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Insights into Imaging
Published in: Insights into Imaging 1/2021

01-12-2021 | Glioma | Educational Review

Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging

Authors: Ahmed Abdel Khalek Abdel Razek, Ahmed Alksas, Mohamed Shehata, Amr AbdelKhalek, Khaled Abdel Baky, Ayman El-Baz, Eman Helmy

Published in: Insights into Imaging | Issue 1/2021

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Abstract

This article is a comprehensive review of the basic background, technique, and clinical applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A variety of AI and radiomics utilized conventional and advanced techniques to differentiate brain tumors from non-neoplastic lesions such as inflammatory and demyelinating brain lesions. It is used in the diagnosis of gliomas and discrimination of gliomas from lymphomas and metastasis. Also, semiautomated and automated tumor segmentation has been developed for radiotherapy planning and follow-up. It has a role in the grading, prediction of treatment response, and prognosis of gliomas. Radiogenomics allowed the connection of the imaging phenotype of the tumor to its molecular environment. In addition, AI is applied for the assessment of extra-axial brain tumors and pediatric tumors with high performance in tumor detection, classification, and stratification of patient’s prognoses.
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Metadata
Title
Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging
Authors
Ahmed Abdel Khalek Abdel Razek
Ahmed Alksas
Mohamed Shehata
Amr AbdelKhalek
Khaled Abdel Baky
Ayman El-Baz
Eman Helmy
Publication date
01-12-2021
Publisher
Springer International Publishing
Published in
Insights into Imaging / Issue 1/2021
Electronic ISSN: 1869-4101
DOI
https://doi.org/10.1186/s13244-021-01102-6

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