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Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction

Objective: We aimed to identify a radiomic signature to be used as a noninvasive biomarker of prognosis in patients with lower-grade gliomas (LGGs) and to reveal underlying biological processes through comprehensive radiogenomic investigation. Methods: We extracted 55 radiomic features from T2-weigh...

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Autores principales: Qian, Zenghui, Li, Yiming, Sun, Zhiyan, Fan, Xing, Xu, Kaibin, Wang, Kai, Li, Shaowu, Zhang, Zhong, Jiang, Tao, Liu, Xing, Wang, Yinyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6224242/
https://www.ncbi.nlm.nih.gov/pubmed/30362964
http://dx.doi.org/10.18632/aging.101594
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author Qian, Zenghui
Li, Yiming
Sun, Zhiyan
Fan, Xing
Xu, Kaibin
Wang, Kai
Li, Shaowu
Zhang, Zhong
Jiang, Tao
Liu, Xing
Wang, Yinyan
author_facet Qian, Zenghui
Li, Yiming
Sun, Zhiyan
Fan, Xing
Xu, Kaibin
Wang, Kai
Li, Shaowu
Zhang, Zhong
Jiang, Tao
Liu, Xing
Wang, Yinyan
author_sort Qian, Zenghui
collection PubMed
description Objective: We aimed to identify a radiomic signature to be used as a noninvasive biomarker of prognosis in patients with lower-grade gliomas (LGGs) and to reveal underlying biological processes through comprehensive radiogenomic investigation. Methods: We extracted 55 radiomic features from T2-weighted images of 233 patients with LGGs (training cohort: n = 85; validation cohort: n = 148). Univariate Cox regression and linear risk score formula were applied to generate a radiomic-based signature. Gene ontology analysis of highly expressed genes in the high-risk score group was conducted to establish a radiogenomic map. A nomogram was constructed for individualized survival prediction. Results: The six-feature radiomic signature stratified patients in the training cohort into low- or high-risk groups for overall survival (P = 0.0018). This result was successfully verified in the validation cohort (P = 0.0396). Radiogenomic analysis revealed that the prognostic radiomic signature was associated with hypoxia, angiogenesis, apoptosis, and cell proliferation. The nomogram resulted in high prognostic accuracy (C-index: 0.92, C-index: 0.70) and favorable calibration for individualized survival prediction in the training and validation cohorts. Conclusions: Our results suggest a great potential for the use of radiomic signature as a biological surrogate in providing prognostic information for patients with LGGs.
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spelling pubmed-62242422018-11-19 Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction Qian, Zenghui Li, Yiming Sun, Zhiyan Fan, Xing Xu, Kaibin Wang, Kai Li, Shaowu Zhang, Zhong Jiang, Tao Liu, Xing Wang, Yinyan Aging (Albany NY) Research Paper Objective: We aimed to identify a radiomic signature to be used as a noninvasive biomarker of prognosis in patients with lower-grade gliomas (LGGs) and to reveal underlying biological processes through comprehensive radiogenomic investigation. Methods: We extracted 55 radiomic features from T2-weighted images of 233 patients with LGGs (training cohort: n = 85; validation cohort: n = 148). Univariate Cox regression and linear risk score formula were applied to generate a radiomic-based signature. Gene ontology analysis of highly expressed genes in the high-risk score group was conducted to establish a radiogenomic map. A nomogram was constructed for individualized survival prediction. Results: The six-feature radiomic signature stratified patients in the training cohort into low- or high-risk groups for overall survival (P = 0.0018). This result was successfully verified in the validation cohort (P = 0.0396). Radiogenomic analysis revealed that the prognostic radiomic signature was associated with hypoxia, angiogenesis, apoptosis, and cell proliferation. The nomogram resulted in high prognostic accuracy (C-index: 0.92, C-index: 0.70) and favorable calibration for individualized survival prediction in the training and validation cohorts. Conclusions: Our results suggest a great potential for the use of radiomic signature as a biological surrogate in providing prognostic information for patients with LGGs. Impact Journals 2018-10-22 /pmc/articles/PMC6224242/ /pubmed/30362964 http://dx.doi.org/10.18632/aging.101594 Text en Copyright © 2018 Qian et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Qian, Zenghui
Li, Yiming
Sun, Zhiyan
Fan, Xing
Xu, Kaibin
Wang, Kai
Li, Shaowu
Zhang, Zhong
Jiang, Tao
Liu, Xing
Wang, Yinyan
Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction
title Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction
title_full Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction
title_fullStr Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction
title_full_unstemmed Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction
title_short Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction
title_sort radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6224242/
https://www.ncbi.nlm.nih.gov/pubmed/30362964
http://dx.doi.org/10.18632/aging.101594
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