Improved Image Quality, Diagnostic Performance, and Reading Efficiency Based on Deep Learning-Reconstructed Accelerated Rectal MRI

Motivation: Accelerated MRI is an imminent need clinically to satisfy the growing disease burden of rectal cancer. Goal(s): This study aims to conduct clinical assessment of DLR-based accelerated rectal MRI, encompassing image acquisition, image quality, diagnostic performance, and reding efficiency. Approach: Two sets of T2WI using standard fast spin-echo (FSEstandard) and DLR-based accelerated FSE (FSEDL) were prospectively compared. Results: FSEDL showed superior image quality and reading efficiency than FSEstandard, with a 65% reduction in acquisition time. DLR could assist to enhance the accuracy of T-staging for junior radiologists, preserving equivalent diagnostic performance in N staging, EMVI, and MRF. Impact: This study offered a comprehensive and viable perspective on the application of DLR in rectal MRI, which facilitated improved image quality and reading efficiency, while reducing acquisition time. Moreover, it enhanced the accuracy of T-staging for junior radiologists.

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/10.58530/2025/1207
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

Improved Image Quality, Diagnostic Performance, and Reading Efficiency Based on Deep Learning-Reconstructed Accelerated Rectal MRI

Wenjing Peng, Hongmei Zhang, Sicong Wang
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
Radiomics and Machine Learning in Medical Imaging
article

Improved Image Quality, Diagnostic Performance, and Reading Efficiency Based on Deep Learning-Reconstructed Accelerated Rectal MRI

Wenjing Peng, Hongmei Zhang, Sicong Wang
article en

Abstract

Motivation: Accelerated MRI is an imminent need clinically to satisfy the growing disease burden of rectal cancer. Goal(s): This study aims to conduct clinical assessment of DLR-based accelerated rectal MRI, encompassing image acquisition, image quality, diagnostic performance, and reding efficiency. Approach: Two sets of T2WI using standard fast spin-echo (FSEstandard) and DLR-based accelerated FSE (FSEDL) were prospectively compared. Results: FSEDL showed superior image quality and reading efficiency than FSEstandard, with a 65% reduction in acquisition time. DLR could assist to enhance the accuracy of T-staging for junior radiologists, preserving equivalent diagnostic performance in N staging, EMVI, and MRF. Impact: This study offered a comprehensive and viable perspective on the application of DLR in rectal MRI, which facilitated improved image quality and reading efficiency, while reducing acquisition time. Moreover, it enhanced the accuracy of T-staging for junior radiologists.

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 65%
Radiomics and Machine Learning in Medical Imaging
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