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Related Experiment Video

Updated: Sep 6, 2025

A Protocol for Rapid Post-mortem Cell Culture of Diffuse Intrinsic Pontine Glioma DIPG
08:46

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Radiomic Features Based on MRI Predict Progression-Free Survival in Pediatric Diffuse Midline Glioma/Diffuse

Matthias W Wagner1,2, Khashayar Namdar1,2, Marc Napoleone1

  • 1Department of Diagnostic Imaging, Division of Neuroradiology, 7979The Hospital for Sick Children, Toronto, Canada.

Canadian Association of Radiologists Journal = Journal L'Association Canadienne Des Radiologistes
|June 30, 2022
PubMed
Summary

Radiomics analysis of MRI scans can predict progression-free survival in pediatric diffuse intrinsic pontine glioma (DIPG). This non-invasive imaging technique offers a promising alternative to biopsies for stratifying DIPG patient subsets.

Keywords:
MRIchildrendiffuse intrinsic pontine gliomafluid-attenuated inversion recoveryradiomics

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Area of Science:

  • Neuro-oncology
  • Medical Imaging
  • Radiomics
  • Pediatric Oncology

Background:

  • H3 K27M mutation status from biopsies predicts survival in diffuse intrinsic pontine glioma (DIPG).
  • Biopsies are invasive and typically reserved for rare presentations or clinical trials.
  • There is a need for non-invasive prognostic markers to stratify DIPG patients.

Purpose of the Study:

  • To evaluate radiomics as a non-invasive prognostic marker for stratifying DIPG subsets.
  • To assess the predictive capability of radiomic features for progression-free survival (PFS) in pediatric DIPG.

Main Methods:

  • Retrospective analysis of diagnostic brain MRIs from 89 children with DIPG.
  • Extraction of radiomic features from tumor segmentations on FLAIR and nonenhanced T1-weighted MRI sequences.
  • Application of a conditional survival forest model for PFS prediction, with data split into training (80%) and testing (20%) sets.

Main Results:

  • Radiomic features from FLAIR and nonenhanced T1-weighted sequences significantly predicted PFS.
  • The best FLAIR radiomics model achieved a concordance of 0.87 at 4 months PFS.
  • The best T1-weighted radiomics model achieved a concordance of 0.82 at 4 months PFS; the combined model showed a concordance of 0.74 at 3 months PFS.

Conclusions:

  • MRI-based radiomics shows potential as a non-invasive method for predicting PFS in pediatric diffuse midline glioma/DIPG.
  • Radiomics can aid in stratifying DIPG patient subsets, potentially guiding treatment decisions.
  • Gray-level size-zone matrix was identified as a predominant predictive radiomic feature.