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Abstract: The goal of this study is to validate fluorescence intensity and lifetime imaging of metabolic co‐enzymes NAD(P)H and FAD (optical metabolic imaging, or OMI) as a method to quantify cell‐cycle status of tumor cells. Heterogeneity in tumor cell‐cycle status (e. g. proliferation, quiescence, apoptosis) increases drug resistance and tumor recurrence. Cell‐cycle status is closely linked to cellular metabolism. Thus, this study applies cell‐level metabolic imaging to distinguish proliferating, quiescent, and apoptotic populations. Two‐photon microscopy and time‐correlated single photon counting are used to measure optical redox ratio (NAD(P)H fluorescence intensity divided by FAD intensity), NAD(P)H and FAD fluorescence lifetime parameters. Redox ratio, NAD(P)H and FAD lifetime parameters alone exhibit significant differences (p<0.05) between population means. To improve separation between populations, linear combination models derived from partial least squares ‐ discriminant analysis (PLS‐DA) are used to exploit all measurements together. Leave‐one‐out cross validation of the model yielded high classification accuracies (92.4 and 90.1 % for two and three populations, respectively). OMI and PLS‐DA also identifies each sub‐population within heterogeneous samples. These results establish single‐cell analysis with OMI and PLS‐DA as a label‐free method to distinguish cell‐cycle status within intact samples. This approach could be used to incorporate cell‐level tumor heterogeneity in cancer drug development. [ABSTRACT FROM AUTHOR]

Significance: Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique to distinguish the unique molecular environment of fluorophores. FLIM measures the time a fluorophore remains in an excited state before emitting a photon, and detects molecular variations of fluorophores that are not apparent with spectral techniques alone. FLIM is sensitive to multiple biomedical processes including disease progression and drug efficacy. Aim: We provide an overview of FLIM principles, instrumentation, and analysis while highlighting the latest developments and biological applications. Approach: This review covers FLIM principles and theory, including advantages over intensity-based fluorescence measurements. Fundamentals of FLIM instrumentation in time- and frequency-domains are summarized, along with recent developments. Image segmentation and analysis strategies that quantify spatial and molecular features of cellular heterogeneity are reviewed. Finally, representative applications are provided including high-resolution FLIM of cell- and organelle-level molecular changes, use of exogenous and endogenous fluorophores, and imaging protein-protein interactions with Förster resonance energy transfer (FRET). Advantages and limitations of FLIM are also discussed. Conclusions: FLIM is advantageous for probing molecular environments of fluorophores to inform on fluorophore behavior that cannot be elucidated with intensity measurements alone. Development of FLIM technologies, analysis, and applications will further advance biological research and clinical assessments. [ABSTRACT FROM AUTHOR]