Radiomics and clinical data predict pseudoprogression after radiotherapy in high-grade glioma - Takeaways - MDSpire

Predictive Models Utilizing Radiomics and Clinical Information for Assessing Pseudoprogression Following Radiotherapy in High-Grade Glioma

  • By

  • Jiang Zhou

  • Zhang Danmeng

  • Yang Hui

  • Xu Zhuohua

  • Wei Mingjing

  • Lu Ying

  • July 20, 2026

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  • 1

    A multivariable model was developed to estimate the risk of pseudoprogression after radiotherapy in high-grade glioma patients.

  • 2

    The study included 222 patients with WHO grade 3 or 4 glioma who underwent surgery followed by radiotherapy.

  • 3

    Seventeen radiomic features were selected to construct the RadScore, which was integrated with clinical and imaging variables.

  • 4

    The integrated model achieved an AUC of 0.811 for predicting pseudoprogression, indicating good internal validation performance.

  • 5

    External validation with standardized imaging protocols is recommended to further assess the model's clinical utility.

Original Source(s)

Radiomics and clinical data predict pseudoprogression after radiotherapy in high-grade glioma

  • by Jiang Zhou, Zhang Danmeng, Yang Hui, Xu Zhuohua, Wei Mingjing, Lu Ying

  • July 20, 2026

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