1. Image quality assessment and automation in late gadolinium-enhanced MRI of the left atrium in atrial fibrillation patients.
- Author
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Orkild B, Arefeen Sultan KM, Kholmovski E, Kwan E, Bieging E, Morris A, Stoddard G, MacLeod RS, Elhabian S, Ranjan R, and DiBella E
- Abstract
Background: Late gadolinium-enhanced (LGE) MRI has become a widely used technique to non-invasively image the left atrium prior to catheter ablation. However, LGE-MRI images are prone to variable image quality, with quality metrics that do not necessarily correlate to the image's diagnostic quality. In this study, we aimed to define consistent clinically relevant metrics for image and diagnostic quality in 3D LGE-MRI images of the left atrium, have multiple observers assess LGE-MRI image quality to identify key features that measure quality and intra/inter-observer variabilities, and train and test a CNN to assess image quality automatically., Methods: We identified four image quality categories that impact fibrosis assessment in LGE-MRI images and trained individuals to score 50 consecutive pre-ablation atrial fibrillation LGE-MRI scans from the University of Utah hospital image database. The trained individuals then scored 146 additional scans, which were used to train a convolutional neural network (CNN) to assess diagnostic quality., Results: There was excellent agreement among trained observers when scoring LGE-MRI scans, with inter-rater reliability scores ranging from 0.65 to 0.76 for each category. When the quality scores were converted to a binary diagnostic/non-diagnostic, the CNN achieved a sensitivity of 0.80 ± 0.06 and a specificity of 0.56 ± 0.10 ., Conclusion: The use of a training document with reference examples helped raters achieve excellent agreement in their quality scores. The CNN gave a reasonably accurate classification of diagnostic or non-diagnostic 3D LGE-MRI images of the left atrium, despite the use of a relatively small training set., Competing Interests: Declarations. Ethics approval: This retrospective study was approved by the University of Utah Internal Review Board (IRB). Consent to participate: This study was retrospective and was thus conducted on already available MRI data in the University of Utah Hospital database, so no patient consent was necessary. All MRI scans were de-identified. Competing interests: Ravi Ranjan has research grants and/or consults for Biosense Webster (Johnson and Johnson), Abbott (St Jude), Medtronic, and Boston Scientific. Alan Morris has equity interest in Marrek, Inc., which has licensed technologies from the University of Utah for performing 3D LGE-MRI of left atrium and quantification of fibrosis/scar from such scans. Alan Morris also serves as a consultant for Marrek, Inc. Eugene Kholmovski has equity interest in Marrek, Inc., which has licensed technologies from the University of Utah for performing 3D LGE-MRI of left atrium and quantification of fibrosis/scar from such scans. Eugene Kholmovski also serves as a consultant for Marrek, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
- Published
- 2024
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