High-Speed three-dimensional glioma morphology imaging and grade discrimination using micro-optical coherence tomography

Glioma is one of the most common types of central nervous system (CNS) tumor with an average survival of 1.5 to 2 years. One way to improve the patient survival is to identify and excise the glioma tumor precisely and completely to seek for subsequent treatment. Due to the system complexity and limited performances of the existing diagnostic tools, however, the identification of glioma tumor is difficult, and therefore, it is imperative to develop new diagnostic imaging tools that could be able to identify glioma rapidly and reliably. In this study, we construct a free-spaced micro-optical coherence tomography (μOCT) system, which achieves a spatial resolution of 2.0 μm, for glioma imaging, and then, evaluate its capability for identifying the cellular/sub-cellular structures of glioma lesions. Imaging results demonstrate that the μOCT system is not only able to acquire cellular/sub-cellular glioma microstructure images, but it is also able to differentiate between the low-grade and high-grade glioma lesions with the three-dimensional (3D) tissue morphology appearances. The low system complexity enables μOCT to be integrated onto surgical pick tip and utilized as an intraoperative diagnostic tool, while the high-resolution imaging capability of μOCT could help neurosurgeons identify the interfaces between glioma lesions and non-cancerous tissues fast and reliably, and thus, help neurosurgeons make appropriate treatment decisions. Such results convincingly demonstrate the potential of μOCT for neurosurgery in clinical practice.