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Journal of Neuro-Oncology

, Volume 111, Issue 2, pp 153–161 | Cite as

Real-time multi-modality imaging of glioblastoma tumor resection and recurrence

  • Shawn Hingtgen
  • Jose-Luiz Figueiredo
  • Christian Farrar
  • Matthias Duebgen
  • Jordi Martinez-Quintanilla
  • Deepak Bhere
  • Khalid ShahEmail author
Laboratory Investigation

Abstract

The lack of relevant pre-clinical animal models incorporating the clinical scenario of Glioblastoma multiforme (GBM) resection and recurrence has contributed significantly to the inability to successfully treat GBM. A multi-modality imaging approach that allows real-time assessment of tumor resection during surgery and non-invasive detection of post-operative tumor volumes is urgently needed. In this study, we report the development and implementation of an optical imaging and magnetic resonance imaging (MRI) approach to guide GBM resection during surgery and track tumor recurrence at multiple resolutions in mice. Intra-operative fluorescence-guided surgery allowed real-time monitoring of intracranial tumor removal and led to greater than 90 % removal of established intracranial human GBM. The fluorescent signal clearly delineated tumor margins, residual tumor, and correlated closely with the clinically utilized fluorescence surgical marker 5-aminolevulinic acid/porphyrin. Post-operative non-invasive optical imaging and MRI confirmed near-complete tumor removal, which was further validated by immunohistochemistry (IHC). Longitudinal non-invasive imaging and IHC showed rapid recurrence of multi-focal tumors that exhibited a faster growth rate and altered blood-vessel density compared to non-resected tumors. Surgical tumor resection significantly extended long-term survival, however mice ultimately succumbed to the recurrent GBM. This multi-modality imaging approach to GBM resection and recurrence in mice should provide an important platform for investigating multiple aspects of GBM and ultimately evaluating novel therapeutics.

Keywords

Glioma Image-Guided resection In vivo imaging Recurrence 

Notes

Acknowledgments

This work was supported by Alliance for Cancer Cell and Gene Therapy (KS), American Cancer Society (KS), James McDonald Foundation (KS) and National Institute of Health, R01-NSO71197 (KS).

Conflict of interest

The authors have no conflicts to disclose.

Supplementary material

11060_2012_1008_MOESM1_ESM.tif (1.4 mb)
Supplemental Figure 1 Pre-resection tumor progression. Representative images and summary data demonstrating the direct correlation of U87-GFPFLuc cell number with bioluminescence signal in vitro. Scale bar, 100 μm (TIFF 1458 kb)
11060_2012_1008_MOESM2_ESM.tif (3.1 mb)
Supplemental Figure 2 H&E staining of primary and recurrent tumors. Representative white light H&E images of brain sections from mice 2 weeks after primary tumor implantation (a) or tumor recurrence (b). Scale bars, 100 μm (TIFF 3223 kb)
Supplemental Movie 1

Image-guided surgical debulking. Representative movie depicting the initial stages of fluorescence guided surgical resection (MOV 4314 kb)

Supplemental Movie 2

Image-guided surgical debulking. Representative movie depicting the final stages fluorescence guided surgical resection when the tumor is excised from the brain leaving an empty cavity with residual tumors cells visible at the border of the cavity (MOV 1520 kb)

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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Shawn Hingtgen
    • 1
  • Jose-Luiz Figueiredo
    • 1
  • Christian Farrar
    • 2
  • Matthias Duebgen
    • 1
  • Jordi Martinez-Quintanilla
    • 1
  • Deepak Bhere
    • 1
  • Khalid Shah
    • 1
    • 3
    • 4
    Email author
  1. 1.Molecular Neurotherapy and Imaging Laboratory, Massachusetts General HospitalHarvard Medical SchoolBostonUSA
  2. 2.Department of Radiology, Massachusetts General HospitalAthinoula A. Martinos Center for Biomedical Imaging, Harvard Medical SchoolBostonUSA
  3. 3.Department of Neurology, Massachusetts General HospitalHarvard Medical SchoolBostonUSA
  4. 4.Harvard Stem Cell Institute, Harvard UniversityCambridgeUSA

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