Volume 51 Issue 11
Nov.  2022
Turn off MathJax
Article Contents

Yao Jing, Yu Zhipeng, Gao Yufeng, Ye Shiwei, Zheng Wei, Lai Puxiang. Advances of large field-of-view two-photon microscopy system (invited)[J]. Infrared and Laser Engineering, 2022, 51(11): 20220550. doi: 10.3788/IRLA20220550
Citation: Yao Jing, Yu Zhipeng, Gao Yufeng, Ye Shiwei, Zheng Wei, Lai Puxiang. Advances of large field-of-view two-photon microscopy system (invited)[J]. Infrared and Laser Engineering, 2022, 51(11): 20220550. doi: 10.3788/IRLA20220550

Advances of large field-of-view two-photon microscopy system (invited)

doi: 10.3788/IRLA20220550
  • Received Date: 2022-04-05
  • Rev Recd Date: 2022-05-25
  • Publish Date: 2022-11-30
  • Two-photon microscopy (TPM) imaging has the characteristics of high resolution, natural chromatography capability and large penetration depth, and plays an important role in the imaging of living animals. How to enlarge the field-of-view (FOV) of TPM while maintaining the high resolution to monitor large-scale dynamic responses in biomedical applications especially brain science, however, remains challenging. In this paper, the recent progress of large-FOV two-photon imaging technology is reviewed. The theoretical basis of achieving large-FOV TPM is elaborated from the perspective of optical invariant. Large- FOV TPM methods can be divided into three categories: FOV-edge aberration calibration with scanning relay engines, the design and manufacture of high-throughput objectives and correcting aberrations with adaptive optics. These methods have highly strengthened the capability of TPM used in large scale biomedical imaging. If further improved especially the imaging speed, large-FOV TPM will have great potential to contribute the development of life science and broaden the cognitive of large-scale biological activities. Large-FOV TPM, based on its outstanding spatial and temporal resolution, will become a powerful tool for dynamic monitoring across large-area in some applications that requires high resolution and mesoscale imaging simultaneously.
  • [1] Lai P, Nie L, Wang L. Special issue “Photoacoustic imaging: microscopy, tomography, and their recent applications in biomedicine” in visual computation for industry, biomedicine, and art [J]. Visual Computing for Industry, Biomedicine, and Art, 2021, 4(1): 16. doi:  https://doi.org/10.1186/s42492-021-00082-0
    [2] Konig K. Multiphoton microscopy in life sciences [J]. J Microsc, 2000, 200(2): 83-104.
    [3] Tehrani K F, Latchoumane C V, Southern W M, et al. Five-dimensional two-photon volumetric microscopy of in-vivo dynamic activities using liquid lens remote focusing [J]. Biomed Opt Express, 2019, 10(7): 3591-3604. doi:  10.1364/BOE.10.003591
    [4] Helmchen F, Denk W. Deep tissue two-photon microscopy [J]. Nat Methods, 2005, 2(12): 932-940. doi:  10.1038/nmeth818
    [5] Prevedel R, Verhoef A J, Pernia-Andrade A J, et al. Fast volumetric calcium imaging across multiple cortical layers using sculpted light [J]. Nat Methods, 2016, 13(12): 1021-1028. doi:  10.1038/nmeth.4040
    [6] Chamberland S, Yang H H, Pan M M, et al. Fast two-photon imaging of subcellular voltage dynamics in neuronal tissue with genetically encoded indicators [J]. eLife, 2017, 6: e25690. doi:  10.7554/eLife.25690
    [7] Wang Xiao, Tu Shijie, Liu Xin, et al. Advance and prospect for three-dimensional super-resolution microscopy [J]. Laser & Optoelectronics Progress, 2021, 58(22): 2200001. (in Chinese)
    [8] Hu Chunguang, Zha Ridong, Ling Qiuyu, et al. Super-resolution microscopy applications and development in living cell [J]. Infrared and Laser Engineering, 2017, 46(11): 1103002. (in Chinese) doi:  10.3788/IRLA201746.1103002
    [9] Chen Danni, Li Yahui, Liu Wei, et al. Super-resolution infrared microscopy based on VSFG and donut-beam illumination [J]. Infrared and Laser Engineering, 2018, 47(8): 0804003. (in Chinese) doi:  10.3788/IRLA201847.0804003
    [10] Betzig E, Patterson G H, Sougrat R, et al. Imaging intracellular fluorescent proteins at nanometer resolution [J]. Science, 2006, 313(5793): 1642-1645. doi:  10.1126/science.1127344
    [11] Deschout H, Lukes T, Sharipov A, et al. Complementarity of PALM and SOFI for super-resolution live-cell imaging of focal adhesions [J]. Nature Communications, 2016, 7(1): 13693. doi:  10.1038/ncomms13693
    [12] Vaziri A, Tang J, Shroff H, et al. Multilayer three-dimensional super resolution imaging of thick biological samples [J]. Proceedings of the National Academy of Sciences, 2008, 105(51): 20221-20226. doi:  10.1073/pnas.0810636105
    [13] Rust M J, Bates M, Zhuang X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM) [J]. Nature Methods, 2006, 3(10): 793-796. doi:  10.1038/nmeth929
    [14] Nehme E, Weiss L E, Michaeli T, et al. Deep-STORM: super-resolution single-molecule microscopy by deep learning [J]. Optica, 2018, 5(4): 458-464. doi:  10.1364/OPTICA.5.000458
    [15] Hell S W, Wichmann J. Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy [J]. Optics Letters, 1994, 19(11): 780-782. doi:  10.1364/OL.19.000780
    [16] Yu W, Ji Z, Dong D, et al. Super-resolution deep imaging with hollow Bessel beam STED microscopy [J]. Laser & Photonics Reviews, 2016, 10(1): 147-152.
    [17] Gustafsson M G L. Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy [J]. Journal of Microscopy, 2000, 198(2): 82-87. doi:  10.1046/j.1365-2818.2000.00710.x
    [18] Rowlett Veronica W, Margolin W. 3D-SIM super-resolution of FtsZ and its membrane tethers in escherichia coli cells [J]. Biophysical Journal, 2014, 107(8): L17-L20. doi:  10.1016/j.bpj.2014.08.024
    [19] Neil M A, Juškaitis R, Booth M J, et al. Adaptive aberration correction in a two‐photon microscope [J]. Journal of microscopy, 2000, 200(2): 105-108. doi:  10.1046/j.1365-2818.2000.00770.x
    [20] Park J H, Kong L, Zhou Y, et al. Large-field-of-view imaging by multi-pupil adaptive optics [J]. Nat Methods, 2017, 14(6): 581-583. doi:  10.1038/nmeth.4290
    [21] Yu T, Qi Y, Gong H, et al. Optical clearing for multiscale biological tissues [J]. J Biophotonics, 2018, 11(2): e201700187.
    [22] Zheng Y, Chen J, Shi X, et al. Two-photon focal modulation microscopy for high-resolution imaging in deep tissue [J]. J Biophotonics, 2019, 12(1): e201800247. doi:  10.1002/jbio.201800247
    [23] Si K, Gong W, Chen N, et al. Two-photon focal modulation microscopy in turbid media [J]. Applied Physics Letters, 2011, 99(23): 233702.
    [24] Kobat D, Horton N, Xu C. In vivo two-photon microscopy to 1.6-mm depth in mouse cortex [J]. Journal of Biomedical Optics, 2011, 16(10): 106014. doi:  10.1117/1.3646209
    [25] Wang Shaowei, Lei Ming. Near infrared-Ⅱ excited multiphoton fluorescence imaging [J]. Laser & Optoelectronics Progress, 2022, 59(6): 0617002. (in Chinese)
    [26] Nguyen Q T, Callamaras N, Hsieh C, et al. Construction of a two-photon microscope for video-rate Ca2+ imaging [J]. Cell Calcium, 2001, 30(6): 383-393. doi:  10.1054/ceca.2001.0246
    [27] Theriault G, De Koninck Y, McCarthy N. Extended depth of field microscopy for rapid volumetric two-photon imaging [J]. Opt Express, 2013, 21(8): 10095-10104. doi:  10.1364/OE.21.010095
    [28] Lu R, Sun W, Liang Y, et al. Video-rate volumetric functional imaging of the brain at synaptic resolution [J]. Nat Neurosci, 2017, 20(4): 620-628. doi:  10.1038/nn.4516
    [29] van den Broek B, Ashcroft B, Oosterkamp T H, et al. Parallel nanometric 3D tracking of intracellular gold nanorods using multifocal two-photon microscopy [J]. Nano Letters, 2013, 13(3): 980-986. doi:  10.1021/nl3040509
    [30] Bumstead J R, Park J J, Rosen I A, et al. Designing a large field-of-view two-photon microscope using optical invariant analysis [J]. Neurophotonics, 2018, 5(2): 025001.
    [31] Yao J, Gao Y, Yin Y, et al. Exploiting the potential of commercial objectives to extend the field of view of two-photon microscopy by adaptive optics [J]. Opt Lett, 2022, 47(4): 989-992. doi:  10.1364/OL.450973
    [32] Ji N, Freeman J, Smith S L. Technologies for imaging neural activity in large volumes [J]. Nature Neuroscience, 2016, 19(9): 1154-1164. doi:  10.1038/nn.4358
    [33] Tsai P S, Mateo C, Field J J, et al. Ultra-large field-of-view two-photon microscopy [J]. Opt Express, 2015, 23(11): 13833-13847. doi:  10.1364/OE.23.013833
    [34] Rumyantsev O I, Lecoq J A, Hernandez O, et al. Fundamental bounds on the fidelity of sensory cortical coding [J]. Nature, 2020, 580(7801): 100-105. doi:  10.1038/s41586-020-2130-2
    [35] Negrean A, Mansvelder H D. Optimal lens design and use in laser-scanning microscopy [J]. Biomed Opt Express, 2014, 5(5): 1588-1609. doi:  10.1364/BOE.5.001588
    [36] Yu C-H, Stirman J N, Yu Y, et al. Diesel2 p mesoscope with dual independent scan engines for flexible capture of dynamics in distributed neural circuitry [J]. Nature Communications, 2021, 12(1): 6639. doi:  10.1038/s41467-021-26736-4
    [37] Clough M, Chen I A, Park S W, et al. Flexible simultaneous mesoscale two-photon imaging of neural activity at high speeds [J]. Nature Communications, 2021, 12(1): 6638. doi:  10.1038/s41467-021-26737-3
    [38] Fan J, Suo J, Wu J, et al. Video-rate imaging of biological dynamics at centimetre scale and micrometre resolution [J]. Nature Photonics, 2019, 13(11): 809-816. doi:  10.1038/s41566-019-0474-7
    [39] Demas J, Manley J, Tejera F, et al. High-speed, cortex-wide volumetric recording of neuroactivity at cellular resolution using light beads microscopy [J]. Nature Methods, 2021, 18(9): 1103-1111. doi:  10.1038/s41592-021-01239-8
    [40] Sofroniew N J, Flickinger D, King J, et al. A large field of view two-photon mesoscope with subcellular resolution for in vivo imaging [J]. Elife, 2016, 5: e14472.
    [41] Stirman J N, Smith I T, Kudenov M W, et al. Wide field-of-view, multi-region, two-photon imaging of neuronal activity in the mammalian brain [J]. Nat Biotechnol, 2016, 34(8): 857-862. doi:  10.1038/nbt.3594
    [42] Yang M, Zhou Z, Zhang J, et al. MATRIEX imaging: multiarea two-photon real-time in vivo explorer [J]. Light: Science & Applications, 2019, 8(1): 109.
    [43] Lecoq J, Savall J, Vučinić D, et al. Visualizing mammalian brain area interactions by dual-axis two-photon calcium imaging [J]. Nature Neuroscience, 2014, 17(12): 1825-1829. doi:  10.1038/nn.3867
    [44] Yao Jing, Wu Ting, Ye Shiwei, et al. Off-axis parabolic mirror afocal scanning system extends the imaging area of two-photon microscopy [J]. Acta Laser Biology Sinica, 2020, 29(3): 217-224. (in Chinese) doi:  10.3969/j.issn.1007-7146.2020.03.004
    [45] 陈帅, 任林, 周镇乔, 等. 在体跨尺度双光子显微成像技术[J]. 中国光学 (中英文), 2022, 15: 1-16.

    Chen Shuai, Ren Lin, et al. In-vivo across-scales two-photon microscopy[J]. Chinese Optics. doi:  10.37188/CO.2022-0086
    [46] Gao Y, Liu L, Yin Y, et al. Adaptive optics via pupil ring segmentation improves spherical aberration correction for two-photon imaging of optically cleared tissues [J]. Optics Express, 2020, 28(23): 34935-34947. doi:  10.1364/OE.408621
    [47] Zhao Y, Yu T, Zhang C, et al. Skull optical clearing window for in vivo imaging of the mouse cortex at synaptic resolution [J]. Light: Science & Applications, 2018, 7(2): 17153.
    [48] Cheng S, Li H, Luo Y, et al. Artificial intelligence-assisted light control and computational imaging through scattering media [J]. Journal of Innovative Optical Health Sciences, 2019, 12(4): 1930006. doi:  10.1142/S1793545819300064
    [49] Li H, Woo C M, Zhong T, et al. Adaptive optical focusing through perturbed scattering media with a dynamic mutation algorithm [J]. Photonics Research, 2021, 9(2): 202-212. doi:  10.1364/PRJ.412884
    [50] Woo C M, Zhao Q, Zhong T, et al. Optimal efficiency of focusing diffused light through scattering media with iterative wavefront shaping [J]. APL Photonics, 2022, 7(4): 046109. doi:  10.1063/5.0085943
    [51] Yu Z, Li H, Zhong T, et al. Wavefront shaping: A versatile tool to conquer multiple scattering in multidisciplinary fields [J]. The Innovation, 2022, 3(5): 100292.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(6)

Article Metrics

Article views(340) PDF downloads(93) Cited by()

Related
Proportional views

Advances of large field-of-view two-photon microscopy system (invited)

doi: 10.3788/IRLA20220550
  • 1. Department of Biomedical Engineering, the Hong Kong Polytechnic University, Hong Kong SAR, China
  • 2. The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen 518055, China
  • 3. Research Center for Biomedical Optics and Molecular Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
  • 4. Photonics Research Institute, the Hong Kong Polytechnic University, Hong Kong SAR, China

Abstract: Two-photon microscopy (TPM) imaging has the characteristics of high resolution, natural chromatography capability and large penetration depth, and plays an important role in the imaging of living animals. How to enlarge the field-of-view (FOV) of TPM while maintaining the high resolution to monitor large-scale dynamic responses in biomedical applications especially brain science, however, remains challenging. In this paper, the recent progress of large-FOV two-photon imaging technology is reviewed. The theoretical basis of achieving large-FOV TPM is elaborated from the perspective of optical invariant. Large- FOV TPM methods can be divided into three categories: FOV-edge aberration calibration with scanning relay engines, the design and manufacture of high-throughput objectives and correcting aberrations with adaptive optics. These methods have highly strengthened the capability of TPM used in large scale biomedical imaging. If further improved especially the imaging speed, large-FOV TPM will have great potential to contribute the development of life science and broaden the cognitive of large-scale biological activities. Large-FOV TPM, based on its outstanding spatial and temporal resolution, will become a powerful tool for dynamic monitoring across large-area in some applications that requires high resolution and mesoscale imaging simultaneously.

    • 双光子显微镜是一种基于非线性双光子激发效应构建的三维扫描显微镜 [1-3]。当一个基态荧光分子同时吸收两个光子后跃迁到激发态,再次回到基态的时会释放出双光子荧光光子。这种非线性的双光子激发特性使双光子显微镜相比于传统共聚焦显微镜具有它得天独厚的优势:由于荧光信号仅在焦点处被激发,所以双光子显微镜具有更高的信噪比和天然的三维层析能力 [4]。因此自面世以来,双光子显微镜由于其优异的三维成像特性被广泛用于生物细胞与组织成像 [1,5-6]

      近年来,双光子成像技术的发展方向主要聚焦于提高成像分辨率、增加成像深度和提高成像速度等方面。首先,结合各类超分辨显微技术 [7-9]如PALM (Photoactivated Localization Microscopy) [10-12]、STORM (Stochastic Optical Reconstruction Microscopy) [13-14]、STED (Stimulated Emission Depletion) [15-16]和SIM (Structure Illumination Microscopy) [17-18]等,可以将双光子成像的分辨率从几百纳米提高到几十纳米量级,使其可以分辨更精细的生物细胞组织与结构;其次结合自适应光学技术 [19-20]、光透明技术 [21]和焦点调制技术 [22-23]以及近红外二区激光的使用 [24-25],双光子显微镜的成像深度可大大增加;最后利用共振扫描振镜 [26]、电调焦透镜 [3,27]、贝塞尔光束扫描 [28]和多焦点扫描 [29]等技术,可极大地提高双光子成像的成像速度。

      然而,传统双光子显微镜的成像视场一般在1 mm2 以内 [1,2,4],较小的成像视场限制了其在生物医学成像中的作用。例如,在跨多脑区动态监测神经活动或血管中的脱氧血红蛋白浓度时,需要在保证微米级别分辨率的前提下进行全脑大视场或多脑区的实时双光子成像。为解决这一问题,双光子成像领域的研究者们开始将视线移至如何扩大双光子显微镜的成像视场,并开始致力于对双光子显微成像系统进行特殊设计,和通过与其他技术相结合来提高双光子成像显微镜的成像视场。

      文中将从双光子显微成像系统的原理出发,从光学不变量角度讲述大视场双光子成像系统的设计方法。紧接着将综述近年来大视场双光子成像领域的主要进展,主要从三个方向展开综述:(1) 通过透镜组补偿大视场成像过程中大扫描角度产生的离轴像差来提高大视场成像分辨率;(2) 使用自制高通量的物镜来实现更大视场;(3) 使用自适应光学技术增加成像物镜的可用视场。

    • 大视场双光子显微成像系统的设计需要在光学分辨率和成像视场之间进行权衡,最终以具体成像需求为判断依据取得两者间的平衡。实现大视场、高分辨的双光子成像的最大难度便在于如何在保证分辨率的情况下增加成像视场。

      对于双光子成像系统,成像物镜的数值孔径(Numerical Aperture, NA)决定了该系统成像的衍射极限分辨率 [1],即

      式中:ωxyωz分别为横向和轴向的分辨率;λ为入射光波长;NA为数值孔径;n为物镜下介质折射率。要实现近衍射极限分辨率的大视场成像,首先需要大孔径入射光束使有效NA达到物镜标定NA,获得衍射极限分辨率。物镜有效数值孔径可表示为 [30]

      式中:NAeff为有效数值孔径;deff 为实际后背孔径出入射光斑直径;dpupil为物镜后背孔径处入瞳直径;NA为物镜标准数值孔径大小。只有当NAeff = NA,即deff = dpupil时,在不考虑像差等影响的理想情况下,物镜才能实现近衍射极限的高分辨成像。

      物镜放大倍数和视场数将决定成像系统的最大成像视场(Field-of-view, FOV),其视场直径为 [30-32]

      式中:FN为物镜的视场数;M为物镜的放大倍数;FL为物镜的前焦距;θ为光束进入物镜后背孔径的角度。该公式前部分$ {FOV}=\dfrac{FN}{M} $说明,物镜的成像视场由FN视场数和M放大倍数决定,即物镜的场数FN越大,放大倍数越小,其支持的最大成像视场越大。该公式后部分$ F O V=2 \times F L \times \tan \theta$说明,当物镜的焦距越长,后备孔径处入射光束角度越大,其支持的成像视场越大。

      在双光子系统中,可用一个光学量来同时衡量各光学元件(系统)的衍射极限分辨率和视场大小,人们称之为光学不变量I [30],其表达式为:

      式中:数值孔径NA决定了该光学元件(系统)的衍射极限分辨率;视场数FN和放大倍数M决定了该光学元件(系统)的成像视场。对于传统的双光子成像显微镜,一般都是在牺牲成像视场的情况下增大数值孔径NA,即在直径为500 µm左右的视场内保证几百纳米的高分辨成像。而对于大视场双光子成像系统,不仅要保证数值孔径NA接近传统双光子成像系统,而且需要保证成像视场相对提升数倍。所以大视场高分辨的双光子成像需要对成像系统中各元件进行大光学不变量的挑选或特殊设计。

      2018年,Jonathan R. Bumstead等提出了利用光学不变量的原理来设计大视场双光子成像系统 [30]

      在理想双光子成像系统中,可分别计算出系统中各光学元件的光学不变量。对各光学元件的光学不变量的大小对比后,选择该光学成像系统中光学不变量最小的一个或几个光学元件进行替换升级。一般来说,由于成像物镜的设计难度和设计成本较高,所以双光子成像系统中的最大光学不变量是由商业可选的高性能大视场成像物镜决定。在选定物镜的情况下,通过替换或设计其他各光学元件以充分利用物镜的成像性能,从而实现更大视场的高分辨率双光子成像。

      具体来说,在设计大视场双光子成像系统时,可将其大致分为三部分进行分块设计优化,分别为成像物镜、扫描中继系统与荧光收集系统。

      大视场成像物镜一般选择10、4倍等放大倍数较小的型号。选定几款低放大倍数的双光子成像物镜,对比这些物镜的光学不变量之后选择最大光学不变量的一款,以保证在增大视场的情况下尽可能提高最终成像分辨率。如图1(a)所示,物镜入射光学不变量为入射光束半径和入射角度正弦值之积r0sinθ0,出射光学不变量为聚焦半光锥角的正弦值和成像视场半径的乘积F0sinα0。该文认为对于整个成像系统,其光学不变量最大的限制来自于物镜,物镜限制了除物镜外双光子成像系统所能达到的最大光学不变量,而物镜的出射光学不变量决定了最后整个成像系统能达到的最大成像视场。

      Figure 1.  Definition of optical invariants. (a) Optical invariants of the imaging objectives; (b) Optical invariants of the scanning relay; (c) Optical invariants of the fluorescence collection system

      设计扫描中继时,他们对现有的光学透镜进行光学不变量计算后,在不影响系统结构的情况下选择了光学不变量等于或超过物镜的透镜元件。扫描中继可视作一个整体进行光学不变量分析,如图1(b)所示,其入射光学不变量等于出射光学不变量,即:

      式中:rr'分别为入射光束和出射光束的半径;θθ'分别为入射光束和出射光束的最大扫描角度。通常双光子系统中含两个扫描中继,从X扫描振镜共轭到Y扫描振镜的第一个扫描中继,以及Y振镜共轭到物镜后背孔径处的由扫描镜和与物镜配套的管镜组成的第二个扫描中继。

      荧光收集系统的光学不变量同样应等于或大于选定物镜的光学不变量。荧光收集系统中光学元件包括二向色镜(Dichroic mirror, DM)、收集透镜(系统)(Collective lens, CL),荧光收集系统的光学不变量主要由收集透镜(系统)决定,因此可视为单透镜分析。如图1(c)所示,入射光学不变量r’sinθ’等于出射光学不变量FFluosinαFluor’θFFluoαFluo分别为入射光束半径、入射角、荧光收集设备靶面半径和出射半光锥角。

      Bumstead等最终实现视场直径为7 mm,横向分辨率<1.7 μm,轴向分辨率<28 μm的高分辨大视场双光子成像。其成像系统和血管成像结果如图2所示。

      Figure 2.  Design of a large-FOV two-photon microscope system using optical invariant analysis. (a) Optical layout; (b) Cerebral vasculature imaged over the mouse cortex with the large-FOV two-photon microscopy

    • 双光子成像系统属于激光点扫描式显微镜的一种,要实现大视场双光子成像,必须进行大角度扫描以增加实际光学不变量。而大角度扫描过程中由扫描系统引起的像差会对整个系统的成像性能造成较大影响。上文中提及到,扫描中继主要包括两部分:振镜间的中继以及振镜到达物镜后背孔径处的中继。传统振镜间的扫描中继是由两个双胶合消色差透镜构成。然而,要实现较大的成像视场,即以较大的角度扫描时,激光通过该类扫描中继透镜边缘位置时会产生较大的离轴像差。对于双光子成像系统中另一组由扫描透镜和管镜组成的扫描中继,传统扫描透镜为f-θ平场扫描镜,传统管镜应同物镜相配套。因为传统管镜无法支持较大的扫描角度,所以大视场成像中使用自制或双胶合透镜组成的管镜。而使用f-θ平场扫描镜与自制大视场管镜相搭配时,该组扫描中继也将产生较大的由大扫描角度引起的离轴像差。扫描系统引起的离轴像差最终会导致大视场成像时视场边缘位置信号弱,信号质量差。

      2015年,Philbert S. Tsai等提出了一种使用大孔径的多透镜组合的方法 [33],减小了扫描系统引起的像差实现接近于衍射极限的高分辨率(中心横向:1.2 μm;轴向:16 μm)大视场(8 mm × 10 mm)双光子成像。该显微成像系统的光路设计如图3(a)所示,准直后的激光经过正负透镜像差矫正后打至X扫描振镜。XY振镜间由两个远心f-θ镜实现共轭中继,并在该扫描中继之间加入正负透镜组来补偿X方向扫描像差。激光被Y振镜反射之后分别经过两组双胶合透镜构成的扫描透镜和管透镜共轭中继到物镜后背孔径处,并在管镜之后加入正负透镜组补偿Y方向扫描像差。最终激光经物镜聚焦后在样品面激发荧光信号,实现大视场近衍射极限高分辨成像。该方法主要是从传统光学设计角度以及光学像差的光学补偿角度优化大视场成像系统,通过补偿大视场扫描引起的大离轴像差,最终在近衍射极限的分辨率下监测到了不同脑区的血管以及神经活动(见图3(c),分辨率结果见图3(b))。

      Figure 3.  Large field-of-view two-photon microscopy by optimizing the off-axis aberrations using lens series. (a) Optical layout; (b) Experimental measurements of the PSF (point-spread-function) as a function of FOV, measured by 0.5 µm fluorescence beads; (c) Large-FOV two-photon image (λ= 800 nm, max intensity project) of vasomotion in cortical arterioles across both hemispheres of an awake, head-fixed mouse through dual transcranial windows

    • 上文提到成像物镜的光学不变量限制了整个双光子成像系统的光学不变量,也限制了最终的成像视场与分辨率。所以无论对物镜前的光路进行多复杂的特殊设计,最终影响整个大视场双光子系统的关键元件仍然是物镜。目前市面上支持大光学不变量的商业物镜有限,同时这些商业物镜支持的最大视场也有限 [34-35]。所以,要实现更大视场的高分辨双光子成像,使用高通量的自制成像物镜是将成像视场进一步拓展的关键 [36-39]

      2016,Nicholas James Sofroniew等设计的用于大视场成像的双光子随机扫描显微镜 [40](Two-photon random access mesoscope, 2-p RAM),其最大可实现成像视场为5 mm × 5 mm,并具有亚细胞级别的近衍射极限的分辨率(横向:0.66 μm;轴向:4.09 μm)。如图4(b)所示,视场中心位置横向分辨率为0.66 μm, 轴向分辨率为4.09 μm,视场边缘近似相等。该系统使用自主设计的高性能、大光学不变量成像物镜实现大视场高分辨双光子成像。

      Figure 4.  Large-FOV two-photon random access microscopy. (a) Optical layout; (b) PSF at middle position and edge position of the FOV, measured by 0.5 µm microbeads; (c) Large-FOV two-photon image of fluorescent proteins in anesthetized thy-1 mice (max intensity project) and higher magnification image (dashed box in the large-FOV image)

      该系统光路图如图4(a)所示。相比于传统的双光子显微成像系统,除实现了更大视场的双光子成像外,该系统的主要亮点为快速的三维扫描成像。在大视场双光子成像过程中,若需接近系统衍射极限的分辨率,必须要提高像素的采样数,而这会严重降低成像速度。另一方面,在脑科学成像中,需要以极快的速度观察钙离子信号的动态变化。所以在快速观察大视场内神经活动的等应用中,系统必须同时具有快速扫描的功能。该文设计的2-p RAM,在横向使用特殊设计的扫描单元快速扫描视场的任意区域,在轴向使用远心聚焦单元快速扫描不同成像深度。具体来讲,横向特殊设计的扫描单元由一个快速共振振镜和三个检流计振镜组成。使用这种复杂扫描设计的原因主要是用于快速扫描的共振振镜无法满足大视场成像的扫描。尽管共振扫描振镜的扫描速度非常快,但是其扫描角度却非常有限(10°,光学角度,峰-峰值)。换言之,这种小扫描角度对应物镜下的视场区域也将非常小,小于等于0.6 mm。这种特殊设计的横向扫描单元的优势是可以通过单个振镜的更小扫描角度实现更快的横向扫描。在轴向方向他们使用远心聚焦单元进行快速扫描。相比于传统的使用步进电机移动物镜或样品实现Z轴向扫描,使用远心聚焦单元能实现更快速变焦。在大视场全脑或多脑区神经成像的应用中,也需要同时观察不同深度大脑皮层的活动,快速的轴向位置切换将会有效的提高神经活动的监测效率。最终他们通过该系统对麻醉的转基因小鼠实现了大视场的神经活动分析,其大视场成像结果如图4(c)所示。

      同年,Jeffrey N Stirman等设计了一款超大视场(>9.5 mm)的双光子显微镜 [41],用于快速的同时扫描多区域分散的神经细胞元群体。该大视场双光子系统同样基于自制大通量成像物镜进行设计。该成像物镜具有超大的光学不变量,即具有较低放大倍数的同时具有较高的数值孔径,从而可以实现大视场成像的高分辨成像。

      该大视场成像系统的主要亮点在于同时的跨多区域成像。成像光路见图5(a),激光经扩束后被偏振分束器(Polarization beam splitter, PBS)分为两束偏振方向不同的光,一路为正常光路,另一路中加入光学时延。这两路光分别通过部分相同的扫描中继到达物镜后背孔径处被物镜聚焦,并在不同的视场位置激发处荧光信号。荧光信号被二向色镜DM反射后再由收集透镜聚焦,最终被光电倍增管(Photomultiplier, PMT)收集成像。除物镜通过特殊设计之外,该系统中的多个扫描中继系统,均通过光学设计的方法进行像差与成像性能优化。

      Figure 5.  Large field-of-view and multi-region two-photon microscopy. (a) Optical layout; (b) PSF at middle position and edge position of the FOV, measured by 0.2 µm microbeads; (c) Large-FOV imaging was used to examine neuronal activity of a transgenic mouse expressing the genetically encoded fluorescent calcium indicator GCaMP6 s; (d) Segmenting the image sequence can yield 5,361 active neurons; (e) Simultaneous two region imaging to monitor neuronal activity between two cortical visual areas

      该大视场成像系统的分辨率结果如图5(b)所示,结果显示其视场边缘区域分辨率相比于中心区域分辨率(中心横向:1.2 μm;轴向:11.8 μm)差别不大。最终他们通过该大视场多区域系统测量了小鼠视觉处理过程中两个皮层视觉区域之间的活动相关性,部分结果如图5(c)~(e)所示。

      总的来说,在活体生物成像中,大视场扫描的同时不可避免的会降低成像的速度,这会造成对生物组织的光漂白和光毒性增加,同时也会造成荧光信号的衰减。所以快速大视场扫描 [37]和同时多区域扫描 [36-37,42-43]是两种可将大视场双光子显微镜拓展至生物医学应用领域的有效思路。

    • 上述提到的大视场成像系统均需要复杂的光学元件设计和定制光学组件的组装,而这种复杂性限制了生物学家接受和利用该类大视场双光子成像系统。在不增加系统复杂度和不使用高成本和高设计难度的自制光学元件和成像物镜的前提下,如何增大传统大视场商业物镜的光学不变量实现更大视场双光子成像,是拓展其应用到病理和生物机理分析领域的关键。

      通常情况下,商业成像物镜都会有一个厂商标定的最大成像视场区域。在该区域内,物镜厂商通过光学设计尽可能的对像差进行优化。而超过该标定视场时,像差会急剧的增加。2022年,Yao等提出一种更通用的大视场双光子方法 [31]。该系统最终成像视场直径为3.46 mm,轴向分辨率为0.84 μm,轴向分辨率为5.8 μm。在不改变系统复杂度和无需复杂设计的前提下,该技术通过自适应光学实现了大视场、高分辨和高信噪比的双光子成像。该策略通过自适应光学技术来补偿超过标定视场扫描过程中成像物镜产生的大离轴像差,其原理如图6(a)所示。

      Figure 6.  Extending the field of view of two-photon microscopy using adaptive optics. (a) Schematic diagram; (b) Imaging optical path diagram; (c) Large-FOV two-photon image of the brain slice of thy-1 mice (max intensity project); (d) Comparison before and after adaptive optics correction in the yellow solid area of Fig. (c)

      该大视场双光子成像系统的光路见图6(b)。在光学系统设计方面,该系统首先将XY振镜之间的扫描中继从传统的消色差双胶合透镜替换为离轴抛物面反射镜(Off axis parabolic mirror, OAPM) [44],在支持更大扫描角度的同时减小了扫描引起的离轴像差。该大视场技术的亮点是在不改变系统整体结构的情况下,仅在系统中添加光学像差矫正元件空间光调制器(Spatial light modulator, SLM),利用无波前测量的自适应光学方法矫正了超过标定视场之外的大离轴像差,最后成功增大了成像物镜的可用视场。其大视场成像结果如图6(c)所示,证明其通过自适应光学成功增强了扩展视场的荧光信号强度。该技术具有较好的通用性,一方面该技术不仅适用于普通的大视场双光子成像系统,对于传统的含高倍数物镜的小视场双光子显微镜,也可在光路前加入波前矫正元件来拓展其最大视场。另一方面,可以将该技术拓展到任何激光扫描显微成像领域,通过像差补偿元件的加入成功增加成像系统的可用视场。

    • 通过各类方法提高双光子成像系统的成像视场,能在保证其高分辨率的情况下,增大可探测区域。具体来说,相比于传统的双光子成像,大视场双光子成像系统可将成像视场直径拓展至5~10倍,即在保证亚细胞级别分辨率的情况下将探测区域最大拓展100倍左右。目前,双光子用于小鼠脑成像主要有两个方向:脑内血管成像和脑内神经元或钙离子成像。大视场双光子脑内血管成像结果如图2(b)、图3(c)所示,能够分辨全脑或多脑区小鼠脑内血管状态,为肿瘤分析、缺血或败血模型等病理应用提供一种有效的工具。在小鼠脑内神经元或钙离子成像中,支持感觉编码和运动输出的神经元活动分布在新皮质的多个区域。从图4(c)、图5(c)~(e)和图6(c)所示大视场双光子神经元或钙离子成像结果中可以看出,大视场双光子成像系统可以同时跨多个皮层区域成像,从而获得扩展皮质网络的细胞分辨率视图,这对多皮层协调的神经活动或系统的阐明神经编码的原理至关重要。

    • 文中从大视场双光子成像系统的设计原理出发,从光学不变量的角度阐述了如何实现大视场双光子成像。随后综述了如何使用光学设计补偿大视场扫描像差,从而提高大视场双光子成像的视场边缘分辨率。之后提到了两种使用特殊设计的大光通量物镜实现更大成像视场的系统。在这两篇自制物镜大视场成像系统中,第一篇大视场双光子随机扫描显微系统采用了一种特殊设计的扫描结构提高了三维成像速度,另一篇大视场多区域双光子扫描显微成像系统通过不同时延的双光路实现了双区域的同时扫描成像。最后,我们综述了一种通过自适应光学方法增加物镜光学不变量从而实现更大成像视场。该方法仅需在成像系统中添加自适应光学补偿元件,降低了大视场成像的成本,同时又具有较好的通用性。

      大视场双光子成像是近些年来拓展的双光子成像领域的新方向,尽管已有数篇文献已报道了多种不同的大视场成像技术 [45],但是无论是自制成像物镜或使用自适应光学提高双光子成像系统的视场,将这些方法广泛拓展到具体的实际医学或生物应用中时仍然在设计难度和成本问题上难以妥协。通过自适应光学提高双光子成像系统的视场,尽管相比于自制物镜尽管已经将系统成本降低,但是对于大部分的生物或医学实验室,自适应光学元件的成本仍限制了这种方法的推广。所以在之后的大视场双光子显微成像系统的设计过程中,或许需要一种更通用的方式,通过更具性价比的方式解除成像视场的限制。

      此外,将大视场成像技术与其他领域技术相结合,是大视场双光子成像的另一个发展方向。例如,可以通过大视场成像技术和贝塞尔扫描技术结合来提高成像速度;可将大视场成像技术和光透明 [46-47]、光学波前整形 [48-51]等技术结合来提高成像深度,实现大视场大深度的双光子成像。

Reference (51)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return