
Fast fluorescence lifetime imaging techniques: A review on challenge and development
Author(s) -
Xiongbo Liu,
Danying Lin,
Wolfgang Becker,
Jingjing Niu,
Bin Yu,
Liwei Liu,
Junle Qu
Publication year - 2019
Publication title -
journal of innovative optical health sciences/journal of innovation in optical health science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 24
eISSN - 1793-5458
pISSN - 1793-7205
DOI - 10.1142/s1793545819300039
Subject(s) - fluorescence lifetime imaging microscopy , data acquisition , computer science , biomedicine , biological imaging , sensitivity (control systems) , fluorescence , microscopy , nanotechnology , biological system , materials science , physics , optics , bioinformatics , biology , engineering , electronic engineering , operating system
Fluorescence lifetime imaging microscopy (FLIM) is increasingly used in biomedicine, material science, chemistry, and other related research fields, because of its advantages of high specificity and sensitivity in monitoring cellular microenvironments, studying interaction between proteins, metabolic state, screening drugs and analyzing their efficacy, characterizing novel materials, and diagnosing early cancers. Understandably, there is a large interest in obtaining FLIM data within an acquisition time as short as possible. Consequently, there is currently a technology that advances towards faster and faster FLIM recording. However, the maximum speed of a recording technique is only part of the problem. The acquisition time of a FLIM image is a complex function of many factors. These include the photon rate that can be obtained from the sample, the amount of information a technique extracts from the decay functions, the efficiency at which it determines fluorescence decay parameters from the recorded photons, the demands for the accuracy of these parameters, the number of pixels, and the lateral and axial resolutions that are obtained in biological materials. Starting from a discussion of the parameters which determine the acquisition time, this review will describe existing and emerging FLIM techniques and data analysis algorithms, and analyze their performance and recording speed in biological and biomedical applications.