The Impact of Model-based Deep-learning Reconstruction Compared with that of Compressed Sensing–Sensitivity Encoding on the Image Quality and Precision of Cine Cardiac MR in Evaluating Left-ventricular Volume and Strain: A Study on Healthy Volunteers
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Le résumé fourni par la source
PURPOSE: To evaluate the effect of model-based deep-learning reconstruction (DLR) compared with that of compressed sensing-sensitivity encoding (CS) on cine cardiac magnetic resonance (CMR). METHODS: Cine CMR images of 10 healthy volunteers were obtained with reduction factors of 2, 4, 6, and 8 and reconstructed using CS and DLR. The visual image quality scores assessed sharpness, image noise, and artifacts. Left-ventricular (LV) end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), and ejection fraction (EF) were manually measured. LV global circumferential strain (GCS) was automatically measured using the software. The precision of EDV, ESV, SV, EF, and GCS measurements was compared between CS and DLR using Bland-Altman analysis with full-sampling data as the gold standard. RESULTS: Compared with CS, DLR significantly improved image quality with reduction factors of 6 and 8. The precision of EDV and ESV with a reduction factor of 8, and GCS with reduction factors of 6 and 8 measurements improved with DLR compared with CS, whereas those of SV and EF measurements were not different between DLR and CS. CONCLUSION: The effect of DLR on cine CMR's image quality and precision in evaluating quantitative volume and strain was equal or superior to that of CS. DLR may replace CS for cine CMR.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- The Impact of Model-based Deep-learning Reconstruction Compared with that of Compressed Sensing–Sensitivity Encoding on the Image Quality and Precision of Cine Cardiac MR in Evaluating Left-ventricular Volume and Strain: A Study on Healthy Volunteers
- Date Crossref
- 01/01/2025
- Éditeur
- Japanese Society for Magnetic Resonance in Medicine
- 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.
Où se fait cette recherche
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Hokkaido University Department of Diagnostic and Interventional Radiology pays non établi dans la noticeUniversité ou école supérieure
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Hokkaido University Hospital pays non établi dans la noticeÉtablissement de santé
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Philips Japan pays non établi dans la noticeEntreprise
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Graduate School of Dental Medicine Department of Oral Health Science pays non établi dans la noticeUniversité ou école supérieure
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Graduate School of Medicine Department of Diagnostic Imaging pays non établi dans la noticeUniversité ou école supérieure
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Faculty of Medicine Global Center for Biomedical Science and Engineering pays non établi dans la noticeUniversité ou école supérieure
Department of Diagnostic and Interventional Radiology — Hokkaido University, Hokkaido University Hospital et Philips Japan, avec 3 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.