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Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline

Diffusion tensor imaging (DTI) is particularly suitable for kidney studies due to tubules, collector ducts and blood vessels in the medulla that produce spatially restricted diffusion of water molecules, thus reflecting the high grade of anisotropy detectable by DTI. Kidney DTI is still a challengin...

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Autores principales: Borrelli, Pasquale, Cavaliere, Carlo, Basso, Luca, Soricelli, Andrea, Salvatore, Marco, Aiello, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726597/
https://www.ncbi.nlm.nih.gov/pubmed/31484949
http://dx.doi.org/10.1038/s41598-019-49170-5
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author Borrelli, Pasquale
Cavaliere, Carlo
Basso, Luca
Soricelli, Andrea
Salvatore, Marco
Aiello, Marco
author_facet Borrelli, Pasquale
Cavaliere, Carlo
Basso, Luca
Soricelli, Andrea
Salvatore, Marco
Aiello, Marco
author_sort Borrelli, Pasquale
collection PubMed
description Diffusion tensor imaging (DTI) is particularly suitable for kidney studies due to tubules, collector ducts and blood vessels in the medulla that produce spatially restricted diffusion of water molecules, thus reflecting the high grade of anisotropy detectable by DTI. Kidney DTI is still a challenging technique where the off-resonance susceptibility artefacts and subject motion can severely affect the reproducibility of results. The aim of this study is to design a reliable processing pipeline by assessing different image processing approaches in terms of reproducibility and image artefacts correction. The results of four different processing pipelines (eddy: correction of eddy-currents and motion between DTI volume; eddy-s2v: eddy and within DTI volume motion correction; topup: eddy and geometric distortion correction; topup-s2v: topup and within DTI volume motion correction) are compared in terms of reproducibility by test-retest analysis in 14 healthy subjects. Within-subject coefficient of variation (wsCV) and intra-class correlation coefficient (ICC) are measured to assess the reproducibility and Dice similarity index is evaluated for the spatial alignment between DTI and anatomical images. Topup-s2v pipeline provides highest reproducibility (wsCV = 0.053, ICC = 0.814) and best correction of image distortion (Dice = 0.83). This study definitely provides a recipe for data processing, enabling for a clinical suitability of kidney DTI.
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spelling pubmed-67265972019-09-18 Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline Borrelli, Pasquale Cavaliere, Carlo Basso, Luca Soricelli, Andrea Salvatore, Marco Aiello, Marco Sci Rep Article Diffusion tensor imaging (DTI) is particularly suitable for kidney studies due to tubules, collector ducts and blood vessels in the medulla that produce spatially restricted diffusion of water molecules, thus reflecting the high grade of anisotropy detectable by DTI. Kidney DTI is still a challenging technique where the off-resonance susceptibility artefacts and subject motion can severely affect the reproducibility of results. The aim of this study is to design a reliable processing pipeline by assessing different image processing approaches in terms of reproducibility and image artefacts correction. The results of four different processing pipelines (eddy: correction of eddy-currents and motion between DTI volume; eddy-s2v: eddy and within DTI volume motion correction; topup: eddy and geometric distortion correction; topup-s2v: topup and within DTI volume motion correction) are compared in terms of reproducibility by test-retest analysis in 14 healthy subjects. Within-subject coefficient of variation (wsCV) and intra-class correlation coefficient (ICC) are measured to assess the reproducibility and Dice similarity index is evaluated for the spatial alignment between DTI and anatomical images. Topup-s2v pipeline provides highest reproducibility (wsCV = 0.053, ICC = 0.814) and best correction of image distortion (Dice = 0.83). This study definitely provides a recipe for data processing, enabling for a clinical suitability of kidney DTI. Nature Publishing Group UK 2019-09-04 /pmc/articles/PMC6726597/ /pubmed/31484949 http://dx.doi.org/10.1038/s41598-019-49170-5 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Borrelli, Pasquale
Cavaliere, Carlo
Basso, Luca
Soricelli, Andrea
Salvatore, Marco
Aiello, Marco
Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline
title Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline
title_full Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline
title_fullStr Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline
title_full_unstemmed Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline
title_short Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline
title_sort diffusion tensor imaging of the kidney: design and evaluation of a reliable processing pipeline
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726597/
https://www.ncbi.nlm.nih.gov/pubmed/31484949
http://dx.doi.org/10.1038/s41598-019-49170-5
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