Kinghorn Cancer Centre, Garvan Institute of Medical Research, University of New South Wales, Sydney, Australia.
St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, Australia.
Elife. 2018 Jul 9;7:e35800. doi: 10.7554/eLife.35800.
Intravital microscopy can provide unique insights into the function of biological processes in a native context. However, physiological motion caused by peristalsis, respiration and the heartbeat can present a significant challenge, particularly for functional readouts such as fluorescence lifetime imaging (FLIM), which require longer acquisition times to obtain a quantitative readout. Here, we present and benchmark , a versatile multi-platform software tool for image-based correction of sample motion blurring in both time resolved and conventional laser scanning fluorescence microscopy data in two and three dimensions. We show that is able to resolve intravital FLIM-FRET images of intra-abdominal organs in murine models and NADH autofluorescence of human dermal tissue imaging subject to a wide range of physiological motions. Thus, can enable FLIM imaging in situations where a stable imaging platform is not always possible and rescue previously discarded quantitative imaging data.
活体显微镜可以在天然环境中提供对生物过程功能的独特见解。然而，蠕动、呼吸和心跳引起的生理运动，特别是对于荧光寿命成像 (FLIM) 等功能读数，会带来重大挑战，因为这类读数需要更长的采集时间才能获得定量读数。在这里，我们介绍并基准测试了一种通用的多平台软件工具，用于基于图像的校正，以纠正二维和三维时间分辨和传统激光扫描荧光显微镜数据中样本运动模糊。我们表明，该软件可以解决在鼠模型中进行的腹腔内器官的活体 FLIM-FRET 成像以及人类皮肤组织的 NADH 自发荧光成像中的问题，这些问题涉及广泛的生理运动。因此，该软件可以使 FLIM 成像在并非总是能够获得稳定成像平台的情况下成为可能，并恢复以前丢弃的定量成像数据。
