Emerging In Vivo Imaging Modalities for Improved Glioblastoma Surgery and Monitoring

Oluwagbenga Dada1, Shikshita Singh1, Francheska Sumadchat1

  • 1Rocky Vista University, College of Osteopathic Medicine, Ivins, UT 84738, USA.

Biomedicines
|May 4, 2026
PubMed

Insights

Detecting residual glioblastoma (GBM) cells after surgery is challenging due to tumor infiltration and heterogeneity. Advanced optical imaging techniques show promise but require integrated, biologically informed strategies for improved detection and surgical guidance.

Area of Science:

  • Neuro-oncology
  • Biomedical Imaging
  • Cancer Biology

Background:

  • Glioblastoma (GBM) is an aggressive brain tumor with high recurrence rates.
  • Current imaging lacks resolution to detect microscopic tumor invasion.
  • Maximal surgical resection improves outcomes but is limited by residual disease.

Purpose of the Study:

  • To review optical imaging modalities for detecting residual GBM cells.
  • To assess the capabilities and limitations of these advanced imaging techniques.
  • To highlight the need for integrated imaging approaches in neuro-oncology.

Main Methods:

  • Review of multiple optical imaging technologies: multi-photon microscopy, NIR II fluorescence, bioluminescence, photoacoustic imaging, OCT, CLE, Raman spectroscopy, autofluorescence, and fluorescence macroscopy.
  • Focus on the ability of each modality to detect residual GBM cells.
  • Analysis of limitations including molecular targets, blood-brain barrier penetration, and signal variability.

Main Results:

  • Emerging in vivo imaging offers cellular/near-single-cell resolution for preclinical research.
  • These technologies are relevant for surgical guidance and treatment adaptation.
  • Significant advances exist, but limitations hinder widespread clinical application.

Conclusions:

  • Residual GBM cells are difficult to detect due to dispersal and diversity.
  • Current single-modality or single-marker strategies are insufficient.
  • Integrated, biologically informed imaging is crucial for improving residual disease detection and surgical decision-making.

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