Deep Learning Reconstruction Enables Accelerated Prostate MRI Without Compromising Reader-Assessed Visual Quality

Motivation: MRI demand for prostate cancer detection is rising, necessitating reduced scan times. While deep learning (DL) shows promise for accelerating MRI, the perceived visual quality of DL-reconstructed images by expert radiologists remains underexplored. Goal(s): To assess expert radiologists' perceived visual quality of DL-reconstructed prostate MRI scans with various acceleration factors (3x, 6x). Approach: A retrospective study with 120 prostate MRIs was conducted. Expert radiologists evaluated image quality using a split-plot design and ordinal mixed-effects modeling. Results: Up to 6x acceleration did not significantly reduce perceived image quality. Interestingly, 3x accelerated images even improved perceived quality compared to non-accelerated images. Impact: DL-based reconstruction can generate high-quality T2-weighted prostate MRIs from accelerated acquisitions without any perceived loss in overall visual quality by expert radiologists compared with the original non-accelerated images.

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/10.58530/2025/2649
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
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article

Deep Learning Reconstruction Enables Accelerated Prostate MRI Without Compromising Reader-Assessed Visual Quality

Jaap Borstlap, Frank Simonis, Jasper J. Twilt, Barış Türkbey 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
Prostate Cancer Diagnosis and Treatment
article

Deep Learning Reconstruction Enables Accelerated Prostate MRI Without Compromising Reader-Assessed Visual Quality

Jaap Borstlap, Frank Simonis, Jasper J. Twilt, Barış Türkbey, Thomas C. Kwee, Jonas Teuwen, Stefan J. Fransen, Quintin van Lohuizen, Jurgen J. Fütterer, Dennis B. Rouw, HenkJan J. Huisman, Christian Roest, S Whitney, Yuki Arita, George Yiasemis, Derya Yakar, Ivo G. Schoots, Maarten de Rooij
article en

Abstract

Motivation: MRI demand for prostate cancer detection is rising, necessitating reduced scan times. While deep learning (DL) shows promise for accelerating MRI, the perceived visual quality of DL-reconstructed images by expert radiologists remains underexplored. Goal(s): To assess expert radiologists' perceived visual quality of DL-reconstructed prostate MRI scans with various acceleration factors (3x, 6x). Approach: A retrospective study with 120 prostate MRIs was conducted. Expert radiologists evaluated image quality using a split-plot design and ordinal mixed-effects modeling. Results: Up to 6x acceleration did not significantly reduce perceived image quality. Interestingly, 3x accelerated images even improved perceived quality compared to non-accelerated images. Impact: DL-based reconstruction can generate high-quality T2-weighted prostate MRIs from accelerated acquisitions without any perceived loss in overall visual quality by expert radiologists compared with the original non-accelerated images.

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 64%
Prostate Cancer Diagnosis and Treatment
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