Time-resolved fluorescence (TRF) measurements from layered biological tissue provide chemical and structural
information which may be useful for imaging or single-point tissue diagnostics. While several techniques for analyzing
TRF data have been proposed in the literature, a rigorous theoretical evaluation of these approaches has not been
performed. In this study we have evaluated the sensitivity and robustness of four methods for analyzing TRF signals:
biexponential deconvolution, single exponential deconvolution, Laguerre deconvolution, and direct peak width
computation. Each of these analyses was performed on a large dataset of synthetic fluorescence decay curves. Each
decay curve was generated by numerically convolving a pre-recorded nitrogen laser pulse with a biexponential decay
based on fluorescence lifetimes of colonic mucosa. The relative contribution of each mucosal layer to the total TRF
signal as well as the superficial layer's inherent lifetime were varied so as to investigate sensitivity to morphological and
biochemical changes representative of a neoplastic disease process. To evaluate robustness, pre-set levels of Gaussian-distributed
noise were added to the convolved curves to achieve variations in the signal-to-noise ratio. The relative
merits and pitfalls of each analytical method are discussed.
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