Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.

<h4>Purpose</h4>Medulloblastoma (MB) is a highly malignant pediatric brain tumor. In the latest classification, medulloblastoma is divided into four distinct groups: wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4. We analyzed the magnetic resonance imaging radiomics features...

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Autores principales:	Feng-Chi Chang, Tai-Tong Wong, Kuo-Sheng Wu, Chia-Feng Lu, Ting-Wei Weng, Muh-Lii Liang, Chih-Chun Wu, Wan Yuo Guo, Cheng-Yu Chen, Kevin Li-Chun Hsieh
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/01143ad365d34de7b8192999c52f79a9
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spelling	oai:doaj.org-article:01143ad365d34de7b8192999c52f79a92021-12-02T20:08:54ZMagnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.1932-620310.1371/journal.pone.0255500https://doaj.org/article/01143ad365d34de7b8192999c52f79a92021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0255500https://doaj.org/toc/1932-6203<h4>Purpose</h4>Medulloblastoma (MB) is a highly malignant pediatric brain tumor. In the latest classification, medulloblastoma is divided into four distinct groups: wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4. We analyzed the magnetic resonance imaging radiomics features to find the imaging surrogates of the 4 molecular subgroups of MB.<h4>Material and methods</h4>Frozen tissue, imaging data, and clinical data of 38 patients with medulloblastoma were included from Taipei Medical University Hospital and Taipei Veterans General Hospital. Molecular clustering was performed based on the gene expression level of 22 subgroup-specific signature genes. A total 253 magnetic resonance imaging radiomic features were generated from each subject for comparison between different molecular subgroups.<h4>Results</h4>Our cohort consisted of 7 (18.4%) patients with WNT medulloblastoma, 12 (31.6%) with SHH tumor, 8 (21.1%) with Group 3 tumor, and 11 (28.9%) with Group 4 tumor. 8 radiomics gray-level co-occurrence matrix texture (GLCM) features were significantly different between 4 molecular subgroups of MB. In addition, for tumors with higher values in a gray-level run length matrix feature-Short Run Low Gray-Level Emphasis, patients have shorter survival times than patients with low values of this feature (p = 0.04). The receiver operating characteristic analysis revealed optimal performance of the preliminary prediction model based on GLCM features for predicting WNT, Group 3, and Group 4 MB (area under the curve = 0.82, 0.72, and 0.78, respectively).<h4>Conclusion</h4>The preliminary result revealed that 8 contrast-enhanced T1-weighted imaging texture features were significantly different between 4 molecular subgroups of MB. Together with the prediction models, the radiomics features may provide suggestions for stratifying patients with MB into different risk groups.Feng-Chi ChangTai-Tong WongKuo-Sheng WuChia-Feng LuTing-Wei WengMuh-Lii LiangChih-Chun WuWan Yuo GuoCheng-Yu ChenKevin Li-Chun HsiehPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0255500 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Feng-Chi Chang Tai-Tong Wong Kuo-Sheng Wu Chia-Feng Lu Ting-Wei Weng Muh-Lii Liang Chih-Chun Wu Wan Yuo Guo Cheng-Yu Chen Kevin Li-Chun Hsieh Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.
description	<h4>Purpose</h4>Medulloblastoma (MB) is a highly malignant pediatric brain tumor. In the latest classification, medulloblastoma is divided into four distinct groups: wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4. We analyzed the magnetic resonance imaging radiomics features to find the imaging surrogates of the 4 molecular subgroups of MB.<h4>Material and methods</h4>Frozen tissue, imaging data, and clinical data of 38 patients with medulloblastoma were included from Taipei Medical University Hospital and Taipei Veterans General Hospital. Molecular clustering was performed based on the gene expression level of 22 subgroup-specific signature genes. A total 253 magnetic resonance imaging radiomic features were generated from each subject for comparison between different molecular subgroups.<h4>Results</h4>Our cohort consisted of 7 (18.4%) patients with WNT medulloblastoma, 12 (31.6%) with SHH tumor, 8 (21.1%) with Group 3 tumor, and 11 (28.9%) with Group 4 tumor. 8 radiomics gray-level co-occurrence matrix texture (GLCM) features were significantly different between 4 molecular subgroups of MB. In addition, for tumors with higher values in a gray-level run length matrix feature-Short Run Low Gray-Level Emphasis, patients have shorter survival times than patients with low values of this feature (p = 0.04). The receiver operating characteristic analysis revealed optimal performance of the preliminary prediction model based on GLCM features for predicting WNT, Group 3, and Group 4 MB (area under the curve = 0.82, 0.72, and 0.78, respectively).<h4>Conclusion</h4>The preliminary result revealed that 8 contrast-enhanced T1-weighted imaging texture features were significantly different between 4 molecular subgroups of MB. Together with the prediction models, the radiomics features may provide suggestions for stratifying patients with MB into different risk groups.
format	article
author	Feng-Chi Chang Tai-Tong Wong Kuo-Sheng Wu Chia-Feng Lu Ting-Wei Weng Muh-Lii Liang Chih-Chun Wu Wan Yuo Guo Cheng-Yu Chen Kevin Li-Chun Hsieh
author_facet	Feng-Chi Chang Tai-Tong Wong Kuo-Sheng Wu Chia-Feng Lu Ting-Wei Weng Muh-Lii Liang Chih-Chun Wu Wan Yuo Guo Cheng-Yu Chen Kevin Li-Chun Hsieh
author_sort	Feng-Chi Chang
title	Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.
title_short	Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.
title_full	Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.
title_fullStr	Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.
title_full_unstemmed	Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.
title_sort	magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric medulloblastoma.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/01143ad365d34de7b8192999c52f79a9
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Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma.

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