Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?

Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub
Proceedings of The 5th International Conference on Medical Imaging with Deep Learning, PMLR 172:1005-1018, 2022.

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.

Cite this Paper

BibTeX
@InProceedings{pmlr-v172-saeed22a, title = {Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?}, author = {Saeed, Numan and Hardan, Shahad and Abutalip, Kudaibergen and Yaqub, Mohammad}, booktitle = {Proceedings of The 5th International Conference on Medical Imaging with Deep Learning}, pages = {1005--1018}, year = {2022}, editor = {Konukoglu, Ender and Menze, Bjoern and Venkataraman, Archana and Baumgartner, Christian and Dou, Qi and Albarqouni, Shadi}, volume = {172}, series = {Proceedings of Machine Learning Research}, month = {06--08 Jul}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v172/saeed22a/saeed22a.pdf}, url = {https://proceedings.mlr.press/v172/saeed22a.html}, 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.} }
Endnote
%0 Conference Paper %T Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models? %A Numan Saeed %A Shahad Hardan %A Kudaibergen Abutalip %A Mohammad Yaqub %B Proceedings of The 5th International Conference on Medical Imaging with Deep Learning %C Proceedings of Machine Learning Research %D 2022 %E Ender Konukoglu %E Bjoern Menze %E Archana Venkataraman %E Christian Baumgartner %E Qi Dou %E Shadi Albarqouni %F pmlr-v172-saeed22a %I PMLR %P 1005--1018 %U https://proceedings.mlr.press/v172/saeed22a.html %V 172 %X 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.
APA
Saeed, N., Hardan, S., Abutalip, K. & Yaqub, M.. (2022). Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?. Proceedings of The 5th International Conference on Medical Imaging with Deep Learning, in Proceedings of Machine Learning Research 172:1005-1018 Available from https://proceedings.mlr.press/v172/saeed22a.html.

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