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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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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. |
format | Online Article Text |
id | pubmed-8321137 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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