Study On Fluorescence Lifetime Analysis Method For Low Photon Count Case

Fluorescence lifetime imaging microscopy(FLIM)makes use of the advantage that fluorescence lifetime can reflect the interaction between fluorophores and the changes of microenvironment in imaging,and makes up for the defect that fluorescence intensity imaging is generally difficult to achieve quantitative measurement.It has been widely used in biomedical research such as cell microenvironment parameter measurement and protein interactions,and has gradually become a frequently used analysis tool in modern biology and biomedical research.At present,the time-domain FLIM technique,which uses the time correlated single photon counting(TCSPC)method for fluorescence lifetime detection,has been widely used due to its long development time,maturity and stability,and high sensitivity and resolution.In TCSPC-FLIM,how to estimated lifetime accurately from the measured photon count data is a critical aspect.The measurement of TCSPC reproduces the process of fluorescence decay,transforming the fluorescence decay curve into a photon count histogram over time.For most fluorescence lifetime analysis algorithms,the lower the photon counts measured,the greater the deviation from the true lifetime value.Conversely,the higher the photon counts,the more accurate the analysis.However,the higher the photon counts collected by the system generally means longer acquisition time,which limits the imaging speed and prolongs the sample illumination time and is not good for real-time monitoring of live cell samples.Therefore,it is of great significance to develop a fluorescence lifetime analysis algorithm suitable for low photon count cases,which will be benefit for the development of fast FLIM imaging technologies and their applications.At present,the widely used fluorescence lifetime analysis algorithms include nonlinear least squares fitting,maximum likelihood estimation,etc.Most of these methods cannot obtain accurate fluorescence lifetime in the case of low photon count.In this thesis,the fluorescence lifetime analysis of TCSPC-FLIM is regarded as a sparse inverse problem,and a new fluorescence lifetime analysis algorithm based on alternating descent conditional gradient(ADCG),called ADCG-FLIM,is proposed to improve the accuracy and precision of lifetime analysis for low photon count data.The research work in this thesis includes:1.The TCSPC-FLIM detection model is constructed,and the effects of periodic pulse excitation during experimental imaging,the Poisson noise from photon detection as well as potential background noise are included into the model,making it more approximated to the real situation.2.The fluorescence lifetime analysis is transformed into a sparse inverse problem,an ADCG-FLIM optimization model is established,and the ADCG algorithm framework is used to solve the problem,where different variables to be determined(e.g.,total photon count,lifetime,background noise)in the optimization problem are reduced independently in coordinates until final convergence.Analyses on simulation data and experimental data are carried out using this algorithm,and the results are compared with those using other existing lifetime analysis algorithms,showing that ADCG-FLIM can obtain the lifetime value from low photon count decay data more accurately.3.The ADCG-FLIM is further extended to analyze the case where the fluorescence decay is double exponential(i.e.,the two-component lifetime case).Through the calculation and analysis of the simulation data,it is demonstrated that the extended ADCG-FLIM can be used for stable quantitative analysis of the proportion of each lifetime component,which has a promising application prospect in the quantitative analysis of protein interaction,the measurement of cellular energy metabolism state,etc.The innovative achievements of this thesis primarily include:1.A new fluorescence lifetime analysis algorithm ADCG-FLIM,which enables more accurate lifetime analysis even with low photon count and low signal-to-noise ratio decay data in TCSPC-FLIM,is proposed.2.The ADCG-FLIM algorithm is further extended to realize quantitative analysis of component proportion in two-component lifetime cases with known lifetimes,which is expected to provide a new method for rapid FLIM analysis.