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Automated inversion time selection for black-blood late gadolinium enhancement cardiac imaging in clinical practice

OBJECTIVE: To simplify black-blood late gadolinium enhancement (BL-LGE) cardiac imaging in clinical practice using an image-based algorithm for automated inversion time (TI) selection. MATERIALS AND METHODS: The algorithm selects from BL-LGE TI scout images, the TI corresponding to the image with th...

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Detalles Bibliográficos
Autores principales: Maillot, Aurélien, Sridi, Soumaya, Pineau, Xavier, André-Billeau, Amandine, Hosteins, Stéphanie, Maes, Jean-David, Montier, Géraldine, Nuñez-Garcia, Marta, Quesson, Bruno, Sermesant, Maxime, Cochet, Hubert, Stuber, Matthias, Bustin, Aurélien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667449/
https://www.ncbi.nlm.nih.gov/pubmed/37294423
http://dx.doi.org/10.1007/s10334-023-01101-2
Descripción
Sumario:OBJECTIVE: To simplify black-blood late gadolinium enhancement (BL-LGE) cardiac imaging in clinical practice using an image-based algorithm for automated inversion time (TI) selection. MATERIALS AND METHODS: The algorithm selects from BL-LGE TI scout images, the TI corresponding to the image with the highest number of sub-threshold pixels within a region of interest (ROI) encompassing the blood-pool and myocardium. The threshold value corresponds to the most recurrent pixel intensity of all scout images within the ROI. ROI dimensions were optimized in 40 patients’ scans. The algorithm was validated retrospectively (80 patients) versus two experts and tested prospectively (5 patients) on a 1.5 T clinical scanner. RESULTS: Automated TI selection took ~ 40 ms per dataset (manual: ~ 17 s). Fleiss’ kappa coefficient for automated-manual, intra-observer and inter-observer agreements were [Formula: see text] = 0.73, [Formula: see text]  = 0.70 and [Formula: see text]  = 0.63, respectively. The agreement between the algorithm and any expert was better than the agreement between the two experts or between two selections of one expert. DISCUSSION: Thanks to its good performance and simplicity of implementation, the proposed algorithm is a good candidate for automated BL-LGE imaging in clinical practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10334-023-01101-2.