Automated inversion time selection for black-blood late gadolinium enhancement cardiac imaging in clinical practice.
Details
Serval ID
serval:BIB_A825434BEC1D
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Automated inversion time selection for black-blood late gadolinium enhancement cardiac imaging in clinical practice.
Journal
Magma
ISSN
1352-8661 (Electronic)
ISSN-L
0968-5243
Publication state
Published
Issued date
12/2023
Peer-reviewed
Oui
Volume
36
Number
6
Pages
877-885
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Publication Status: ppublish
Abstract
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.
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.
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.
Thanks to its good performance and simplicity of implementation, the proposed algorithm is a good candidate for automated BL-LGE imaging in clinical practice.
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.
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.
Thanks to its good performance and simplicity of implementation, the proposed algorithm is a good candidate for automated BL-LGE imaging in clinical practice.
Keywords
Humans, Contrast Media, Gadolinium, Retrospective Studies, Heart/diagnostic imaging, Myocardium, Magnetic Resonance Imaging/methods, Black-blood imaging, Gadolinium Enhancement, Magnetic resonance imaging, Myocardial infarction
Pubmed
Web of science
Open Access
Yes
Create date
14/06/2023 9:50
Last modification date
08/08/2024 7:38