Abstract. Fluorescence lifetime imaging (FLIM) aims at quantifying the exponential decay rate of fluorophores to yield lifetime maps over the imaged sample. When combined with Förster resonance energy transfer (FRET), the technique can be used to indirectly sense interactions at the nanoscale such as protein-protein interactions, protein-DNA interactions, and protein conformational changes. In the case of FLIM-FRET, the fluorescence intensity decays are fitted to a biexponential model in order to estimate the lifetime and fractional amplitude coefficients of each component of the population of the donor fluorophore (quenched and nonquenched). Numerous time data points, also called temporal or time gates, are typically employed for accurately estimating the model parameters, leading to lengthy acquisition times and significant computational demands. This work investigates the effect of the number and location of time gates on model parameter estimation accuracy. A detailed model of a FLIM-FRET imaging system is used for the investigation, and the simulation outcomes are validated with in vitro and in vivo experimental data. In all cases investigated, it is found that 10 equally spaced time gates allow robust estimation of model-based parameters with accuracy similar to that of full temporal datasets (90 gates).

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Fluorescence lifetime imaging (FLIM) when paired with Förster resonance energy transfer (FLIM-FRET) enables the monitoring of nanoscale interactions in living biological samples. FLIM-FRET model-based estimation methods allow the quantitative retrieval of parameters such as the quenched (interacting) and unquenched (non-interacting) fractional populations of the donor fluorophore and/or the distance of the interactions. The quantitative accuracy of such model-based approaches is dependent on multiple factors such as signal-to-noise ratio and number of temporal points acquired when sampling the fluorescence decays. For high-throughput or in vivo applications of FLIM-FRET, it is desirable to acquire a limited number of temporal points for fast acquisition times. Yet, it is critical to acquire temporal data sets with sufficient information content to allow for accurate FLIM-FRET parameter estimation. Herein, an optimal experimental design approach based upon sensitivity analysis is presented in order to identify the time points that provide the best quantitative estimates of the parameters for a determined number of temporal sampling points. More specifically, the D-optimality criterion is employed to identify, within a sparse temporal data set, the set of time points leading to optimal estimations of the quenched fractional population of the donor fluorophore. Overall, a reduced set of 10 time points (compared to a typical complete set of 90 time points) was identified to have minimal impact on parameter estimation accuracy (≈5%), with in silico and in vivo experiment validations. This reduction of the number of needed time points by almost an order of magnitude allows the use of FLIM-FRET for certain high-throughput applications which would be infeasible if the entire number of time sampling points were used.

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