Imaging studies for predicting hematoma expansion: from traditional imaging signs to artificial intelligence-based multimodal fusion - Takeaways - MDSpire

Imaging studies for predicting hematoma expansion: from traditional imaging signs to artificial intelligence-based multimodal fusion

  • By

  • Jie Wu

  • Jinping Sheng

  • Yu Xiao

  • Fa Wu

  • Pingping He

  • Rui Jiang

  • Zhiwei Zuo

  • Peng Wang

  • June 26, 2026

  • 0 min

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  • 1

    Hematoma expansion (HE) is a critical event post-intracerebral hemorrhage, affecting patient outcomes and requiring accurate prediction for targeted intervention.

  • 2

    Revised hematoma expansion (rHE) incorporates intraventricular hemorrhage growth, improving sensitivity for predicting poor outcomes compared to traditional HE definitions.

  • 3

    Ultraearly hematoma growth (uHG) emphasizes the rate of bleeding, with uHG > 10.2 mL/h identified as a strong predictor of adverse outcomes.

  • 4

    AI-driven methodologies, including radiomics and deep learning, enhance predictive capabilities beyond traditional imaging markers for HE.

  • 5

    Challenges in HE prediction include model generalizability, interpretability, and clinical translation, necessitating future advancements in AI and multimodal data fusion.

Original Source(s)

Imaging studies for predicting hematoma expansion: from traditional imaging signs to artificial intelligence-based multimodal fusion

  • by Jie Wu, Jinping Sheng, Yu Xiao, Fa Wu, Pingping He, Rui Jiang, Zhiwei Zuo, Peng Wang

  • June 26, 2026

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