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单光子峰事件检测 (SPEED):一种用于荧光寿命成像显微镜中快速光子计数的计算方法。

Single-photon peak event detection (SPEED): a computational method for fast photon counting in fluorescence lifetime imaging microscopy.

出版信息

Opt Express. 2021 Nov 8;29(23):37759-37775. doi: 10.1364/OE.439675.

Abstract

Fluorescence lifetime imaging microscopy (FLIM) characterizes samples by examining the temporal properties of fluorescence emission, providing useful contrast within samples based on the local physical and biochemical environment of fluorophores. Despite this, FLIM applications have been limited in scope by either poor accuracy or long acquisition times. Here, we present a method for computational single-photon counting of directly sampled time-domain FLIM data that is capable of accurate fluorescence lifetime and intensity measurements while acquiring over 160 Mega-counts-per-second with sub-nanosecond time resolution between consecutive photon counts. We demonstrate that our novel method of Single-photon PEak Event Detection (SPEED) is more accurate than direct pulse sampling and faster than established photon counting FLIM methods. We further show that SPEED can be implemented for imaging and quantifying samples that benefit from higher -throughput and -dynamic range imaging with real-time GPU-accelerated processing and use this capability to examine the NAD(P)H-related metabolic dynamics of apoptosis in human breast cancer cells. Computational methods for photon counting such as SPEED open up more opportunities for fast and accurate FLIM imaging and additionally provide a basis for future innovation into alternative FLIM techniques.

摘要

荧光寿命成像显微镜(FLIM)通过检查荧光发射的时间特性来对样品进行特征化描述,基于荧光团的局部物理和生化环境,为样品提供有用的对比度。尽管如此,FLIM 的应用范围受到准确性差或采集时间长的限制。在这里,我们提出了一种用于直接采样时域 FLIM 数据的计算单光子计数方法,该方法能够在亚纳秒时间分辨率下进行超过 160 Mega 计数/秒的高速采集,同时实现荧光寿命和强度的精确测量。我们证明了我们的单光子峰值事件检测(SPEED)新方法比直接脉冲采样更准确,比现有的光子计数 FLIM 方法更快。我们进一步表明,SPEED 可以用于成像和定量分析受益于更高吞吐量和动态范围成像的样品,具有实时 GPU 加速处理能力,并利用这一能力来检测人乳腺癌细胞中与 NAD(P)H 相关的代谢动力学的细胞凋亡。像 SPEED 这样的光子计数计算方法为快速准确的 FLIM 成像开辟了更多机会,并为替代 FLIM 技术的未来创新提供了基础。

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