Correction of B0-related distortions in diffusion-weighted images of malignant and normal cervical tissue

Motivation: DWI in cervical cancer evaluation suffers from distortions, especially pronounced by intestinal gas, potentially impeding lesion detection/delineation. Goal(s): To evaluate a combined prospective-retrospective distortion reduction approach, based on distortion correction of female pelvic DWI acquired with reduced-FOV. Approach: Two correction methods, RPG and Topup, were applied on images from cervical cancer patients and volunteers. Distortion correction performance was evaluated by the concordance between tumour/cervix borders in images before and after correction. Results: Topup outperformed RPG, with statistically significant but modest improvements of initially small distortions resulting from the reduced-FOV acquisition. Occasional correction failures and limitations in the proton density correction warrant alternative approaches. Impact: Topup distortion correction, commonly used for brain studies, shows statistically significant but modest improvements in female pelvic reduced-FOV DWI. Despite indications of clinical utility, limited improvements and occasional correction failures suggest alternative approaches and prospective distortion reduction as potential strategies.

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
2024-11-26
DOI
https://doi.org/10.58530/2024/2581
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

Correction of B0-related distortions in diffusion-weighted images of malignant and normal cervical tissue

Joshua Kuperman, Rebecca Rakow‐Penner, Katarzyna Kozar, Elin Lundström 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
Radiomics and Machine Learning in Medical Imaging
article

Correction of B0-related distortions in diffusion-weighted images of malignant and normal cervical tissue

Joshua Kuperman, Rebecca Rakow‐Penner, Katarzyna Kozar, Elin Lundström, Björg Jónsdóttir, Stéphane Loubrie, Ana Rodríguez-Soto, Stephan Jordan, Marianne S. Hom, Alexandra Schlein, Tyler M. Seibert, Elisabeth Hedlund, Michael G. Hahn, Anthoula Koliadi, Anders M. Dale, Christopher C. Conlin, Sheida Ebrahimi, Per Liss, Shira Varon, Alexandra H. Besser, Cheryl Saenz, Michael McHale
article en

Abstract

Motivation: DWI in cervical cancer evaluation suffers from distortions, especially pronounced by intestinal gas, potentially impeding lesion detection/delineation. Goal(s): To evaluate a combined prospective-retrospective distortion reduction approach, based on distortion correction of female pelvic DWI acquired with reduced-FOV. Approach: Two correction methods, RPG and Topup, were applied on images from cervical cancer patients and volunteers. Distortion correction performance was evaluated by the concordance between tumour/cervix borders in images before and after correction. Results: Topup outperformed RPG, with statistically significant but modest improvements of initially small distortions resulting from the reduced-FOV acquisition. Occasional correction failures and limitations in the proton density correction warrant alternative approaches. Impact: Topup distortion correction, commonly used for brain studies, shows statistically significant but modest improvements in female pelvic reduced-FOV DWI. Despite indications of clinical utility, limited improvements and occasional correction failures suggest alternative approaches and prospective distortion reduction as potential strategies.

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
Good health and well-being
Openalex Percentile: Top 65%
Radiomics and Machine Learning in Medical Imaging
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