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Accelerated Diffusion-Weighted Magnetic Resonance Imaging of the Liver at 1.5 T With Deep Learning-Based Image Reconstruction: Impact on Image Quality and Lesion Detection.
- Source :
-
Journal of computer assisted tomography [J Comput Assist Tomogr] 2024 May 06. Date of Electronic Publication: 2024 May 06. - Publication Year :
- 2024
- Publisher :
- Ahead of Print
-
Abstract
- Objective: To perform image quality comparison between deep learning-based multiband diffusion-weighted sequence (DL-mb-DWI), accelerated multiband diffusion-weighted sequence (accelerated mb-DWI), and conventional multiband diffusion-weighted sequence (conventional mb-DWI) in patients undergoing clinical liver magnetic resonance imaging (MRI).<br />Methods: Fifty consecutive patients who underwent clinical MRI of the liver at a 1.5-T scanner, between September 1, 2021, and January 31, 2022, were included in this study. Three radiologists independently reviewed images using a 5-point Likert scale for artifacts and image quality factors, in addition to assessing the presence of liver lesions and lesion conspicuity.<br />Results: DL-mb-DWI acquisition time was 65.0 ± 2.4 seconds, significantly (P < 0.001) shorter than conventional mb-DWI (147.5 ± 19.2 seconds) and accelerated mb-DWI (94.3 ± 1.8 seconds). DL-mb-DWI received significantly higher scores than conventional mb-DWI for conspicuity of the left lobe (P < 0.001), sharpness of intrahepatic vessel margin (P < 0.001), sharpness of the pancreatic contour (P < 0.001), in-plane motion artifact (P = 0.002), and overall image quality (P = 0.005) by reader 2. DL-mb-DWI received significantly higher scores for conspicuity of the left lobe (P = 0.006), sharpness of the pancreatic contour (P = 0.020), and in-plane motion artifact (P = 0.042) by reader 3. DL-mb-DWI received significantly higher scores for strength of fat suppression (P = 0.004) and sharpness of the pancreatic contour (P = 0.038) by reader 1. The remaining quality parameters did not reach statistical significance for reader 1.<br />Conclusions: Novel diffusion-weighted MRI sequence with deep learning-based image reconstruction demonstrated significantly decreased acquisition times compared with conventional and accelerated mb-DWI sequences, while maintaining or improving image quality for routine abdominal MRI. DL-mb-DWI offers a potential alternative to conventional mb-DWI in routine clinical liver MRI.<br />Competing Interests: Thomas Benkert is a Siemens Healthcare employee, who provided technical assistance, but was not involved in the data acquisition or evaluation, nor had direct control of the data. The other authors declare no conflict of interest.<br /> (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1532-3145
- Database :
- MEDLINE
- Journal :
- Journal of computer assisted tomography
- Publication Type :
- Academic Journal
- Accession number :
- 38722777
- Full Text :
- https://doi.org/10.1097/RCT.0000000000001622