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Radiomics as an emerging tool in the management of brain metastases
Brain metastases (BM) are associated with significant morbidity and mortality in patients with advanced cancer. Despite significant advances in surgical, radiation, and systemic therapy in recent years, the median overall survival of patients with BM is less than 1 year. The acquisition of medical i...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583687/ https://www.ncbi.nlm.nih.gov/pubmed/36284932 http://dx.doi.org/10.1093/noajnl/vdac141 |
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author | Nowakowski, Alexander Lahijanian, Zubin Panet-Raymond, Valerie Siegel, Peter M Petrecca, Kevin Maleki, Farhad Dankner, Matthew |
author_facet | Nowakowski, Alexander Lahijanian, Zubin Panet-Raymond, Valerie Siegel, Peter M Petrecca, Kevin Maleki, Farhad Dankner, Matthew |
author_sort | Nowakowski, Alexander |
collection | PubMed |
description | Brain metastases (BM) are associated with significant morbidity and mortality in patients with advanced cancer. Despite significant advances in surgical, radiation, and systemic therapy in recent years, the median overall survival of patients with BM is less than 1 year. The acquisition of medical images, such as computed tomography (CT) and magnetic resonance imaging (MRI), is critical for the diagnosis and stratification of patients to appropriate treatments. Radiomic analyses have the potential to improve the standard of care for patients with BM by applying artificial intelligence (AI) with already acquired medical images to predict clinical outcomes and direct the personalized care of BM patients. Herein, we outline the existing literature applying radiomics for the clinical management of BM. This includes predicting patient response to radiotherapy and identifying radiation necrosis, performing virtual biopsies to predict tumor mutation status, and determining the cancer of origin in brain tumors identified via imaging. With further development, radiomics has the potential to aid in BM patient stratification while circumventing the need for invasive tissue sampling, particularly for patients not eligible for surgical resection. |
format | Online Article Text |
id | pubmed-9583687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-95836872022-10-24 Radiomics as an emerging tool in the management of brain metastases Nowakowski, Alexander Lahijanian, Zubin Panet-Raymond, Valerie Siegel, Peter M Petrecca, Kevin Maleki, Farhad Dankner, Matthew Neurooncol Adv Review Brain metastases (BM) are associated with significant morbidity and mortality in patients with advanced cancer. Despite significant advances in surgical, radiation, and systemic therapy in recent years, the median overall survival of patients with BM is less than 1 year. The acquisition of medical images, such as computed tomography (CT) and magnetic resonance imaging (MRI), is critical for the diagnosis and stratification of patients to appropriate treatments. Radiomic analyses have the potential to improve the standard of care for patients with BM by applying artificial intelligence (AI) with already acquired medical images to predict clinical outcomes and direct the personalized care of BM patients. Herein, we outline the existing literature applying radiomics for the clinical management of BM. This includes predicting patient response to radiotherapy and identifying radiation necrosis, performing virtual biopsies to predict tumor mutation status, and determining the cancer of origin in brain tumors identified via imaging. With further development, radiomics has the potential to aid in BM patient stratification while circumventing the need for invasive tissue sampling, particularly for patients not eligible for surgical resection. Oxford University Press 2022-09-06 /pmc/articles/PMC9583687/ /pubmed/36284932 http://dx.doi.org/10.1093/noajnl/vdac141 Text en © The Author(s) 2022. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Nowakowski, Alexander Lahijanian, Zubin Panet-Raymond, Valerie Siegel, Peter M Petrecca, Kevin Maleki, Farhad Dankner, Matthew Radiomics as an emerging tool in the management of brain metastases |
title | Radiomics as an emerging tool in the management of brain metastases |
title_full | Radiomics as an emerging tool in the management of brain metastases |
title_fullStr | Radiomics as an emerging tool in the management of brain metastases |
title_full_unstemmed | Radiomics as an emerging tool in the management of brain metastases |
title_short | Radiomics as an emerging tool in the management of brain metastases |
title_sort | radiomics as an emerging tool in the management of brain metastases |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583687/ https://www.ncbi.nlm.nih.gov/pubmed/36284932 http://dx.doi.org/10.1093/noajnl/vdac141 |
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