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Utility of CT texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma
The purpose of this study was to examine differences in texture features between olfactory neuroblastoma (ONB) and sinonasal squamous cell carcinoma (SCC) on contrast-enhanced CT (CECT) images, and to evaluate the predictive accuracy of texture analysis compared to radiologists’ interpretations. For...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907098/ https://www.ncbi.nlm.nih.gov/pubmed/33633160 http://dx.doi.org/10.1038/s41598-021-84048-5 |
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author | Ogawa, Masaki Osaga, Satoshi Shiraki, Norio Kawakita, Daisuke Hanai, Nobuhiro Tamaki, Tsuneo Tsukahara, Satoshi Kawaguchi, Takatsune Urano, Misugi Shibamoto, Yuta |
author_facet | Ogawa, Masaki Osaga, Satoshi Shiraki, Norio Kawakita, Daisuke Hanai, Nobuhiro Tamaki, Tsuneo Tsukahara, Satoshi Kawaguchi, Takatsune Urano, Misugi Shibamoto, Yuta |
author_sort | Ogawa, Masaki |
collection | PubMed |
description | The purpose of this study was to examine differences in texture features between olfactory neuroblastoma (ONB) and sinonasal squamous cell carcinoma (SCC) on contrast-enhanced CT (CECT) images, and to evaluate the predictive accuracy of texture analysis compared to radiologists’ interpretations. Forty-three patients with pathologically-diagnosed primary nasal and paranasal tumor (17 ONB and 26 SCC) were included. We extracted 42 texture features from tumor regions on CECT images obtained before treatment. In univariate analysis, each texture features were compared, with adjustment for multiple comparisons. In multivariate analysis, the elastic net was used to select useful texture features and to construct a texture-based prediction model with leave-one-out cross-validation. The prediction accuracy was compared with two radiologists’ visual interpretations. In univariate analysis, significant differences were observed for 28 of 42 texture features between ONB and SCC, with areas under the receiver operating characteristic curve between 0.68 and 0.91 (median: 0.80). In multivariate analysis, the elastic net model selected 18 texture features that contributed to differentiation. It tended to show slightly higher predictive accuracy than radiologists’ interpretations (86% and 74%, respectively; P = 0.096). In conclusion, several texture features contributed to differentiation of ONB from SCC, and the texture-based prediction model was considered useful. |
format | Online Article Text |
id | pubmed-7907098 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79070982021-02-26 Utility of CT texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma Ogawa, Masaki Osaga, Satoshi Shiraki, Norio Kawakita, Daisuke Hanai, Nobuhiro Tamaki, Tsuneo Tsukahara, Satoshi Kawaguchi, Takatsune Urano, Misugi Shibamoto, Yuta Sci Rep Article The purpose of this study was to examine differences in texture features between olfactory neuroblastoma (ONB) and sinonasal squamous cell carcinoma (SCC) on contrast-enhanced CT (CECT) images, and to evaluate the predictive accuracy of texture analysis compared to radiologists’ interpretations. Forty-three patients with pathologically-diagnosed primary nasal and paranasal tumor (17 ONB and 26 SCC) were included. We extracted 42 texture features from tumor regions on CECT images obtained before treatment. In univariate analysis, each texture features were compared, with adjustment for multiple comparisons. In multivariate analysis, the elastic net was used to select useful texture features and to construct a texture-based prediction model with leave-one-out cross-validation. The prediction accuracy was compared with two radiologists’ visual interpretations. In univariate analysis, significant differences were observed for 28 of 42 texture features between ONB and SCC, with areas under the receiver operating characteristic curve between 0.68 and 0.91 (median: 0.80). In multivariate analysis, the elastic net model selected 18 texture features that contributed to differentiation. It tended to show slightly higher predictive accuracy than radiologists’ interpretations (86% and 74%, respectively; P = 0.096). In conclusion, several texture features contributed to differentiation of ONB from SCC, and the texture-based prediction model was considered useful. Nature Publishing Group UK 2021-02-25 /pmc/articles/PMC7907098/ /pubmed/33633160 http://dx.doi.org/10.1038/s41598-021-84048-5 Text en © The Author(s) 2021 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ogawa, Masaki Osaga, Satoshi Shiraki, Norio Kawakita, Daisuke Hanai, Nobuhiro Tamaki, Tsuneo Tsukahara, Satoshi Kawaguchi, Takatsune Urano, Misugi Shibamoto, Yuta Utility of CT texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma |
title | Utility of CT texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma |
title_full | Utility of CT texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma |
title_fullStr | Utility of CT texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma |
title_full_unstemmed | Utility of CT texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma |
title_short | Utility of CT texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma |
title_sort | utility of ct texture analysis to differentiate olfactory neuroblastoma from sinonasal squamous cell carcinoma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907098/ https://www.ncbi.nlm.nih.gov/pubmed/33633160 http://dx.doi.org/10.1038/s41598-021-84048-5 |
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