Cell spectral imaging device and method

Abstract

The invention relates to a spectral imaging technology, and particularly provides a cell spectral imaging device and method, the imaging device comprises a light source and a detector; the adjusting unit reflects emergent light of the light source, so that the reflected light sweeps cells flowing in the channel in two dimensions, and the cells are stained with fluorescein; the light splitting unit splits fluorescence emitted by the excited cell, and the detector outputs three-dimensional spectrum data related to the position and wavelength; the processing unit is used for carrying out spectrum unfolding on the three-dimensional spectrum data to obtain a multi-channel image; and the controller is used for driving the adjusting unit and the detector to sample and trigger. The method has the advantages of high resolution and the like, and is applied to single cell analysis.

Description

Technical Field

[0001] The present invention relates to spectral imaging technology, and particularly to a cell spectral imaging device and method. Background Art

[0002] Currently, fluorescence spectral imaging of cells is relatively difficult. Specifically: after fluorescently staining cells, the cells are placed on a glass slide, and imaging of the fluorescent dye inside the cells is obtained by scanning with a laser confocal microscope. In this way, cell fluorescence images with relatively high resolution quality can be obtained, but the disadvantages are as follows: 1. The acquisition efficiency is relatively low, the imaging speed is slow, and at the same time, the number of fluorescent channels that can be acquired is limited. Restricted by the wavelength interference of the fluorescent dye, the use of fluorescent channels is very limited, which is very disadvantageous for observing multiple fluorescent channels.

[0003] As Figure 1 shown, there are many tissues inside the cells. After fluorescent staining, different proteins are stained with different fluoresceins. Spatially, many of them overlap. The traditional method can only perform spatial imaging on proteins labeled with one or a few fluorescent dyes and cannot solve the problem of simultaneous imaging of multiple fluorescences.

[0004] 2. The traditional laser confocal microscope can only perform point-by-point scanning on fixed samples under static conditions, and its spatial resolution is limited by the Abbe diffraction limit; at the same time, multi-color fluorescence depends on the central wavelength λc and half-width Δλ of the filter, resulting in band overlap and signal crosstalk.

[0005] 3. Although the existing flow cytometers have achieved a throughput of 10 4 cells·s -1 level, due to the use of broadband integrated detectors, they cannot resolve sub-pixel sub-band information and are difficult to reveal the multiple fluorescence distributions in cell sub-compartments. Summary of the Invention

[0006] To solve the deficiencies in the above-mentioned prior art solutions, the present invention provides a cell spectral imaging device.

[0007] The purpose of the present invention is achieved through the following technical solutions: A cell spectral imaging device includes a light source and a detector; the cell spectral imaging device further includes: An adjustment unit that reflects the emitted light of the light source so that the reflected light sweeps across the cells flowing in the channel in two dimensions, and the cells are stained with fluorescein; A spectral splitting unit that splits the fluorescence emitted by the excited cells, and the detector outputs three-dimensional spectral data related to position and wavelength; A processing unit that is used to perform spectral deconvolution on the three-dimensional spectral data to obtain multi-channel images; A controller, which is used to drive the adjustment unit and trigger the detector sampling.

[0008] Another object of the present invention is to provide a cell spectral imaging method, and this object of the invention is achieved through the following technical solutions.

[0009] The cell spectral imaging method includes the following steps: The emitted light of the light source is reflected by the adjustment unit, so that the reflected light sweeps across the cells flowing in the channel in two dimensions, and the cells are stained with fluorescein; The excited cells emit fluorescence, and the fluorescence is received by the detector after being spectroscopically analyzed, thereby outputting three-dimensional spectral data related to position and wavelength; The processing unit performs spectral deconvolution on the three-dimensional spectral data to obtain a multi-channel image; During the above process, the controller controls the movement of the adjustment unit and the sampling trigger of the detector.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention uses the adjustment unit to achieve rapid two-dimensional scanning of single cells stained with fluorescein, obtain the full fluorescence spectrum, and then obtain the fluorescence components through spectroscopic analysis and spectral deconvolution, so as to obtain the fluorescence signal at each pixel point of the cell, realizing flow cytometry rapid single-cell multi-fluorescence component imaging.

[0011] 1. Achieve synchronization of spatial resolution less than 2 µm and spectral resolution less than 0.15 nm; 2. The acquisition time per cell is less than 2 µs, up to 5×10 4 cells·s -1 Real-time multi-fluorescence mapping; 3. Using regularized non-negative matrix factorization, the upper limit of the fluorescence channel is increased to 40+, and the crosstalk suppression ratio is increased by 8 dB. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Referring to the accompanying drawings, the disclosure of the present invention will become more understandable. It is easy for those skilled in the art to understand that these drawings are only used to illustrate the technical solutions of the present invention and are not intended to limit the protection scope of the present invention. In the figures: Figure 1 is a schematic diagram of a cell; Figure 2 is a schematic structural diagram of the cell spectral imaging device according to the present invention; Figure 3 is a schematic two-dimensional scanning diagram of the cell according to the present invention; Figure 4 is a schematic spectral deconvolution diagram according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0013] Figures 2 - 4 The following description and the following illustrate alternative specific embodiments of the present invention to teach those skilled in the art how to implement and reproduce the present invention. To teach the technical solution of the present invention, some conventional aspects have been simplified or omitted. Those skilled in the art should understand that variations or substitutions derived from these specific embodiments will fall within the scope of the present invention. Those skilled in the art should understand that the following features can be combined in various ways to form multiple variations of the present invention. Thus, the present invention is not limited to the following alternative specific embodiments, but is only defined by the claims and their equivalents.

[0014] Example 1.

[0015] As Figure 2 shown, the cell spectral imaging device of this embodiment includes: A light source and a detector. The light source generally uses a laser, and the detector uses a linear array photodetector.

[0016] An adjustment unit, such as a galvanometer or a rotating prism, as Figure 3 shown, for reflecting the emitted light of the light source, so that the reflected light sweeps across the cells flowing in the channel in two dimensions, and the cells are stained with fluorescein.

[0017] A spectroscopic unit, such as a prism grating spectroscopic module, for splitting the fluorescence emitted by the excited cells, and the detector outputs three-dimensional spectral data related to position and wavelength.

[0018] A processing unit, such as a spectral deconvolution software, for performing spectral deconvolution on the three-dimensional spectral data to obtain a multi-channel image, as Figure 4 shown.

[0019] A controller, such as an FPGA, which is used to drive the adjustment unit and the detector sampling trigger.

[0020] To improve the rate and accuracy of spectral deconvolution, further, the processing unit is solved by a non-negative matrix factorization algorithm with a regularization term, and the objective function is , S = MC + ε.

[0021] S is the spectral matrix output by the detector, M is the reference spectral basis matrix, C is the abundance matrix to be solved, α is the spatial smooth regularization weight (the value ranges from 0.01 - 0.1, and a 10-fold dynamic range covers the prototype test interval of common SNR 2dB - 20dB), is the gradient of C in the pixel grid in the x and y dimensions, is the Frobenius norm, and ε is the measurement noise.

[0022] To control the operation of the adjustment unit, further, the adjustment unit uses a galvanometer, and the scanning frequency fscan and the central flow velocity v in the channel flow satisfy: f scan = v flow / Δx, where Δx is the pixel step, which refers to the sampling interval on the horizontal pixel grid. The galvanometer is driven by a triangular wave, and the angular frequency ω = 2πf scan .

[0023] For spectral imaging, further, a collimating lens, a variable diffraction aperture, an adjustment unit, an objective lens, and a flow tube are sequentially arranged on the outgoing light path, and the flow tube, a spectroscopic unit, and a detector are sequentially arranged on the fluorescence light path. The outgoing light forms an Airy disk incident on the cells behind the objective lens.

[0024] The cell spectral imaging method according to the embodiment of the present invention, that is, the working method of the imaging device in this embodiment, the imaging method includes the following steps: The outgoing light of the light source is reflected by the adjustment unit, so that the reflected light sweeps across the cells flowing in the channel in two dimensions, and the cells are stained with fluorescein.

[0025] The excited cells emit fluorescence, and the fluorescence is received by the detector after spectroscopy, so as to output three-dimensional spectral data related to position and wavelength.

[0026] The processing unit performs spectral decomposition on the three-dimensional spectral data to obtain a multi-channel image.

[0027] In the above process, the controller controls the movement of the adjustment unit and the sampling trigger of the detector.

[0028] To improve the rate and accuracy of spectral decomposition, further, the spectral decomposition method is: Construct a reference spectral basis matrix M and solve it using the alternating direction method of multipliers.

[0029] , S = MC + ε.

[0030] S is the spectral matrix output by the detector, C is the abundance matrix to be solved, α is the spatial smooth regularization weight, is the gradient of C in the x and y dimensions of the pixel grid, is the Frobenius norm, and ε is the measurement noise.

[0031] Map each row of the abundance matrix C to be solved to the pixel grid (x, y) to obtain a multi-channel image G(x, y).

[0032] In this embodiment, the way to obtain the weight α is: The first term in the objective function ensures that the spectral decomposition residual is minimized, and the second term uses pixel-spectral gradient constraints Suppress stripes / noise, and α is the weight of the two terms.

[0033] First, unify the dimension and scale.

[0034] Normalization: Perform column vector l_2-norm normalization on the original spectrum S and the basis matrix M, such that |S|_F |MC|_F.

[0035] Gradient term scaling: If the pixel step size Δx is different for each frame, multiply by Δx (or Δt) for normalization, such that the two-norm | |_F roughly falls between 0 and 1.

[0036] After this step, the orders of magnitude of |S - MC|_F^2 and | |_F^2 on the same data set are comparable, which is why the range of 0.01 - 0.1 can cover a 10-fold dynamic range without being too large or too small.

[0037] Example 2.

[0038] An application example of the cell spectral imaging device and method according to Embodiment 1 of the present invention.

[0039] 1. As Figure 2 shown, in the outgoing light optical path, the light source uses a laser, the central wavelength λ0 of the outgoing light is 488 nm, and the power P exc = 30 nW. The outgoing light sequentially passes through the collimating lens L1 and the variable diffraction aperture.

[0040] The adjustment unit uses a two-dimensional scanning galvanometer G1, driven by a triangular wave, with an angular frequency ω = 2πf scan .

[0041] The cell diameter is 12 µm, the target lateral pixel step size Δx = 0.4 µm, and f scan = v flow / Δx ≈ 5·10 5 Hz, and the single-pixel dwell time τ pix = 1 / f scan = 2 µs.

[0042] On the outgoing light optical path, an Airy disk radius W0 ≈ 1.22λ0 / (2NA) = 0.31 µm is formed behind the objective lens (NA = 0.95, f = 200 mm).

[0043] On the fluorescence optical path, the beam splitting unit uses a transmissive prism grating beam splitting module (line density 1200 lp·mm -1 ), and its spectral resolution is estimated as: δλ = d / (mNcosβ) ≈ 0.12 nm, diffraction order m = 1, grating constant d = 0.833 μm, number of illuminated grooves N = 2400, diffraction angle β = 15 degrees.

[0044] 2. In the flow path, the configured cell suspension is 10 6 cells mL -1 , sheath: sample = 100:1, and the liquid injected into the capillary is 50 μL. In the flow cytometry pipeline, the inner diameter D of the capillary h = 120 μm, flow velocity v flow = 0.2 m·s -1 . After sheath flow focusing, the cells are centered and the radial drift is less than 1 μm.

[0045] The corresponding Reynolds number Re = ρ·v flow ·D h / A ≈ 24, forming a laminar flow structure, where ρ is the fluid density and A is the dynamic viscosity.

[0046] 3. The controller uses a 200 MHz FPGA as the core to generate the galvanometer drive and the CMOS multi-channel APD sampling trigger for the detector. The time alignment error δt of the same pixel is less than 5 ns, and it can be considered that δy = v flow ·δt is not greater than 1 nm and can be ignored.

[0047] 4. The spectral deconvolution method of the processing unit is as follows: The detector outputs a three-dimensional hyperspectral data cube I(x, y, λ), where (x, y) is the pixel grid.

[0048] Construct a reference spectral basis matrix M (m×n, where the cells are stained with n dyes), and solve it using the alternating direction method of multipliers.

[0049] , S = MC + ε.

[0050] S is the spectral matrix output by the detector (m wavelength samplings × p pixels), C is the abundance matrix to be solved (n×p), α is the spatial smoothing regularization weight, is the gradient of C in the x and y dimensions of the pixel grid, is the Frobenius norm, and ε is the measurement noise.

[0051] Map each row of the abundance matrix C to be solved to the pixel grid (x, y) to obtain a multi-channel image G(x, y).

[0052] Average number of photons per pixel , quantum efficiency η = 0.35, h is Planck's constant, v = c / λ, c is the speed of light, corresponding to SNR ≈ 21 dB.

Claims

1. A cell spectral imaging device, comprising a light source and a detector; characterized in that, The cell spectral imaging device further includes: An adjustment unit that reflects the emitted light of the light source so that the reflected light sweeps across the cells flowing in the channel in two dimensions, and the cells are stained with fluorescein; A spectroscopic unit that spectroscopically analyzes the fluorescence emitted by the excited cells, and the detector outputs three-dimensional spectral data related to position and wavelength; A processing unit that is used to perform spectral deconvolution on the three-dimensional spectral data to obtain multi-channel images; A controller that is used to drive the adjustment unit and the detector sampling trigger.

2. The imaging device according to claim 1, wherein The processing unit is solved by a non-negative matrix factorization algorithm with a regularization term, and the objective function is , S = MC + ε, S is the spectral matrix output by the detector, M is the reference spectral basis matrix, C is the abundance matrix to be solved, α is the spatial smooth regularization weight, is the gradient of C in the x and y dimensions of the pixel grid, is the Frobenius norm, and ε is the measurement noise.

3. The imaging device according to claim 1, characterized in that, The adjustment unit uses a galvanometer scanner, and the scanning frequency f scan and the central flow velocity v in the channel flow satisfy: f scan = v flow / Δx, where Δx is the pixel step size.

4. The imaging device according to claim 3, characterized in that, The galvanometer is driven by a triangular wave with an angular frequency ω = 2πf scan .

5. The imaging device according to claim 1, wherein The light source uses a laser, and the spectroscopic unit uses a transmissive prism grating spectroscopic module.

6. The imaging device according to claim 5, characterized in that, A collimating lens, a variable diffraction aperture, an adjustment unit, an objective lens, and a flow-through pipeline are sequentially arranged on the emitted light path, and the flow-through pipeline, the spectroscopic unit, and the detector are sequentially arranged on the fluorescence light path. The emitted light forms an Airy disk incident on the cells after passing through the objective lens.

7. A cell spectral imaging method, including the following steps: The emitted light of the light source is reflected by the adjustment unit so that the reflected light sweeps across the cells flowing in the channel in two dimensions, and the cells are stained with fluorescein; The excited cells emit fluorescence, and the fluorescence is received by the detector after spectroscopic analysis, thereby outputting three-dimensional spectral data related to position and wavelength; The processing unit performs spectral deconvolution on the three-dimensional spectral data to obtain multi-channel images; During the above process, the controller controls the movement of the adjustment unit and the sampling trigger of the detector.

8. The imaging method according to claim 7, wherein The method of spectral deconvolution is as follows: Construct a reference spectral basis matrix M and solve it using the alternating direction method of multipliers; , S = MC + ε, S is the spectral matrix output by the detector, C is the abundance matrix to be solved, and α is the spatial smooth regularization weight. is the gradient of C in the x and y dimensions of the pixel grid. is the Frobenius norm, and ε is the measurement noise. Map each row in the abundance matrix C to be solved to the pixel grid (x, y) to obtain the multi-channel image G(x, y).

9. The imaging method according to claim 7, wherein The adjustment unit uses a galvanometer scanner, and the scanning frequency f scan and the central flow velocity v in the channel flow satisfy: f scan = v flow / Δx, where Δx is the pixel step size.

10. The imaging method according to claim 7, characterized in that, The emitted light sequentially passes through the collimating lens and the variable diffraction aperture, and then is reflected by the adjustment unit, and then forms an Airy disk incident on the cells in the flow-through pipeline after passing through the objective lens.

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