Advances in fluorescence lifetime imaging microscopy: Techniques and biomedical applications

荧光寿命成像显微镜 计算机科学 纳米技术 可视化 吞吐量 医学影像学 数据采集 光学成像 影像学 高分辨率 分子成像 材料科学 生物成像 图像处理 人工智能 成像技术 超分辨率
作者
Fangrui Lin,Chenshuang Zhang,Zhenlong Huang,Yiqiang Wang,Min Yi,Jia Li,Xiaoyu Weng,Yu Chen,Puxiang Lai,Junle Qu
出处
期刊:Applied physics reviews [American Institute of Physics]
卷期号:13 (1)
标识
DOI:10.1063/5.0300853
摘要

Fluorescence lifetime imaging microscopy (FLIM) has emerged as a powerful biomedical imaging technique for the quantitative visualization of intricate molecular and cellular processes. Significant advancements in photonics, sensor technology, data acquisition systems, and computational algorithms have substantially improved the spatiotemporal resolution, imaging depth, and analytical throughput of FLIM. These developments have diversified FLIM methodologies, including time-domain techniques such as time-correlated single-photon counting (TCSPC), time-gated detection, streak cameras, and direct pulse-recording systems, as well as frequency-domain approaches. Concurrently, FLIM has been successfully integrated with advanced imaging modalities, such as multiphoton microscopy, light-sheet imaging, and endoscopy. This review provides a comprehensive synthesis of advanced FLIM technologies. We present in-depth discussions on the principles of lifetime quantification, recent innovations in hardware and algorithms for lifetime recovery, and state-of-the-art strategies to accelerate imaging speed while maintaining resolution and sensitivity. Moreover, we explore FLIM's unique capability to investigate dynamic metabolic states through endogenous autofluorescent cofactors, quantify physicochemical parameters of the cellular microenvironment (e.g., pH, polarity, viscosity, and ion concentrations), and facilitate the diagnosis of diseases such as cancer and neurodegeneration. Finally, we discuss future directions for FLIM development, including integration with deep learning, miniaturized hardware for point-of-care applications, and real-time clinical translation. Collectively, this review aims to provide researchers, clinicians, and engineers with both fundamental knowledge and forward-looking perspectives to further unlock the potential of FLIM in advancing biomedical science.
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