Fluorescence Lifetime Imaging Data Analysis and Interpretation

Fluorescence lifetime imaging microscopy (FLIM) has emerged as a powerful tool for analyzing biological systems through the measurement of fluorescence decay characteristics of endogenous fluorophores. This comprehensive review examines two primary approaches for FLIM data analysis and interpretation: multi-exponential fitting and phasor-plot representation. The multi-exponential approach utilizes mathematical decomposition of fluorescence decay curves, typically employing two-exponential regression to characterize fast and slow lifetime components. This method enables quantitative assessment of cellular metabolism through analysis of key endogenous fluorophores, including NAD(P)H, FAD, tryptophan, and collagen. Applications demonstrate successful visualization of skin capillaries, assessment of fibroblast metabolic activity on different ceramic substrates, and evaluation of the epidermal layer structure. The phasor-plot approach provides an alternative graphical representation that transforms fluorescence lifetime data into a two-dimensional coordinate system through Fourier analysis. This method offers intuitive visualization of multi-component systems and has proven valuable for glucose stimulation studies in pancreatic β-cells, wound healing assessment in diabetic versus healthy tissue, and cancer diagnostics through exosome analysis. Clinical applications span diverse biomedical fields, including dermatology, oncology, and metabolic research. In dermatological applications, FLIM successfully differentiates skin cell types, monitors wound healing processes, and evaluates photodynamic therapy effectiveness. Oncological applications include colorectal cancer diagnosis through blood exosome analysis and metabolic characterization of cancer spheroids. The technique also enables bacterial differentiation and antibiotic susceptibility assessment. Both analytical approaches demonstrate complementary strengths: multi-exponential fitting provides quantitative lifetime parameters suitable for comparative studies, while phasor plots offer rapid visual discrimination of different biological states. The integration of these methodologies with advanced imaging systems enables non-invasive, label-free characterization of cellular metabolism and pathological conditions, positioning FLIM as an invaluable tool for both research and clinical diagnostics in modern biomedical applications.