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(18)F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma
BACKGROUND: The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) promoter has emerged as a favorable independent prognostic and predictive biomarker in glioma. This study aimed to build a radiomics signature based on (18)F-fluorodeoxyglucose (FDG) positron emission tomograph...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701097/ https://www.ncbi.nlm.nih.gov/pubmed/31426864 http://dx.doi.org/10.1186/s40644-019-0246-0 |
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author | Kong, Ziren Lin, Yusong Jiang, Chendan Li, Longfei Liu, Zehua Wang, Yuekun Dai, Congxin Liu, Delin Qin, Xuying Wang, Yu Liu, Zhenyu Cheng, Xin Tian, Jie Ma, Wenbin |
author_facet | Kong, Ziren Lin, Yusong Jiang, Chendan Li, Longfei Liu, Zehua Wang, Yuekun Dai, Congxin Liu, Delin Qin, Xuying Wang, Yu Liu, Zhenyu Cheng, Xin Tian, Jie Ma, Wenbin |
author_sort | Kong, Ziren |
collection | PubMed |
description | BACKGROUND: The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) promoter has emerged as a favorable independent prognostic and predictive biomarker in glioma. This study aimed to build a radiomics signature based on (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) for noninvasive measurement of the MGMT promoter methylation status in glioma. METHODS: One hundred and seven pathology-confirmed primary diffuse glioma patients were retrospectively included and randomly assigned to the primary (n = 71) or validation cohort (n = 36). The MGMT promoter methylation status was measured by pyrosequencing. A total of 1561 radiomics features were extracted from the three-dimensional region of interest (ROI) on the standard uptake value (SUV) maps that were generated from the original (18)F-FDG PET data. A radiomics signature, a clinical signature and a fusion signature that combined the clinical and radiomics features together were generated. The performance of the three signatures was evaluated by receiver operating characteristic (ROC) curve analysis, and the patient prognosis was stratified based on the MGMT promoter methylation status and the signature with the best performance. RESULTS: Five radiomics features were selected to construct the radiomics signature, and displayed the best performance with area under the receiver operating characteristic (ROC) curve (AUC) reaching 0.94 and 0.86 in the primary and validation cohorts, respectively, which outweigh the performances of clinical signature and fusion signature. With a median follow-up time of 32.4 months, the radiomics signature stratified the glioma patients into two risk groups with significantly different prognoses (p = 0.04). CONCLUSIONS: (18)F-FDG-PET-based radiomics is a promising approach for preoperatively evaluating the MGMT promoter methylation status in glioma and predicting the prognosis of glioma patients noninvasively. |
format | Online Article Text |
id | pubmed-6701097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-67010972019-08-26 (18)F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma Kong, Ziren Lin, Yusong Jiang, Chendan Li, Longfei Liu, Zehua Wang, Yuekun Dai, Congxin Liu, Delin Qin, Xuying Wang, Yu Liu, Zhenyu Cheng, Xin Tian, Jie Ma, Wenbin Cancer Imaging Research Article BACKGROUND: The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) promoter has emerged as a favorable independent prognostic and predictive biomarker in glioma. This study aimed to build a radiomics signature based on (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) for noninvasive measurement of the MGMT promoter methylation status in glioma. METHODS: One hundred and seven pathology-confirmed primary diffuse glioma patients were retrospectively included and randomly assigned to the primary (n = 71) or validation cohort (n = 36). The MGMT promoter methylation status was measured by pyrosequencing. A total of 1561 radiomics features were extracted from the three-dimensional region of interest (ROI) on the standard uptake value (SUV) maps that were generated from the original (18)F-FDG PET data. A radiomics signature, a clinical signature and a fusion signature that combined the clinical and radiomics features together were generated. The performance of the three signatures was evaluated by receiver operating characteristic (ROC) curve analysis, and the patient prognosis was stratified based on the MGMT promoter methylation status and the signature with the best performance. RESULTS: Five radiomics features were selected to construct the radiomics signature, and displayed the best performance with area under the receiver operating characteristic (ROC) curve (AUC) reaching 0.94 and 0.86 in the primary and validation cohorts, respectively, which outweigh the performances of clinical signature and fusion signature. With a median follow-up time of 32.4 months, the radiomics signature stratified the glioma patients into two risk groups with significantly different prognoses (p = 0.04). CONCLUSIONS: (18)F-FDG-PET-based radiomics is a promising approach for preoperatively evaluating the MGMT promoter methylation status in glioma and predicting the prognosis of glioma patients noninvasively. BioMed Central 2019-08-19 /pmc/articles/PMC6701097/ /pubmed/31426864 http://dx.doi.org/10.1186/s40644-019-0246-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Kong, Ziren Lin, Yusong Jiang, Chendan Li, Longfei Liu, Zehua Wang, Yuekun Dai, Congxin Liu, Delin Qin, Xuying Wang, Yu Liu, Zhenyu Cheng, Xin Tian, Jie Ma, Wenbin (18)F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma |
title | (18)F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma |
title_full | (18)F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma |
title_fullStr | (18)F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma |
title_full_unstemmed | (18)F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma |
title_short | (18)F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma |
title_sort | (18)f-fdg-pet-based radiomics signature predicts mgmt promoter methylation status in primary diffuse glioma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701097/ https://www.ncbi.nlm.nih.gov/pubmed/31426864 http://dx.doi.org/10.1186/s40644-019-0246-0 |
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