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The first-line treatment for brain cancer is surgery, which focuses on maximizing the percentage of the tumor removed during surgery (i.e., extent of resection) while minimizing damage to healthy brain tissue. Data show that extent of resection is one of the most critical factors associated with prolonged survival. However, differentiating between tumor and healthy tissue intraoperatively remains a significant clinical challenge, resulting in an exceedingly low 5-year survival rate of only ~35%. In this work, we show that quantitative oblique back illumination microscopy (qOBM), a novel label-free optical imaging technique that achieves tomographic quantitative phase imaging (QPI) in thick scattering samples, clearly differentiates between tumor and healthy tissue. Using a 9L gliosarcoma rat tumor model, we show that quantitative image features from qOBM provide a robust set of biomarkers for disease. In addition, tumor regions, including diffuse tumor, and healthy brain structures, show excellent structural agreement with H&E stained and sliced brightfield images, the gold standard for cancer detection. The unique attribute of qOBM—low-cost, easy-to-use, label-free, and real-time—make this technology ideally suited to help guide neurosurgery and address this important unmet need. Here we describe our free-space qOBM system and present quantitative results from the 9L gliosarcoma rat tumor model.
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