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

PURPOSE: 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...

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Autores principales: Chang, Feng-Chi, Wong, Tai-Tong, Wu, Kuo-Sheng, Lu, Chia-Feng, Weng, Ting-Wei, Liang, Muh-Lii, Wu, Chih-Chun, Guo, Wan Yuo, Chen, Cheng-Yu, Hsieh, Kevin Li-Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321137/
https://www.ncbi.nlm.nih.gov/pubmed/34324588
http://dx.doi.org/10.1371/journal.pone.0255500
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author Chang, Feng-Chi
Wong, Tai-Tong
Wu, Kuo-Sheng
Lu, Chia-Feng
Weng, Ting-Wei
Liang, Muh-Lii
Wu, Chih-Chun
Guo, Wan Yuo
Chen, Cheng-Yu
Hsieh, Kevin Li-Chun
author_facet Chang, Feng-Chi
Wong, Tai-Tong
Wu, Kuo-Sheng
Lu, Chia-Feng
Weng, Ting-Wei
Liang, Muh-Lii
Wu, Chih-Chun
Guo, Wan Yuo
Chen, Cheng-Yu
Hsieh, Kevin Li-Chun
author_sort Chang, Feng-Chi
collection PubMed
description PURPOSE: 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. MATERIAL AND METHODS: 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. RESULTS: 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). CONCLUSION: 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.
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spelling pubmed-83211372021-07-31 Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma Chang, Feng-Chi Wong, Tai-Tong Wu, Kuo-Sheng Lu, Chia-Feng Weng, Ting-Wei Liang, Muh-Lii Wu, Chih-Chun Guo, Wan Yuo Chen, Cheng-Yu Hsieh, Kevin Li-Chun PLoS One Research Article PURPOSE: 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. MATERIAL AND METHODS: 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. RESULTS: 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). CONCLUSION: 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. Public Library of Science 2021-07-29 /pmc/articles/PMC8321137/ /pubmed/34324588 http://dx.doi.org/10.1371/journal.pone.0255500 Text en © 2021 Chang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Chang, Feng-Chi
Wong, Tai-Tong
Wu, Kuo-Sheng
Lu, Chia-Feng
Weng, Ting-Wei
Liang, Muh-Lii
Wu, Chih-Chun
Guo, Wan Yuo
Chen, Cheng-Yu
Hsieh, Kevin Li-Chun
Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma
title 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_short 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321137/
https://www.ncbi.nlm.nih.gov/pubmed/34324588
http://dx.doi.org/10.1371/journal.pone.0255500
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