aims To determine whether fully automated artificial intelligence-based global circumferential strain (GCS) assessed during vasodilator stress cardiovascular (CV) magnetic resonance (CMR) can provide incremental prognostic value. Methods and results Between 2016 and 2018, a longitudinal study included all consecutive patients with abnormal stress CMR defined by the presence of inducible ischaemia and/or late gadolinium enhancement. Control subjects with normal stress CMR were selected using a propensity score-matching. Stress-GCS was assessed using a fully automatic machine-learning algorithm based on featured-tracking imaging from short-axis cine images. The primary outcome was the occurrence of major adverse clinical events (MACE) defined as CV mortality or nonfatal myocardial infarction. Cox regressions evaluated the association between stress-GCS and the primary outcome after adjustment for traditional prognosticators. In 2152 patients [66 ± 12 years, 77% men, 1:1 matched patients (1076 with normal and 1076 with abnormal CMR)], stress-GCS was associated with MACE [median follow-up 5.2 (4.8–5.5) years] after adjustment for risk factors in the propensity-matched population [adjusted hazard ratio (HR), 1.12 (95% CI, 1.06–1.18)], and patients with normal CMR [adjusted HR, 1.35 (95% CI, 1.19–1.53), both P < 0.001], but not in patients with abnormal CMR (P = 0.058). In patients with normal CMR, an increased stress-GCS showed the best improvement in model discrimination and reclassification above traditional and stress CMR findings (C-statistic improvement: 0.14; NRI = 0.430; IDI = 0.089, all P < 0.001; LR-test P < 0.001). Conclusion Stress-GCS is not a predictor of MACE in patients with ischaemia, but has an incremental prognostic value in those with a normal CMR although the absolute event rate remains low.
- Subjects
CARDIOVASCULAR disease related mortality; LEFT heart ventricle; PHYSIOLOGICAL stress; CARDIOVASCULAR diseases risk factors; EVALUATION of medical care; CONFIDENCE intervals; VENTRICULAR ejection fraction; MAJOR adverse cardiovascular events; LOG-rank test; CARDIOVASCULAR diseases; ARTIFICIAL intelligence; MACHINE learning; MYOCARDIAL infarction; MANN Whitney U Test; AUTOMATION; VASODILATORS; DESCRIPTIVE statistics; CHI-squared test; SURVIVAL analysis (Biometry); KAPLAN-Meier estimator; COMPUTER-aided diagnosis; STATISTICAL correlation; DATA analysis software; LONGITUDINAL method; ALGORITHMS; PROPORTIONAL hazards models
- Publication
European Heart Journal - Cardiovascular Imaging, 2023, Vol 24, Issue 9, p1269
- ISSN
2047-2404
- Publication type
Article
- DOI
10.1093/ehjci/jead100