Pushing the limits of cardiac MRI: deep-learning based real-time cine imaging in free breathing vs breath hold
Rattachement africain : de. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
OBJECTIVE: To evaluate deep-learning (DL) based real-time cardiac cine sequences acquired in free breathing (FB) vs breath hold (BH). MATERIALS AND METHODS: In this prospective single-centre cohort study, 56 healthy adult volunteers were investigated on a 1.5-T MRI scanner. A set of real-time cine sequences, including a short-axis stack, 2-, 3-, and 4-chamber views, was acquired in FB and with BH. A validated DL-based cine sequence acquired over three cardiac cycles served as the reference standard for volumetric results. Subjective image quality (sIQ) was rated by two blinded readers. Volumetric analysis of both ventricles was performed. RESULTS: sIQ was rated as good to excellent for FB real-time cine images, slightly inferior to BH real-time cine images (p < 0.0001). Overall acquisition time for one set of cine sequences was 50% shorter with FB (median 90 vs 180 s, p < 0.0001). There were significant differences between the real-time sequences and the reference in left ventricular (LV) end-diastolic volume, LV end-systolic volume, LV stroke volume and LV mass. Nevertheless, BH cine imaging showed excellent correlation with the reference standard, with an intra-class correlation coefficient (ICC) > 0.90 for all parameters except right ventricular ejection fraction (RV EF, ICC = 0.887). With FB cine imaging, correlation with the reference standard was good for LV ejection fraction (LV EF, ICC = 0.825) and RV EF (ICC = 0.824) and excellent (ICC > 0.90) for all other parameters. CONCLUSION: DL-based real-time cine imaging is feasible even in FB with good to excellent image quality and acceptable volumetric results in healthy volunteers. KEY POINTS: Question Conventional cardiac MR (CMR) cine imaging is challenged by arrhythmias and patients unable to hold their breath, since data is acquired over several heartbeats. Findings DL-based real-time cine imaging is feasible in FB with acceptable volumetric results and reduced acquisition time by 50% compared to real-time breath-hold sequences. Clinical relevance This study fits into the wider goal of increasing the availability of CMR by reducing the complexity, duration of the examination and improving patient comfort and making CMR available even for patients who are unable to hold their breath.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Pushing the limits of cardiac MRI: deep-learning based real-time cine imaging in free breathing vs breath hold
- Date Crossref
- 23/08/2025
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Les institutions déclarées
Une affiliation ne permet pas de déduire la nationalité d’un auteur.