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双光子成像技术在非侵入性角膜检查中的应用。

Two-Photon Imaging for Non-Invasive Corneal Examination.

机构信息

Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, 3000-548 Coimbra, Portugal.

Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal.

出版信息

Sensors (Basel). 2022 Dec 11;22(24):9699. doi: 10.3390/s22249699.

DOI:10.3390/s22249699
PMID:36560071
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9783858/
Abstract

Two-photon imaging (TPI) microscopy, namely, two-photon excited fluorescence (TPEF), fluorescence lifetime imaging (FLIM), and second-harmonic generation (SHG) modalities, has emerged in the past years as a powerful tool for the examination of biological tissues. These modalities rely on different contrast mechanisms and are often used simultaneously to provide complementary information on morphology, metabolism, and structural properties of the imaged tissue. The cornea, being a transparent tissue, rich in collagen and with several cellular layers, is well-suited to be imaged by TPI microscopy. In this review, we discuss the physical principles behind TPI as well as its instrumentation. We also provide an overview of the current advances in TPI instrumentation and image analysis. We describe how TPI can be leveraged to retrieve unique information on the cornea and to complement the information provided by current clinical devices. The present state of corneal TPI is outlined. Finally, we discuss the obstacles that must be overcome and offer perspectives and outlooks to make clinical TPI of the human cornea a reality.

摘要

双光子成像(TPI)显微镜,即双光子激发荧光(TPEF)、荧光寿命成像(FLIM)和二次谐波产生(SHG)模式,近年来已成为检查生物组织的有力工具。这些模式依赖于不同的对比机制,通常同时使用,以提供关于被成像组织的形态、代谢和结构特性的互补信息。角膜是一种透明组织,富含胶原蛋白,有几个细胞层,非常适合 TPI 显微镜成像。在这篇综述中,我们讨论了 TPI 的物理原理及其仪器。我们还概述了 TPI 仪器和图像分析的最新进展。我们描述了如何利用 TPI 来获取关于角膜的独特信息,并补充当前临床设备提供的信息。概述了角膜 TPI 的现状。最后,我们讨论了必须克服的障碍,并提供了观点和展望,以使人类角膜的临床 TPI 成为现实。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/4a4dc296e4f5/sensors-22-09699-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/fe6a915ea877/sensors-22-09699-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/6fe90749429d/sensors-22-09699-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/65c95160a2fc/sensors-22-09699-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/411d5665d833/sensors-22-09699-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/0c66e51cbc9a/sensors-22-09699-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/4684b5141e1d/sensors-22-09699-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/4a4dc296e4f5/sensors-22-09699-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/fe6a915ea877/sensors-22-09699-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/6fe90749429d/sensors-22-09699-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/65c95160a2fc/sensors-22-09699-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/411d5665d833/sensors-22-09699-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/0c66e51cbc9a/sensors-22-09699-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/4684b5141e1d/sensors-22-09699-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7805/9783858/4a4dc296e4f5/sensors-22-09699-g007.jpg

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本文引用的文献

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BME Front. 2021 Jan 25;2021:3973857. doi: 10.34133/2021/3973857. eCollection 2021.
2
Effectiveness of collagen cross-linking induced by two-photon absorption properties of a femtosecond laser in human corneal stroma.飞秒激光双光子吸收特性诱导人角膜基质胶原交联的有效性。
Biomed Opt Express. 2022 Sep 1;13(9):5067-5081. doi: 10.1364/BOE.468593.
3
Two-photon collagen crosslinking in ex vivo human corneal lenticules induced by near-infrared femtosecond laser.
眼科中的双光子激发荧光:功能诊断的安全性与改进成像
Front Med (Lausanne). 2024 Jan 3;10:1293640. doi: 10.3389/fmed.2023.1293640. eCollection 2023.
近红外飞秒激光诱导离体人角膜透镜中的双光子胶原交联
J Biophotonics. 2023 Feb;16(2):e202200160. doi: 10.1002/jbio.202200160. Epub 2022 Oct 4.
4
Improved segmentation of collagen second harmonic generation images with a deep learning convolutional neural network.深度学习卷积神经网络提高胶原二次谐波图像分割效果。
J Biophotonics. 2022 Dec;15(12):e202200191. doi: 10.1002/jbio.202200191. Epub 2022 Sep 25.
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