A Video Data Based Transfer Learning Approach for Classification of MGMT Status in Brain Tumor MR Images

D. M. Lang, J. C. Peeken, S. E. Combs, J. J. Wilkens, S. Bartzsch

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Patient MGMT (O 6 methylguanine DNA methyltransferase) status has been identified essential for the responsiveness to chemotherapy in glioblastoma patients and therefore depicts an important clinical factor. Testing for MGMT methylation is invasive, time consuming and costly and lacks a uniform gold standard. We studied MGMT status assessment by multi-parametric magnetic resonance imaging (mpMRI) scans and tested the ability of deep learning for classification of this task. To overcome the limited number of training examples we used a transfer learning approach based on the video clip classification network C3D [30], allowing for full exploitation of three dimensional information in the MR images. MRI sequences were fused using a locally connected layer. Our approach was able to differentiate MGMT methylated from unmethylated patients with an area under the receiver operating characteristics curve (AUC) of 0.689 for the public validation set. On the private test set AUC was given by 0.577. Further studies for assessment of clinical importance and predictive power in terms of survival are needed.

Original languageEnglish
Title of host publicationBrainlesion
Subtitle of host publicationGlioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Revised Selected Papers
EditorsAlessandro Crimi, Spyridon Bakas
PublisherSpringer Science and Business Media Deutschland GmbH
Pages306-314
Number of pages9
ISBN (Print)9783031089985
DOIs
StatePublished - 2022
Event7th International Brain Lesion Workshop, BrainLes 2021, held in conjunction with the Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 - Virtual, Online
Duration: 27 Sep 202127 Sep 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12962 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Brain Lesion Workshop, BrainLes 2021, held in conjunction with the Medical Image Computing and Computer Assisted Intervention, MICCAI 2021
CityVirtual, Online
Period27/09/2127/09/21

Keywords

  • Deep learning
  • Glioblastoma
  • MGMT status
  • Transfer learning

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