Abstract
Safely maximizing brain cancer removal without injuring adjacent healthy tissue is crucial for optimal treatment outcomes. However, it is challenging to distinguish cancer from noncancer intraoperatively. This study aimed to explore the feasibility of diffuse reflectance spectroscopy (DRS) as a label-free and real-time detection technology for discrimination between brain cancer and noncancer tissues. Fifty-five fresh cancer and noncancer specimens from 19 brain surgeries were measured with DRS, and the results were compared with co-registered clinical standard histopathology. Tissue optical properties were quantitatively obtained from the diffuse reflectance spectra and compared among different types of brain tissues. A machine learning-based classifier was trained to differentiate cancerous versus noncancerous tissues. Our method could achieve a sensitivity of 93% and specificity of 95% for discriminating high-grade glioma from normal white matter. Our results showed that DRS has the potential to be used for label-free, real-time in vivo cancer detection during brain surgery.
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