Abstract

Light-sheet microscopy (LSM) has emerged as a powerful tool for high-speed volumetric imaging of live model organisms and large optically cleared specimens. When designing cleared-tissue LSM systems with certain desired imaging specifications (e.g. resolution, contrast, and working distance), various design parameters must be taken into consideration. In order to elucidate some of the key design tradeoffs for LSM systems, we present a diffraction-based analysis of single- and dual-objective LSM configurations using simulations of LSM point spread functions. We assume Gaussian illumination is utilized. Specifically, we analyze the effects of the illumination and collection numerical aperture (NA), as well as their crossing angle, on spatial resolution and contrast. Assuming an open-top light-sheet (OTLS) architecture, we constrain these parameters based on fundamental geometric considerations as well as those imposed by currently available microscope objectives. In addition to revealing the performance tradeoffs of various single- and dual-objective LSM configurations, our analysis showcases the potential advantages of a novel, non-orthogonal dual-objective (NODO) architecture, especially for moderate-resolution imaging applications (collection NA of 0.5 to 0.8).

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2020 (1)

2019 (4)

M. Hoffmann and B. Judkewitz, “Diffractive oblique plane microscopy,” Optica 6(9), 1166–1170 (2019).
[Crossref]

T. Chakraborty, M. K. Driscoll, E. Jeffery, M. M. Murphy, P. Roudot, B.-J. Chang, S. Vora, W. M. Wong, C. D. Nielson, H. Zhang, V. Zhemkov, C. Hiremath, E. D. De La Cruz, Y. Yi, I. Bezprozvanny, H. Zhao, R. Tomer, R. Heintzmann, J. P. Meeks, D. K. Marciano, S. J. Morrison, G. Danuser, K. M. Dean, and R. Fiolka, “Light-sheet microscopy of cleared tissues with isotropic, subcellular resolution,” Nat. Methods 16(11), 1109–1113 (2019).
[Crossref]

F. F. Voigt, D. Kirschenbaum, E. Platonova, S. Pagès, R. A. A. Campbell, R. Kastli, M. Schaettin, L. Egolf, A. Bourg, P. Bethge, K. Haenraets, N. Frézel, T. Topilko, P. Perin, D. Hillier, S. Hildebrand, A. Schueth, A. Roebroeck, B. Roska, E. T. Stoeckli, R. Pizzala, N. Renier, H. U. Zeilhofer, T. Karayannis, U. Ziegler, L. Batti, A. Holtmaat, C. Lüscher, A. Aguzzi, and F. Helmchen, “The mesoSPIM initiative: open-source light-sheet microscopes for imaging cleared tissue,” Nat. Methods 16(11), 1105–1108 (2019).
[Crossref]

A. K. Glaser, N. P. Reder, Y. Chen, C. Yin, L. Wei, S. Kang, L. A. Barner, W. Xie, E. F. McCarty, C. Mao, A. R. Halpern, C. R. Stoltzfus, J. S. Daniels, M. Y. Gerner, P. R. Nicovich, J. C. Vaughan, L. D. True, and J. T. C. Liu, “Multi-immersion open-top light-sheet microscope for high-throughput imaging of cleared tissues,” Nat. Commun. 10(1), 2781 (2019).
[Crossref]

2018 (2)

B. Migliori, M. S. Datta, C. Dupre, M. C. Apak, S. Asano, R. Gao, E. S. Boyden, O. Hermanson, R. Yuste, and R. Tomer, “Light sheet theta microscopy for rapid high-resolution imaging of large biological samples,” BMC Biol. 16(1), 57 (2018).
[Crossref]

M. Kumar, S. Kishore, J. Nasenbeny, D. McLean, and Y. Kozorovitskiy, “Integrated one- and two-photon scanned oblique plane illumination (SOPi) microscopy for rapid volumetric imaging,” Opt. Express 26(10), 13027 (2018).
[Crossref]

2017 (4)

R. M. Power and J. Huisken, “A guide to light-sheet fluorescence microscopy for multiscale imaging,” Nat. Methods 14(4), 360–373 (2017).
[Crossref]

N. Tanaka, S. Kanatani, R. Tomer, C. Sahlgren, P. Kronqvist, D. Kaczynska, L. Louhivuori, L. Kis, C. Lindh, P. Mitura, A. Stepulak, S. Corvigno, J. Hartman, P. Micke, A. Mezheyeuski, C. Strell, J. W. Carlson, C. Fernández Moro, H. Dahlstrand, A. Östman, K. Matsumoto, P. Wiklund, M. Oya, A. Miyakawa, K. Deisseroth, and P. Uhlén, “Whole-tissue biopsy phenotyping of three-dimensional tumours reveals patterns of cancer heterogeneity,” Nat. Biomed. Eng. 1(10), 796–806 (2017).
[Crossref]

A. K. Glaser, N. P. Reder, Y. Chen, E. F. McCarty, C. Yin, L. Wei, Y. Wang, L. D. True, and J. T. C. Liu, “Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens,” Nat. Biomed. Eng. 1(7), 0084 (2017).
[Crossref]

R. Mcgorty, D. Xie, and B. Huang, “High-NA open-top selective-plane illumination microscopy for biological imaging,” Opt. Express 25(15), 17798–17810 (2017).
[Crossref]

2016 (3)

2015 (5)

T. Li, S. Ota, J. Kim, Z. J. Wong, Y. Wang, X. Yin, and X. Zhang, “Axial Plane Optical Microscopy,” Sci. Rep. 4(1), 7253 (2015).
[Crossref]

K. Dean, P. Roudot, E. Welf, G. Danuser, and R. Fiolka, “Deconvolution-free Subcellular Imaging with Axially Swept Light Sheet Microscopy,” Biophys. J. 108(12), 2807–2815 (2015).
[Crossref]

N. Scherf and J. Huisken, “The smart and gentle microscope,” Nat. Biotechnol. 33(8), 815–818 (2015).
[Crossref]

M. B. Bouchard, V. Voleti, C. S. Mendes, C. Lacefield, W. B. Grueber, R. S. Mann, R. M. Bruno, and E. M. C. Hillman, “Swept confocally-aligned planar excitation (SCAPE) microscopy for high-speed volumetric imaging of behaving organisms,” Nat. Photonics 9(2), 113–119 (2015).
[Crossref]

R. McGorty, H. Liu, D. Kamiyama, Z. Dong, S. Guo, and B. Huang, “Open-top selective plane illumination microscope for conventionally mounted specimens,” Opt. Express 23(12), 16142–16153 (2015).
[Crossref]

2014 (5)

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, J. N. Bembenek, A.-C. Reymann, R. Böhme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: Imaging molecules to embryos at high spatiotemporal resolution,” Science 346(6208), 1257998 (2014).
[Crossref]

A. Kumar, Y. Wu, R. Christensen, P. Chandris, W. Gandler, E. McCreedy, A. Bokinsky, D. A. Colón-Ramos, Z. Bao, M. McAuliffe, G. Rondeau, and H. Shroff, “Dual-view plane illumination microscopy for rapid and spatially isotropic imaging,” Nat. Protoc. 9(11), 2555–2573 (2014).
[Crossref]

R. Tomer, L. Ye, B. Hsueh, and K. Deisseroth, “Advanced CLARITY for rapid and high-resolution imaging of intact tissues,” Nat. Protoc. 9(7), 1682–1697 (2014).
[Crossref]

J. Kim, T. Li, Y. Wang, and X. Zhang, “Vectorial point spread function and optical transfer function in oblique plane imaging,” Opt. Express 22(9), 11140–11151 (2014).
[Crossref]

A. R. Gardner, C. K. Hayakawa, and V. Venugopalan, “Coupled forward-adjoint Monte Carlo simulation of spatial-angular light fields to determine optical sensitivity in turbid media,” J. Biomed. Opt. 19(6), 065003 (2014).
[Crossref]

2013 (2)

D. Wang, Y. Chen, Y. Wang, and J. T. C. Liu, “Comparison of line-scanned and point-scanned dual-axis confocal microscope performance,” Opt. Lett. 38(24), 5280–5283 (2013).
[Crossref]

Y. Chen and J. T. C. Liu, “Optimizing the performance of dual-axis confocal microscopes via Monte-Carlo scattering simulations and diffraction theory,” J. Biomed. Opt. 18(6), 066006 (2013).
[Crossref]

2012 (1)

2011 (2)

S. Kumar, D. Wilding, M. B. Sikkel, A. R. Lyon, K. T. MacLeod, and C. Dunsby, “High-speed 2D and 3D fluorescence microscopy of cardiac myocytes,” Opt. Express 19(15), 13839–13847 (2011).
[Crossref]

J. Chen and X. Intes, “Comparison of Monte Carlo methods for fluorescence molecular tomography-computational efficiency,” Med. Phys. 38(10), 5788–5798 (2011).
[Crossref]

2008 (4)

C. Dunsby, “Optically sectioned imaging by oblique plane microscopy,” Opt. Express 16(25), 20306–20316 (2008).
[Crossref]

C. A. Konopka and S. Y. Bednarek, “Variable-angle epifluorescence microscopy: a new way to look at protein dynamics in the plant cell cortex,” Plant J. 53(1), 186–196 (2008).
[Crossref]

M. Tokunaga, N. Imamoto, and K. Sakata-Sogawa, “Highly inclined thin illumination enables clear single-molecule imaging in cells,” Nat. Methods 5(2), 159–161 (2008).
[Crossref]

E. J. Botcherby, R. Juškaitis, M. J. Booth, and T. Wilson, “An optical technique for remote focusing in microscopy,” Opt. Commun. 281(4), 880–887 (2008).
[Crossref]

2007 (3)

J. Swoger, P. Verveer, K. Greger, J. Huisken, and E. H. K. Stelzer, “Multi-view image fusion improves resolution in three-dimensional microscopy,” Opt. Express 15(13), 8029–8042 (2007).
[Crossref]

E. J. Botcherby, R. Juskaitis, M. J. Booth, and T. Wilson, “Aberration-free optical refocusing in high numerical aperture microscopy,” Opt. Lett. 32(14), 2007–2009 (2007).
[Crossref]

H.-U. Dodt, U. Leischner, A. Schierloh, N. Jährling, C. P. Mauch, K. Deininger, J. M. Deussing, M. Eder, W. Zieglgänsberger, and K. Becker, “Ultramicroscopy: three-dimensional visualization of neuronal networks in the whole mouse brain,” Nat. Methods 4(4), 331–336 (2007).
[Crossref]

2004 (1)

J. Huisken, J. Swoger, F. D. Bene, J. Wittbrodt, and E. H. K. Stelzer, “Optical Sectioning Deep Inside Live Embryos by Selective Plane Illumination Microscopy,” Science 305(5686), 1007–1009 (2004).
[Crossref]

1997 (1)

Abeytunge, S.

Aguzzi, A.

F. F. Voigt, D. Kirschenbaum, E. Platonova, S. Pagès, R. A. A. Campbell, R. Kastli, M. Schaettin, L. Egolf, A. Bourg, P. Bethge, K. Haenraets, N. Frézel, T. Topilko, P. Perin, D. Hillier, S. Hildebrand, A. Schueth, A. Roebroeck, B. Roska, E. T. Stoeckli, R. Pizzala, N. Renier, H. U. Zeilhofer, T. Karayannis, U. Ziegler, L. Batti, A. Holtmaat, C. Lüscher, A. Aguzzi, and F. Helmchen, “The mesoSPIM initiative: open-source light-sheet microscopes for imaging cleared tissue,” Nat. Methods 16(11), 1105–1108 (2019).
[Crossref]

Apak, M. C.

B. Migliori, M. S. Datta, C. Dupre, M. C. Apak, S. Asano, R. Gao, E. S. Boyden, O. Hermanson, R. Yuste, and R. Tomer, “Light sheet theta microscopy for rapid high-resolution imaging of large biological samples,” BMC Biol. 16(1), 57 (2018).
[Crossref]

Arteaga, C. L.

E. Sapoznik, B.-J. Chang, R. J. Ju, E. S. Welf, D. Broadbent, A. F. Carisey, S. J. Stehbens, K.-m. Lee, A. Marín, A. B. Hanker, J. C. Schmidt, C. L. Arteaga, B. Yang, R. Kruithoff, D. P. Shepherd, A. Millett-Sikking, A. G. York, K. M. Dean, and R. P. Fiolka, “A Single-Objective Light-Sheet Microscope with 200 nm-Scale Resolution,” bioRxiv p. 2020.04.07.030569 (2020). Publisher: Cold Spring Harbor Laboratory Section: New Results.

Asano, S.

B. Migliori, M. S. Datta, C. Dupre, M. C. Apak, S. Asano, R. Gao, E. S. Boyden, O. Hermanson, R. Yuste, and R. Tomer, “Light sheet theta microscopy for rapid high-resolution imaging of large biological samples,” BMC Biol. 16(1), 57 (2018).
[Crossref]

Balazs, B.

P. Strnad, S. Gunther, J. Reichmann, U. Krzic, B. Balazs, G. Medeiros, N. Norlin, T. Hiiragi, L. Hufnagel, and J. Ellenberg, “Inverted light-sheet microscope for imaging mouse pre-implantation development,” Nat. Methods 13(2), 139–142 (2016).
[Crossref]

Bao, Z.

A. Kumar, Y. Wu, R. Christensen, P. Chandris, W. Gandler, E. McCreedy, A. Bokinsky, D. A. Colón-Ramos, Z. Bao, M. McAuliffe, G. Rondeau, and H. Shroff, “Dual-view plane illumination microscopy for rapid and spatially isotropic imaging,” Nat. Protoc. 9(11), 2555–2573 (2014).
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Figures (15)

Fig. 1.
Fig. 1. Overview of single- and dual-objective light-sheet microscope (LSM) architectures. (a) Optical schematic of a conventional orthogonal dual-objective (ODO) open-top light-sheet (OTLS) system, showing the illumination (blue) and collection (green) light paths. (b) Inset of illumination and collection objectives of an ODO system, showing that the system’s effective working distance (WDsystem) is much less than the collection objective’s working distance (WDobjective). (c) Optical schematic of a non-orthogonal single-objective (NOSO) OTLS system, showing the illumination (blue) and collection (green) light paths. (d) Inset of the shared primary objective of a NOSO system, showing the angled light sheet and collection path. CL: cylindrical lens, TL: tube lens, DBS: dichroic beam splitter.
Fig. 2.
Fig. 2. Outline of the analysis approach followed. Three key design parameters were identified that, in the context of cleared tissue imaging, primarily determine the optical performance of an LSM system (regardless of specific architecture): the numerical aperture (NA) of the illumination beam, the NA of the collection beam, and the crossing angle between them. We then introduced limits on these parameters based on practical constraints including available objectives and the physical placement of those objectives. These limits give rise to a range of feasible designs. Finally, we assess the optical performance of these designs in terms of spatial resolution and contrast.
Fig. 3.
Fig. 3. Geometry of a proposed non-orthogonal, dual-objective (NODO) design showing (a) the optical schematic and (b) inset of the illumination and collection objectives. The crossing angle $\theta$ is less than 90° so that the collection objective can be oriented in the normal direction with respect to the horizontal sample holder, as in a NOSO system. This allows the full working distance of the collection objective to be used and minimizes sensitivity to refractive-index mismatch. Unlike the NOSO architecture, NODO also allows the full NA of the collection objective to be used and allows for a higher crossing angle between the illumination and collection beams (with implications for axial resolution and contrast). The NODO design uses a remote focus, as in a NOSO system. CL: cylindrical lens, TL: tube lens, WD: working distance.
Fig. 4.
Fig. 4. Axial resolution of a dual-objective system. (a) Axial resolution depends strongly on crossing angle at small angles but does not improve much beyond angles of 60°. Curves for two example illumination and collection NA pairs are shown ($\mathrm {NA_i} = 0.1$, $\mathrm {NA_c} = 0.4$; $\mathrm {NA_i} = 0.2$, $\mathrm {NA_c} = 0.7$), but these trends are consistent across different choices of illumination and collection NA. (b) The minimum angle plotted for each system is the minimum crossing angle before the objective cones overlap. (c) The maximum crossing angle is 90° (the conventional ODO case), which yields the maximum possible axial resolution.
Fig. 5.
Fig. 5. Impact of illumination NA on axial resolution for (a) an ODO system, (b) a NODO system at a crossing angle of 60°, and (c) a NOSO system using a 1.0 NA primary objective. In all cases, illumination NA is a primary driver of axial resolution. Collection NAs of 0.4 and 0.7 are shown, but trends are similar for other collection NAs. A diagram of each configuration is shown below each corresponding plot.
Fig. 6.
Fig. 6. Lateral resolution as a function of collection NA for (a) an ODO system and (b) a NODO system with a 60° crossing angle. Different curves on each plot indicate different choices of illumination NA. Curves are largely unchanged both within each plot and between plots, indicating that lateral resolution in a dual-objective system is primarily determined by collection NA and is independent of illumination NA and crossing angle.
Fig. 7.
Fig. 7. Lateral and axial resolution as a function of collection NA for a NOSO system in the case of (a) a moderate-NA primary objective (0.75 NA) and (b) a high-NA primary objective (1.0 NA). In each plot, the primary objective NA is held constant to reveal the different performance combinations a designer could achieve with a given optical element. For simplicity, the illumination NA is also held constant (0.2). Note that changing the collection NA implicitly changes the effective crossing angle in our NOSO simulations. (c) Cone angles and PSF schematic for a moderate-NA shared primary objective. At moderate objective NAs, the crossing angle $\theta$ is constrained to relatively small values. Any further reduction in crossing angle, resulting from an increase in collection NA, leads to a degradation in axial resolution. Thus, there is a tradeoff between axial and lateral resolution. (d) Cone angles and PSF schematic for a high-NA shared primary objective. The crossing angle $\theta$ is relatively large in all cases, such that axial resolution is less sensitive to changes in collection NA. For ease of comparison, a single example collection NA (0.6) is shown in both (c) and (d).
Fig. 8.
Fig. 8. Contrast of a dual-objective system. (a) Impact of crossing angle on contrast is plotted for three illumination NAs (different curves). A collection NA of 0.7 is used in this example, though the trends shown hold for other collection NAs (with slight improvements in contrast overall at higher collection NAs). The minimum angle plotted for each system is the minimum crossing angle before the illumination and collection cones overlap. The maximum angle plotted is 90° (the conventional ODO case) which gives the maximum possible contrast. These cases are shown for a 0.1 illumination NA and 0.7 collection NA system in (b) and (c), respectively. Contrast improves with higher crossing angles, but gains begin to saturate around 60°.
Fig. 9.
Fig. 9. Comparison of contrast for ODO, NODO (60° crossing angle), and NOSO systems that can be built using (a) a moderate-NA (0.7) primary objective and (b) a high-NA (1.0) primary objective (i.e. the collection objective for dual-objective systems or the shared primary objective for single-objective systems). For simplicity, the effective collection NA is held constant for each NOSO curve (0.5 for the moderate-NA case and 0.7 for the high-NA case). For all systems, increasing the illumination NA improves contrast but offers diminishing returns at higher illumination NAs. The NOSO system provides poorer contrast than the ODO or NODO systems in the moderate-NA case, while all systems provide similar contrast in the high-NA case.
Fig. 10.
Fig. 10. (a) Optical schematic of a non-orthogonal single-objective (NOSO) LSM system, showing the illumination (blue) and collection (green) light paths. (b) Inset of the shared primary objective of a NOSO system showing the angled light sheet and collection path. (c,d) Inset of the remote focus of a NOSO system (c) without a refractive prism, showing some light is lost at the remote focus and (d) with a refractive prism, showing collection of otherwise lost light. CL: cylindrical lens, TL: tube lens, DBS: dichroic beam splitter.
Fig. 11.
Fig. 11. Computational methods for analyzing the resolution and contrast of a given configuration. (a) Three-dimensional point spread functions (PSFs) (assuming Gaussian illumination and uniform collection) are computed separately and multiplied together using the adjoint method to calculate a system PSF. (b) Resolution is computed by finding the full width at half maximum through the center of the system PSF in the lateral and axial directions (relative to the collection objective). (c) To analyze relative differences in image contrast, the system PSF is convolved with a random bead phantom, in which single voxels are set to a value of 1 to simulate diffraction-limited fluorescent beads. Relative contrast levels are then computed based on the value of the response at the locations of the beads ($I_{beads}$) relative to the background signal level seen in the images ($I_{background}$).
Fig. 12.
Fig. 12. Example diffraction-limited fluorescent bead phantom and response for contrast computation. A 0.01% bead concentration is shown for an orthogonal dual-objective (ODO) system with 0.7 collection NA and 0.2 illumination NA. Note that the figure shows a single slice of a 3D phantom, so many beads visible in the response cannot be seen in the phantom as they are in planes in front of or behind the plane shown.
Fig. 13.
Fig. 13. Variation in contrast measurement for a dual-objective system for various bead concentrations in the simulated fluorescent phantom. (a-c) Impact of crossing angle on contrast for 0.01%, 0.1%, and 0.5% bead phantoms. Each plot shows contrast at three different illumination NAs (different curves). A collection NA of 0.7 is used for all systems in this example. (d-f) Example phantom responses for bead concentrations of 0.01%, 0.1%, and 0.5%, respectively. Near-perfect contrast is achieved regardless of configuration at low concentrations (sparsely labeled samples; a,d), but varies significantly with configuration at higher concentrations (densely labeled samples; c,f).
Fig. 14.
Fig. 14. Impact of illumination NA on PSF volume for (a) an ODO system, (b) a NODO system at a crossing angle of 60°, and (c) a NOSO system using a 1.0 NA primary objective. Collection NAs of 0.4 and 0.7 are shown. In all cases, PSF volume depends significantly on both illumination NA and collection NA. All three configurations show similar focal volume trends, indicating that architecture is not a significant driver of focal volume on its own.
Fig. 15.
Fig. 15. Contrast of a dual-objective system as a function of crossing angle for collection NAs of 0.4, 0.7, and 1.0. In all cases, contrast improves with crossing angle until around 60°, at which point further gains are minimal. Contrast also improves slightly at higher collection NAs, as the collection objective provides some additional optical sectioning at higher NAs.

Tables (2)

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Table 1. Survey of commercial objectives for cleared tissue imaging

Tables Icon

Table 2. Comparison of effective system working distance between ODO and NOSO/NODO configurations

Equations (13)

Equations on this page are rendered with MathJax. Learn more.

ϕ = sin 1 ( N A / n )
θ ϕ i + ϕ c
θ + ϕ i + ϕ c 180
θ = 2 ϕ o b j ϕ c ϕ i
θ t i l t = 90 ϕ o b j + ϕ i
n a i r sin θ 1 = n 2 sin θ 2
( 1.0 ) sin 90 = n 2 sin θ 2
1.0 = n 2 sin θ 2
N A r e m o t e = n 2 sin θ 2
N A r e m o t e = 1.0
ϕ i + 2 ϕ c 2 ϕ o b j
C = I b e a d s I b a c k g r o u n d I b e a d s + I b a c k g r o u n d
V = 4 3 π R x R y R z