The human brain is made up of functional regions governing movement, sensation, language, and cognition. Unintentional injury during neurosurgery can result in significant neurological deficits and morbidity. The current standard for localizing function to brain tissue during surgery, intraoperative electrical stimulation or recording, significantly increases the risk, time, and cost of the procedure. There is a need for a fast, cost-effective, and high-resolution intraoperative technique that can avoid damage to functional brain regions. We propose that optical coherence tomography (OCT) can fill this niche by imaging differences in the cellular composition and organization of functional brain areas. We hypothesized this would manifest as differences in the attenuation coefficient measured using OCT. Five functional regions (prefrontal, somatosensory, auditory, visual, and cerebellum) were imaged in ex vivo porcine brains (n=3), a model chosen due to a similar white/gray matter ratio as human brains. The attenuation coefficient was calculated using a depth-resolved model and quantitatively validated with Intralipid phantoms across a physiological range of attenuation coefficients (absolute difference < 0.1cm-1). Image analysis was performed on the attenuation coefficient images to derive quantitative endpoints. We observed a statistically significant difference among the median attenuation coefficients of these five regions (one-way ANOVA, p<0.05). Nissl-stained histology will be used to validate our results and correlate OCT-measured attenuation coefficients to neuronal density. Additional development and validation of OCT algorithms to discriminate brain regions are planned to improve the safety and efficacy of neurosurgical procedures such as biopsy, electrode placement, and tissue resection.
Daniel A. Gil, Hansen C. Bow, Jin-H. Shen, Karen M. Joos, and Melissa C. Skala, "Differentiating functional brain regions using optical coherence tomography (Conference Presentation)," Proc. SPIE 10050, Clinical and Translational Neurophotonics, 1005006 (Presented at SPIE BiOS: January 28, 2017; Published: 19 April 2017); https://doi.org/10.1117/12.2252820.5370387607001.
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