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A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate

A computational algorithm was designed to produce a measure of DW image distortion across the prostate. This algorithm was tested and validated on virtual phantoms incorporating known degrees and distributions of distortion. A study was then carried out on DW image volumes from three sets of 10 pati...

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Autores principales: Gill, Andrew B., Czarniecki, Marcin, Gallagher, Ferdia A., Barrett, Tristan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5629196/
https://www.ncbi.nlm.nih.gov/pubmed/28983116
http://dx.doi.org/10.1038/s41598-017-13097-6
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author Gill, Andrew B.
Czarniecki, Marcin
Gallagher, Ferdia A.
Barrett, Tristan
author_facet Gill, Andrew B.
Czarniecki, Marcin
Gallagher, Ferdia A.
Barrett, Tristan
author_sort Gill, Andrew B.
collection PubMed
description A computational algorithm was designed to produce a measure of DW image distortion across the prostate. This algorithm was tested and validated on virtual phantoms incorporating known degrees and distributions of distortion. A study was then carried out on DW image volumes from three sets of 10 patients who had been imaged previously. These volumes had been radiologically assessed to have, respectively, ‘no distortion’ or ‘significant distortion’ or the potential for ‘significant distortion’ due to susceptibility effects from hip prostheses. Prostate outlines were drawn on a T2-weighted (T2W) image ‘gold-standard’ volume and on an ADC image volume derived from DW images acquired over the same region. The algorithm was then applied to these outlines to quantify and map image distortion. The proposed method correctly reproduced known distortion values and distributions in virtual phantoms. It also successfully distinguished between the three groups of patients: mean distortion in ‘non-distorted’ image volumes, 1.942 ± 0.582 mm; ‘distorted’, 4.402 ± 1.098 mm; and ‘hip patients’ 8.083 ± 4.653 mm; P < 0.001. This work has demonstrated and validated a means of quantifying and mapping image distortion in clinical prostate MRI cases.
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spelling pubmed-56291962017-10-13 A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate Gill, Andrew B. Czarniecki, Marcin Gallagher, Ferdia A. Barrett, Tristan Sci Rep Article A computational algorithm was designed to produce a measure of DW image distortion across the prostate. This algorithm was tested and validated on virtual phantoms incorporating known degrees and distributions of distortion. A study was then carried out on DW image volumes from three sets of 10 patients who had been imaged previously. These volumes had been radiologically assessed to have, respectively, ‘no distortion’ or ‘significant distortion’ or the potential for ‘significant distortion’ due to susceptibility effects from hip prostheses. Prostate outlines were drawn on a T2-weighted (T2W) image ‘gold-standard’ volume and on an ADC image volume derived from DW images acquired over the same region. The algorithm was then applied to these outlines to quantify and map image distortion. The proposed method correctly reproduced known distortion values and distributions in virtual phantoms. It also successfully distinguished between the three groups of patients: mean distortion in ‘non-distorted’ image volumes, 1.942 ± 0.582 mm; ‘distorted’, 4.402 ± 1.098 mm; and ‘hip patients’ 8.083 ± 4.653 mm; P < 0.001. This work has demonstrated and validated a means of quantifying and mapping image distortion in clinical prostate MRI cases. Nature Publishing Group UK 2017-10-05 /pmc/articles/PMC5629196/ /pubmed/28983116 http://dx.doi.org/10.1038/s41598-017-13097-6 Text en © The Author(s) 2017 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
Gill, Andrew B.
Czarniecki, Marcin
Gallagher, Ferdia A.
Barrett, Tristan
A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate
title A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate
title_full A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate
title_fullStr A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate
title_full_unstemmed A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate
title_short A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate
title_sort method for mapping and quantifying whole organ diffusion-weighted image distortion in mr imaging of the prostate
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5629196/
https://www.ncbi.nlm.nih.gov/pubmed/28983116
http://dx.doi.org/10.1038/s41598-017-13097-6
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