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.

Details

Title
Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging
Author
Abdel Razek Ahmed Abdel Khalek 1 ; Alksas Ahmed 2 ; Shehata, Mohamed 2 ; AbdelKhalek Amr 3 ; Khaled, Abdel Baky 4 ; El-Baz, Ayman 2 ; Helmy Eman 1   VIAFID ORCID Logo 

 Mansoura University, Department of Diagnostic Radiology, Faculty of Medicine, Mansoura, Egypt (GRID:grid.10251.37) (ISNI:0000000103426662) 
 University of Louisville, Biomaging Lab, Department of Bioengineering, Louisville, USA (GRID:grid.266623.5) (ISNI:0000 0001 2113 1622) 
 Internship at Mansoura University Hospital, Mansoura Faculty of Medicine, Mansoura, Egypt (GRID:grid.10251.37) (ISNI:0000000103426662) 
 Port Said University, Department of Diagnostic Radiology, Faculty of Medicine, Port Said, Egypt (GRID:grid.440879.6) (ISNI:0000 0004 0578 4430) 
Publication year
2021
Publication date
Dec 2021
Publisher
Springer Nature B.V.
e-ISSN
18694101
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2584135339
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.