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<p>Glioblastoma is characterized by aggressive infiltration into surrounding brain tissue, hindering complete surgical resection and contributing to poor patient outcomes. Identifying tumor-specific invasion patterns is essential for advancing our understanding of glioblastoma progression and improving surgical and radiotherapeutic strategies. Here, we leverage in vivo dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to noninvasively quantify interstitial fluid velocity, direction, and diffusion within and around glioblastomas. We introduce a novel vector-based pathline analysis to trace downstream accumulation of fluid flow originating from the tumor core, providing a spatially explicit perspective on local flow patterns. We find that localized fluid transport metrics predict glioblastoma invasion and progression, offering a new framework to non-invasively identify high-risk regions and guide targeted treatment approaches.</p>

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Interstitial fluid transport dynamics predict glioblastoma invasion and progression

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月3日

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  • Cora M. Carman-Esparza,
  • Caleb A. Stine,
  • Naciye Atay,
  • Kathryn M. Kingsmore,
  • Maosen Wang,
  • Ryan T. Woodall,
  • Russell C. Rockne,
  • Jessica J. Cunningham,
  • Jennifer M. Munson

摘要

Glioblastoma is characterized by aggressive infiltration into surrounding brain tissue, hindering complete surgical resection and contributing to poor patient outcomes. Identifying tumor-specific invasion patterns is essential for advancing our understanding of glioblastoma progression and improving surgical and radiotherapeutic strategies. Here, we leverage in vivo dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to noninvasively quantify interstitial fluid velocity, direction, and diffusion within and around glioblastomas. We introduce a novel vector-based pathline analysis to trace downstream accumulation of fluid flow originating from the tumor core, providing a spatially explicit perspective on local flow patterns. We find that localized fluid transport metrics predict glioblastoma invasion and progression, offering a new framework to non-invasively identify high-risk regions and guide targeted treatment approaches.