AI-assisted Methods for Detection of Brain Tumor Margins Using Optical Coherence Tomography

Abstract

In brain cancer surgery, it is critical to achieve extensive tumor resection without compromising adjacent healthy brain tissue. Various technologies (e.g. intraoperative magnetic resonance imaging and computed tomography) have made major contributions; however, these technologies do not provide quantitative, real-time and three-dimensional (3D) continuous guidance. Optical Coherence Tomography (OCT) is a non-invasive, label-free, real-time, high-resolution imaging modality that has been explored for glioma infiltration detection. Here we report a series of AI-based methods for computer-aided detection (CAD) system for automated, real-time, in situ detection of glioma infiltration. Volumetric OCT datasets were intraoperatively obtained from resected brain tissue specimens of 21 patients with glioma tumors of different stages and labeled as either non-cancerous or glioma-infiltrated based on histopathology evaluation (gold standard). Labeled OCT images from 12 patients were used as training dataset to develop the AI-assisted OCT-based models. Unlabeled OCT images from the other 9 patients were used as a validation dataset to quantify the method detection performance. Our methods outperformed current techniques in the literature and achieved excellent levels of both sensitivity and specificity (~90%) for detecting glioma-infiltrated tissue with high spatial resolution (~16 um laterally). Previous methods for OCT-based detection of glioma-infiltrated brain tissue rely on underlying optical properties such as attenuation coefficient from the OCT signal requiring sacrificing spatial resolution and cumbersome calibration procedures. By overcoming these major challenges, our novel AI-assisted CAD system methods will enable implementing practical OCT-guided surgical tools for continuous, real-time and accurate intra-operative detection of glioma-infiltrated brain tissue, facilitating maximal glioma resection and superior surgical outcomes for glioma patients.