Label-Free Detection of the Architectural Feature of Blood Vessels in Glioblastoma Based on Multiphoton Microscopy

Abstract

Glioblastoma (GBM) is a highly angiogenesis malignant tumor with a significant heterogeneity of vascular morphology. The vascular patterns could be served as an indicator of vascular morphological complexity that associated with postoperative prognosis of patients with GBM. Here, multiphoton microscopy (MPM), based on second harmonic generation (SHG) and two-photon excited fluorescence (TPEF), is applied for detecting the architectural feature of blood vessels from ex vivo, unfixed, and unstained human GBM specimens. Combined with the image processing algorithms, the morphology, location, orientation, alignment, and density of vascular collagen are qualitatively and quantitatively visualized, revealing the presented method not only contribute to differentiate GBM from normal brain tissue, but also provide important indicators of different vascular patterns, which may serve as a reference to the prognosis more accurately. Therefore, these results can provide prognosis-related histopathological diagnosis of GBM, holding a translational potential to be used as a label-free, quick, and on-site imaging tool for clinicians to determine the extent of excision involving brain functional areas.