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Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images

INTRODUCTION: Diffusion Weighted Imaging (DWI), which is based on Echo Planar Imaging (EPI) protocols, is becoming increasingly important for neurosurgical applications. However, its use in this context is limited in part by significant spatial distortion inherent to EPI. METHOD: We evaluated an eff...

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Autores principales: Treiber, Jeffrey Mark, White, Nathan S., Steed, Tyler Christian, Bartsch, Hauke, Holland, Dominic, Farid, Nikdokht, McDonald, Carrie R., Carter, Bob S., Dale, Anders Martin, Chen, Clark C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814112/
https://www.ncbi.nlm.nih.gov/pubmed/27027775
http://dx.doi.org/10.1371/journal.pone.0152472
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author Treiber, Jeffrey Mark
White, Nathan S.
Steed, Tyler Christian
Bartsch, Hauke
Holland, Dominic
Farid, Nikdokht
McDonald, Carrie R.
Carter, Bob S.
Dale, Anders Martin
Chen, Clark C.
author_facet Treiber, Jeffrey Mark
White, Nathan S.
Steed, Tyler Christian
Bartsch, Hauke
Holland, Dominic
Farid, Nikdokht
McDonald, Carrie R.
Carter, Bob S.
Dale, Anders Martin
Chen, Clark C.
author_sort Treiber, Jeffrey Mark
collection PubMed
description INTRODUCTION: Diffusion Weighted Imaging (DWI), which is based on Echo Planar Imaging (EPI) protocols, is becoming increasingly important for neurosurgical applications. However, its use in this context is limited in part by significant spatial distortion inherent to EPI. METHOD: We evaluated an efficient algorithm for EPI distortion correction (EPIC) across 814 DWI scans from 250 brain tumor patients and quantified the magnitude of geometric distortion for whole brain and multiple brain regions. RESULTS: Evaluation of the algorithm’s performance revealed significantly higher mutual information between T1-weighted pre-contrast images and corrected b = 0 images than the uncorrected b = 0 images (p < 0.001). The distortion magnitude across all voxels revealed a median EPI distortion effect of 2.1 mm, ranging from 1.2 mm to 5.9 mm, the 5(th) and 95(th) percentile, respectively. Regions adjacent to bone-air interfaces, such as the orbitofrontal cortex, temporal poles, and brain stem, were the regions most severely affected by DWI distortion. CONCLUSION: Using EPIC to estimate the degree of distortion in 814 DWI brain tumor images enabled the creation of a topographic atlas of DWI distortion across the brain. The degree of displacement of tumors boundaries in uncorrected images is severe but can be corrected for using EPIC. Our results support the use of distortion correction to ensure accurate and careful application of DWI to neurosurgical practice.
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spelling pubmed-48141122016-04-05 Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images Treiber, Jeffrey Mark White, Nathan S. Steed, Tyler Christian Bartsch, Hauke Holland, Dominic Farid, Nikdokht McDonald, Carrie R. Carter, Bob S. Dale, Anders Martin Chen, Clark C. PLoS One Research Article INTRODUCTION: Diffusion Weighted Imaging (DWI), which is based on Echo Planar Imaging (EPI) protocols, is becoming increasingly important for neurosurgical applications. However, its use in this context is limited in part by significant spatial distortion inherent to EPI. METHOD: We evaluated an efficient algorithm for EPI distortion correction (EPIC) across 814 DWI scans from 250 brain tumor patients and quantified the magnitude of geometric distortion for whole brain and multiple brain regions. RESULTS: Evaluation of the algorithm’s performance revealed significantly higher mutual information between T1-weighted pre-contrast images and corrected b = 0 images than the uncorrected b = 0 images (p < 0.001). The distortion magnitude across all voxels revealed a median EPI distortion effect of 2.1 mm, ranging from 1.2 mm to 5.9 mm, the 5(th) and 95(th) percentile, respectively. Regions adjacent to bone-air interfaces, such as the orbitofrontal cortex, temporal poles, and brain stem, were the regions most severely affected by DWI distortion. CONCLUSION: Using EPIC to estimate the degree of distortion in 814 DWI brain tumor images enabled the creation of a topographic atlas of DWI distortion across the brain. The degree of displacement of tumors boundaries in uncorrected images is severe but can be corrected for using EPIC. Our results support the use of distortion correction to ensure accurate and careful application of DWI to neurosurgical practice. Public Library of Science 2016-03-30 /pmc/articles/PMC4814112/ /pubmed/27027775 http://dx.doi.org/10.1371/journal.pone.0152472 Text en © 2016 Treiber et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Treiber, Jeffrey Mark
White, Nathan S.
Steed, Tyler Christian
Bartsch, Hauke
Holland, Dominic
Farid, Nikdokht
McDonald, Carrie R.
Carter, Bob S.
Dale, Anders Martin
Chen, Clark C.
Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images
title Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images
title_full Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images
title_fullStr Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images
title_full_unstemmed Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images
title_short Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images
title_sort characterization and correction of geometric distortions in 814 diffusion weighted images
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814112/
https://www.ncbi.nlm.nih.gov/pubmed/27027775
http://dx.doi.org/10.1371/journal.pone.0152472
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