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Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI

Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal...

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Autores principales: Zhang, Guangwen, Wang, Shuangshuang, Wen, Didi, Zhang, Jing, Wei, Xiaocheng, Ma, Wanling, Zhao, Weiwei, Wang, Mian, Wu, Guosheng, Zhang, Jinsong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5146921/
https://www.ncbi.nlm.nih.gov/pubmed/27934928
http://dx.doi.org/10.1038/srep38782
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author Zhang, Guangwen
Wang, Shuangshuang
Wen, Didi
Zhang, Jing
Wei, Xiaocheng
Ma, Wanling
Zhao, Weiwei
Wang, Mian
Wu, Guosheng
Zhang, Jinsong
author_facet Zhang, Guangwen
Wang, Shuangshuang
Wen, Didi
Zhang, Jing
Wei, Xiaocheng
Ma, Wanling
Zhao, Weiwei
Wang, Mian
Wu, Guosheng
Zhang, Jinsong
author_sort Zhang, Guangwen
collection PubMed
description Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal cancer, and to determine the optimal model for investigating the water diffusion properties and characterization of rectal carcinoma. Fifty-nine consecutive patients with pathologically confirmed rectal adenocarcinoma underwent DWI with 16 b-values at a 3.0 T MRI system. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models (IVIM-mono, IVIM-bi and SEM) on primary tumor and adjacent normal rectal tissue. Parameters of standard apparent diffusion coefficient (ADC), slow- and fast-ADC, fraction of fast ADC (f), α value and distributed diffusion coefficient (DDC) were generated and compared between the tumor and normal tissues. The SEM exhibited the best fitting results of actual DWI signal in rectal cancer and the normal rectal wall (R(2) = 0.998, 0.999 respectively). The DDC achieved relatively high area under the curve (AUC = 0.980) in differentiating tumor from normal rectal wall. Non-Gaussian diffusion models could assess tissue properties more accurately than the ADC derived Gaussian diffusion model. SEM may be used as a potential optimal model for characterization of rectal cancer.
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spelling pubmed-51469212016-12-16 Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI Zhang, Guangwen Wang, Shuangshuang Wen, Didi Zhang, Jing Wei, Xiaocheng Ma, Wanling Zhao, Weiwei Wang, Mian Wu, Guosheng Zhang, Jinsong Sci Rep Article Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal cancer, and to determine the optimal model for investigating the water diffusion properties and characterization of rectal carcinoma. Fifty-nine consecutive patients with pathologically confirmed rectal adenocarcinoma underwent DWI with 16 b-values at a 3.0 T MRI system. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models (IVIM-mono, IVIM-bi and SEM) on primary tumor and adjacent normal rectal tissue. Parameters of standard apparent diffusion coefficient (ADC), slow- and fast-ADC, fraction of fast ADC (f), α value and distributed diffusion coefficient (DDC) were generated and compared between the tumor and normal tissues. The SEM exhibited the best fitting results of actual DWI signal in rectal cancer and the normal rectal wall (R(2) = 0.998, 0.999 respectively). The DDC achieved relatively high area under the curve (AUC = 0.980) in differentiating tumor from normal rectal wall. Non-Gaussian diffusion models could assess tissue properties more accurately than the ADC derived Gaussian diffusion model. SEM may be used as a potential optimal model for characterization of rectal cancer. Nature Publishing Group 2016-12-09 /pmc/articles/PMC5146921/ /pubmed/27934928 http://dx.doi.org/10.1038/srep38782 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Zhang, Guangwen
Wang, Shuangshuang
Wen, Didi
Zhang, Jing
Wei, Xiaocheng
Ma, Wanling
Zhao, Weiwei
Wang, Mian
Wu, Guosheng
Zhang, Jinsong
Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI
title Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI
title_full Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI
title_fullStr Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI
title_full_unstemmed Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI
title_short Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI
title_sort comparison of non-gaussian and gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 t mri
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5146921/
https://www.ncbi.nlm.nih.gov/pubmed/27934928
http://dx.doi.org/10.1038/srep38782
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