Simultaneous label-free autofluorescence-multiharmonic microscopy driven by femtosecond sources based on self-phase modulation enabled spectral selection

Wang Xiao-Ying; Xing Yu-Ting; Chen Run-Zhi; Jia Xue-Qi; Wu Ji-Hua; Jiang Jin; Li Lian-Yong; Chang Guo-Qing

doi:10.7498/aps.71.20212282

Abstract

Nonlinear optical microscopy technique has unique advantages in tissue imaging, such as enhanced contrast, high resolution, and label-free deep optical sectioning capabilities. Nonlinear optical microscopy also has multiple imaging modalities, corresponding to various components in biological tissues. Unfortunately, its wide applications are hindered due to the lack of broadly tunable femtosecond sources designed for driving multimodalities simultaneously. To solve this challenge, we propose a new wavelength conversion approach—self-phase modulation (SPM) enabled spectral selection, dubbed as SESS. The SESS employs SPM to broaden the input spectrum in a short fiber, and the broadened spectrum features well-isolated spectral lobes. Using the suitable optical filters to select the outermost spectral lobes produces nearly transform-limited femtosecond pulses. In this work, we demonstrate a fiber-optic SESS source for multimodal nonlinear optical microscopy. Based on a 43-MHz Yb-fiber laser, this SESS source can emit 990-nm, 84-fs pulses with >5-nJ energy and ~84-fs pulse duration; it can also produce 1110-nm, 48-fs pulses with 15-nJ energy. The 990-nm pulses are used to drive two-photon excitation fluorescence of many important fluorophores and second-harmonic generation microscopy, which, combined with image splicing technology, enables us to obtain a large field of view image of the gastric tissue. We also employ the 1110-nm pulses to drive simultaneous label-free autofluorescence-multiharmonic microscopy for multimodal imaging of gastric tissue. Two-photon excitation fluorescence, three-photon excitation fluorescence, second-harmonic generation and third-harmonic generation signals of gastric tissue are simultaneously excited efficiently. Such a multimodal nonlinear optical microscopy driven by SESS sources becomes a powerful tool in biomedical imaging.

Keywords:

Authors and contacts

1.
Department of Gastroenterology, Strategic Support Force Medical Center, Beijing 100101, China
2.
Key Laboratory of Optical Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China
3.
Department of Pathology, Strategic Support Force Medical Center, Beijing 100101, China

Corresponding author: Wu Ji-Hua, jh_02821@126.com ; Chang Guo-Qing, guoqing.chang@iphy.ac.cn

Funds: Project supported by the Strategic Support Force Medical Center Clinical Innovation Topics for Medicine and health, China (Grant No. 19ZX40), the National Natural Science Foundation of China (Grant No. 11774234), and the Program of Development of a New Multiphoton Microscope for Large Depth and High Precision Imaging of Three-dimensional Biological Models, China (Grant No. YJKYYQ20190034)

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References

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Cited By

图 1 基于SESS的非线性光学显微镜实验装置. ISO: 隔离器, LD: 二极管泵浦激光源, WDM: 波分复用器, Amp: 光纤放大器, HWP: 半波片, PBS: 偏振分束器, L: 透镜, LPF: 长通滤波器, NLOM: 非线性光学显微镜

Figure 1. Schematic setup of the nonlinear optical microscopy driven by SESS. ISO: isolator, LD: laser diode, WDM: wavelength-division multiplexing, Amp: amplifier, HWP: half-wave plate, PBS: polarization beam splitter, L: lens, LPF: long pass filter, NLOM: nonlinear optical microscopy.

DownLoad: Full-Size Img PowerPoint

图 2 放大脉冲的光谱和自相关轨迹　(a)光谱; (b)自相关轨迹. 红色曲线: 测量得到的自相关轨迹, 黑色曲线: 通过光谱计算得到的变换极限脉冲的自相关轨迹

Figure 2. Spectrum and autocorrelation trace of the amplified pulse: (a) Spectrum; (b) autocorrelation trace. Red curve: measured autocorrelation trace. Black curve: calculated from the transform-limited pulses allowed by the amplified pulse spectrum.

DownLoad: Full-Size Img PowerPoint

图 3 当耦合到光纤里的能量为44 nJ时输出的展宽光谱以及990 nm处滤波得到的脉冲光谱和自相关轨迹　(a)展宽光谱; (b)自相关轨迹. 红色曲线: 测量得到的自相关轨迹, 黑色曲线: 通过光谱计算得到的变换极限脉冲的自相关轨迹. 插图: 990 nm处滤波得到的脉冲光谱

Figure 3. Spectrum broadening with coupled energy of 44 nJ, spectrum and autocorrelation trace of the filtered pulses at 990 nm: (a) Broadened spectrum; (b) autocorrelation trace. Red curve: measured autocorrelation trace. Black curve: calculated from the transform-limited pulses allowed by the spectrum at 990 nm. Inset: filtered spectrum at 990 nm.

DownLoad: Full-Size Img PowerPoint

图 4 当耦合到光纤里的能量为50 nJ时输出的展宽光谱以及1110 nm处滤波得到的脉冲光谱和自相关曲线　(a)展宽光谱; (b)自相关轨迹. 红色曲线: 测量得到的自相关轨迹, 黑色曲线: 通过光谱计算得到的变换极限脉冲的自相关轨迹, 插图: 1110 nm处滤波得到的脉冲光谱

Figure 4. Spectrum broadening with coupled energy of 50 nJ, spectrum and autocorrelation trace of the filtered pulses at 1110 nm: (a) Broadened spectrum; (b) autocorrelation trace. Red curve: measured autocorrelation trace. Black curve: calculated from the transform-limited pulses allowed by the spectrum at 1110 nm. Inset: filtered spectrum at 1110 nm.

DownLoad: Full-Size Img PowerPoint

图 5 离体人体胃组织的2PEF/SHG图像　(a) 2PEF图像; (b) SHG图像; (c) 2PEF和SHG的叠加图像. 白色箭头: 上皮细胞; 黄色箭头: 胶原蛋白. 比例尺: 100 μm

Figure 5. 2PEF/SHG images of ex vivo human gastric tissue: (a) 2PEF image; (b) SHG image; (c) merging of 2PEF and SHG images. White arrow: epithelial cells; yellow arrow: collagen. Scale bar: 100 μm.

DownLoad: Full-Size Img PowerPoint

图 6 离体人体胃组织的2PEF/SHG/3PEF/THG图像　(a) 2PEF图像; (b) SHG图像; (c) 3PEF图像; (d) THG图像; (e) 2PEF/SHG/3PEF/THG的叠加图像. 粉色箭头: 弹力纤维; 黄色箭头: 胶原纤维; 白色箭头: 脂肪细胞. 比例尺: 100 μm.

Figure 6. 2PEF/SHG/3PEF/THG images of ex vivo human gastric tissue: (a) 2PEF image; (b) SHG image; (c) 3PEF image; (d) THG image; (e) merging of 2PEF/SHG/3PEF/THG images. Pink arrow: elastic; yellow arrow: collagen; white arrow: adipocyte. Scale bar: 100 μm.

DownLoad: Full-Size Img PowerPoint

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[2]	Masters B R, So P T C, Gratton E 1997 Biophys. J. 72 2405 Google Scholar
[3]	König K, Riemann I 2003 J. Biomed. Opt. 8 432 Google Scholar
[4]	König K, Ehlers A, Stracke F, Riemann I 2006 Skin Pharmacol. Physiol. 19 78 Google Scholar
[5]	König K, Ehlers A, Riemann I, Schenkl S, Bückle R, Kaatz M 2007 Microsc. Res. Tech. 70 398 Google Scholar
[6]	Paoli J, Smedh M, Wennberg A M, Ericson M B 2008 J. Invest. Dermatol. 128 1248 Google Scholar
[7]	Breunig H G, Studier H, König K 2010 Opt. Express 18 7857 Google Scholar
[8]	El Madani H A, Tancrède-Bohin E, Bensussan A, Colonna A, Dupuy A, Bagot M, Pena A M 2012 J. Biomed. Opt. 17 026009 Google Scholar
[9]	Balu M, Mazhar A, Hayakawa C K, Mittal R, Krasieva T B, König K, Venugopalan V, Tromberg B J 2013 Biophys. J. 104 258 Google Scholar
[10]	Cahill L C, Giacomelli M G, Tadayuki Y 2018 Lab. Invest. 98 150 Google Scholar
[11]	Cahill L C, Fujimoto J G, Giacomelli M G 2019 Mod. Pathol. 32 1158 Google Scholar
[12]	Sun C K, Chien T K, Ming L W 2019 J. Biophotonics 12 1
[13]	You S, Tu H, Chaney E J, Sun Y, Zhao Y, Bower A J, Liu Y Z, Marjanovic M, Sinha S, Pu Y, Boppart S A 2018 Nat. Commun. 9 2125 Google Scholar
[14]	Brown E, McKee T, diTomaso E, Pluen A, Seed B, Boucher Y, Jain R K 2003 Nat. Med. 9 796 Google Scholar
[15]	Sun C K, Chen C C, Chu S W, Tsai T H, Chen Y C, Lin B L 2003 Opt. Lett. 28 2488 Google Scholar
[16]	Tai S P, Tsai T H, Lee W J, Shieh D B, Liao Y H, Huang H Y, Zhang K, Liu H L, Sun C K 2005 Opt. Express 13 8231 Google Scholar
[17]	Chen S Y, Wu H Y, Sun C K 2009 J. Biomed. Opt. 14 060505 Google Scholar
[18]	Yasui T, Takahashi Y, Ito M, Fukushima S, Araki T 2009 Appl. Opt. 48 D88 Google Scholar
[19]	Chen S Y, Chen S U, Wu H Y, Lee W J, Liao Y H, Sun C K 2010 IEEE J. Sel. Top. Quantum Electron. 16 478 Google Scholar
[20]	Tsai N R, Chen S Y, Shieh D B, Lou P J, Sun C K 2011 Biomed. Opt. Express 2 2317 Google Scholar
[21]	Zumbusch A, Holtom G R, Xie X S 1999 Phys. Rev. Lett. 82 4142 Google Scholar
[22]	Hellerer T, Enejder A M, Zumbusch A 2004 Appl. Phys. Lett. 85 25 Google Scholar
[23]	Legesse F B, Medyukhina A, Heuke S, Popp J 2015 Comput. Med. Imaging Graph. 43 36 Google Scholar
[24]	Freudiger C W, Min W, Saar B G, Lu S, Holtom G R, He C, Tsai J C, Kang J X, Xie X S 2008 Science 322 1857 Google Scholar
[25]	Ji M, Lewis S, Camelo-Piragua S, Ramkissoon S H, Snuderl M, Venneti S, Fisher-Hubbard A, Garrard M, Fu D, Wang A C, Heth J A, Maher C O, Sanai N, Johnson T D, Freudiger C W, Sagher O, Xie X S, Orringer D A 2015 Sci. Transl. Med. 7 309ra163 Google Scholar
[26]	Georgakoudi I, Quinn K P 2012 Annu. Rev. Biomed. Eng. 14 351 Google Scholar
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[28]	Hou J, Wright H J, Chan N S K, Tran R D H, Razorenova O V, Potma E O, Tromberg B J 2016 J Biomed Opt. 21 060503 Google Scholar
[29]	Huang S H, Heikal A A, Webb W W 2002 Biophys. J. 82 2811 Google Scholar
[30]	Zoumi A, Yeh A, Tromberg B J 2002 Proc. Natl. Acad. Sci. U. S. A. 99 11014 Google Scholar
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[32]	Chu S W, Chen I H, Liu T M, Chen P C, Sun C K, Lin B L 2001 Opt. Lett. 26 1909 Google Scholar
[33]	Xu C, Wise F W 2013 Nat. Photonics 7 875 Google Scholar
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[35]	Takayanagi J, Sugiura T, Yoshida M, Nishizawa N 2006 IEEE Photonics Technol. Lett. 18 2284 Google Scholar
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[42]	Gottschall T, Meyer T, Schmitt M, Popp J, Limpert J, Tünnermann A 2015 Opt. Express 23 23968 Google Scholar
[43]	Liu W, Li C, Zhang Z, Kärtner F X, Chang G Q 2016 Opt. Express 24 15328 Google Scholar
[44]	Liu W, Chia S H, Chung H Y, Greinert R, Kärtner F X, Chang G Q 2017 Opt. Express 25 6822 Google Scholar
[45]	Chung H Y, Liu W, Cao Q, Kärtner F X, Chang G Q 2017 Opt. Express 25 15760 Google Scholar
[46]	Chung H Y, Liu W, Cao Q, Song L W, Kärtner F X, Chang G Q 2018 Opt. Express 26 3684 Google Scholar
[47]	Chung H Y, Liu W, Cao Q, Greinert R, Kärtner F X, Chang G Q 2019 IEEE J. Sel. Top. Quantum Electron 25 6800708 Google Scholar
[48]	Chung H Y, Greinert R, Kärtner F X, Chang G Q 2019 Biomed. Opt. Express 10 514 Google Scholar
[49]	Herz J, Siffrin V, Hauser A E, Brandt A U, Leuenberger T, Radbruch H, Zipp F, Niesne R A 2010 Biophys. J. 98 715 Google Scholar
[50]	Bissell M J, Radisky D 2001 Nat. Rev. Cancer 1 46 Google Scholar

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