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Use of advanced neuroimaging and artificial intelligence in meningiomas
Anatomical cross‐sectional imaging methods such as contrast‐enhanced MRI and CT are the standard for the delineation, treatment planning, and follow‐up of patients with meningioma. Besides, advanced neuroimaging is increasingly used to non‐invasively provide detailed insights into the molecular and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877736/ https://www.ncbi.nlm.nih.gov/pubmed/35213083 http://dx.doi.org/10.1111/bpa.13015 |
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author | Galldiks, Norbert Angenstein, Frank Werner, Jan‐Michael Bauer, Elena K. Gutsche, Robin Fink, Gereon R. Langen, Karl‐Josef Lohmann, Philipp |
author_facet | Galldiks, Norbert Angenstein, Frank Werner, Jan‐Michael Bauer, Elena K. Gutsche, Robin Fink, Gereon R. Langen, Karl‐Josef Lohmann, Philipp |
author_sort | Galldiks, Norbert |
collection | PubMed |
description | Anatomical cross‐sectional imaging methods such as contrast‐enhanced MRI and CT are the standard for the delineation, treatment planning, and follow‐up of patients with meningioma. Besides, advanced neuroimaging is increasingly used to non‐invasively provide detailed insights into the molecular and metabolic features of meningiomas. These techniques are usually based on MRI, e.g., perfusion‐weighted imaging, diffusion‐weighted imaging, MR spectroscopy, and positron emission tomography. Furthermore, artificial intelligence methods such as radiomics offer the potential to extract quantitative imaging features from routinely acquired anatomical MRI and CT scans and advanced imaging techniques. This allows the linking of imaging phenotypes to meningioma characteristics, e.g., the molecular‐genetic profile. Here, we review several diagnostic applications and future directions of these advanced neuroimaging techniques, including radiomics in preclinical models and patients with meningioma. |
format | Online Article Text |
id | pubmed-8877736 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88777362022-03-01 Use of advanced neuroimaging and artificial intelligence in meningiomas Galldiks, Norbert Angenstein, Frank Werner, Jan‐Michael Bauer, Elena K. Gutsche, Robin Fink, Gereon R. Langen, Karl‐Josef Lohmann, Philipp Brain Pathol Invited Reviews Anatomical cross‐sectional imaging methods such as contrast‐enhanced MRI and CT are the standard for the delineation, treatment planning, and follow‐up of patients with meningioma. Besides, advanced neuroimaging is increasingly used to non‐invasively provide detailed insights into the molecular and metabolic features of meningiomas. These techniques are usually based on MRI, e.g., perfusion‐weighted imaging, diffusion‐weighted imaging, MR spectroscopy, and positron emission tomography. Furthermore, artificial intelligence methods such as radiomics offer the potential to extract quantitative imaging features from routinely acquired anatomical MRI and CT scans and advanced imaging techniques. This allows the linking of imaging phenotypes to meningioma characteristics, e.g., the molecular‐genetic profile. Here, we review several diagnostic applications and future directions of these advanced neuroimaging techniques, including radiomics in preclinical models and patients with meningioma. John Wiley and Sons Inc. 2022-02-25 /pmc/articles/PMC8877736/ /pubmed/35213083 http://dx.doi.org/10.1111/bpa.13015 Text en © 2021 The Authors. Brain Pathology published by John Wiley & Sons Ltd on behalf of International Society of Neuropathology https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Invited Reviews Galldiks, Norbert Angenstein, Frank Werner, Jan‐Michael Bauer, Elena K. Gutsche, Robin Fink, Gereon R. Langen, Karl‐Josef Lohmann, Philipp Use of advanced neuroimaging and artificial intelligence in meningiomas |
title | Use of advanced neuroimaging and artificial intelligence in meningiomas |
title_full | Use of advanced neuroimaging and artificial intelligence in meningiomas |
title_fullStr | Use of advanced neuroimaging and artificial intelligence in meningiomas |
title_full_unstemmed | Use of advanced neuroimaging and artificial intelligence in meningiomas |
title_short | Use of advanced neuroimaging and artificial intelligence in meningiomas |
title_sort | use of advanced neuroimaging and artificial intelligence in meningiomas |
topic | Invited Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877736/ https://www.ncbi.nlm.nih.gov/pubmed/35213083 http://dx.doi.org/10.1111/bpa.13015 |
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