Document Type

Article

Publication Title

arXiv

Abstract

Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most cancer types, can be improved if a particular genetic sequence in the tumor known as MGMT promoter is methylated. However, to identify the state of the MGMT promoter, the conventional approach is to perform a biopsy for genetic analysis, which is time and effort consuming. A couple of recent publications proposed a connection between the MGMT promoter state and the MRI scans of the tumor and hence suggested the use of deep learning models for this purpose. Therefore, in this work, we use one of the most extensive datasets, BraTS 2021, to study the potency of employing deep learning solutions, including 2D and 3D CNN models and vision transformers. After conducting a thorough analysis of the models' performance, we concluded that there seems to be no connection between the MRI scans and the state of the MGMT promoter. © 2022, CC BY-NC-SA.

DOI

doi.org/10.48550/arXiv.2201.06086

Publication Date

1-16-2022

Keywords

Alkylation, Chemotherapy, Deep learning, Brain tumors, Deep learning, Genetic sequence, Glioblastomas, Learning models, MGMT promoter, MRI scan, Older adults, Promoter methylation, Radiogenomic, Tumors, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV)

Comments

Preprint: arXiv

Archived with thanks to arXiv

Preprint License: CC BY-NC-SA 4.0

Uploaded 25 March 2022

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