Tumor Margin Detection Using Quantitative NIRF Molecular Imaging Targeting EpCAM Validated by Far Red Gene Reporter iRFP

2013 ◽  
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Murat Kaya Yapici ◽  
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Bhaskar Banerjee ◽  
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Neurosurgery ◽  
2017 ◽  
Vol 64 (CN_suppl_1) ◽  
pp. 264-264 ◽  
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Abstract INTRODUCTION Optical coherence tomography (OCT) is an emerging technology with the potential to allow for rapid intraoperative detection of brain tumor margins by detecting differences in structure, intensity, spectral signal, and attenuation. OCT systems are capable of rapid imaging of large three-dimensional volumes with cellular level resolution. However, OCT imaging has previously been limited by speckle artifact and the lack of suitable contrast agents, limitations that are surmounted in this study. METHODS We prepared nude mice with orthotopic U87 glioblastoma xenografts and glass cranial windows. We also created large gold nanorods (LGNR) with plasmonic peaks tuned to the spectral range of the OCT scanner. LGNRs were injected intravenously into tumor-bearing mice and OCT imaging was performed in vivo utilizing a novel method for the removal of speckle artifact called Speckle-Free OCT (SFOCT). Fresh ex-vivo patient samples were also imaged. RESULTS >OCT and SFOCT readily distinguished tumor from normal brain with cellular level spatial resolution and to a depth of 1.5 mm. Additionally, SFOCT allowed for the highest resolution ever seen in vivo of mouse white matter architecture. Cortical layers were also readily visible in SFOCT in both live mice and in the ex-vivo human samples, representing a novel ability to interrogate cortical cytoarchitecture across a large field of view. Systemically administered LGNRs were tumor specific and provided excellent spectral contrast using OCT. Ex-vivo hyperspectral and IHC imaging confirmed the localization of LGNRs within the tumor and found that the LGNRs were largely localized within tumor associated macrophages. CONCLUSION SFOCT and LGNR enhanced OCT imaging are promising state of the art technologies for intraoperative tumor margin detection.


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