HR-DWI with Super-Resolution DLR vs. Conventional DWI: Scan Time, Image Quality and Diagnostic Performance in Hepato-Pancreato-Biliary Tumors

Motivation: Super-resolution deep learning reconstruction (SR-DLR) improves image quality and differentiation capability of hepato-pancreato-biliary (HPB) tumors on high-resolution diffusion-weighted imaging (HR-DWIs) obtained with different NEXs as compared with conventional diffusion-weighted imaging (cDWI). Goal(s): The goal was to compare capability of SR-DLR for improving image quality and HPB tumor differentiation among cDWI and HR-DWIs with different NEXs. Approach: This clinical study obtained cDWI and HR-DWIs , and diagnostic performance was statistically compared among all DWIs. Results: Specificities and accuracies of HR-DWIs with 1, 3 or 5 NEXs were significantly higher than those of cDWI (p<0.05). Impact: SR-DLR had superior potential for acquisition time reduction with image quality and diagnostic capability improvements on HR-DWI, when compared with cDWI. When applied SR-DLR for HR-DWI, 3 NEX would be better to be applied in this setting.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/2674
Primary Topic
Pancreatic and Hepatic Oncology Research
Type
article
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article

HR-DWI with Super-Resolution DLR vs. Conventional DWI: Scan Time, Image Quality and Diagnostic Performance in Hepato-Pancreato-Biliary Tumors

Masao Yui, Daisuke Takenaka, Masanori Ozaki, Takeshi Yoshikawa et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Pancreatic and Hepatic Oncology Research
article

HR-DWI with Super-Resolution DLR vs. Conventional DWI: Scan Time, Image Quality and Diagnostic Performance in Hepato-Pancreato-Biliary Tumors

Masao Yui, Daisuke Takenaka, Masanori Ozaki, Takeshi Yoshikawa, Hiroyuki Nagata, Kaori Yamamoto, Takahiro Ueda, Yoshiharu Ohno, Masato Ikedo, Yoshiyuki Ozawa, Masahiko Nomura, Yuichiro Sano
article en

Abstract

Motivation: Super-resolution deep learning reconstruction (SR-DLR) improves image quality and differentiation capability of hepato-pancreato-biliary (HPB) tumors on high-resolution diffusion-weighted imaging (HR-DWIs) obtained with different NEXs as compared with conventional diffusion-weighted imaging (cDWI). Goal(s): The goal was to compare capability of SR-DLR for improving image quality and HPB tumor differentiation among cDWI and HR-DWIs with different NEXs. Approach: This clinical study obtained cDWI and HR-DWIs , and diagnostic performance was statistically compared among all DWIs. Results: Specificities and accuracies of HR-DWIs with 1, 3 or 5 NEXs were significantly higher than those of cDWI (p<0.05). Impact: SR-DLR had superior potential for acquisition time reduction with image quality and diagnostic capability improvements on HR-DWI, when compared with cDWI. When applied SR-DLR for HR-DWI, 3 NEX would be better to be applied in this setting.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 66%
Pancreatic and Hepatic Oncology Research
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HR-DWI with Super-Resolution DLR vs. Conventional DWI: Scan Time, Image Quality and Diagnostic Performance in Hepato-Pancreato-Biliary Tumors — Masao Yui, Daisuke Takenaka, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2025) | TGRS Research Map | TGRS