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Molecular, morphological, and physiological heterogeneity is the inherent property of cells which governs differences in their response to external influence. Tumor cell metabolic heterogeneity is of a special interest due to its clinical relevance to tumor progression and therapeutic outcomes. Rapid, sensitive, and noninvasive assessment of metabolic heterogeneity of cells is a great demand for biomedical sciences. Fluorescence lifetime imaging (FLIM), which is an all-optical technique, is an emerging tool for sensing and quantifying cellular metabolism by measuring fluorescence decay parameters of endogenous fluorophores, such as NAD(P)H. To achieve accurate discrimination between metabolically diverse cellular subpopulations, appropriate approaches to FLIM data collection and analysis are needed. In this paper, the unique capability of FLIM to attain the overarching goal of discriminating metabolic heterogeneity is demonstrated. This has been achieved using an approach to data analysis based on the nonparametric analysis, which revealed a much better sensitivity to the presence of metabolically distinct subpopulations compared to more traditional approaches of FLIM measurements and analysis. The approach was further validated for imaging cultured cancer cells treated with chemotherapy. These results pave the way for accurate detection and quantification of cellular metabolic heterogeneity using FLIM, which will be valuable for assessing therapeutic vulnerabilities and predicting clinical outcomes. 

Advanced stage glioma is the most aggressive form of malignant brain tumors with a short survival time. Real-time pathology assisted, or image guided surgical procedures that eliminate tumors promise to improve the clinical outcome and prolong the lives of patients. Our work is focused on the development of a rapid and sensitive assay for intraoperative diagnostics of glioma and identification of optical markers essential for differentiation between tumors and healthy brain tissues. We utilized fluorescence lifetime imaging (FLIM) of endogenous fluorophores related to metabolism of the glioma from freshly excised brains tissues. Macroscopic time-resolved fluorescence images of three intracranial animal glioma models and surgical samples of patients’ glioblastoma together with the white matter have been collected. Several established and new algorithms were applied to identify the imaging markers of the tumors. We found that fluorescence lifetime parameters characteristic of the glioma provided background for differentiation between the tumors and intact brain tissues. All three rat tumor models demonstrated substantial differences between the malignant and normal tissue. Similarly, tumors from patients demonstrated statistically significant differences from the peritumoral white matter without infiltration. While the data and the analysis presented in this paper are preliminary and further investigation with a larger number of samples is required, the proposed approach based on the macroscopic FLIM has a high potential for diagnostics of glioma and evaluation of the surgical margins of gliomas.