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      Recent innovations in fluorescence lifetime imaging microscopy for biology and medicine

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          Abstract.

          Significance: Fluorescence lifetime imaging microscopy (FLIM) measures the decay rate of fluorophores, thus providing insights into molecular interactions. FLIM is a powerful molecular imaging technique that is widely used in biology and medicine.

          Aim: This perspective highlights some of the major advances in FLIM instrumentation, analysis, and biological and clinical applications that we have found impactful over the last year.

          Approach: Innovations in FLIM instrumentation resulted in faster acquisition speeds, rapid imaging over large fields of view, and integration with complementary modalities such as single-molecule microscopy or light-sheet microscopy. There were significant developments in FLIM analysis with machine learning approaches to enhance processing speeds, fit-free techniques to analyze images without a priori knowledge, and open-source analysis resources. The advantages and limitations of these recent instrumentation and analysis techniques are summarized. Finally, applications of FLIM in the last year include label-free imaging in biology, ophthalmology, and intraoperative imaging, FLIM of new fluorescent probes, and lifetime-based Förster resonance energy transfer measurements.

          Conclusions: A large number of high-quality publications over the last year signifies the growing interest in FLIM and ensures continued technological improvements and expanding applications in biomedical research.

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          Most cited references38

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          The phasor approach to fluorescence lifetime imaging analysis.

          Changing the data representation from the classical time delay histogram to the phasor representation provides a global view of the fluorescence decay at each pixel of an image. In the phasor representation we can easily recognize the presence of different molecular species in a pixel or the occurrence of fluorescence resonance energy transfer. The analysis of the fluorescence lifetime imaging microscopy (FLIM) data in the phasor space is done observing clustering of pixels values in specific regions of the phasor plot rather than by fitting the fluorescence decay using exponentials. The analysis is instantaneous since is not based on calculations or nonlinear fitting. The phasor approach has the potential to simplify the way data are analyzed in FLIM, paving the way for the analysis of large data sets and, in general, making the FLIM technique accessible to the nonexpert in spectroscopy and data analysis.
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            Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications

            Abstract. 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.
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              Rapid Global Fitting of Large Fluorescence Lifetime Imaging Microscopy Datasets

              Fluorescence lifetime imaging (FLIM) is widely applied to obtain quantitative information from fluorescence signals, particularly using Förster Resonant Energy Transfer (FRET) measurements to map, for example, protein-protein interactions. Extracting FRET efficiencies or population fractions typically entails fitting data to complex fluorescence decay models but such experiments are frequently photon constrained, particularly for live cell or in vivo imaging, and this leads to unacceptable errors when analysing data on a pixel-wise basis. Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. It makes efficient use of both computer processor and memory resources, requiring less than a minute to analyse time series and multiwell plate datasets with hundreds of FLIM images on standard personal computers. This lifetime analysis takes account of repetitive excitation, including fluorescence photons excited by earlier pulses contributing to the fit, and is able to accommodate time-varying backgrounds and instrument response functions. We demonstrate that this global approach allows us to readily fit time-resolved fluorescence data to complex models including a four-exponential model of a FRET system, for which the FRET efficiencies of the two species of a bi-exponential donor are linked, and polarisation-resolved lifetime data, where a fluorescence intensity and bi-exponential anisotropy decay model is applied to the analysis of live cell homo-FRET data. A software package implementing this algorithm, FLIMfit, is available under an open source licence through the Open Microscopy Environment.
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                Author and article information

                Contributors
                Journal
                J Biomed Opt
                J Biomed Opt
                JBOPFO
                JBO
                Journal of Biomedical Optics
                Society of Photo-Optical Instrumentation Engineers
                1083-3668
                1560-2281
                10 July 2021
                July 2021
                10 July 2021
                : 26
                : 7
                : 070603
                Affiliations
                [a ]Morgridge Institute for Research , Madison, Wisconsin, United States
                [b ]University of Wisconsin , Department of Biomedical Engineering, Madison, Wisconsin, United States
                Author notes
                [* ]Address all correspondence to Melissa C. Skala, mcskala@ 123456wisc.edu
                [†]

                These authors equally contributed to this work.

                Author information
                https://orcid.org/0000-0002-6432-2389
                https://orcid.org/0000-0002-1470-3300
                https://orcid.org/0000-0002-6320-7637
                Article
                JBO-210093-PER 210093-PER
                10.1117/1.JBO.26.7.070603
                8271181
                34247457
                f4840d38-5e0e-4091-8e92-8482248ad25f
                © 2021 The Authors

                Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

                History
                : 30 March 2021
                : 11 June 2021
                Page count
                Figures: 3, Tables: 1, References: 38, Pages: 11
                Funding
                Funded by: National Institutes of Health (NIH) https://doi.org/10.13039/100000002
                Award ID: R01 CA185747
                Award ID: R01 CA205101
                Award ID: R01 CA211082
                Award ID: R21 CA224280
                Award ID: U01 TR002383
                Award ID: R37 CA226526
                Award ID: U01 EY032333
                Award ID: P01 CA250972
                Award ID: P30 CA014520
                Funded by: National Science Foundation (NSF) https://doi.org/10.13039/100000001
                Award ID: CBET-1642287
                Funded by: Stand Up to Cancer
                Award ID: SU2C-AACR-IG-08-16
                Award ID: SU2C-AACR-PS-18
                Funded by: University of Wisconsin Carbone Cancer Center
                Award ID: P30 CA014520
                Funded by: UWCCC Pancreatic Cancer Taskforce
                Categories
                Perspectives
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                Custom metadata
                Datta et al.: Recent innovations in fluorescence lifetime imaging microscopy for biology and medicine

                Biomedical engineering
                fluorescence lifetime,microscopy,fluorescence lifetime imaging microscopy,image analysis,perspectives

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