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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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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. |
format | Online Article Text |
id | pubmed-4814112 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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