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Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

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Diffusion tensor invasive phenotypes can predict progression-free survival in glioblastomas.

L A Mohsen¹, V Shi, R Jena

¹Department of Radiology, University of Cambridge , Cambridge , UK.

British Journal of Neurosurgery

|March 1, 2013

Summary

Diffusion tensor imaging (DTI) identified three glioblastoma invasion patterns. A minimally invasive phenotype showed significantly longer progression-free survival, suggesting a better prognosis.

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Published on: April 16, 2019

Area of Science:

Neuro-oncology
Medical imaging
Radiology

Background:

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with poor prognosis.
Tumor invasion into surrounding brain tissue limits treatment efficacy.
Previous studies indicate variable GBM invasion patterns, ranging from <1 cm to >3 cm from the tumor core.

Purpose of the Study:

To utilize Diffusion Tensor Imaging (DTI) to characterize GBM invasive patterns.
To correlate identified invasion patterns with progression-free survival (PFS).

Main Methods:

Retrospective analysis of 25 GBM patients treated per EORTC/NCIC protocol.
Post-operative imaging using 1.5 T MRI with standard anatomical and DTI sequences.
Classification of patients into diffuse, localized, or minimally invasive patterns based on DTI-derived p and q maps.

Main Results:

Median PFS differed significantly across invasion patterns: 278 days (diffuse), 605 days (localized), and 820 days (minimally invasive).
A minimally invasive pattern was associated with a significantly longer PFS.
Three-quarters of patients with a minimally invasive phenotype remained progression-free at 24 months (p=0.010).

Conclusions:

Diffusion tensor imaging can differentiate three distinct invasive phenotypes in GBM.
These phenotypes exhibit significantly different progression-free survival outcomes.
A minimally invasive GBM phenotype, observed in approximately 20% of patients, predicts a delayed progression.