• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The invention is a method for identifying a particle contained in a sample having the illumination of the sample with a light source, the latter producing an incident light wave propagating towards the sample, then the acquisition, with the aid of a matrix photodetector, of an image of the sample, the sample being disposed between said light source and the photodetector, such that the matrix photodetector is exposed to a light wave comprising interferences between the incident light wave and a diffraction wave produced by each particle. The method is characterized in that it comprises the application of a digital reconstruction algorithm to the image acquired by the photodetector, for estimating a characteristic quantity of the light wave reaching the detector, at a plurality of distances from the photodetector . The evolution of the characteristic quantity as a function of the distance makes it possible to identify the particle.
    公开号:FR3034196A1
    申请号:FR1552443
    申请日:2015-03-24
    公开日:2016-09-30
    发明作者:Cedric Allier；Pierre Blandin；Cherif Anais Ali
    申请人:Commissariat a lEnergie Atomique CEA；Horiba ABX SAS；Commissariat a lEnergie Atomique et aux Energies Alternatives CEA；
    IPC主号:
    专利说明:

    [0001] TECHNICAL FIELD The invention is in the field of counting and identifying particles present in a liquid and in particular a body fluid, for example blood. PRIOR ART Body fluids, in particular blood, may comprise particles, for example cells, the number and type of which it is useful to know.
    [0002] In the blood, for example, type and blood count, or blood count, analyzes are commonly performed in laboratory analysis. This type of analysis makes it possible to determine the number and to identify the main constituents of the blood, in particular cells of the red blood cell line, white blood cells, or platelets.
    [0003] These examinations are commonly performed, using powerful automata, but we are looking for simpler, less expensive methods, to obtain comparable performance. One of the areas of research is the use of simple optical methods, such as lensless imaging. The observation of biological particles by lensless imaging has been developing since the end of the 2000s. This technique involves inserting a sample between a light source and a matrix photodetector. The image collected on the photodetector is formed by interference between the incident wave produced by the light source and the wave diffracted by the particles making up the sample. Thus, for each particle, a diffraction pattern, or diffraction pattern, of its own can be recorded at the sensor. Applied to biological samples, this technique has been described in WO2008090330. It is then possible to perform a simple analysis of each particle, by comparing the diffraction pattern that it generates with previously established diffraction patterns, corresponding to known particles. But this method can find limits when the concentration of particles increases.
    [0004] Indeed, the counting and identification of particles on the sole basis of the diffraction patterns detected by the photodetector shows a certain limit as the concentration of particles in the sample increases. In particular, when the sample is blood, and the particles are red blood cells, above 100000 particles per pl, their count is no longer reliable, as reported in the publication Seo Sungjyu, "High -throughput lensfree blood analysis on a chip, Anal Chem, 2010 June 1.
    [0005] It is then possible to apply so-called digital holographic reconstruction mathematical treatments in order to establish an image, called complex image, of each particle present in the sample. This method consists in retro-propagating the light wave in the object plane, in which the particles are located, the latter being placed at a known distance from the imager. The publication cited above shows that such a holographic reconstruction makes it possible to count red blood cells present in high concentration in a sample. This publication shows that, on the reconstructed complex image, the white blood cells, having undergone preliminary labeling, have a signature different from that of the red blood cells.
    [0006] A method of identifying particles, and particularly blood cells, which can be applied to samples in which the particle concentration is high is sought. The method must also have an extended field of view, and must be simple to implement, in particular by avoiding prior particle marking. Furthermore, the method must make it possible to reliably discriminate particles which may be in a body fluid, in particular cells of red blood cell lines, white blood cells and platelets. In addition, a method is sought that does not require precise knowledge of the distance between the particles and the photodetector.
    [0007] SUMMARY OF THE INVENTION The invention addresses this problem by providing a method for identifying a particle present in a sample, for example a sample of a biological fluid, such as blood, the method comprising the following steps: illumination of said sample with the aid of a light source, the light source producing an incident light wave propagating towards the sample along an axis of propagation, acquisition, with the aid of a matrix photodetector, of an image of the sample, the sample being disposed between said light source and said photodetector, such that the matrix photodetector is exposed to a light wave comprising interference between the incident light wave and a diffraction wave produced by each particle, the method being characterized in that it also comprises the following steps: - determining a position of said particle in a plane parallel to a plane according to which the matrix photodetector extends, application of a digital reconstruction algorithm to said acquired image, so as to estimate at least one characteristic quantity of said light wave to which the matrix photodetector is exposed, to a plurality of reconstruction distances of the latter, determination of the evolution of said characteristic quantity as a function of said reconstruction distance, along an axis parallel to said axis of propagation and passing through said position, - identification of the particle as a function of said evolution. The characteristic quantity can be obtained by estimating, at each reconstruction distance, a complex expression of the light wave to which the matrix photodetector is exposed. The characteristic quantity can be determined from the modulus of said complex expression, in which case it is representative of the amplitude of said light wave to which the detector is exposed. The characteristic quantity can be determined from the argument of said complex expression, in which case it is representative of the phase of said light wave to which the matrix photodetector is exposed.
    [0008] The identification can be developed by comparing the evolution of said characteristic quantity with typical profiles determined during a learning phase. The position of each particle, in a plane parallel to the plane of the matrix photodetector, can be determined using the image acquired by the photodetector or by means of the complex expression of the light wave to which is exposed the photodetector.
    [0009] The light source is preferably a spatially coherent source, and for example a light-emitting diode, in which case a spatial filter is preferably disposed between the light source and the sample. The light source may be temporally coherent, for example being a laser diode.
    [0010] The matrix photodetector comprises a matrix of pixels capable of collecting the wave to which the photodetector is exposed. The distance between the pixels and the sample may vary between 50 μm and 2 cm, and preferably between 100 μm and 5 mm. Preferably, the sample is not disposed in direct contact with the pixels of the photodetector. Preferably, no magnification optics are disposed between the sample and the matrix photodetector. The sample may in particular comprise blood cells. In this case, the particles can be identified among cell lines of white blood cells, red blood cells or platelets.
    [0011] Another object of the invention is a device for identifying a particle, said particle being contained in a sample, the device comprising: a light source arranged to produce an incident light wave, along an axis of propagation, in the direction of said sample, a support, for holding the sample between said light source and a matrix photodetector, the matrix photodetector, arranged to acquire an image of the sample, the matrix photodetector being adapted to be exposed to a light wave, resulting from the interference between said incident light wave and a diffraction wave formed by said particle, characterized in that the device comprises a processor, of electronic or microprocessor type, configured to carry out the following operations: - determination of a position of said particle in a plane parallel to the plane of the matrix photodetector, - app application of a digital reconstruction algorithm to said acquired image, so as to estimate at least one characteristic magnitude of said lightwave to which the matrix photodetector is exposed at a plurality of reconstruction distances thereof; the evolution of said characteristic quantity as a function of said reconstruction distance, along an axis parallel to said axis of propagation and passing through said position, - identification of the particle as a function of said evolution. Preferably, the device has no magnification optics between the matrix photodetector and the analyzed sample. The processor may comprise or be connected to a programmable memory, comprising a sequence of instructions allowing the implementation of the previously described steps. It can in particular be able to: determine, at each reconstruction distance, the complex expression of the optical radiation to which the detector is exposed, - estimate said characteristic quantity, at each reconstruction distance, by determining the module or the argument of said complex amplitude. FIGURES FIG. 1 represents the device according to one embodiment of the invention. FIG. 2A represents an image acquired by the matrix photodetector.
    [0012] FIG. 2B represents the profile of a characteristic quantity, called complementary amplitude, of the light wave to which the photodetector is exposed, as a function of the distance with respect to the photodetector, according to a first example, for different types of particles. FIG. 3A shows the profile of a characteristic quantity, called complementary amplitude, of the light wave to which the photodetector is exposed, as a function of the distance with respect to the photodetector, for different white blood cells, according to this first example. FIG. 3B represents the profile of a characteristic quantity, called complementary amplitude, of the light wave to which the photodetector is exposed, as a function of the distance with respect to the photodetector, for different red blood cells, according to this first example. FIG. 4A shows a region of interest of the image acquired by the photodetector, centered on a platelet aggregate, according to this first example.
    [0013] FIG. 4B represents the profile of a characteristic quantity, called complementary amplitude, of the light wave to which the photodetector is exposed, for various plates forming part of the aggregate represented in FIG. 4A. FIG. 5A represents the profile of a characteristic quantity, called complementary amplitude, of the light wave to which the photodetector is exposed, as a function of the distance with respect to the photodetector, for different types of particles, according to a second example. FIG. 5B represents the profile of the phase of the light wave to which the photodetector is exposed, as a function of the distance z with respect to the photodetector, for different types of particles, according to a second example.
    [0014] FIG. 6A shows the profile of a characteristic quantity, called complementary amplitude, of the light wave to which the photodetector is exposed, as a function of the distance with respect to the photodetector, for different types of particles, according to a third example. FIG. 6B shows the profile of the phase of the light wave to which the photodetector is exposed, as a function of the distance from the photodetector, for different types of particles, according to a third example. FIGS. 7A, 7B and 7C respectively represent the profile of a composite quantity characteristic of the light wave to which the photodetector is exposed, as a function of distance, according to the first, second and third examples.
    [0015] DESCRIPTION OF PARTICULAR EMBODIMENTS FIG. 1 represents an exemplary device that is the subject of the invention. A light source 11 is able to produce a light wave 12, referred to as an incident light wave, in the direction of a sample 14, along an axis of propagation Z. The sample 14 comprises a medium 10, for example a biological fluid, comprising particles 1, 2, 3, 4, 5, 9, which are to be identified from among predetermined particle types. A particle can be a cell. In particular, when the medium is blood, or a solution comprising blood, a particle may be a red blood cell, a white blood cell or a wafer.
    [0016] A particle may also be an organic or inorganic microbead, for example a metal microbead, a polymer or glass microbead, this type of microbead being commonly used in the production of biological protocols. A particle may also be a droplet, for example a lipid droplet, immersed in the medium 10. In general, a particle has a size advantageously less than 1 mm, or even less than 500 μm, and preferably a size between 0.5 μm and 500 μm. Thus, the term "particle" refers to both endogenous particles, initially present in the examined sample, and exogenous particles added to that sample prior to analysis. The medium is most frequently a liquid medium, and especially a body fluid, but it can also act agar, or air, or the dry residue of a liquid. The method which is the subject of the invention makes it possible to identify each particle observed. By identification is meant the classification of the particle into a predetermined class of particles. The distance 4 between the light source and the sample is preferably greater than 1 cm. It is preferably between 2 and 30 cm. Preferably, the light source, seen by the sample, is considered as point. This means that its diameter (or diagonal) is preferably less than one-tenth, better one-hundredth of the distance between the sample and the light source. Thus, the light arrives at the sample in the form of plane waves, or can be considered as such. The light source 11 may be punctual, or be associated with a diaphragm, or spatial filter, not shown in Figure 1, so as to appear punctual. The opening of the diaphragm is typically between 5 μm and 1 mm, preferably between 50 μm and 500 μm.
    [0017] The diaphragm may be replaced by an optical fiber having a first end facing a light source and a second end facing the sample. In this case, said second end can be likened to a point light source 11. The sample 14 is delimited by an enclosure having a bottom 15 and a cover 13. The side walls of the enclosure are not shown. In the example, the chamber is a fluid chamber Neubauer C-chip. The distance between the bottom 15 and the cover 13 is 100 μm. In general, the thickness of the enclosure, along the axis of propagation Z, is less than a few cm, for example less than 1 cm, or even less than 1 mm, for example between 50 μm and 500 μm. .
    [0018] The light source 11 may be temporally coherent but this is not necessary.
    [0019] In this first example, the light source is a laser diode emitting at the wavelength of 405 nm. It is located at a distance of 15 cm from the sample. The sample 14 is disposed between the light source 11 and a matrix photodetector 16. The latter preferably extends parallel to, or substantially parallel to, the bottom 15 of the enclosure delimiting the sample. The term substantially parallel means that the two elements may not be strictly parallel, an angular tolerance of a few degrees, less than 10 ° being allowed. Preferably, the light source is of small spectral width, for example less than 100 nm, even 20 nm and even more preferably less than 5 nm. The term spectral width refers to the half-height width of the emission peak of the light source. The photodetector 16 may be a matrix photodetector comprising a matrix of pixels, of the CCD type or a CMOS. CMOS are the preferred photodetectors because the size of the pixels is smaller, which makes it possible to acquire images whose spatial resolution is more favorable.
    [0020] In this example, the detector is a 12-bit APTINA sensor, reference MT9P031. This is a CMOS RGB sensor, whose inter-pixel pitch is 2.2 μm. The effective area of the photodetector is 5.7 x 4.3 mm 2. The photodetector extends along a detection plane P, preferably perpendicular to the propagation axis Z of the incident light wave 12.
    [0021] Preferably, the photodetector comprises a matrix of pixels, over which a transparent protective window is disposed. The distance between the pixel matrix and the protection window is generally between a few tens of one to 150 or 200 μm. Photodetectors whose inter pixel pitch is less than 3 μm are preferred in order to improve the spatial resolution of the image. The distance d between the particles 1,2, ... 9 and the pixel matrix of the photodetector 16 is, in this example, equal to 1.5 mm. But it can fluctuate depending on the thickness of the fluidic chamber used. In general, and irrespective of the embodiment, the distance d between a particle and the pixels of the photodetector is preferably between 50 μm and 2 cm, preferably between 100 μm and 2 mm.
    [0022] The absence of magnification optics between the matrix photodetector 16 and the sample 14 is noted. This does not prevent the possible presence of focusing microlenses at each pixel of the photodetector 16. In this first example, Sample is plasma enriched in white blood cells, obtained according to a usual protocol, after sedimentation of red blood cells in the presence of Dextran (Sigma Aldrich reference D4876) 6% in Alsever solution, then recovery of rich plasma white blood cells and platelets. The plasma obtained is then diluted in a PBS buffer at physiological pH (acronym for Phosphate Buffer Saline - Saline Phosphate Buffer). The depletion of red blood cells is not complete and the enriched plasma obtained has residual red blood cells. Particles can be classified into several types of particles, including red blood cells, white blood cells or platelets. The particles do not undergo any prior marking. FIG. 2A shows an image obtained by the photodetector 16. This image represents a global diffraction figure, in which elemental diffraction figures can be distinguished, each elementary diffraction figure being respectively associated with the particles. Each elemental diffraction pattern comprises a disk-shaped central area around which concentric, alternately dark and clear rings extend. Such an elementary figure enables the selection of a particle to be identified, as well as the determination of the coordinates (x, y) of said particle in the detection plane P. These coordinates are for example the center of the corresponding elementary diffraction pattern. to said particle. Each elemental diffraction pattern is formed by the interference between the incident light wave 12 produced by the source 11, upstream of the sample, and a wave resulting from the diffraction of the incident wave by a particle. Thus, the photodetector 16 is exposed to a light wave 22 formed by the superposition of: - the light wave 12 emitted by the source 11, upstream of the sample 14, - the light wave diffracted by each of the particles or other diffracting elements present in the sample 14.
    [0023] A processor 20, for example a microprocessor, receives the images from the matrix photodetector 16, and performs a reconstruction of characteristic quantities of the light wave 30 to which the photodetector is exposed, along the axis of propagation Z. The reconstruction is carried out in particular between the photodetector and the sample observed. The processor 20 may be able to execute a sequence of instructions stored in a memory, for the implementation of the steps of the identification method. The processor may be a microprocessor, or other electronic calculator capable of processing the images provided by the matrix photodetector, to perform one or more steps described in this description. The image I shown in FIG. 2A represents the spatial distribution of the intensity 1 (x, y) of the light wave 22, where x and y designate the coordinates in the plane of the photodetector.
    [0024] According to the well-known principles of digital holographic reconstruction, described in Ryle et al., "Digital in-line holography of biological specimens", Proc. Of SPIE Vol.6311 (2006), by carrying out a product of convolution between the intensity 1 (x, y) measured by the photodetector, and a propagation operator h (x, y, z), it is possible to reconstruct a complex expression U (x, y, z) of the light wave 22 at any coordinate point (x, y, z) of the space, and in particular in a plane located at a distance 1z1 from the photodetector. The propagation operator h (x, y, z) has the function of describing the propagation of light between the photodetector 16 and a coordinate point (x, y, z). It is then possible to determine the amplitude u (x, y, z) and the phase cf: 1 (x, y, z) of this light wave at this distance lzl, called the reconstruction distance, with: 20 - u ( x, y, z) = abs [U (x, y, z)], - (p (x, y, z) = arg [U (x, y, z)] The operators abs and arg respectively denote the module The application of the propagation operator makes it possible in particular to estimate the complex expression at a distance 1 z 1 from the photodetector, upstream of the latter, the complex value of the light wave 22 being reconstructed. before the latter reaches the detector.This is called back-propagation By assigning the coordinate z = 0 to the detection plane P, this backpropagation is implemented by applying a propagation operator h (x, y The terms upstream and downstream are to be understood according to the direction of propagation of the incident wave 12.
    [0025] If I (x, y) = I (x, y, z = 0) corresponds to the intensity of the signal measured by the photodetector, a relation between the measured intensity 1 (x, y) and the complex expression of the light wave U (x, y), at the level of the detection plane P is given by: / (x, y) = IU (x, y) I 2. The complex expression of the light wave (22) ), at a coordinate (x, y, z) is given by 5 U (x, y, z) =, 1 / (x, y) * h (x, y, z), the symbol * denoting a product of convolution. with: z <0 in the half-space delimited by the detection plane P, comprising the sample 14 z> 0 in the half-space delimited by the detection plane P and not comprising the sample 14. In the half space defined by the detection plane P and comprising the sample 14, the complex expression of the light wave can also be written: U (x, y, z) =, 1 / (x, y) * h (x, y, -1z1) Preferably a mathematical preprocessing is pre-applied to the measured intensity 1 (x, y) before the holographic reconstruction. This improves the quality of results, including reducing artifacts when applying the propagation operator. Thus, we determine an intensity f (x, y), called normalized intensity, such that f (x, y) = (/ (x, y) - average (I)) / average (I) with 1 (x, y) = intensity measured by the photodetector at the coordinate (x, y), Average (I) = average of the intensity measured in a region of interest of the image I, including said coordinate (x, y). This region of interest may correspond to the entire image formed by the photodetector.
    [0026] This pre-treatment is similar to a normalization of the intensity measured by the intensity of the incident light wave (12), the latter being estimated by the Average operator (I). Then the complex expression of the wave (22) is determined from the normalized intensity f (x, y) according to the equation U (x, y, z) = / ((x, y) * h ( x, y, z) as previously explained.
    [0027] Numerical reconstruction can notably be based on the Fresnel diffraction model. In this example, the propagation operator is the Fresnel-Helmholtz function, such that: h (x, y, z) = 1 eJ27exp un-xAz). where X denotes the wavelength. 2 (-Xi) + ("i2)) dXidYi j2rc ff f- (- iuc yj expun- 5 Thus, U (x, y, z) = zej Az where x 'and y' denote the coordinates in the plane of the photodetector x and y denote the coordinates in the reconstruction plane, the latter being situated at a distance Izi of the photodetector, z is the coordinate of the image reconstructed along the propagation axis Z of the incident light wave (12) From the values of the complex expression U (x, y, z), it is possible to extract characteristic quantities of the light wave 22 resulting from the diffraction, by the particles (1,2.9). of the incident light wave 12 emitted by the source 11. As previously mentioned, the amplitude u (x, y, z) or the phase (p (x, y, z) can be evaluated, but it is It is also possible to evaluate any function of amplitude or phase, for example, a characteristic quantity, called complementary amplitude, ft (x, y, z) such that: ft (x, y, z) = abs (1 - U (x, y, z)) From each reconstructed complex expression U (x, y, z), it is possible to constitute: an image uz of the amplitude of the wave 22, in a plane parallel to the plane of the detector, at a distance I z I of the latter, with uz (x, y) = abs [U (x, y, z)], an image (pz of the phase of the wave 22, in a plane parallel to the plane of the detector, at a distance I z I of the latter, with (1) z (x, y) = arg [U (x, y, z)], an image ri; of the complementary amplitude, as previously defined, of the wave 22, in a plane parallel to the plane of the detector, at a distance I z I of the latter, with ii; (x, y, z) = abs [1 - U (x, y, z)]. In this first example, an image Ti is reconstructed; the amplitude complementary to a plurality of coordinates zi ... zm, along the axis of propagation Z, M being here equal to 21, - from each image1-77 ', with ISnSM, the value ft is extracted (xn, yn, zm), (xn, yn) representing the coordinates of the particle n in a plane parallel to the plane of the photodetector 16, - different values of ft (xn, yn, z) are obtained, with zn, < z <zn,. + 1 by interpolation between two quantities fi (xn, yn, zm) and ft previously determined. The coordinates (xn, yn), in a plane parallel to the plane of the photodetector 16, of each particle n examined, are determined either by means of the acquired image 1 (x, y) or from an image ftz at a given reconstruction height z. FIG. 2B represents, for different types of particles, the evolution of the complementary amplitude ft (xn, yn, z), as previously defined, as a function of the reconstruction distance I z I, for 9 different particles: particles 1 to 4: white blood cells designated by the acronym WBC, particles 5 and 6: red blood cells, designated by the acronym RBC, particles 7 to 9: platelets, designated by the letter PLT. The reconstruction distance I z I varies between zmjn = 1000 and zmax = 1500 μm. Parallel to these operations, each particle (1, ..., 9) was observed under a microscope, the observation under the microscope serving as a reference measurement, allowing a certain identification. It is observed that for the sample studied in this example: for the particles 1 to 4, which are WBC white corpuscles, the curve ft (z) representing the evolution of the complementary amplitude as a function of the present reconstruction distance. a minimum lower than a threshold of amplitude j ".. i ..- threshold, followed by a rise towards the baseline BL, this rise having marked oscillations, for the particles 5 and 6, corresponding to red corpuscles In RBC, the curve ft (z) has a minimum between the baseline BL and the threshold of magnitude fi -threshold, followed by a monotonous rise towards the base line BL: for the particles 7 to 9, corresponding to PLT chips, the curve ft (z) follows the baseline BL and remains confined between two values BL ± s.
    [0028] Thus, for each particle n detected, whose position along a plane parallel to the plane of the detector is (xn, yn), it is possible to establish a profile ft (xn, yn, z) representing the evolution of the amplitude complementary to a plurality of reconstruction heights z, and use this profile to perform an identification of the particle between a red blood cell, a white blood cell 5 and a wafer. This profile can in particular be compared to a library of profiles made, during a learning phase, on known particles. In other words, the profile ft (z) representing the evolution of the complementary amplitude, along the axis of propagation Z (z coordinate axis), constitutes a signature of the type of the observed particle.
    [0029] Contrary to the prior art, a complex image of a particle is not formed by carrying out a holographic reconstruction at a predetermined distance from the sample, but a characteristic of the wave 22, resulting from the diffraction of the sample, is reconstructed. a particle with the incident wave 12, along the propagation direction of the incident wave, at a plurality of distances from the photodetector. The information obtained is richer and allows a clear classification between different types of particles. FIGS. 3A and 3B show complementary amplitude profiles ft (z), of the detector wave 22, respectively obtained for 50 WBC white cells and 240 RBC red cells. Sufficient repeatability of the profiles is observed to allow a robust classification of the particles on the basis of this profile. These profiles were obtained under experimental conditions similar to those of the preceding example. The sample used to make the measurements shown in Figure 3A is an enriched plasma similar to the sample described in connection with Figures 2A and 2B.
    [0030] The sample used to carry out the measurements shown in FIG. 3B comprises whole blood diluted in a previously mentioned phosphate phosphate buffer PBS, dilution factor 1/400. FIG. 4A represents complementary amplitude profiles ft (z), along the Z axis, obtained for 4 platelets 101, 102, 103, 104, on a sample of enriched plasma type as previously described.
    [0031] Microscopic observation showed that platelets 101, 102, 103 and 104 were aggregated.
    [0032] FIG. 4B represents a region of interest of the image I acquired by the photodetector 16. It makes it possible to identify the coordinates (xioi, Y1o1), (x102, Y102), (x103, Y103), (x104, Y1o4) of each wafer of the aggregate. These profiles were obtained under experimental conditions similar to those of the first example. It is observed that the profile ft (z) is similar whether the platelets are aggregated or not, and remains confined around a baseline BL, in a gap BL ± s. Thus, according to the identification method that is the subject of the invention, the platelets are correctly identified whether they are aggregated or not.
    [0033] In a second example, the light source 11 is a white light-emitting diode coupled to an Omega optical 485-DF-22 filter, centered on the wavelength λ = 485 nm and with a width at half-height equal to 22 nm. The distance 4 between the light source and the detector is 8 cm. The sample is an enriched plasma as previously described. According to this example, a reconstruction of the complex expression U (x, y, z) of the wave 22 at a plurality of distances z of the detector was performed at coordinates (x, y). different particles, the complementary amplitude and the phase of the radiation. Then ft (z) and (p (z) profiles of the complementary amplitude and the phase as a function of z were established, as in the preceding examples, the nature of the particles observed was confirmed by an observation at microscope.
    [0034] Figures 5A and 5B show the complementary amplitude ft (x, y, z) and the phase (p (x, y, z) respectively as a function of the distance z for different particles. for the WBC white cell particles, the curve ft (z) representing the evolution of the complementary amplitude as a function of the reconstruction distance has a marked minimum below a threshold of amplitude j ". ..- threshold, followed by a rise towards the base line BL, this rise having marked oscillations, for the particles corresponding to RBC RBCs, the curve ft (z) has a minimum between the baseline BL and the amplitude threshold is then threshoid, then the curve follows a monotonous rise towards baseline BL; for particles corresponding to PLT platelets, the curve ft (z) ) follows the baseline BL and remains confined between two BL ± s values. for each detected particle n whose position in a plane parallel to the plane of the detector is (xn, yn), it is possible to establish a profile ft (xn, yn, z) representing the evolution of the complementary amplitude ft, as previously defined, of the wave 22 to which the detector is exposed, at a plurality of reconstruction heights z, and to use this profile to perform a classification of the particle between an RBC red cell, a white blood cell WBC and a PLT wafer. Classification is therefore possible with a light source different from a laser source.
    [0035] In FIG. 5B, it is observed that: for the particles corresponding to WBC white corpuscles, the curve (p (z) representing the evolution of the cf: 1 phase as a function of the reconstruction distance z has a maximum greater than a first phase threshold (Pthresholdl, then a minimum less than a second phase threshold (pthreshoid2, followed by a rise towards the baseline BL, for the particles corresponding to RBC RBCs, the curve (p (z ) has a maximum greater than said first phase threshold (pthreshoidl then a minimum greater than said second phase threshold (r), hreshold2, then * the curve follows a monotonic rise towards the base line BL; for the particles corresponding to platelets PLT, the curve (p (z) representing the evolution of the cf: 1 phase as a function of the reconstruction distance remains confined between the two values (pthreshoidl and (pthreshoid2.) The measured values remain between the first and second values. Phase I thresholds.
    [0036] Thus, for each detected particle n whose position in a plane parallel to the plane of the detector is (xn, yn), it is possible to establish a profile (p (xn, y, z) representing the evolution of the phase of the radiation to which the detector is exposed, at a plurality of reconstruction heights z, and use this profile to perform a classification of the particle between a red blood cell, a white blood cell and a wafer.
    [0037] According to a third example, the light source 11 is a white light-emitting diode coupled to an Omega optical 610-DF-20 filter, centered on the wavelength λ = 610 nm and half-width 20 nm, placed at a distance 4, equal to 8 cm, from the sample. The procedure and the sample are similar to the previous example. Figures 6A and 6B show the complementary amplitude ft (x, y, z) and the phase (p (x, y, z) respectively as a function of the distance z for different particles. for the particles corresponding to WBC white cells, the curve ft (z) representing the evolution of the amplitude u as a function of the reconstruction distance z has a marked minimum less than a complementary amplitude threshold j ". it is followed by a rise towards the baseline BL, this rise having marked oscillations, for the particles corresponding to RBC RBCs, the curve ft (z) has a minimum between the baseline. BL and the threshold of amplitude i% .., .. threshoid, then the curve follows a monotonous rise towards the base line BL; 15 - for the particles corresponding to platelets PLT, the curve ft (z) follows baseline BL and remains confined between two BL ± s values so for each particle n detected, whose position in a plane parallel to the plane of the detector is (xn, yn), it is possible to establish a profile ft (xn, y ,, z) representing the evolution of the complementary amplitude, such as As previously defined, radiation to which the detector is exposed, at a plurality of reconstruction heights z, and use this pattern to perform a classification of the particle between an RBC RBC, a WBC white blood cell and a PLT wafer. In FIG. 6B, it can be observed that: for the particles corresponding to WBC white corpuscles, the curve (p (z) representing the evolution of the cf: 1 phase as a function of the reconstruction distance z has a maximum greater than a first phase threshold (Pthresholdl, then a minimum lower than a second phase threshold (pthreshoid2, followed by a rise towards baseline BL, for particles corresponding to RBC RBCs, the curve (p (z ) has a maximum greater than said first phase threshold (pthreshoidl then a minimum higher than said second phase threshold (Pthreshold2, then the curve follows a monotonous rise towards baseline BL, for particles corresponding to PLT platelets, the curve (p (z) representing the evolution of the phase (f) as a function of the reconstruction distance z remains confined between two values (Pthresholdl r (Pthreshold2. The measured values remain between said first and second The two previous examples show that a complementary amplitude profile ft (z) or in phase (p (z) makes it possible to characterize the particles.
    [0038] It is also possible to constitute a composite optical parameter, denoted k, combining the complementary amplitude and the phase, in the form of a ratio, for example k (z) = (p (z) u (z). FIGS. 7A, 7B and 7C show the evolution of said composite optical parameter along the propagation axis Z, by implementing the respective configurations of the first example (laser source at 405 nm), of the second example (light source of FIG. white LED type combined with a filter centered on X = 485nm) and the third example (white LED light source combined with a filter centered on X = 610nm) In each configuration, the sample observed is an enriched plasma such as As previously described, on each curve, the analyzed particles are three white blood cells (WBC) and one red blood cell (RBC) .It is observed that whatever the source, the fluctuations of the profile k (z) are more important for the white blood cells only for the globules In particular, it is possible to determine a first composite threshold kthresholdi and a second composite threshold kthreshoé, so that when the profile k (z) remains lower than the first composite threshold kthresholdi and greater than the second composite threshold kthreshoé, the analyzed particle is a red blood cell. When the profile crosses one of these thresholds, the examined particle is identified as a white blood cell. The described method is not limited to blood and can be applied to other body fluids, for example urine, cerebrospinal fluid, bone marrow, etc. Moreover, method 3034196 can be applied to non-bodily fluids, in particular for the analysis of pollutants or toxins in water or other aqueous solution. The method also applies to the detection and identification of particles placed in a non-liquid medium, for example an agar or the dry residue of a body fluid, for example a blood smear resulting in extensive deposition of blood. dry on a blade. In the latter case, the particles are isolated from each other by dry residues or air. Moreover, as previously indicated, the particles may be endogenous (for example blood particles) or exogenous (microbeads, droplets).
    [0039] The examples described above disclose simple identification criteria, based on the evolution of the profile of a characteristic quantity as a function of the reconstruction distance, and comparisons using pre-established thresholds. The validity of the criteria is related to the medium in which the particles are placed, as well as to the sample preparation protocol. Other criteria may apply to particles having undergone a different preparation protocol.
    [0040] Thus, for a given type of sample, the identification criteria can be defined during a learning phase, carried out on standard samples, comprising known particles. In addition, other classification methods, more complex and more robust, can be implemented, without departing from the scope of the invention.
    权利要求:
    Claims (13)
    [0001]
    REVENDICATIONS1. A method for identifying a particle (1, 2, ... 9, 101 ... 104) contained in a sample (14), the method comprising the steps of: illuminating said sample with a light source ( 11), the light source producing an incident light wave (12) propagating towards the sample (14) along an axis of propagation (Z), acquisition, with the aid of a matrix photodetector (16), of an image of the sample, the sample being disposed between said light source and the matrix photodetector, such that the matrix photodetector is exposed to a light wave (22) comprising interference between the incident light wave (12) and a diffraction wave produced by each particle, the method being characterized in that it also comprises the steps of: determining a position of said particle in a plane parallel (x, y) to a plane (P) according to which extends the matrix photodetector (16), applying a digital reconstruction algorithm to said acquired image, so as to estimate at least one characteristic magnitude (u, ft, cp, k) of said light wave (22) to which the matrix photodetector (16) is exposed, at a plurality of distances (I z I) of reconstruction of the latter, determination of the evolution (u (z), il (z), (p (z), k (z)) of said characteristic quantity as a function of said distance, along an axis parallel to said axis of propagation (Z) and passing through said position (x, y), - identification of the particle according to said evolution.
    [0002]
    2. Method according to claim 1, wherein said characteristic quantity is obtained by estimating, at each reconstruction distance, a complex expression U (x, y, z) of the light wave (22) to which the photodetector is exposed. matrix.
    [0003]
    The method of claim 2, wherein the characteristic quantity is determined from the module or argument of said complex expression U (x, y, z). 3034196 21
    [0004]
    4. The method according to claim any one of the preceding claims, wherein the identification is made by comparing the evolution of said characteristic quantity with typical profiles determined during a learning phase.
    [0005]
    5. Method according to any one of claims 1 to 4, wherein the position of each particle, in a plane parallel to the plane of the matrix photodetector, is determined using the image acquired by the photodetector or the using the complex expression U (x, y, z) of the light wave (22) to which the matrix photodetector is exposed.
    [0006]
    The method of any of the preceding claims, wherein the light source is a spatially coherent source.
    [0007]
    The method of any of the preceding claims, wherein the light source is a light emitting diode or a laser diode.
    [0008]
    The method of any of the preceding claims, wherein no magnification optics are disposed between the sample and the matrix photodetector. 20
    [0009]
    The method of any one of the preceding claims, wherein the sample comprises blood cells.
    [0010]
    10. A method according to any one of the preceding claims, wherein the particles are identified from cell lines of white blood cells, red blood cells or platelets.
    [0011]
    11. Device for identifying a particle, said particle being contained in a sample (14), the device comprising: a light source (11) arranged to produce an incident light wave (12), 30 along an axis of propagation (Z ), in the direction of said sample (14), a support, for holding the sample (14) between said light source (11) and a matrix photodetector (16), the matrix photodetector (16) being arranged for acquiring an image of the sample, by being exposed to a light wave (22), resulting from the interference between said incident light wave (12) and a diffraction wave formed by said particle, the device being characterized in that it comprises a processor (20), and in particular a microprocessor configured to implement the following steps: determining a position of said particle in a plane parallel (x, y) to a plane (P) according to which the photodetector matrix (16), applying a digital reconstruction algorithm to said acquired image, so as to estimate at least one characteristic magnitude (u, ft, cp, k) of said light wave (22) to which the photodetector is exposed matrix (16), at a plurality of distances (I z I) of reconstruction of the latter, determination of the evolution (u (z), ft (z), (p (z), k (z)) of said characteristic quantity according to said reconstruction distance, along an axis parallel to said axis of propagation and passing through said position (x, y), 15 - identification of the particle as a function of said evolution.
    [0012]
    12. Device according to claim 11, wherein the device has no magnification optics between the matrix photodetector and the sample analyzed.
    [0013]
    13. Device according to any one of claims 11 or 12, wherein the processor is able: to determine, at each reconstruction distance, the complex expression U (x, y, z) of the optical radiation to which is exposed the detector, estimating said characteristic quantity, at each reconstruction distance, by determining the module or the argument of said complex amplitude U (x, y, z). 25
    类似技术:
    公开号 | 公开日 | 专利标题
    FR3034196A1|2016-09-30|PARTICLE ANALYSIS METHOD
    EP3274694B1|2019-12-18|Method for determining the state of a cell
    EP3234550B1|2022-01-05|Method for identifying biological particles using stacks of defocused holographic images
    EP3218769B1|2019-03-20|Analysis method including the holographic determination of a position of a biological particle
    WO2017162985A1|2017-09-28|Method for observing a sample, by calculation of a complex image
    EP3208599B1|2022-03-09|Method for using a submersible probe, as a function of a particle concentration
    FR3049348A1|2017-09-29|METHOD OF CHARACTERIZATION OF A PARTICLE IN A SAMPLE
    EP3199941A1|2017-08-02|Method for observing a sample by lens-free imaging
    EP3559631B1|2021-01-06|Method for counting particles in a sample by means of lensless imaging
    FR3027107B1|2019-09-13|METHOD AND DEVICE FOR OPTICALLY DETECTING NANOPARTICLES IN A FLUID SAMPLE
    FR3056749A1|2018-03-30|METHOD FOR NUMBERING LEUKOCYTES IN A SAMPLE
    EP2872871B1|2021-08-18|Method and system for reconstructing optical properties of diffracting objects bathed in a liquid medium
    EP2024771B1|2010-04-07|Interferometric confocal microscope
    EP3270232A1|2018-01-17|Device for observing a sample
    FR3034524A1|2016-10-07|METHOD FOR DETERMINING THE AGGLUTINATION LEVEL OF PARTICLES IN A SAMPLE
    EP3637194B1|2021-11-03|Method for determining parameters of a particle
    EP2877836A1|2015-06-03|Optical methods for observing samples and for detecting or metering chemical or biological species
    FR3082943A1|2019-12-27|METHOD FOR COUNTING SMALL PARTICLES IN A SAMPLE
    FR3073047A1|2019-05-03|OPTICAL METHOD FOR ESTIMATING A REPRESENTATIVE VOLUME OF PARTICLES PRESENT IN A SAMPLE
    FR3081552A1|2019-11-29|DEVICE AND METHOD FOR OBSERVING A FLUORESCENT SAMPLE BY DEFOCUSED IMAGING
    FR3018603A1|2015-09-18|DEVICE FOR ANALYZING AND IMAGING A SURFACE BY DEFLECTOMETRY AND CORRESPONDING METHOD
    同族专利:
    公开号 | 公开日
    US20180080760A1|2018-03-22|
    CN107532989B|2021-08-17|
    JP6727229B2|2020-07-22|
    FR3034196B1|2019-05-31|
    KR20180011762A|2018-02-02|
    EP3274689B1|2022-02-16|
    JP2018514759A|2018-06-07|
    CN107532989A|2018-01-02|
    US10379027B2|2019-08-13|
    EP3274689A1|2018-01-31|
    WO2016151248A1|2016-09-29|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US20090290156A1|2008-05-21|2009-11-26|The Board Of Trustee Of The University Of Illinois|Spatial light interference microscopy and fourier transform light scattering for cell and tissue characterization|
    US20140327944A1|2011-12-02|2014-11-06|Csir|Hologram processing method and system|WO2018060589A1|2016-09-28|2018-04-05|Commissariat à l'énergie atomique et aux énergies alternatives|Method for counting white blood cells in a sample|US20080208511A1|2005-03-07|2008-08-28|Michael Trainer|Methods and apparatus for determining characteristics of particles|
    ITRM20050120A1|2005-03-16|2006-09-17|Consiglio Nazionale Ricerche|HOLOGRAPHIC METHOD IN NUMERICAL RECONSTRUCTION TO OBTAIN A PICTURE OF A THREE-DIMENSIONAL OBJECT IN WHICH THERE ARE ALSO POINTS OUTSIDE THE DEPTH OF FIELD, AND THE HOLOGRAPHIC APPARATUS USING THIS METHOD.|
    GB0701201D0|2007-01-22|2007-02-28|Cancer Rec Tech Ltd|Cell mapping and tracking|
    US8791985B2|2007-10-30|2014-07-29|New York University|Tracking and characterizing particles with holographic video microscopy|
    JP5639654B2|2009-10-20|2014-12-10|ザ リージェンツ オブ ザ ユニバーシティ オブ カリフォルニア|On-chip incoherent lens-free holography and microscopy|
    WO2011149525A1|2010-05-25|2011-12-01|Arryx, Inc.|Holographic fluctuation microscopy apparatus and method for determining mobility of particle and/or cell dispersions|
    US9569664B2|2010-10-26|2017-02-14|California Institute Of Technology|Methods for rapid distinction between debris and growing cells|
    CN103238120B|2010-11-12|2016-08-10|布鲁塞尔大学|For characterizing the optical means of transparent grain|
    US8842901B2|2010-12-14|2014-09-23|The Regents Of The University Of California|Compact automated semen analysis platform using lens-free on-chip microscopy|
    EP2661603A4|2011-01-06|2014-07-23|Univ California|Lens-free tomographic imaging devices and methods|
    EP2676173A4|2011-02-16|2017-11-08|Phase Holographic Imaging Phi AB|Determination of physical parameters associated with erythrocytes|
    CA2842377C|2011-07-19|2019-08-27|Ovizio Imaging Systems N.V.|A method and system for detecting and/or classifying cancerous cells in a cell sample|
    CN102660457A|2012-04-17|2012-09-12|南昌航空大学|Device and method for analyzing and counting blood cells by lensless holographic diffraction imaging|
    US20130310270A1|2012-05-21|2013-11-21|Vib|Holographic Imaging for Analyzing Molecules|
    FR2993372B1|2012-07-13|2015-04-10|Commissariat Energie Atomique|METHOD AND SYSTEM FOR RECONSTRUCTING OPTICAL PROPERTIES OF DIFFRACTING OBJECTS BATHING IN A LIQUID ENVIRONMENT|
    WO2014012031A1|2012-07-13|2014-01-16|The Regents Of The University Of California|High throughput lens-free three-dimensional tracking of sperm|
    FR3002634B1|2013-02-28|2015-04-10|Commissariat Energie Atomique|METHOD OF OBSERVING AT LEAST ONE OBJECT, SUCH AS A BIOLOGICAL ENTITY, AND ASSOCIATED IMAGING SYSTEM|
    US10012589B2|2013-08-16|2018-07-03|The General Hospital Corporation|Portable diffraction-based imaging and diagnostic systems and methods|
    FR3020682B1|2014-04-30|2016-05-27|Commissariat Energie Atomique|METHOD AND SYSTEM FOR DETECTING AT LEAST ONE PARTICLE IN A BODILY LIQUID, AND ASSOCIATED METHOD FOR DIAGNOSING MENINGITIS|
    FR3030749B1|2014-12-19|2020-01-03|Commissariat A L'energie Atomique Et Aux Energies Alternatives|METHOD OF IDENTIFYING BIOLOGICAL PARTICLES BY STACKS OF DEFOCALIZED HOLOGRAPHIC IMAGES|FR3049348A1|2016-03-23|2017-09-29|Commissariat Energie Atomique|METHOD OF CHARACTERIZATION OF A PARTICLE IN A SAMPLE|
    FR3049347B1|2016-03-23|2018-04-27|Commissariat A L'energie Atomique Et Aux Energies Alternatives|METHOD FOR OBSERVING A SAMPLE BY CALCULATING A COMPLEX IMAGE|
    DE102016215419A1|2016-08-17|2018-02-22|Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.|Measuring arrangement and method for directing and detecting particles|
    FR3060746B1|2016-12-21|2019-05-24|Commissariat A L'energie Atomique Et Aux Energies Alternatives|METHOD FOR NUMBERING PARTICLES IN AN IMAGING SAMPLE WITHOUT LENS|
    FR3063085A1|2017-02-17|2018-08-24|Commissariat A L'energie Atomique Et Aux Energies Alternatives|OPTICAL METHOD FOR MONITORING IN-VITRO AMPLIFICATION OF A NUCLEOTIDE SEQUENCE|
    FR3066503B1|2017-05-22|2021-05-07|Commissariat Energie Atomique|MICROORGANISMS ANALYSIS PROCESS|
    FR3071609B1|2017-09-27|2019-10-04|Commissariat A L'energie Atomique Et Aux Energies Alternatives|METHOD FOR DETECTING MICROORGANISMS IN A SAMPLE|
    FR3073047B1|2017-11-02|2021-01-29|Commissariat Energie Atomique|OPTICAL PROCESS FOR ESTIMATING A REPRESENTATIVE VOLUME OF PARTICLES PRESENT IN A SAMPLE|
    FR3076617B1|2018-01-08|2020-02-07|Horiba Abx Sas|HOLOGRAPHIC IMAGING SYSTEM AND HOLOGRAPHIC IMAGING ANALYSIS METHOD WITH DETECTION OF FAULTS IN THE OBSERVATION CHAMBER|
    FR3081997B1|2018-05-31|2021-04-16|Commissariat Energie Atomique|DEVICE AND METHOD FOR OBSERVING PARTICLES, IN PARTICULAR SUBMICRONIC PARTICLES|
    FR3082944A1|2018-06-20|2019-12-27|Commissariat A L'energie Atomique Et Aux Energies Alternatives|METHOD FOR OBSERVING A SAMPLE WITH LENS-FREE IMAGING, TAKING INTO ACCOUNT A SPATIAL DISPERSION IN THE SAMPLE|
    FR3082943A1|2018-06-20|2019-12-27|Commissariat A L'energie Atomique Et Aux Energies Alternatives|METHOD FOR COUNTING SMALL PARTICLES IN A SAMPLE|
    JP2020041928A|2018-09-11|2020-03-19|株式会社東芝|Self-check system|
    FR3086758B1|2018-09-28|2020-10-02|Commissariat Energie Atomique|METHOD AND DEVICE FOR OBSERVING A SAMPLE UNDER AMBIENT LIGHT|
    FR3087009B1|2018-10-09|2020-10-09|Commissariat Energie Atomique|PROCESS FOR DETERMINING PARAMETERS OF A PARTICLE|
    法律状态:
    2016-03-31| PLFP| Fee payment|Year of fee payment: 2 |
    2016-09-30| PLSC| Publication of the preliminary search report|Effective date: 20160930 |
    2017-03-31| PLFP| Fee payment|Year of fee payment: 3 |
    2018-03-29| PLFP| Fee payment|Year of fee payment: 4 |
    2020-03-31| PLFP| Fee payment|Year of fee payment: 6 |
    2021-03-30| PLFP| Fee payment|Year of fee payment: 7 |
    优先权:
    申请号 | 申请日 | 专利标题
    FR1552443|2015-03-24|
    FR1552443A|FR3034196B1|2015-03-24|2015-03-24|PARTICLE ANALYSIS METHOD|FR1552443A| FR3034196B1|2015-03-24|2015-03-24|PARTICLE ANALYSIS METHOD|
    KR1020177030554A| KR20180011762A|2015-03-24|2016-03-23|Particle analysis method|
    EP16717422.6A| EP3274689B1|2015-03-24|2016-03-23|Method and apparatsu for analysing particles|
    CN201680022598.1A| CN107532989B|2015-03-24|2016-03-23|Method for analysing particles|
    PCT/FR2016/050643| WO2016151248A1|2015-03-24|2016-03-23|Method for analysing particles|
    JP2017550232A| JP6727229B2|2015-03-24|2016-03-23|Particle analysis method|
    US15/560,763| US10379027B2|2015-03-24|2016-03-23|Method for identifying blood particles using a photodetector|
    [返回顶部]