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Current Advances and Challenges in Radiomics of Brain Tumors
Imaging diagnosis is crucial for early detection and monitoring of brain tumors. Radiomics enable the extraction of a large mass of quantitative features from complex clinical imaging arrays, and then transform them into high-dimensional data which can subsequently be mined to find their relevance w...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551958/ https://www.ncbi.nlm.nih.gov/pubmed/34722274 http://dx.doi.org/10.3389/fonc.2021.732196 |
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author | Yi, Zhenjie Long, Lifu Zeng, Yu Liu, Zhixiong |
author_facet | Yi, Zhenjie Long, Lifu Zeng, Yu Liu, Zhixiong |
author_sort | Yi, Zhenjie |
collection | PubMed |
description | Imaging diagnosis is crucial for early detection and monitoring of brain tumors. Radiomics enable the extraction of a large mass of quantitative features from complex clinical imaging arrays, and then transform them into high-dimensional data which can subsequently be mined to find their relevance with the tumor’s histological features, which reflect underlying genetic mutations and malignancy, along with grade, progression, therapeutic effect, or even overall survival (OS). Compared to traditional brain imaging, radiomics provides quantitative information linked to meaningful biologic characteristics and application of deep learning which sheds light on the full automation of imaging diagnosis. Recent studies have shown that radiomics’ application is broad in identifying primary tumor, differential diagnosis, grading, evaluation of mutation status and aggression, prediction of treatment response and recurrence in pituitary tumors, gliomas, and brain metastases. In this descriptive review, besides establishing a general understanding among protocols, results, and clinical significance of these studies, we further discuss the current limitations along with future development of radiomics. |
format | Online Article Text |
id | pubmed-8551958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85519582021-10-29 Current Advances and Challenges in Radiomics of Brain Tumors Yi, Zhenjie Long, Lifu Zeng, Yu Liu, Zhixiong Front Oncol Oncology Imaging diagnosis is crucial for early detection and monitoring of brain tumors. Radiomics enable the extraction of a large mass of quantitative features from complex clinical imaging arrays, and then transform them into high-dimensional data which can subsequently be mined to find their relevance with the tumor’s histological features, which reflect underlying genetic mutations and malignancy, along with grade, progression, therapeutic effect, or even overall survival (OS). Compared to traditional brain imaging, radiomics provides quantitative information linked to meaningful biologic characteristics and application of deep learning which sheds light on the full automation of imaging diagnosis. Recent studies have shown that radiomics’ application is broad in identifying primary tumor, differential diagnosis, grading, evaluation of mutation status and aggression, prediction of treatment response and recurrence in pituitary tumors, gliomas, and brain metastases. In this descriptive review, besides establishing a general understanding among protocols, results, and clinical significance of these studies, we further discuss the current limitations along with future development of radiomics. Frontiers Media S.A. 2021-10-14 /pmc/articles/PMC8551958/ /pubmed/34722274 http://dx.doi.org/10.3389/fonc.2021.732196 Text en Copyright © 2021 Yi, Long, Zeng and Liu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Yi, Zhenjie Long, Lifu Zeng, Yu Liu, Zhixiong Current Advances and Challenges in Radiomics of Brain Tumors |
title | Current Advances and Challenges in Radiomics of Brain Tumors |
title_full | Current Advances and Challenges in Radiomics of Brain Tumors |
title_fullStr | Current Advances and Challenges in Radiomics of Brain Tumors |
title_full_unstemmed | Current Advances and Challenges in Radiomics of Brain Tumors |
title_short | Current Advances and Challenges in Radiomics of Brain Tumors |
title_sort | current advances and challenges in radiomics of brain tumors |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551958/ https://www.ncbi.nlm.nih.gov/pubmed/34722274 http://dx.doi.org/10.3389/fonc.2021.732196 |
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