Spectro-Temporal Autofluorescence Contrast–Based Imaging for Brain Tumor Margin Detection and Biobanking

2017 ◽  
pp. 355-368
Author(s):  
Asael Papour ◽  
Zach Taylor ◽  
Linda Liau ◽  
William H. Yong ◽  
Oscar Stafsudd ◽  
...  
Neurosurgery ◽  
2017 ◽  
Vol 64 (CN_suppl_1) ◽  
pp. 264-264 ◽  
Author(s):  
Derek W Yecies ◽  
Orly Liba ◽  
Elliot SoRelle ◽  
Rebecca Dutta ◽  
Christy Wilson ◽  
...  

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.


2021 ◽  
Author(s):  
Tae Il Yoon ◽  
Jae Sung Park ◽  
Byeong Ha Lee ◽  
Tae Joong Eom

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Derek Yecies ◽  
Orly Liba ◽  
Elliott D. SoRelle ◽  
Rebecca Dutta ◽  
Edwin Yuan ◽  
...  

2018 ◽  
Author(s):  
Derek Yecies ◽  
Orly Liba ◽  
Elliott SoRelle ◽  
Rebecca Dutta ◽  
Edwin Yuan ◽  
...  

AbstractCurrent in vivo neuroimaging techniques provide limited field of view or spatial resolution and often require exogenous contrast. These limitations prohibit detailed structural imaging across wide fields of view and hinder intraoperative tumor margin detection. Here we present a novel neuroimaging technique, speckle-modulating optical coherence tomography (SM-OCT), which allows us to image the brains of live mice and ex vivo human samples with unprecedented resolution and wide field of view using only endogenous contrast. The increased effective resolution provided by speckle elimination reveals white matter fascicles and cortical layer architecture in the brains of live mice. To our knowledge, the data reported herein represents the highest resolution imaging of murine white matter structure achieved in vivo across a wide field of view of several millimeters. When applied to an orthotopic murine glioblastoma xenograft model, SM-OCT readily identifies brain tumor margins with near single-cell resolution. SM-OCT of ex vivo human temporal lobe tissue reveals fine structures including cortical layers and myelinated axons. Finally, when applied to an ex vivo sample of a low-grade glioma resection margin, SM-OCT is able to resolve the brain tumor margin. Based on these findings, SM-OCT represents a novel approach for intraoperative tumor margin detection and in vivo neuroimaging.


2012 ◽  
Vol 39 (11) ◽  
pp. 6929-6942 ◽  
Author(s):  
Wei Yang ◽  
Qianjin Feng ◽  
Mei Yu ◽  
Zhentai Lu ◽  
Yang Gao ◽  
...  

2011 ◽  
Vol 11 (4) ◽  
pp. 891-896 ◽  
Author(s):  
Alejandro Garcia-Uribe ◽  
Cheng-Chung Chang ◽  
Murat Kaya Yapici ◽  
Jun Zou ◽  
Bhaskar Banerjee ◽  
...  

2006 ◽  
Author(s):  
Steven C. Gebhart ◽  
Shovan K. Majumder ◽  
Anita Mahadevan-Jansen

2007 ◽  
Author(s):  
Shovan K. Majumder ◽  
Steven Gebhart ◽  
Reid Thompson ◽  
Kyle D. Weaver ◽  
Mahlon D. Johnson ◽  
...  

Author(s):  
V. Artyushenko ◽  
U. Zabarylo ◽  
A. Bogomolov ◽  
O. Minet ◽  
H. Krause ◽  
...  

2014 ◽  
Author(s):  
Yan Zhou ◽  
Cheng-hui Liu ◽  
Jiyou Li ◽  
Zhongwu Li ◽  
Lixin Zhou ◽  
...  

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