Automatic Segmentation of Rare Pediatric Brain Tumors Using Knowledge Transfer From Adult Data

Xinyang Liu*, Erin R. Bonner, Zhifan Jiang, Holger R. Roth, Syed Muhammad Anwar, Roger J. Packer, Miriam Bornhorst, Marius George Linguraru

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Diffuse midline glioma (DMG) is a rare but fatal pediatric brain tumor. An automatic pipeline to analyze patient MRI can help monitor tumor progression and predict overall survival. Clinical implementation requires automatic segmentations of subregions of DMG. Given the rarity of data, we investigated how pretraining state-of-the-art deep learning models on adult brain tumor data would allow for a knowledge transfer to pediatric data and improve overall segmentation performance. We retrospectively collected multisequence MRI of 45 children diagnosed with DMG (a total of 82 scans with different timepoints). Five-fold cross-validations were performed on the DMG dataset using SegResNet and nnU-Net, each with and without pretraining on the BraTS2021 dataset of 1,251 glioblastoma multiform subjects. Best segmentation results were achieved using nnU-Net with pretraining (Dice scores of 0.859±0.229 and 0.880±0.072 for the enhancing region and the whole tumor, respectively). Our results suggest knowledge transfer from adult brain tumor images can improve pediatric brain tumor segmentation performance. Using pretraining also helped in speeding up training convergence for downstream tasks.

Original languageEnglish (US)
Title of host publication2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023
PublisherIEEE Computer Society
ISBN (Electronic)9781665473583
DOIs
StatePublished - 2023
Event20th IEEE International Symposium on Biomedical Imaging, ISBI 2023 - Cartagena, Colombia
Duration: Apr 18 2023Apr 21 2023

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2023-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference20th IEEE International Symposium on Biomedical Imaging, ISBI 2023
Country/TerritoryColombia
CityCartagena
Period4/18/234/21/23

Keywords

  • Diffuse midline glioma
  • brain tumor
  • deep learning
  • pediatric tumor
  • segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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