Method and system for characterizing the agglutination of particles contained in a liquid

Description

[0001] The present invention relates to a method for characterizing a variation in the speed of particles or an agglomeration of particles according to claim 1 and a system for characterizing the agglutination of particles contained in a liquid according to claim 12.

[0002] The invention also relates to a system for characterizing the variation in the speed of particles or the agglomeration of particles contained in the liquid, such as blood particles.

[0003] The invention relates in particular to the field of imaging without a focusing lens of the light beam illuminating the fluidic chamber, in order to characterize a liquid, such as blood.

[0004] The invention applies in particular to the determination of a parameter relating to blood coagulation, in particular the measurement of coagulation time. It also applies to the determination of a parameter relating to the agglutination of particles in the blood, in particular the determination of the blood group by characterizing a cellular aggregation between the blood to be tested and an antibody.

[0005] Document EP 2 233 923 A1 discloses a method and a characterization system of the aforementioned type. The method described aims to characterize the coagulation or sedimentation dynamics of a fluid containing blood. The system for implementing this method comprises a fluidic chamber for receiving the liquid, a spatially coherent light source capable of emitting an illuminating light beam and a mirror for reflecting the light beam towards the chamber. The light beam extends in a longitudinal direction from the reflection mirror towards the fluidic chamber.

[0006] The documents Piederrière Y. et al "Evaluation of blood plasma coagulation dynamics by speckle analysis" and Tripathi M. et al "Assessing blood coagulation status with laser speckle rheology" describe optical methods for characterizing blood coagulation.

[0007] The document Piederrière Y. et al "Particle aggregation monitoring by speckle size measurement; application to blood platelets aggregation" describes a method for monitoring platelet aggregation.

[0008] The system also includes an image sensor, such as a CCD (Commonly Array) type matrix sensor. Charged-Coupled Device ) or CMOS (from English Complementary Metal Oxide Semiconductor ), arranged to enable the acquisition of a time series of images of an optical granularity pattern generated by the interaction between the particles contained in the chamber and the light beam. The characterization system also comprises a unit for processing said time series of images.

[0009] The fluidic chamber is arranged between the mirror and the image sensor in the longitudinal direction. The distance between the fluidic chamber and the image sensor in the longitudinal direction is a few centimeters or tens of centimeters. The light beam emitted by the spatially coherent light source has a surface area of ​​between 10 µm 2< and a few mm 2< along a plane perpendicular to the longitudinal direction and passing through the fluidic chamber.

[0010] Such a system and method make it possible to effectively characterize the dynamics of coagulation or sedimentation of blood contained in the liquid.

[0011] However, such a system is quite bulky. In addition, it allows the coagulation phenomenon to be observed only in a relatively small volume of the fluid chamber.

[0012] The aim of the invention is therefore to propose a method and a characterization system making it possible to observe a larger volume of liquid while limiting the size of the characterization system.

[0013] To this end, the invention relates to a characterization method according to the appended claim 1

[0014] According to other advantageous aspects of the invention, the characterization method comprises one or more of the following characteristics, taken in isolation or in all technically possible combinations: the light beam has a surface area of ​​between 5 mm 2< and 200 mm 2< , preferably equal to 25 mm 2< , along a plane perpendicular to the longitudinal direction, said plane being arranged in contact with the fluidic chamber; the light beam directly illuminates the fluidic chamber, and the image is formed directly by the radiation transmitted by the illuminated fluidic chamber, in the absence of a magnification optic arranged between the fluidic chamber and the photodetector; This does not exclude the possible use of focusing microlenses arranged at each pixel of the photodetector; the light source is a spatially and temporally coherent light source, such as a laser;the method further comprises a step of mixing the liquid with a reagent capable of causing an agglomeration of the particles, in which, during the calculation step, a second calculated indicator is an indicator for each acquired image, the second indicator being representative of the intensity of the pixels of the image in a predetermined region of the image and in which the method further comprises a step of determining a state of agglomeration of the particles from the second calculated indicator; the state of agglomeration is determined when the second indicator exceeds a predetermined threshold; the state of agglomeration is determined when the second indicator exceeds a reference indicator, obtained by an image taken in a reference area; the blood particles are red blood cells, the reagent comprises an antibody, and information relating to the blood group is further determined from the state of agglomeration;the liquid comprises an analyte, the method then comprising estimating the quantity of said analyte in the liquid, as a function of said second indicator; and the fluidic chamber comprises several fluid circulation channels, and in which, during the calculation step, an indicator is calculated for each of the channels.;

[0015] The invention also relates to a system according to the appended claim 13.

[0016] According to another advantageous aspect of the invention, the matrix photodetector comprises a plurality of pixels, each pixel having dimensions each less than or equal to 4 µm.

[0017] These characteristics and advantages of the invention will appear on reading the description which follows, given solely by way of non-limiting example, and made with reference to the appended drawings, in which: there figure 1is a very schematic representation of a characterization system according to the invention, comprising a fluidic chamber for receiving the liquid to be characterized, a light source suitable for illuminating the chamber in a longitudinal direction, a matrix photodetector for acquiring images of the radiation transmitted by the illuminated chamber and an information processing unit, the figure 2 is a very schematic representation of the characterization system. following another arrangement of the light source in relation to the matrix photodetector, the figure 3 is a schematic view of the fluid chamber in the longitudinal direction, as well as the arrangement of the matrix photodetector of the figure 1 in relation to the room, according to a first variant, the figure 4 is a view analogous to that of the figure 3 according to a second variant, the Figure 5 is a flowchart of a characterization process. figure 6is an image of an empty channel of the chamber of the figure 1 , acquired by the matrix photodetector, the figures 7 and 8 are images of the chamber containing the liquid, acquired by the photodetector at different time instants, these figures not corresponding to the subject of the appended claims. figures 9 and 10 are correlation images, calculated by the processing unit of the figure 1 , from images acquired at different time instants, these figures not corresponding to the subject of the appended claims. figure 11 is a representation of the temporal evolution of an indicator characterizing a variation in the speed of the particles contained in the liquid, such as a slowing down of the particles, this figure not corresponding to the subject of the appended claims. figure 12 is a table illustrating the cases of cell aggregations according to the blood group and the antibody deposited, the figure 13is a view similar to that of the Figures 3 and 4 according to a second embodiment, the fluidic chamber comprising two channels, the figures 14 and 15 are respective images of the first and second channels of the chamber of the figure 13 , the second channel showing cellular aggregation, the images being acquired by the photodetector of the figure 1 , THE figures 16 and 17 are histograms of the gray level of the acquired images of the figures 14 and 15 , THE figures 18 to 21 are images of the liquid to be characterized, acquired by the photodetector according to a second example of the second embodiment, the liquid to be characterized containing blood, to which a variable quantity of antibodies is added, these images being acquired for increasing quantities of antibodies, the figures 22 to 25 are histograms of the gray level of the acquired images of the figures 18 to 21 respectively, the figures 26 to 29 are images of the liquid characterized on the figures 18 to 21respectively, obtained, after dilution, using a microscope and forming reference images, the figures 30 to 34 are images of the liquid to be characterized, acquired by the photodetector according to a third example of the second embodiment, the liquid to be characterized containing blood, a variable quantity of protein A, and the same quantity of antibody added, the figures 35 to 39 are histograms of the gray level of the acquired images of the figures 30 to 34 respectively, the figures 40 to 44 are images of the liquid characterized on the figures 30 to 34 respectively, obtained after dilution using a microscope and forming reference images, and the figure 45 is a very schematic representation of the agglutination of red blood cells and protein A using antibodies.

[0018] On the figure 1, a characterization system 10 is intended to characterize an agglomeration of particles, the particles, such as blood particles, being contained in a liquid 12, via the acquisition of images formed by radiation transmitted by the illuminated liquid 12, then the processing of these images.

[0019] Thus, in general, the characterization system 10 is intended to characterize a parameter of a liquid comprising particles, this liquid being in particular blood. This parameter is, for example, an agglomeration of particles constituting the liquid.

[0020] By particle, we mean, for example, a biological particle, that is to say a cell (for example a red blood cell, a white blood cell, or a platelet), a bacterium, a virus or any other molecule (for example a protein).

[0021] Agglutination (or agglomeration) means the formation of a three-dimensional structure of particles linked together, under the effect of an introduced reagent.

[0022] By state of agglutination (or agglomeration) we mean an estimate, relative or absolute, of the size of the agglutinates or relative to the quantity of particles present in the agglutinates.

[0023] The characterization system 10 comprises a fluid chamber 14 intended to receive the liquid 12, a light source 16 capable of emitting an excitation light beam 18 to illuminate the fluid chamber 14, the light beam 18 directed in a longitudinal direction X through the fluid chamber 14, and a matrix photodetector 20 capable of acquiring images of the radiation transmitted by the fluid chamber 14 illuminated by the light beam 18. By transmitted radiation is meant the radiation passing through the fluid chamber, such that the matrix photodetector 20 and the light source 16 are located on either side of the fluid chamber 14.

[0024] The characterization system 10 comprises an information processing unit 21 and a screen 22 for displaying an image of the chamber 14.

[0025] In the embodiment described, the characterization system 10 is capable of characterizing the agglutination of blood particles, the agglutination of blood particles making it possible to determine the associated blood group. The liquid 12 then contains blood. The liquid 12 is, for example, whole blood, a fraction of blood, or even blood plasma. Alternatively, the liquid 12 is another bodily fluid, such as urine, sweat, etc.

[0026] The fluidic chamber 14 is arranged between the light source 16 and the matrix photodetector 20 in the longitudinal direction X. The fluidic chamber 14 comprises a liquid deposition zone 26 and one or more channels 28 for circulation of the liquid 12, as shown in the figure 3 .

[0027] The fluidic chamber 14 comprises at least one fluidic channel, delimited, in the direction X, by an upper plate and a lower plate, not shown. These plates are at least partially translucent in order to allow the illumination of the liquid 12 by the light source 16, as well as the detection of the radiation transmitted by the matrix detector 20.

[0028] The lower and upper plates are, for example, two glass slides, not shown and separated by spacers not shown, so that the glass slides are spaced about 160 µm apart in the longitudinal direction X.

[0029] The fluidic chamber 14 has a thickness E in the longitudinal direction X. The thickness E is, for example, of a value between 20 µm and 1000 µm, preferably between 30 µm and 300 µm.

[0030] The light source 16 is capable of emitting the light beam 18 in the longitudinal direction X.

[0031] The light source 16 is arranged at a first distance D1 from the fluid chamber 14 in the longitudinal direction X. The first distance D1 preferably has a value between 1 cm and 30 cm, for example equal to 20 cm.

[0032] In the described embodiment, the light source 16 is a spatially and temporally coherent source. The light source 16 is, for example, a laser. Alternatively, the light source 16 is a laser diode (LD) or a VCSEL type laser diode (VCSEL). Vertical Cavity Surface Emitting Laser ) .

[0033] Alternatively, the light source 16 is a light-emitting diode, also called an LED (from the English Light-Emitting Diode ), monochromatic and having dimensions sufficiently small to be considered spatially coherent, the diameter of the LED being less than one tenth of the first distance D1 separating this LED from the chamber.

[0034] The light beam 18, oriented in the longitudinal direction X, has at the level of the fluidic chamber, a surface area of ​​between 5 mm 2< and 200 mm 2< , preferably equal to 25 mm 2< , along a plane P perpendicular to the longitudinal direction X, as shown in the figure 1 . The plane P is arranged in contact with the fluid chamber 14. Thus, the illuminated fluid surface is larger than in the state of the art. This makes it possible to avoid local fluctuations in the parameter that one wishes to determine.

[0035] The light beam 18 is capable of directly illuminating the fluid chamber 14, preferably in the absence of a magnification optic arranged between the light source 16 and the fluid chamber 14.

[0036] The matrix photodetector 20 is a pixelated image sensor, comprising a plurality of pixels, not shown. Each pixel of the photodetector 20 has dimensions less than or equal to 10 µm, or even 4 µm. Each pixel is, for example, in the shape of a square whose side is of value less than or equal to 10 µm, or even 4 µm. In the embodiment described, each pixel is in the shape of a square with a side of 4 µm. Alternatively, each pixel is in the shape of a square with a side of 2.2 µm.

[0037] The matrix photodetector 20 is arranged at a second distance D2 from the fluid chamber 14 in the longitudinal direction X. The second distance D2 has a value less than 1 cm, and preferably between 100 µm and 2 mm. Favoring a short distance between the detector and the chamber makes it possible to limit interference phenomena between the different diffraction patterns. Indeed, when this distance increases, this interference is likely to make the image unusable, in particular when the number of diffracting particles increases. This is due to the fact that the volume of illuminated fluid is greater than in the device described in application EP 2 233 923 A1 of the prior art. By placing the detector at a distance greater than 1 cm, the image obtained on the detector would be difficult to use.

[0038] The images acquired by the matrix photodetector 20 are formed by the radiation transmitted directly by the illuminated fluid chamber 14, in the absence of a magnifying optic disposed between the fluid chamber 14 and the matrix photodetector 20. The matrix photodetector 20 is also called a lensless imaging device, and is capable of forming an image of the fluid chamber 14, while being placed at a short distance from the latter. By short distance is meant a distance of less than 1 cm.

[0039] The matrix photodetector 20 is capable of generating at least one image every 5 seconds, and the acquisition rate is therefore greater than 0.2 Hz. The matrix photodetector 20 is a two-dimensional image sensor, namely in a plane perpendicular to the longitudinal axis X. The image acquisition frequency is preferably between 1 Hz and 20 Hz.

[0040] The matrix photodetector 20 is, for example, a CCD sensor. Alternatively, the photodetector 20 is a CMOS sensor.

[0041] The matrix photodetector 20 is, for example, substantially aligned with the fluid chamber 14 in the longitudinal direction X, as illustrated in the figure 3 where the photodetector 20 is shown in dotted lines.

[0042] Alternatively, the matrix photodetector 20 is slightly offset relative to the chamber 14 along the longitudinal axis X, as illustrated in the figure 4 where the photodetector 20 is also shown in dotted lines.

[0043] Information processing unit 21, visible on the figure 1 , comprises a data processor 30 and a memory 32 associated with the processor.

[0044] In the example of realization of the figure 2, the matrix photodetector 20, the light source 16 and possibly all or part of the information processing unit 21 are integral with the same substrate 23. The characterization system 10 comprises an optical system 24, for example a mirror, making it possible to return the light beam 18 from the light source 16 to the photodetector 20. This makes it possible to have a compact system. The fluidic chamber 14 is, for example, arranged in a removable support 25. The removable support 25 is, for example, disposable and is intended to be inserted directly above the photodetector 20, at a short distance from the latter, so that the fluidic chamber is able to be illuminated by the light beam 18. According to this exemplary embodiment, the support 25 is intended to receive the fluid to be analyzed 12, then to be inserted close to the photodetector 20 so that the analysis can be carried out.It comprises for example a conduit, in which the fluid 12 circulates to the channel 28 of the fluidic chamber, the fluidic chamber 14 being connected to this conduit. When the analysis is finished, the support 25 is removed to be, in particular, discarded. The characterization system 10 is then available to carry out another measurement with another support.

[0045] A person skilled in the art will understand that, in the exemplary embodiment of the figure 2 , the longitudinal direction X corresponds to the last portion of the light beam 18 between the corresponding mirror of the optical system 24 and the photodetector 20, passing through the fluid chamber 14.

[0046] The or each circulation channel 28 has a width L, visible on the Figures 3 and 4 The width L is, for example, between 50 µm and 5 mm, preferably equal to 1.5 mm.

[0047] The memory 32 is capable of storing software 34 for receiving images acquired by the matrix photodetector 20, a second software 38 for calculating a second indicator Ind2 capable of characterizing another desired parameter, in this case the agglomeration of the particles. The memory 32 is also capable of storing software 40 for characterizing the agglomeration of the particles.

[0048] Alternatively, the reception means 34, the first calculation means 36, the second calculation means 38 and the characterization means 40 are produced in the form of programmable logic components or in the form of dedicated integrated circuits.

[0049] The reception software 34 is capable of regularly receiving from the photodetector 20 the images acquired sequentially, at different times. The reception software 34 is capable of receiving at least one image per second, and the image reception rate is greater than 0.2 Hz, typically in the range of 1 Hz to 20 Hz.

[0050] The first calculation software 36, which is not part of the invention, is capable of calculating an image A n , representing the transmission image I n (x,y), from which a local average is subtracted. The latter is obtained by convolving the image I n (x,y) with a kernel k1. This kernel k1 is a matrix of small dimensions compared to I n . For example, the dimensions of the kernel k1 are 10 pixels by 10 pixels, and the dimensions of I n are at least twice those of the kernel k1, or even 10 times greater. The kernel k1, comprising P rows and Q columns, is, for example, homogeneous, all its values ​​being identical. According to the above, P and Q are integers, for example equal to 10. Thus, two images A n and A n+m are established, corresponding respectively to the instants n and n+m, m being an integer. In general, m is equal to 1, the transmission images I n and I n+1 being two successive transmission images. A n x y = I n x y − I n ⊗ k 1 x y A n + m x y = I n + m x y − I n + m ⊗ k 1 x y where I n (x, y), I n+m (x, y) represent two successive transmission images at times n and n+m, x and y representing the coordinates of a point of the respective image, I n (x,y), I n+m (x,y) being matrices having X rows and Y columns, the symbol ⊗ representing the convolution product defined by the following equation: F ⊗ k 1 x y = ∑ p = 0 P ∑ q = 0 Q F x − p , y − q k 1 p q

[0051] F being a matrix with X rows and Y columns,

[0052] k1 representing a kernel for the correlation of the acquired images, k1 being a matrix with P rows and Q columns,

[0053] X, Y, P and Q being integers verifying X ≥ P ≥ 1 and Y ≥ Q ≥ 1.

[0054] The images are, for example, acquired every second by the matrix photodetector 20, and the two transmission images I n (x,y), I n+1 (x,y) are then images acquired at one-second intervals.

[0055] The characterization software 40 is capable of characterizing the agglomeration of particles contained in the liquid 12.

[0056] The operation of the characterization system 10 according to the invention will now be described using the Figure 5 representing a flowchart of the characterization process

[0057] Prior to its use, the circulation channel(s) 28 of the fluidic chamber are empty, and an initial image I 0 of the chamber 14 then shows a white zone corresponding to the circulation channel 28 and zones delimiting the channel, appearing in this example in the form of dark zones corresponding to the rest of the fluidic chamber 14, as shown in the figure 6 .

[0058] During the initial step 100, the liquid 12 is introduced into the deposition zone 26 of the fluid chamber. The liquid 12 flows by capillarity from the deposition zone 26 towards the circulation channel(s) 28.

[0059] The liquid 12 is then optionally, during step 110, mixed with a reagent 112, visible on the Figures 3 and 4 , and capable of triggering or promoting the phenomenon of slowing down particles. Reagent 112 is, for example, a lyophilized reagent capable of promoting the slowing down of blood particles via blood coagulation.

[0060] Reagent 112 is, for example, deposited upstream of the optical detection zone corresponding to the area inside the dotted lines on the figure 3 for which an image is acquired by the photodetector 20. Alternatively, the reagent 112 is arranged inside the optical detection zone, as shown in the figure 4The mixing between the liquid 12 and the reagent 112 takes place when the liquid 12 flows in contact with the reagent 112 inside the circulation channel 28 (arrow F1).

[0061] The liquid 12 is illuminated by the light beam 18 during step 120. The light source 16 in fact emits the light beam 18 towards the fluid chamber 14 in which the liquid 12 is located in the longitudinal direction X.

[0062] During step 130, the matrix photodetector 20 then performs the sequential acquisition of several transmission images I n (x,y), I n+m (x,y) at different times n and n+m. Each transmission image I n (x,y), I n+m (x,y) is formed by the radiation transmitted, at the corresponding acquisition time, by the illuminated fluidic chamber 14.

[0063] The images I n (x,y), I n+m (x,y) are, for example, immediately successive images, m then being equal to 1, preferably acquired every second, as represented in the figures 7 and 8 , where the time difference between the two images I n (x,y), I n+1 (x,y) acquired successively is equal to one second.

[0064] The acquired images I n (x,y), I n+1 (x,y) correspond to the interferences of diffraction patterns generated by particles suspended in the liquid 12. The illumination of the particles by the spatially and temporally coherent beam 18, such as a laser beam, generates a diffraction pattern, which varies over time due to the movement of the particles contained in the liquid 12.

[0065] The observation of a usable diffraction pattern, by placing the matrix photodetector 20 at such a short distance, is notably due to the absence of magnification optics between the fluidic chamber 14 and the photodetector 20.

[0066] During the acquisition step 130, the photodetector 20 is arranged at a short distance from the fluid chamber 14, the second distance D2 between the fluid chamber 14 and the photodetector 20 in the longitudinal direction X being less than 1 cm.

[0067] Step 140 is described below.

[0068] The second distance D2 less than 1 cm between the fluidic chamber 14 and the photodetector 20 also makes it possible to limit the size of the characterization system 10.

[0069] Furthermore, the significant extent of the light beam 18 along the plane P, i.e. greater than 5mm 2< , and for example between 5mm 2< and 200mm 2< , makes it possible to limit the heating of the liquid 12 contained in the fluidic chamber 14. In fact, the large surface area of ​​the light beam 18 makes it possible to have a low power optical density.

[0070] In addition, using an extended light beam and forming an image at a short distance from the chamber allows for the examination of a larger volume of fluid. This limits the influence of local phenomena, which are likely to become predominant when the light beam is finer, and the volume of fluid analyzed is almost point-like. The analysis of the correlation between two transmission images I n , I n+m allows the spatial structure of coagulation to be taken into account, in the plane of the microfluidic channel 28. In other words, the evolution of blood coagulation is observed in two dimensions.

[0071] THE figures 12 to 17 illustrate a second embodiment, forming the subject of the invention as claimed in the appended claims, for which the elements similar to the first embodiment, described previously, are identified by identical references, and are not described again.

[0072] According to the second embodiment, the characterization system 10 is intended to characterize more particularly the agglomeration of particles contained in a liquid 12. The characterization system 10 is, for example, capable of characterizing the agglomeration of blood particles, such as red blood cells, also called agglutination of blood particles.

[0073] Blood group information is then further determined from the agglomeration state, also called agglutination state.

[0074] As known per se, the blood group can be determined according to the Beth-Vincent test by detecting the presence of A or B antigens implying the absence of anti-A or anti-B antibodies. In the case where the red blood cells of the tested blood present an A or B antigen, an antigen-antibody complex will form and lead to cell aggregation as recalled in table 200, visible on the figure 12 .

[0075] The fluidic chamber 14 comprises two separate circulation channels 202, 204, namely a first channel 202 and a second channel 204, as shown in the figure 13 .

[0076] According to the second embodiment, the light source 16 is any type of light source. The light source 16 is not necessarily spatially and temporally coherent.

[0077] According to the second embodiment, the second calculation software 38 is capable of calculating the second indicator Ind2 capable of characterizing the agglomeration of the particles, the second indicator Ind2 being an intensity indicator for each acquired image I n (x,y). The second indicator Ind2 is representative of the histogram of the intensity of each pixel in the image I n , or in a region of interest of the latter. It is determined, for example, by measuring the total intensity of the image I n or in a predetermined region of interest of the image I n , possibly after thresholding.

[0078] The characterization software 40 is then able to determine an agglomeration state of the particles of the liquid 12 from the second calculated indicator Ind2. The agglomeration state is, for example, determined when the second indicator Ind2 exceeds a predetermined threshold.

[0079] In the embodiment described, where the liquid 12 contains blood, the particles are, for example, red blood cells, and the characterization software is then capable of determining information relating to the blood group from the agglomeration state.

[0080] The operation of this second embodiment will now be described using the figures 13 to 17 .

[0081] In the initial step 100, the liquid 12, for example the blood sample of a donor whose blood group is to be determined, is introduced into the deposition zone 26 of the fluid chamber. The liquid 12 then flows from the deposition zone 26 towards the circulation channels 202, 204, for example by capillarity.

[0082] The liquid 12 is then mixed with a first 206 and a second 208 distinct reagents, during step 110, as shown in the figure 13 .

[0083] Each reagent 206, 208 is, for example, deposited upstream of the optical detection zone corresponding to the zone inside the dotted lines on the figure 13 for which an image is acquired by the photodetector 20.

[0084] The mixing between the liquid 12 and the first and second reagents 206, 208 takes place when the liquid 12 flows in contact with the first reagent 206 inside the first channel 202 (arrow F2), and respectively with the second reagent 208 inside the second channel 204 (arrow F3).

[0085] In the described embodiment, the first reagent 206 is a donor serum A, i.e. containing anti-B antibodies, and the second reagent 208 is a donor serum B, i.e. containing anti-A antibodies.

[0086] Depending on the blood group associated with the blood sample 12, cell aggregation will then occur or not in each of the circulation channels 202, 204.

[0087] The liquid 12, such as the blood sample mixed with the first and second reagents 206, 208, is then illuminated by the light beam 18 during step 120.

[0088] During step 130, the matrix photodetector 20 then acquires a transmission image I(x,y) corresponding to an optical detection zone encompassing the two circulation channels 202, 204.

[0089] Those skilled in the art will observe that, according to the second embodiment, the acquisition of a single transmission image I(x,y) makes it possible to characterize the agglomeration of the particles contained in the liquid 12, by comparing this image to a reference image I ref (x,y), the latter being for example an image produced on a reference zone, not shown, in which the blood is not mixed with a reagent. This reference zone is, for example, a third channel, of geometry identical to that of the first or second channel 202, 204, and not comprising any reagent.

[0090] Alternatively, it is an area located on the first channel 202 or on the second channel 204, upstream of the reagent 206, 208.

[0091] Alternatively, the reference image I ref (x,y) is produced at the same location as the transmission image, just after the channel has been filled with the analyzed liquid, the transmission image I(x,y) being produced, under the same conditions, after a certain time, for example 1 minute, so that the possible effect of the reagent on the analyzed liquid is measurable.

[0092] The acquired image I(x,y) corresponds in a similar manner to the diffraction and diffusion of the light beam 18 by the particles suspended in the liquid 12. Preferably, this image is produced under identical conditions for the two channels, as well as for the reference zone. By identical conditions, we mean in particular the illumination conditions, the source-detector distance, the characteristics of the detector used, the exposure time, the observed field, the size of the image.

[0093] The illumination of the particles by the light beam 18 generates a diffraction pattern. As previously indicated, the absence of a magnifying lens between the fluid and the photodetector 20, coupled with the large surface area of ​​the incident beam, makes it possible to form an image that can be used at a short distance, covering a large field of fluid, such as a field having an area of ​​several mm 2< .

[0094] During the acquisition step 130, the photodetector 20 is arranged close to the fluid chamber 14, the second distance D2 between the fluid chamber 14 and the photodetector 20 in the longitudinal direction X being less than 1 cm.

[0095] In the example of realization of the figures 14 and 15, representing an image 210 acquired from the first channel 202, and respectively an image 212 acquired from the second channel 204, a cell aggregation is observed only in the second channel 204 due to the presence of white spots in the image 212. In other words, the blood group associated with the blood sample tested is group B according to table 200 of the figure 12 .

[0096] At the end of the acquisition step 130, the second calculation software 38 calculates, during step 140, the second indicator Ind2 capable of characterizing the agglomeration of the particles, the second indicator Ind2 being an intensity indicator for each acquired image I(x,y). The second indicator Ind2 is representative of the intensity in the predetermined region of interest of the image, in particular of the distribution of the intensity of the pixels in said region.

[0097] The second indicator Ind2 is, for example, a characteristic of the image, and in particular of the histogram of the gray level of the image acquired for each channel 202, 204, and where appropriate, of the reference channel as illustrated in the figures 16 and 17 , representing a histogram 214 of the gray level of the image acquired from the first channel 202, and respectively a histogram 216 of the gray level of the image acquired from the second channel 204. Each gray level histogram 214, 216 presents on the abscissa the gray level values ​​and on the ordinate the population of pixels, that is to say the number of pixels, for a given gray level on the abscissa. A characteristic of the histogram is, for example, the average intensity of the pixels, noted I mean , after a possible thresholding of the image, this thresholding making it possible to retain only the information of the pixels whose intensity is greater than a certain threshold.

[0098] Referring to the example shown on the figures 16 and 17 , after having carried out a thresholding at the intensity corresponding to the value 120, we understand that the average intensity of the image corresponding to the figure 17 , is greater than the average intensity of the image corresponding to the figure 16 This is because the histogram of the figure 17 , representing the observation of particle agglutination, includes more intense pixels (gray levels greater than 200) than the histogram of the figure 16 , the latter representing the observation of non-agglutination. The second indicator Ind2 is then, for example, established according to the average intensity of the image.

[0099] According to a variant, the intensity I max is determined for each image produced, the latter corresponding, on the histogram of the image, to the highest value of the intensity gathering a predetermined number of pixels, for example 500 pixels. The difference between I max and I mean is then determined by the subtraction I max -I mean , the second indicator Ind2 then representing this difference. On the histogram of the figure 17 , the second indicator Ind2 thus defined is higher than on the histogram of the figure 16 The value of the second indicator Ind2 thus determined makes it possible to conclude on the presence or absence of an agglutination phenomenon, via a comparison, for example with an Ind2 ref value obtained on a reference zone, or even with a predetermined value, the predetermination of this value being for example carried out according to experimental tests.

[0100] According to a variant, on each transmission image, the intensity I peak corresponding to the maximum value of the histogram is determined, that is to say the intensity value gathering the highest number of pixels. On the figures 16 and 17 , this value corresponds to the peak of each distribution, respectively equal to 120 and 130. We also determine the maximum value I max gathering a number of pixels of value greater than a predetermined threshold. Referring to the figures 16 and 17 , and by adopting a threshold of 500, I max is respectively equal to 181 and 256. The second indicator Ind2 corresponds to the distance between I max and I peak , respectively 61 for the figure 16 and 126 for the figure 17 . We conclude that there is agglomeration when the second indicator Ind2 is higher, for example by 25%, than a certain predetermined threshold, or when it is higher than the indicator Ind2 ref established for the reference zone.

[0101] Alternatively, the second indicator Ind2 is a comparison indicator between a region of interest of a transmission image I and a reference image I ref not containing a reagent (and therefore in which agglutination does not occur) as below: Ind 2 = ∑ x ∑ y I x y − I ref x y ∑ x ∑ y I x y + I ref x y

[0102] The second indicator Ind2 is compared with a predetermined threshold, for example 0.25. Thus, if the second indicator Ind2 is higher than this threshold; we conclude that there is agglutination.

[0103] The characterization software 40 is then able to determine a state of agglomeration of the particles of the liquid 12 from the second calculated indicator Ind2.

[0104] The state of agglomeration is, for example, determined when the second indicator Ind2 exceeds a predetermined threshold.

[0105] If the comparison is positive, that is to say if the gray level obtained is greater than the predetermined threshold, then the characterization software 40 deduces the presence of a cellular aggregation in the corresponding channel 202, 204.

[0106] In the second embodiment described, the characterization software 40 finally determines the blood group associated with the blood sample 12 tested from the type of the first and second reagents 206, 208, as well as from the table 200.

[0107] The advantages of this second embodiment are identical to those of the first embodiment described previously.

[0108] In addition to the first embodiment, the fluidic chamber 14 comprises a plurality of channels, for example the two channels 202, 204 visible in the figure 13, in order to characterize the variation in the speed of the particles of the liquid 12 when the liquid 12 is mixed with different reagents, a respective reagent then being placed in each channel 202, 204 of the fluidic chamber 14. This makes it possible, with the same device, to determine different analysis parameters of the same liquid sample, for example the coagulation time and the blood group.

[0109] Such a fluidic chamber 14 is, for example, advantageous for characterizing the coagulation of the liquid 12 containing blood, with different reagents capable of promoting the slowing down of the blood particles via blood coagulation, such as the different reagents 112 defined above.

[0110] It is thus understood that the characterization system 10 according to the invention makes it possible to observe a larger part of the fluidic chamber 14, while having a limited footprint.

[0111] THE figures 18 to 29illustrate a second example of the second embodiment, in which the liquid to be characterized 12 is a biological liquid, in particular blood or diluted blood, and the characterization system 10 is capable of characterizing the agglomeration of particles, in this case red blood cells in the biological liquid 12.

[0112] The liquid to be characterized 12 comprises, in this example, blood diluted 1 / 20 in a PBS buffer (from the English Phosphate Buffered Saline ), the buffer containing 1% by volume of FBS (from English Fetal Bovine Serum ) .

[0113] The volume of diluted blood is 40 µl, to which a variable quantity of antibody is added, such as an anti-red blood cell called CD235A, marketed for example by the company Becton Dickinson under the reference BD 555569. The quantity of antibody added varies from 0 to 1 µg of antibody per µl of undiluted blood, which corresponds to a concentration between 0 and 6.7 µM.

[0114] The addition of this antibody helps mask the surface antigens of red blood cells (especially glycophorin A), causing them to clump together.

[0115] The objective of this second example is to show that it is possible to characterize a state of agglutination of blood particles, for example red blood cells, by lensless imaging using the characterization system 10.

[0116] For each quantity of antibody added to the liquid to be characterized 12, an acquisition of the sample of liquid to be characterized 12 is carried out using the characterization system 10, i.e. by lensless imaging, the images 220A, 220B, 220C and 220D obtained being visible on the figures 18 to 21 . A grayscale histogram of the pixel intensity of each of these images 220A, 220B, 220C and 220D is then calculated, the calculated histograms 222A, 222B, 222C and 222D being visible on the figures 22 to 25. Reference images 224A, 224B, 224C and 224D of the liquid sample to be characterized 12 are also obtained with a microscope, as shown in the figures 26 to 29 It should be noted that for microscopic observation, the blood sample is diluted with a dilution factor of one tenth.

[0117] In this second example, the light source 16 is a laser diode, having an emission spectrum centered on a wavelength λ for example equal to 670 nm, and the first distance D1 is substantially equal to 8 cm. The sample is confined in the fluidic chamber 14 comprising a channel 28 of thickness 150 µm arranged between two transparent walls of thickness 200 µm. These walls are made of plastic material, for example COP material (from the English Cyclo Olefin Polymer ).

[0118] The fluidic chamber 14 is directly placed on the glass cover of the matrix photodetector 20, such as a CMOS sensor, comprising 1280 * 1024 pixels, each pixel being of dimension 5 µm x 5 µm, such that the fluidic chamber 14 is arranged between the CMOS sensor and the light source 16. The second distance D2 is then preferably less than 1 cm, for example equal to 550 µm.

[0119] Image acquisitions are for example carried out with an exposure time of 5 ms, with one image per acquisition. Images 220A, 220B, 220C and 220D correspond respectively to an increasing quantity of antibody added. More precisely, images 220A, 220B, 220C and 220D correspond respectively to: an amount of antibody that is substantially zero, an amount of antibody that is less than a threshold concentration C, an amount of antibody that is equal to the threshold concentration C, and an amount of antibody that is twice the threshold concentration C.

[0120] When the amount of antibody added exceeds the threshold concentration C, the red blood cells clump together, and images obtained by lensless imaging using the Characterization System 10 reflect the size of the clumps. The value of the threshold concentration C is, for example, equal to 250 ng of antibody per 1 µl of undiluted blood, which corresponds to 1.7 µM.

[0121] It is observed that the agglomeration of red blood cells leads to the appearance of large light areas (high gray level) delimited by dark areas (low gray level). This effect of image segmentation according to areas comprising several tens, or even hundreds of pixels, of comparable gray levels, can be observed by comparing the 220A images ( figure 18 ) or 220B ( figure 19 ), on which no agglutination is observed, in 220C images ( figure 20 ) and 220D ( figure 21), on which agglutination is observed. The presence or absence of agglutination of particles observable on images 220A, 220B, 220C and 220D is confirmed by the microscope observations shown on images 224A ( figure 26 ), 224B ( figure 27 ), 224C ( figure 28 ) and 224D ( figure 29 ) respectively. This results in an evolution of the histogram of each image, the latter tending to stretch towards low gray level values ​​as the quantity of agglomerates increases, as can be seen from histogram 222A corresponding to image 220A going towards histogram 222D corresponding to image 220D.

[0122] The agglutination state of the blood sample is then quantified by calculating the second indicator Ind2 according to several possible variants: the second indicator Ind2 is, according to a first variant, equal to the standard deviation of the intensity distribution of the pixels of the area of ​​interest examined, and is then noted Ind2 A , the second indicator Ind2 is, according to a second variant, equal to the number of pixels below a certain threshold, this threshold being for example a fraction of the maximum gray level, divided by the total number of pixels in the area of ​​interest examined, and the second indicator Ind2 calculated according to this second variant is then noted Ind2 B . In the example of figures 22 to 25 , the threshold value is equal to 125.

[0123] Table 1 below shows the value of the second indicator Ind2 according to these two variants and for each of the areas of interest represented on the figures 18 to 21 . Figures 18 19 20 21 Ind2 A 36 33 51 59 Ind2 B 6.5 10 -3< 6.5 10 -3< 8.7 10 -2< 1.4 10 -1<

[0124] When the second indicator Ind2 A according to the first variant is below a threshold value, for example between 40 and 45, there is no observable agglutination. Beyond this threshold value, the higher the value of the second indicator Ind2 A, the greater the quantity of agglutinated particles.

[0125] The second indicator Ind2 B, calculated according to the second variant, allows us to arrive at the same conclusions, by taking a threshold value between 1 10 -2< and 5 10 -2<.

[0126] Thus, it is noted that it is possible to observe, or even quantify, a state of agglutination of particles in the biological liquid 12, using an indicator calculated from an image obtained by the characterization system 10, that is to say by lensless imaging, and in particular the second indicator Ind2 A, Ind2 B, according to the first and second variants of this second example, this second indicator being a function of the distribution of the intensity of the pixels of the images 220A, 220B, 220C and 220D acquired by the characterization system 10.

[0127] The use of the characterization system 10 is also conceivable in a diagnostic test based on the detection of agglutinates in a biological fluid.

[0128] THE figures 30 to 45illustrate a third example of the second embodiment, in which the liquid to be characterized 12 is a biological liquid, in particular blood or diluted blood, and the characterization system 10 is capable of characterizing the agglomeration, also called agglutination, of particles in the biological liquid 12.

[0129] In this third example, we demonstrate the detection of agglutination of red blood cells in a blood sample, containing a variable quantity of protein A, the agglutination being caused by the addition of a given quantity of a reagent (an antibody).

[0130] The liquid to be characterized 12 comprises, for example, blood diluted 1 / 20 in a PBS buffer (from the English Phosphate Buffered Saline ), the buffer containing 1% by volume of FBS (from English Fetal Bovine Serum ).

[0131] The diluted blood volume is 40 µl, into which an antibody, such as an anti-red blood cell called CD235A, marketed for example by the company Becton Dickinson under the reference BD 555569, is incubated with a protein A solution in variable quantity. The incubation time is 1 hour.

[0132] Thus, several solutions are available, called antibody - protein A, in which the antibody - protein A molar ratio is variable. These solutions are likely to cause the agglutination of red blood cells, hence the name "pro-agglutinating solutions". A volume of 1.2 µl of each of these solutions is incubated with 40 µl of the diluted blood sample described above, for 1.5 hours, each of these mixtures forming a sample of liquid to be characterized 12.

[0133] In each of the mixtures thus obtained, the molar concentration of antibody S is lower than the threshold C determined in the second previous example. In other words, this concentration of antibody does not allow spontaneous agglutination of red blood cells. In this case, this concentration S is 100 ng of antibody per µl of undiluted blood, or 0.7µM.

[0134] For each of the liquid samples to be characterized 12, an image acquisition is carried out using the characterization system 10, i.e. by lensless imaging, the acquired images 230A, 230B, 230C, 230D and 230E obtained being visible on the figures 30 to 34 . A grayscale histogram of the pixel intensity of each of these images 230A, 230B, 230C, 230D and 230E is then calculated, the calculated histograms 232A, 232B, 232C, 232D and 232E being visible on the figures 35 to 39. Reference images 234A, 234B, 234C, 234D and 234E of each of the liquid samples to be characterized 12 are also obtained with a microscope, as shown in the figures 40 to 44 It should be noted that for microscopic observation, the blood sample is diluted with a dilution factor of one tenth.

[0135] In this third example, the light source 16 is a laser diode, having an emission spectrum centered on a wavelength λ equal to 670 nm, and the first distance D1 is substantially equal to 8 cm. The sample is confined in the fluidic chamber 14 comprising a channel 28 of thickness 150 µm arranged between two transparent walls of thickness 200 µm. These walls are made of plastic material, for example COP material (from the English Cyclo Olefin Polymer ) .

[0136] The fluidic chamber 14 is directly placed on the glass cover of the matrix photodetector 20, such as a CMOS sensor. The CMOS sensor is for example a 1280 by 1024 pixel matrix, each pixel being in the shape of a square with a side of 5 µm; such that the fluidic chamber 14 is arranged between the CMOS sensor and the light source 16. The second distance D2 is then preferably less than 1 cm, for example equal to 550 µm.

[0137] Image acquisitions are for example carried out with an exposure time of 5 ms, with one image per acquisition. Images 230B, 230C, 230D and 230E correspond respectively to an increasing amount of added protein A. More precisely, images 230A, 230B, 230C, 230D and 230E correspond respectively to: absence of antibodies, i.e. a molar ratio of Antibody:Protein A = 0:40 (0 antibody molecules for 40 protein A molecules), absence of protein A, i.e. a molar ratio of Antibody - Protein A = 1:0 (1 antibody molecule for 0 protein A molecules), molar ratio of Antibody:Protein A = 1:1 (1 antibody molecule for 1 protein A molecule), molar ratio of Antibody:Protein A = 1:5 (1 antibody molecule for 5 protein A molecules), and molar ratio of Antibody:Protein A = 1:40 (1 antibody molecule for 40 protein A molecules).

[0138] The antibody here serves as a coupling agent between a protein A molecule and a red blood cell, as will be detailed later.

[0139] In the presence of protein A and the absence of antibodies, no agglutination of red blood cells is observed, as shown in the figure 30. In the presence of antibodies and in the absence of protein A, no agglutination of red blood cells is observed, this being visible on the figure 31 .

[0140] When the antibody:protein A ratio is 1:1, no red blood cell agglutination is also observed, as shown in the figure 32 .

[0141] When the antibody:protein A ratio is equal to 1:5, we observe an agglutination of red blood cells, visible on the figure 33 . When the antibody:protein A ratio is equal to 1:40, we also observe agglutination of red blood cells, visible on the figure 34 , the size of the agglutinates observed on the figure 34 being greater than that of the agglutinates observed on the figure 33 .

[0142] THE figures 35 to 39 represent the histogram of the pixel intensity of the figures 30 to 34 respectively.

[0143] It is observed that the agglomeration of red blood cells leads to the appearance of light areas (high gray level) delimited by a dark area (low gray level). This effect of image segmentation according to areas comprising several tens, or even hundreds of pixels, of comparable gray levels, visible by comparing the 230A images ( figure 30 ) or 230B ( figure 31 ) or 230C ( figure 32 ), on which no agglutination is observed, in 230D images ( figure 33 ) and 230E ( figure 34 ), on which agglutination is observed. The presence or absence of agglutination of particles observable on images 230A, 230B, 230C, 230D and 230E is confirmed by the microscope observations shown on images 234A ( figure 40 ), 234B ( figure 41 ), 234C ( figure 42 ), 234D ( figure 43 ) and 234E ( figure 44) respectively. This results in an evolution of the histogram of each image, the latter tending to stretch towards low gray level values ​​as the quantity of agglomerates increases, as can be seen from histogram 232A corresponding to image 230A going towards histogram 232E corresponding to image 230E. The agglutination state of the blood sample is then quantified by calculating the second indicator Ind2 according to several possible variants: the second indicator Ind2 is, according to a first variant, equal to the standard deviation of the intensity distribution of the pixels of the area of ​​interest examined, and is then noted Ind2 A , the second indicator Ind2 is, according to a second variant, equal to the number of pixels below a certain threshold, this threshold being for example a fraction of the maximum gray level, divided by the total number of pixels in the area of ​​interest examined, and the second indicator Ind2 calculated according to this second variant is then noted Ind2 B . In the example of figures 22 to 25 , the threshold value is for example equal to 125.

[0144] Table 2 below shows the value of the second indicator Ind2 according to these two variants and for each of the areas of interest represented on the figures 30 to 34 . Figures 30 31 32 33 34 Ind2 A 33 39 35 50 52 Ind2 B 4.0 10 -3< 1.5 10 -2< 5.5 10 -3< 6.5 10 -2< 9.5 10 -2<

[0145] When the second indicator Ind2 A according to the first variant is below a threshold value, for example between 40 and 45, there is no observable agglutination. Beyond this threshold value, the higher the value of the second indicator Ind2 A, the greater the quantity of agglutinated particles.

[0146] The second indicator Ind2 B, calculated according to the second variant, allows us to arrive at the same conclusions, by taking a threshold value between 1 10 -2< and 5 10 -2<.

[0147] Thus, it is noted that it is possible to observe, or even quantify, a state of agglutination of particles in the biological liquid 12, using an indicator calculated from an image obtained by the characterization system 10, that is to say by lensless imaging, and in particular the second indicator Ind2 A, Ind2 B, according to the first and second variants of this second example, which is a function of the distribution of the intensity of the pixels of the images 230A, 230B, 230C, 230D and 230E acquired by the characterization system 10.

[0148] Furthermore, the greater the amount of protein A, the greater the size of the agglutinates, the amount of antibody added being constant. Thus, the second indicator Ind2 A, Ind2 B quantifying the agglutination state also makes it possible to quantify a quantity of protein in the blood sample.

[0149] Depending on the antibody-protein A molar ratio, the red blood cells agglomerate and the images 230A, 230B, 230C, 230D and 230E obtained by lensless imaging reflect the size of the agglutinates, i.e. a degree of agglutination. It is then understood that by introducing a determined quantity of antibody into the blood sample, it is possible to estimate the quantity of protein A present in this sample according to the state of agglutination, i.e. according to the second indicator Ind2 A, Ind2 B previously described.

[0150] In other words, the quantity of protein A, beyond which agglutination is observed, constitutes the detection limit of a dosage of this protein in a blood sample, by introducing a given quantity of antibodies into the sample of liquid to be characterized 12.

[0151] Thus, it is understood that it is possible to observe, or even quantify, a state of agglutination of particles in a biological fluid, by indicators relating to the image obtained by lensless imaging, and in particular the second indicator Ind2 A , Ind2 B , according to the first and second variants of this second example, which is a function of the distribution of the intensity of the pixels. This state of agglutination depends, for example, on the concentration of an analyte in the biological fluid, the quantification of this state of agglutination then allowing the dosage of this analyte in the liquid.The example shows that this assay can be carried out by introducing a bi-functional reagent, in this case the antibody 300, into a blood sample, capable of binding both to a particle of the biological fluid, in this case the red blood cells 302, and to the analyte to be assayed, in this case the protein A 304, thus forming a bridge between an analyte 304 and the red blood cells 302, as shown in the . figure 45 .

[0152] The term bi-functional refers to the ability of the reagent to bind to both a particle and an analyte.

[0153] Generally speaking, an analyte is a chemical or biological species present in the liquid, such as a molecule, a macromolecule (for example, protein or nucleic acid), a cell, a bacterium, a virus, or even a spore.

[0154] In addition, analyte 304 must have at least 2 binding sites with the bi-functional reagent, as shown in the figure 45 . Thus, each analyte 304 can be bound, via the bi-functional reagent, to at least two particles. This results in the agglutination of the particles.

[0155] In other words, the state of agglutination of the particles in the liquid 12 depends on the quantity of analyte present in the liquid 12, this quantity being measurable by adding a reagent capable of causing the formation of agglutinates, the reagent 300 then being capable of attaching itself between one of said particles 302 and an analyte 304 so as to form an agglutinate.

[0156] Depending on the quantity of analyte 304 present in the liquid, an agglutinate is formed, composed of particles 302 and analytes 304. By determining the agglutination state corresponding to a given quantity of reagent introduced, it is then possible to estimate the quantity of analyte 304 present in the liquid 12.

[0157] In the second and third examples of the second embodiment, described above, the second distance D2 is less than 1 cm. The inventors have however also observed that, in the case of the characterization of agglutination, values ​​of the second distance D2 greater than 1 cm, such as values ​​of a few centimeters, or even a few tens of centimeters, make it possible to obtain usable results, even if values ​​of the second distance D2 less than 1 cm remain preferable.

[0158] Generally speaking, these second and third examples demonstrate another aspect of the invention. According to this other aspect, the invention relates to a method for characterizing the agglutination of particles, such as biological particles, in a liquid, for example a biological liquid, and in particular a bodily liquid, the characterization method comprising the following steps: introducing the liquid into a fluidic chamber, illuminating the fluidic chamber with a light beam, the light beam coming in particular from a light source, such as a laser diode or a light-emitting diode, acquiring an image, or a plurality of images, of the fluidic chamber by a matrix photodetector, the photodetector preferably being placed at a distance from the fluidic chamber of less than 1 cm, the fluidic chamber being arranged between the light source and the matrix photodetector, processing the image, or the plurality of images, to determine an indicator characterizing the agglutination of particles in the biological fluid, and characterizing the agglutination of particles in the liquid, as a function of the value of the indicator.

[0159] It should be noted that the image is acquired by the photodetector, preferably without magnification optics between the fluid chamber and the matrix photodetector. However, focusing microlenses can be provided at each pixel of the detector, as previously mentioned.

[0160] In addition and optionally, the indicator is an indicator representative of the distribution of the intensity of the pixels in an image, or more generally, any other indicator translating the segmentation of the image according to different zones, each zone comprising several tens to hundreds of pixels of comparable intensity, that is to say whose intensity is distributed in a range of gray levels of the order of half, or even a third, or even a quarter, or even less than a quarter of the dynamic range of the image.

[0161] Additionally and optionally, the characterization process involves the addition of a reagent, which may cause particles to clump together in the liquid.

[0162] As illustrated in the third example of the second embodiment, the agglutination of the particles is, for example, a function of an amount of analyte present in the liquid.

[0163] According to this variant, the invention relates to a method for detecting the quantity of an analyte in a liquid, for example a biological liquid, and in particular a bodily liquid, the detection method comprising the following steps: introducing the liquid into a fluidic chamber, illuminating the fluidic chamber with a light beam, the light beam coming in particular from a light source, such as a laser diode or a light-emitting diode, adding a reagent, capable of causing the formation of agglutinates of particles and analyte in the liquid, acquiring an image, or a plurality of images, of the fluidic chamber by a matrix photodetector, the photodetector preferably being placed at a distance from the fluidic chamber of less than 1 cm, the fluidic chamber being arranged between the light source and the matrix photodetector, processing the image, or the plurality of images, to determine an indicator characterizing the agglutination of particles in the biological liquid, and estimating the quantity of analyte in the liquid, as a function of the value of the indicator.

[0164] According to yet another aspect, the invention relates to a method for determining a parameter of the liquid 12, comprising blood, the method comprising the following steps: the introduction of the liquid 12 into the fluidic chamber 14, the illumination of the fluidic chamber 14 via the excitation light beam 18 emitted by the light source 16, the light beam 18 extending through the fluidic chamber 14 in the longitudinal direction X, the acquisition of at least one image I n (x,y), I n+m (x,y), I(x,y) by the matrix photodetector 20, the image I n (x,y), I n+m (x,y), I(x,y) being formed by radiation transmitted by the illuminated fluidic chamber 14, and the determination of an indicator Ind1 n,n+m , Ind2, from said at least one image I n (x,y), I n+m (x,y), I(x,y).

[0165] During the acquisition step, the photodetector 20 is arranged at the distance D2, less than 1 cm, from the fluidic chamber 14 in the longitudinal direction X.

[0166] Additionally and optionally, the determination method includes one or more of the following characteristics, taken individually or in all technically possible combinations: the light beam 18 directly illuminates the fluidic chamber 14, and the image I n (x,y), I n+m (x,y), I(x,y) is formed directly by the radiation transmitted by the illuminated fluidic chamber 14, in the absence of a magnification optic arranged between the fluidic chamber 14 and the photodetector 20; the parameter is a coagulation, and the method then comprises the following steps: + mixing the liquid 12 with a reagent to promote blood coagulation, + acquiring a series of transmission images I n (x,y), I n+m (x,y) at different time instants n, n+m, + calculating an indicator Ind1 n,n+m to establish a correlation between two areas of the transmission images I n (x,y), I n+m (x,y), the coagulation being determined as a function of the value of said indicator; the parameter is a coagulation time,and the method then comprises the following steps: + mixing the liquid 12 with a reagent to promote blood coagulation + acquiring a series of transmission images I n (x,y), I n+m (x,y) at different time instants n, n+m, + calculating an indicator Ind1 n,n+m to establish a correlation between two images I n (x,y), I n+m (x,y), and + determining a time interval, called coagulation time, between an origin time t0 and the time t2 A, t2 B at which the indicator Ind1 n,n+m takes a determined value. the parameter is an agglutination of blood particles, and the method then comprises the following steps + mixing the liquid 12 with a reagent capable of causing an agglutination of the blood particles, + acquiring a transmission image I(x,y), + calculating an indicator Ind2 as a function of the intensity in a predetermined area of ​​the transmission image I(x,y),and + the determination of an agglutination state when this indicator Ind2 exceeds a predetermined threshold; the blood particles are red blood cells, the reagent comprising an antibody, the agglutination state then giving information relating to the blood group.

[0167] According to this other independent aspect, the invention also relates to a system for determining a parameter of the liquid 12, comprising blood, the determination system comprising: the fluidic chamber 14 intended to receive the liquid 12; the light source 16 capable of emitting the excitation light beam 18 to illuminate the fluidic chamber 14, the light beam 18 extending in the longitudinal direction X; the matrix photodetector 20 capable of acquiring at least one image I n (x,y), I n+1 (x,y), I(x,y) of radiation transmitted by the illuminated fluidic chamber 14; and the information processing unit 21 comprising means for determining an indicator Ind1 n,n+m , Ind2, from said at least one image I n (x,y), I n+m (x,y), I(x,y).

[0168] The photodetector 20 is arranged at the distance D2, less than 1 cm, from the fluid chamber 14 in the longitudinal direction X.

[0169] The parameter is coagulation, clotting time, or agglutination of blood particles.

Claims

1. Method for characterising the agglutination of particles contained in a liquid (12), the method comprising the following steps: - introducing (100) the liquid (12) into a fluid chamber (14); - illuminating (120) the fluid chamber (14) via a light beam (18) emitted by a light source (16) in a longitudinal direction; - acquiring (130) an image (I(x,y)) or a plurality of images (In(x,y), In+m(x,y)) of the fluid chamber (14) by a matrix photodetector (20), the fluid chamber (14) being arranged between the ight source (16) and the matrix photodetector (20); - processing (140) the image (I(x,y)) or the plurality of images ((In(x,y), In+m(x,y)) to determine an indicator (Ind2) characterising the agglutination of particles in the liquid (12), and - characterising the agglutination of particles in the liquid (12) as a function of the value of the indicator (Ind2); the method being characterised in that during the acquisition step (130), the photodetector (20) is positioned at a distance (D2) of less than 1 cm from the fluid chamber (14) in the longitudinal direction (X).

2. Method according to claim 1, wherein the indicator (Ind2) is representative of the intensity of the pixels of the image (I(x,y)) in a predetermined region of the image (I(x,y)).

3. Method according to claim 1 or 2, wherein the particles are biological particles, such as blood cells.

4. Method according to any of the preceding claims, wherein the light source (16) is a laser diode or a light-emitting diode.

5. Method according to any of the preceding claims, wherein the light beam (18) directly illuminates the fluid chamber (14), and the image (In(x,y), In+m(x,y); I(x,y)) is formed directly by the radiation transmitted through the illuminated fluid chamber (14), in the absence of a magnifying optical system arranged between the fluid chamber (14) and the photodetector (20).

6. Method according to any of the preceding claims, wherein agglutination is characterised when the indicator (Ind2) exceeds a predetermined threshold.

7. Method according to any of claims 1 to 5, wherein the state of agglutination is determined when the indicator (Ind2) exceeds a reference indicator (Ind2ref ), obtained from an image taken in a reference area.

8. Method according to any of the preceding claims, wherein the method further comprises a step (110) of mixing the liquid (12) with a reagent (206,208) capable of causing agglutination of the particles.

9. Method according to claim 8 and claim 3, wherein the blood particles are red blood cells, the reagent (206, 208) comprises an antibody, and information relating to the blood group is further determined from the agglutination state.

10. Method according to any of the preceding claims, wherein the liquid (12) comprises an analyte, the method then comprising estimating the amount of said analyte in the liquid (12) based on the indicator (Ind2).

11. Method according to any of the preceding claims, wherein the fluid chamber (14) comprises a plurality of fluid flow channels (202, 204), and wherein, during the processing step (140), the indicator (Ind2) is calculated for each of the channels (202, 204).

12. System (10) for characterising the agglutination of particles contained in a liquid (12), the system (10) comprising: - a fluid chamber (14) for receiving the liquid (12); - a light source (16) capable of emitting an excitation light beam (18) for illuminating the fluid chamber (14), the light beam (18) extending through the fluid chamber (14) in a longitudinal direction (X); - a matrix photodetector (20) capable of acquiring one or more images (In(x,y), In+1(x,y); I(x,y)) of radiation transmitted through the illuminated fluidic chamber (14); and - an information processing unit (21) comprising means (38) for determining, from the image (I(x,y)) or the plurality of images (In (x,y), In+1 (x,y)), an indicator (Ind2) characterising the agglutination of particles in the liquid (12), and means (40) for characterising the agglutination of particles in the liquid (12) as a function of the value of the indicator (Ind2); - the system being characterised in that the photodetector (20) is arranged at a distance (D2) of less than 1 cm from the fluidic chamber in the longitudinal direction (X).

13. System (10) according to claim 12, wherein the matrix photodetector (20) comprises a plurality of pixels, each pixel having dimensions each less than or equal to 4 µm.