Work

Label-free and multiplexed glioblastoma identification based on texture analysis and phasor FLIM

Year: 2026

Type: article

Abstract: Glioblastoma is a highly invasive primary malignant brain tumor, and its precise intraoperative identification has always been a major challenge in clinical practice. In this study, we propose a label-free and multiplexed strategy for glioblastoma identification based on two-photon fluorescence lifetime imaging (FLIM) and a robust quantitative analysis. Specifically, we constructed an orthotopic xenograft model of human glioblastoma and then performed fresh tissue imaging. From the acquired images, we performed a gray-level co-occurrence matrix texture analysis and phasor fluorescence lifetime analysis to quantify the microstructural difference and metabolic characteristics of tumor and peritumor areas. Based on the above analysis, we extracted four morphological texture parameters and four metabolic phasor parameters with potential as identification indicators for glioblastoma. We have integrated the novel multi-parameter analysis strategy to achieve robust and effective discrimination between glioblastoma and peritumoral tissue. This advancement and the method presented in this study will allow for the achievement of real-time, label-free, and multi-dimensional precise glioblastoma identification in the future.

Source: Journal of Innovative Optical Health Sciences

DOI: 10.1142/s1793545826500112