This title appears in the Scientific Report :
2022
Please use the identifier:
http://dx.doi.org/10.1111/bpa.13015 in citations.
Please use the identifier: http://hdl.handle.net/2128/30808 in citations.
Use of advanced neuroimaging and artificial intelligence in meningiomas
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...
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Personal Name(s): | Galldiks, Norbert (Corresponding author) |
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Angenstein, Frank / Werner, Jan-Michael / Bauer, Elena K. / Gutsche, Robin / Fink, Gereon R. / Langen, Karl-Josef / Lohmann, Philipp (Corresponding author) | |
Contributing Institute: |
Physik der Medizinischen Bildgebung; INM-4 Kognitive Neurowissenschaften; INM-3 |
Published in: | Brain pathology, 32 (2022) 2, S. - |
Imprint: |
Oxford
Wiley-Blackwell
2022
|
DOI: |
10.1111/bpa.13015 |
PubMed ID: |
35213083 |
Document Type: |
Journal Article |
Research Program: |
Radiomics basierend auf MRT und Aminosäure PET in der Neuroonkologie Neuroimaging |
Link: |
OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/30808 in citations.
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. |