Related Experiment Video
Updated: Jun 24, 2026
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
Published on: September 13, 2022
Voxel-Wise Radiomics Habitat Analysis of Posttreatment Gliomas for Noninvasive Differentiation of True Progression
Linsha Yang1, Defeng Liu1, Duo Zhang2
1Department of Medical Imaging, The First Hospital of Qinhuangdao, Qinhuangdao, People's Republic of China.
Background:
Differentiating true progression (TP) from pseudoprogression (PsP) after chemoradiotherapy in gliomas remains challenging because conventional MRI findings overlap.
Purpose:
To assess whether voxel-level radiomics habitat metrics improve TP/PsP classification and complement clinical and molecular features.
Study Type:
Retrospective, multi-center.
Subjects:
193 glioma patients after treatment: 121 in the training set (54.2 ± 11.3 years; 74 men; 85 TP/36 PsP) and 72 in the external testing set (51.4 ± 10.4 years; 44 men; 52 TP/20 PsP).
Field Strength/Sequence:
3 and 1.5 T; contrast-enhanced T1-weighted spin-echo imaging (T1CE), T2-weighted fast/turbo spin-echo imaging (T2WI), T2-weighted fluid-attenuated inversion recovery fast/turbo spin-echo imaging (T2-FLAIR), diffusion-weighted echo-planar imaging (DWI), and arterial spin labeling (ASL).
Assessment:
Voxel-wise radiomics features were extracted from contrast-enhancing tumor ROIs. Gaussian mixture models generated soft habitats, from which voxel-level metrics were calculated. Three models were constructed. The Clinical Model included tumor grade, isocitrate dehydrogenase (IDH) status, O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, and time interval. Feature selection used least absolute shrinkage and selection operator (LASSO); classifier optimization employed Optuna-based Bayesian methods.
Statistical Tests:
Receiver operating characteristic (ROC) curve analysis, calibration curves, decision curve analysis (DCA), and SHAP were used. p < 0.05 indicated significance.
Results:
In the testing set, the Clinical, Voxel-wise Habitat, and Combined Models achieved areas under the curve (AUCs) of 0.701 (95% confidence interval [CI]: 0.597-0.806), 0.832 (95% CI: 0.736-0.917), and 0.890 (95% CI: 0.819-0.958), respectively. The Combined Model significantly outperformed the clinical model (difference, 0.189). Voxel-wise Habitat versus Clinical (difference, 0.131; p = 0.164) and Combined versus Voxel-wise Habitat comparisons (difference, 0.058; p = 0.105) were not significant. SHAP ranked CBF_habitat_edge_standard_deviation, CBF_habitat_entropy_mean, and T1CE_habitat_edge_standard_deviation as leading contributors.
Data Conclusion:
Voxel-wise habitat analysis, combined with clinical and molecular features, improved TP/PsP discrimination with interpretable heterogeneity metrics.
Evidence Level:
3.
Technical Efficacy:
Stage 3.
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