# Prognostic role of delta radiomics in pediatric pontine diffuse midline gliomas

## TL;DR

This study shows that delta-radiomics, which compares pre- and post-treatment MRI scans, can better predict survival in children with a deadly brain tumor than traditional methods.

## Contribution

This is the first study to demonstrate the prognostic value of delta-radiomics in pediatric pontine diffuse midline gliomas.

## Key findings

- Delta radiomics features, especially sum entropy from T1 and T2 sequences, showed higher accuracy in predicting survival than static post-treatment features.
- Sum entropy from post-radiotherapy T1 images was an independent predictor of longer overall survival.
- Lower baseline sum average from non-contrast T1 images was associated with shorter survival.

## Abstract

Pontine diffuse midline gliomas (PDMGs) are among the most lethal pediatric brain tumors with a median survival of approximately one year. Reliable prognostic markers are needed to guide treatment strategies and inform families. Our study aims to investigate the prognostic utility of delta-radiomic features in PDMGs.

We retrospectively analyzed 35 pediatric patients with PDMG diagnosed between 2012 and 2020, all treated with radiotherapy plus concomitant and adjuvant temozolomide. Pre- and post-treatment MRI (T1-weighted, T2-weighted, and ADC maps) were subjected to manual segmentation and texture feature extraction using MaZda software. Delta radiomics features were calculated as ratios between post- and pre-treatment values. Diagnostic performance for predicting survival below or above 12 months was assessed using ROC analysis, while overall survival was further evaluated with Kaplan–Meier and Cox regression models.

Median overall survival was 13 months (range: 6–69). Among baseline features, only sum average from non-contrast T1 was significant, with lower values (indicating higher heterogeneity) associated with shorter OS. In the post-radiotherapy setting, sum entropy from T1 images emerged as an independent prognostic predictor, with higher values correlating with longer OS. Delta radiomics parameters, particularly sum entropy derived from T1 and T2 sequences, yielded higher AUC values than single post-treatment features, suggesting superior prognostic accuracy.

Our preliminary results indicate that delta-radiomics outperforms static texture analysis in predicting overall survival in pediatric PDMGs, and to the best of our knowledge, this is the first study to investigate the prognostic utility of delta-radiomics in this population. Evidence is provided that delta radiomics can serve as a non-invasive marker for early prognostic stratification in pediatric PDMGs. Validation in larger, multi-center cohorts is required to confirm its clinical utility.

The online version contains supplementary material available at 10.1007/s11060-026-05457-y.