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Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models

PURPOSE: The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer. MATERIAL AND METHODS: Nineteen patients with rectal adenocarcinoma underwent MRI examin...

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Autores principales: Manikis, Georgios C., Marias, Kostas, Lambregts, Doenja M. J., Nikiforaki, Katerina, van Heeswijk, Miriam M., Bakers, Frans C. H., Beets-Tan, Regina G. H., Papanikolaou, Nikolaos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593499/
https://www.ncbi.nlm.nih.gov/pubmed/28863161
http://dx.doi.org/10.1371/journal.pone.0184197
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author Manikis, Georgios C.
Marias, Kostas
Lambregts, Doenja M. J.
Nikiforaki, Katerina
van Heeswijk, Miriam M.
Bakers, Frans C. H.
Beets-Tan, Regina G. H.
Papanikolaou, Nikolaos
author_facet Manikis, Georgios C.
Marias, Kostas
Lambregts, Doenja M. J.
Nikiforaki, Katerina
van Heeswijk, Miriam M.
Bakers, Frans C. H.
Beets-Tan, Regina G. H.
Papanikolaou, Nikolaos
author_sort Manikis, Georgios C.
collection PubMed
description PURPOSE: The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer. MATERIAL AND METHODS: Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm(2)) at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG) and non-Gaussian (MNG and BNG) were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R(2) and Root Mean Square Error (RMSE). To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC) and F-ratio. RESULTS: All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area. CONCLUSION: No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior.
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spelling pubmed-55934992017-09-15 Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models Manikis, Georgios C. Marias, Kostas Lambregts, Doenja M. J. Nikiforaki, Katerina van Heeswijk, Miriam M. Bakers, Frans C. H. Beets-Tan, Regina G. H. Papanikolaou, Nikolaos PLoS One Research Article PURPOSE: The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer. MATERIAL AND METHODS: Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm(2)) at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG) and non-Gaussian (MNG and BNG) were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R(2) and Root Mean Square Error (RMSE). To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC) and F-ratio. RESULTS: All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area. CONCLUSION: No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior. Public Library of Science 2017-09-01 /pmc/articles/PMC5593499/ /pubmed/28863161 http://dx.doi.org/10.1371/journal.pone.0184197 Text en © 2017 Manikis 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
Manikis, Georgios C.
Marias, Kostas
Lambregts, Doenja M. J.
Nikiforaki, Katerina
van Heeswijk, Miriam M.
Bakers, Frans C. H.
Beets-Tan, Regina G. H.
Papanikolaou, Nikolaos
Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models
title Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models
title_full Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models
title_fullStr Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models
title_full_unstemmed Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models
title_short Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models
title_sort diffusion weighted imaging in patients with rectal cancer: comparison between gaussian and non-gaussian models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593499/
https://www.ncbi.nlm.nih.gov/pubmed/28863161
http://dx.doi.org/10.1371/journal.pone.0184197
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