WO2021205483A1 - Méthode et système de détection et de classification des bactéries et autres cellules dans un échantillon d'urine - Google Patents

Méthode et système de détection et de classification des bactéries et autres cellules dans un échantillon d'urine Download PDF

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WO2021205483A1
WO2021205483A1 PCT/IT2020/000033 IT2020000033W WO2021205483A1 WO 2021205483 A1 WO2021205483 A1 WO 2021205483A1 IT 2020000033 W IT2020000033 W IT 2020000033W WO 2021205483 A1 WO2021205483 A1 WO 2021205483A1
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sample
cells
urine sample
cellular
information
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PCT/IT2020/000033
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Paolo Galiano
Danut Adrian Cojoc
Maria Augusta DO REGO BARROS FERNANDES DE LIMA
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Alifax S.R.L.
Consiglio Nazionale Delle Ricerche
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Priority to PCT/IT2020/000033 priority Critical patent/WO2021205483A1/fr
Publication of WO2021205483A1 publication Critical patent/WO2021205483A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/41—Refractivity; Phase-affecting properties, e.g. optical path length
    • G01N21/45—Refractivity; Phase-affecting properties, e.g. optical path length using interferometric methods; using Schlieren methods
    • G01N21/453—Holographic interferometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N15/1468—Optical investigation techniques, e.g. flow cytometry with spatial resolution of the texture or inner structure of the particle
    • G01N15/147—Optical investigation techniques, e.g. flow cytometry with spatial resolution of the texture or inner structure of the particle the analysis being performed on a sample stream
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/4788—Diffraction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/487—Physical analysis of biological material of liquid biological material
    • G01N33/493—Physical analysis of biological material of liquid biological material urine
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03H—HOLOGRAPHIC PROCESSES OR APPARATUS
    • G03H1/00—Holographic processes or apparatus using light, infrared or ultraviolet waves for obtaining holograms or for obtaining an image from them; Details peculiar thereto
    • G03H1/04—Processes or apparatus for producing holograms
    • G03H1/08—Synthesising holograms, i.e. holograms synthesized from objects or objects from holograms
    • G03H1/0866—Digital holographic imaging, i.e. synthesizing holobjects from holograms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts
    • G06V20/698—Matching; Classification
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N2015/1006—Investigating individual particles for cytology
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N15/1434—Optical arrangements
    • G01N2015/1454—Optical arrangements using phase shift or interference, e.g. for improving contrast
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/4788—Diffraction
    • G01N2021/479—Speckle
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B21/00—Microscopes
    • G02B21/36—Microscopes arranged for photographic purposes or projection purposes or digital imaging or video purposes including associated control and data processing arrangements
    • G02B21/365—Control or image processing arrangements for digital or video microscopes
    • G02B21/367—Control or image processing arrangements for digital or video microscopes providing an output produced by processing a plurality of individual source images, e.g. image tiling, montage, composite images, depth sectioning, image comparison
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/48—Laser speckle optics
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03H—HOLOGRAPHIC PROCESSES OR APPARATUS
    • G03H1/00—Holographic processes or apparatus using light, infrared or ultraviolet waves for obtaining holograms or for obtaining an image from them; Details peculiar thereto
    • G03H1/04—Processes or apparatus for producing holograms
    • G03H1/0443—Digital holography, i.e. recording holograms with digital recording means
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03H—HOLOGRAPHIC PROCESSES OR APPARATUS
    • G03H1/00—Holographic processes or apparatus using light, infrared or ultraviolet waves for obtaining holograms or for obtaining an image from them; Details peculiar thereto
    • G03H1/0005—Adaptation of holography to specific applications
    • G03H2001/0033—Adaptation of holography to specific applications in hologrammetry for measuring or analysing
    • G03H2001/0038—Adaptation of holography to specific applications in hologrammetry for measuring or analysing analogue or digital holobjects
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03H—HOLOGRAPHIC PROCESSES OR APPARATUS
    • G03H1/00—Holographic processes or apparatus using light, infrared or ultraviolet waves for obtaining holograms or for obtaining an image from them; Details peculiar thereto
    • G03H1/0005—Adaptation of holography to specific applications
    • G03H2001/005—Adaptation of holography to specific applications in microscopy, e.g. digital holographic microscope [DHM]
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03H—HOLOGRAPHIC PROCESSES OR APPARATUS
    • G03H1/00—Holographic processes or apparatus using light, infrared or ultraviolet waves for obtaining holograms or for obtaining an image from them; Details peculiar thereto
    • G03H1/04—Processes or apparatus for producing holograms
    • G03H1/0443—Digital holography, i.e. recording holograms with digital recording means
    • G03H2001/0452—Digital holography, i.e. recording holograms with digital recording means arranged to record an image of the object

Definitions

  • the invention pertains to the technical field of diagnostics, and more specifically to a method and system for determining specific parameters of a liquid urine sample by obtaining optical phase information (OPI) and speckle pattern information (SPI) by digital holographic microscopy (DHM) and speckle microscopy (SM).
  • OPI optical phase information
  • SPI speckle pattern information
  • DHM digital holographic microscopy
  • SM speckle microscopy
  • the method offers a non- destructive manner of analyzing bacteria and other cells in urine samples and can be used for the detection of bacteria, leucocytes, erythrocytes and epithelial cells and classification of the urine samples.
  • OPI and SPI are obtained and compared to a set of values in a database relating to cellular parameters.
  • the present invention also discloses a system that employs the method by DHM and SM of the invention as well as a method for updating and/or improving a database comprising set of parameters linked to OPI and the database related thereof.
  • urinalysis is useful to detect bacterial or fungi/yeast infections of urinary system.
  • the Iris iRICELL1500 from Beckman Coulter https://www.beckmancoulter.com/it/products/urinalysis/iricell) integrates urine chemistry and microscopy into a fully automated walk-away solution that is easy to use and maintain. Iris optimizes and advances urinalysis and body fluid testing through its proprietary Digital Flow Morphology (DFM) technology using Auto- Particle Recognition (APR) Software for standardized and accurate results. Automatically classify 12 particles and sub-classify 27 particles with DFM. APR system reduces subjectivity. Process preservative tube samples on the iQ200 for greater flexibility.
  • DFM Digital Flow Morphology
  • APR Auto- Particle Recognition
  • Digital holographic microscopy is an imaging technique that provides phase information (optical path) and hence three-dimensional (3D) information on the sample [1995_JMicrosc_Zicha].
  • the hologram is first recorded on a digital camera as the interference pattern between the reference beam and the object beam diffracted by the sample.
  • the recorded hologram is then digitally processed to reconstruct the intensity and the phase of the object beam.
  • the phase contains the 3D information in the optical path term, which is the product between the refractive index of the material and the geometrical path of the light.
  • DHMs for quantitative study of living cells, imaging of various cell types, including SKOV-3 ovarian cancer cells, fibroblast cells, testate amoeba, diatom skeletons, and red blood cells.
  • DHMs for quantitative phase measurements (QPM) of living cell cultures up to confluence, without the use of any contrast agent and with very low illumination power, high content screening, time lapse measurements and diagnostic. Used in conjunction with the optional fluorescence module, it enables simultaneous DHM and fluorescence measurements.
  • PHI Phase Holographic Imaging AB
  • the Ozero system has been recently employed for label-free leukemia detection by DHM [2018_AdvScience_Ugele].
  • Classification of the cells in healthy and leukemic cells is performed by extracting cell parameters as the optical volume and height, based on the phase information obtained by DHM, and using Principal Component Analysis (PCA).
  • PCA Principal Component Analysis
  • the technique requires sample preparation and 2D hydrodynamic focusing of the sample flow to about 10 microns as required by the depth of focus of the system.
  • Different versions of DHM have been proposed in literature in the last years for new applications in biomedicine.
  • quantitative phase microscopy has been proposed to extract spatial signatures of cancer cells
  • the purpose of the present invention is to provide a method and system for determining specific parameters of a liquid urine sample by obtaining optical phase information (OPI) by digital holographic microscopy (DHM) and speckle pattern information (SPI) by speckle microscopy (SM).
  • OPI optical phase information
  • DLM digital holographic microscopy
  • SPI speckle pattern information
  • SM speckle microscopy
  • a further purpose is to provide a system configured to analyze and classify urine samples into negative and positive samples.
  • the Applicant has devised, tested and embodied the present invention to overcome the shortcomings of the state of the art and to obtain these and other purposes and advantages.
  • the present invention provides for a free-label method and system for analyzing liquid urine samples in a non-destructive, fast, inexpensive and objective manner and to detect the presence of bacteria in three (low / medium / high) levels, detect and count leukocytes, erythrocytes and epithelial cells present in the sample.
  • said liquid urine sample are analyzed by a digital holographic microscope (DHM) allowing to obtain also speckle pattern information (SPI)).
  • DHM digital holographic microscope
  • the practitioner is provided with a digital report, comprising diagnostic information on the presence, concentration and size of bacteria in the urine sample as well as a set of cellular parameters related to cells present in the sample. This will give the practitioner or pathologist the chance to evaluate the raw sample in an unbiased manner, by taking the provided cell sample parameters into account. Diagnosis can be solely based on the report provided by the system or, if desirable, the practitioner or pathologist can proceed by more conventional means of diagnosing. DHM and SM provide the detection of negative and positive samples by a fast screening of urine samples. DHM provides both a highly specific and sensitive method for analyzing urine samples, which is often a problem for other analytical methods currently known.
  • DHM enables the study of living cells without the need for markers or dyes and enables quantitative analysis of the morphology of cells suspended in fluid as well as various sub-sections of said cells by obtaining a three-dimensional image from the optical phase information.
  • the possibilities of DHM have increased during the last years due to an increase in the development of digital sensors and computers.
  • the method allows to visualize cells without any staining up to a degree of sub-cellular distinguishability which allows efficiently segmenting the cells, counting their number and reliably classify them according to their type.
  • SM allows studying behavior of bunch of small particles and enables qualitative analysis of the bacteria concentration.
  • SM has been improved in the last years by the availability of cameras with higher sensitivity and resolution.
  • SM in the context of the current invention, is a complementary technique to DHM, speckle pattern information is employed when the bacteria concentration is high and DHM cannot work.
  • the SPI derived from the SM, has been found by the inventors to be a highly reliable parameter for detecting bacteriuria with high concentration. SPI is defined by intensity distribution and granularity. These two parameters determine direct sample classification in high concentration bacteria.
  • the optical path difference is derived from the optical phase information (OPI).
  • OPD has been found by inventors to be a consistent parameter, which is correlated with other parameters extracted from the holographic information, allows to evaluate the presence of bacteria and its concentration over the sample and to classify the sample in one of the three bacteria concentration categories: low/medium/high.
  • At least one cellular parameter is derived from holographic information.
  • the cellular size and shape, derived from the holographic information, have been found by the inventors to be highly reliable parameters for cell detection and identification of cell types.
  • Cellular size is characterized by a set of sub-parameters: maximum lengths in two orthogonal directions measured on the two-dimensional projection of the cell hologram, cell area from the same projection, cell maximum height from the OPI.
  • the second parameter, the cell shape is also characterized by a set of sub-parameters: cell volume calculated from the 3D reconstruction from OPI, ratio between cell volume and cell area, nucleus volume, ratio between cell volume and nucleus volume, cell height variation.
  • a scoring vector SV is appointed to the cells of said cell sample, based on said cellular parameters. Said SV determines the recognition and classification of said cells
  • the scoring vector SV above defined is a vector that comprises elements calculated using the cellular parameters described above and determined during measurement and processing.
  • the elements can be: size, shape, volume area, height, nucleus volume.
  • Scoring Vector SV For each type of cell a reference vector is defined and compared by correlation with the measured vector. The result is called Scoring Vector SV. This is used to validate the measurement according to the values of each element of the SV. The criterium depends on the type of measurement and tolerance.
  • Gram positive and Gram negative bacteria are discriminated from the holographic information, analyzing the size and the shape of bacteria in a given volume of a static sample. This allows to choose the specific antibiotics for the two classes of bacteria and check the effect of antibiotics according to the bacteria type.
  • the effect after treatment with antibiotics is evaluated from the bacteria’s vitality determined by morphological parameters (changes in the size and shape parameters) and dynamic parameters (diffusion coefficient, spatial and time variation of the intensity of the scattered light) of the bacteria freely moving in the urine sample.
  • a relevant number of bacteria are analyzed and a score vector, including the parameters above mentioned, the treatment length and antibiotic concentration is elaborated to evaluate the antibiotics effect.
  • the antibiogram test can be performed in a continuous flow on the same urine sample used in the system by the use of DHM.
  • a scoring vector SV is appointed to each sample, whereby the SV determines the classification of said urine sample, cell content and cell type.
  • SPI Speckle Pattern Information
  • OPI Optical Phase Information
  • a scoring vector SV is appointed to each sample, whereby the SV determines the classification of said urine sample, cell content and cell type.
  • FIG. 1 depicts a schematic overview of one embodiment of the current invention, where flowing urine is analyzed
  • FIG. 2 depicts a schematic overview of the processing for sample classification
  • FIG. 3 depicts an example of recorded digital hologram and the reconstructed optical path difference OPD of 1 microLiter urine sample, where two bacteria (marked by squares) are identified;
  • FIG. 4 depicts a recorded hologram and the reconstruction of the OPD for a erythrocyte detected in the urine sample. The cell height is measured;
  • FIG. 5 depicts a recorded hologram and the reconstruction of the OPD for a leukocyte detected in the urine sample. The cell height is measured;
  • FIG. 6 depicts a recorded hologram and the reconstruction of the OPD for an epithelial cell detected in the urine sample. The cell height is measured;
  • FIG. 7 depicts a recorded hologram and the reconstruction of a Candida yeast cell detected in the urine sample. The cell height is measured;
  • - Figure 8 depicts a recorded hologram and the reconstruction of a positive sample with high concentration of bacteria. Both the hologram and reconstruction show speckle like structure; - Figure 9 depicts a recorded hologram of crystals detected in urine sample.
  • FIG. 10 depicts the classification results obtained with the invention for urine samples previously analyzed by flow-cytometry. Dotted lines define the 6 groups of samples. The description of samples is given in table 1. It is understood that elements and characteristics of one embodiment can conveniently be incorporated into other embodiments without further clarifications.
  • the present invention provides for a method and system for determining specific parameters of a liquid urine sample by obtaining optical phase information (OPI) and speckle pattern information (SPI) by digital holographic microscopy (DHM) and speckle microscopy (SM).
  • OPI optical phase information
  • SPI speckle pattern information
  • DLM digital holographic microscopy
  • SM speckle microscopy
  • a method to detect bacteria and other cells in a urine sample comprising the following steps: a) providing a urine sample; b) analyzing said urine sample by digital holographic microscopy (DHM) to obtain optical phase information (OPI); c) deriving at least one cellular parameter from said analysis, and; d) classifying bacteria and other cells of said urine sample based on said at least one cellular parameter derived from said analysis obtained from said DHM.
  • DHM digital holographic microscopy
  • OPI optical phase information
  • a system 10 according to the present invention is a custom inverted microscope combined with a custom digital holographic microscope (DHM).
  • the system 10 is depicted schematically in Figure 1.
  • the cover of the system 10 is not showed to make visible the internal elements installed on a support 12 and a base 14,
  • the inventive system 10 for the classification of bacteria and cells in a urine sample comprises, as main components: a) a digital holographic microscope (DHM) comprising an interferometer like subsystem, composed by: coherent light source 22 with fiber coupler and splitters 22a and 22b, and an imaging subsystem composed by the objective lens 26, tube lens 28 and digital recording device 32 connected to a server; b) at least one exchangeable sample vial or sample carrier or capillary 16 comprising a urine sample; and c) a computer 40 and software capable of acquiring data and providing a digital report related to said urine sample, wherein the digital report related to said cell sample comprises classification of said cells of the cell sample, wherein the classification of said cells is based on at least one cellular parameter derived from optical phase information of the urine sample obtained from the DHM, and wherein the at least one cellular parameter comprises a characteristic the cells.
  • DHM digital holographic microscope
  • the sample carrier or capillary 16 is, for example a glass capillary, with an inner diameter between 0.3 to 1 mm.
  • the urine sample is flowed through the sample capillary 16 by a drawing device 18, for example a syringe pump, at flow rates going from 10 to 200 microliter / min.
  • a vial distributor 20, fixed or rotating, may cooperate with the drawing device 18 to feed exchangeable sample vials containing urine samples.
  • the sample capillary 16 may finish in a waste collector 21, e.g. a tank to collect analyzed urine.
  • the coherent light source 22 e.g. a laser diode (LD) emitting coherent laser- light, is coupled in a single mode fiber and it is used to illuminate the sample flowing in the sample capillary 16 for the digital holographic mode.
  • LD laser diode
  • a non-coherent light source 23 e.g. a white LED, used to illuminate the urine sample for brightfield imaging, may be also provided.
  • the two illumination modes are coupled towards the urine sample by a dichroic mirror 24 and work alternatively with timing controlled by LED 23 and Laser Diode 22 drivers from a control unit 19.
  • the combination of illuminations of the sample represents the first original solution allowing to observe the sample both in brightfield and holographic imaging.
  • the system 10 uses a simple lens. This allows having a compact system and reducing the internal reflections present in a microscope objective with more lenses that would disturb the interference pattern of the recorded digital hologram.
  • the objective lens 26 and the tube lens 28 may be associated to slides 30 that allow focal length variation.
  • a second digital recording device 34 different of that used to record holograms, can be provided.
  • the digital recording devices are digital cameras such as CCD-camera or CMOS-camera.
  • the brightfield image is formed on a first CMOS camera 34 with 8 bit depth / pixel, while the hologram is recorded on a CMOS second camera 32 with 16 bit/pixel (high dynamic range) and fast acquisition (up to 500 frames/second).
  • the camera used for brightfield recording may be connected to the server as well.
  • Both cameras 32, 34 are placed at a focal fTL distance from the tube lens 28, the two optical paths being separated by a dichroic mirror 36.
  • Brightfield imaging allows fast inspection of the sample previously to the holographic imaging and decision to go through this second step.
  • brightfield imaging of the sample can be recorded also during the holographic recording, providing supplementary information on the sample.
  • the hologram is obtained by interference of a first laser beam generated from source 22a passing through the sample and a second laser beam generated from source 22b, called reference beam, which is provided by the same diode laser 22 and coupled in optical fiber 25.
  • the reference beam 22b is introduced in the optical path of the microscope by a cube beam splitter 38, placed between the objective lens 26 and the tube lens 28.
  • the end of the optical fiber 25 is positioned at a focal distance fTL from the tube lens 28.
  • This solution represents the third original element, that simplifies the setup.
  • the reference beam is introduced after the tube lens requiring an additional optical element, which complicates the alignment and perturbates the quality of the hologram due to the internal reflections.
  • the fourth original element is related to the holographic principle and the way in which the optical Fourier transforms are implemented.
  • the hologram is formed by interference between the object beam (laser beam passing through the sample) and the reference beam.
  • the axes of the two beams should be slightly tilted and this is controlled by the angle of the cube beam splitter.
  • the second condition is that the optical setup should perform two Fourier transforms of the sample. In a classic setup, the sample is illuminated with a plane wave and the first Fourier transform is obtained in the focal plane of the objective lens. The second Fourier transform is performed by the tube lens, and it is obtained on the sensor of the CMOS camera (in the focal plane of the TL).
  • the tube lens and the objective lens should be confocal, i.e. the focal planes are in the same plane.
  • the solution of the present application uses the fact that a Fourier transform can be obtained also with spherical illumination.
  • the exit of the fiber is micron size, hence we can consider it as a point source generating spherical beam/wave.
  • the Fourier transform is obtained in a plane after the objective lens, conjugated with the plane of the exit of the fiber. Since the focal length fob is short, this plane is close to the focal plane of the objective lens with the exit of the fiber being at two focal distances, instead of one, from the objective lens.
  • the hologram in this configuration is an interference pattern containing also a blurred image of the sample ( Figure 4).
  • the image is not in focus and not clearly represented. Therefore, the brightfield image, providing an image in focus, is useful to monitor the sample.
  • the hologram contains more information about the object, i.e. besides the intensity information present in the brightfield image it contains the phase information. This phase information is reconstructed numerically from the intensity information of the recorded digital hologram. It provides the user with additional useful information about the sample, as the height and volume which cannot be by brightfield imaging.
  • the urine sample is flowed through the capillary and the holograms are acquired at a frame rate of 100 fps.
  • the stack of holograms can be organized in a movie .avi extension. Lower or higher frequencies can be chosen for the frame rate, according to the application. Processing the digital holographic video and extracting parameters for sample classification
  • the speckle effect in the hologram and in the OPD image is analysed.
  • the speckle is evaluated by the granularity and intensity distribution and allocating a score.
  • a high score means high speckle effect, the granularity is small and intensity distribution randomly distributed over the image.
  • the evaluation is performed over all the holograms and reconstructions, and an average score is calculated.
  • a high score indicates a high bacteria concentration and the sample is classified as positive. It is the abundant presence of bacteria (turbulence) which creates the speckle effect and makes it difficult reconstructing correctly the holograms. This is an original, fast and reliable assay to classify positive plus samples.
  • the OPD is analysed and the OPD coefficient is calculated for all the frames.
  • the coefficient over a frame is determined selecting six sub-regions of size 30x30 microns, calculating firstly the mean OPD for each, and then the mean over six and standard deviation (SD). If the sub-regions are all similar (SD ⁇ imposed value) the frame coefficient fOPD is calculated. The mean value over all the frames gives the cOPD. This coefficient is compared against a pre-imposed value.
  • Gram positive, and Gram negative bacteria can be discriminated from the holographic information, analyzing the size and the shape of bacteria in a given volume of a static sample. This allows to choose the specific antibiotics for the two classes of bacteria and check the effect of antibiotics according to the bacteria type.
  • the effect after treatment with antibiotics is evaluated from the bacteria’s vitality determined by morphological parameters (changes in the size and shape parameters) and dynamic parameters (diffusion coefficient, spatial and time variation of the intensity of the scattered light) of the bacteria freely moving in the urine sample.
  • a relevant number of bacteria are analyzed and a score vector, including the parameters above mentioned, the treatment length and antibiotic concentration is elaborated to evaluate the antibiotics effect.
  • a method for updating and/or improving a database comprising thresholds linked to holographic information comprising the steps of: characterized in that. a) obtaining holographic information linked to a sample wherein said holographic information is obtained using digital holographic microscopy (DHM); b) deriving at least one parameter from said holographic information, wherein said at least one parameter comprises optical path difference of cells in the sample; c) comparing said parameter to said thresholds stored in database; d) classifying objects in the sample based on said comparison of said parameter, and said thresholds; e) reporting said classification of said objects; f) obtaining feedback with regards to said classification; and g) updating said database on the basis of said feedback.
  • DLM digital holographic microscopy
  • a database of objects comprising a set of thresholds, queries and holographic information and/or parameters related to a characteristic of the morphology of cells in a urine sample, wherein a) said holographic information is obtained from a sample using a digital holographic microscope and/or parameters derived thereof; b) said thresholds and queries are related to the analysis of said holographic information and/or parameters; wherein the database further comprises c) classifications of the objects derived from said holographic information obtained from the sample using the digital holographic microscope and or parameters derived thereof; d) validation of susceptibility test of any antibiotic agent based on morphological cell analysis before and after sample treatment. d) image identification; e) identification information.

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Abstract

La présente invention concerne une méthode et un système permettant de détecter et de classer des bactéries et d'autres cellules, dans des échantillons d'urine primaire et de classer les échantillons. La méthode comprend la fourniture d'un échantillon d'urine liquide ; l'obtention d'informations de phase optique à partir de l'échantillon d'urine liquide par holographie numérique et microscopie de granularité ; la localisation et le suivi des cellules s'écoulant dans l'échantillon cellulaire fluide ; la dérivation des paramètres cellulaires (p. ex. taille, forme, volume, rapport d'aspect) à partir des informations de phase optique, et la classification des cellules sur la base des paramètres cellulaires extraits.
PCT/IT2020/000033 2020-04-08 2020-04-08 Méthode et système de détection et de classification des bactéries et autres cellules dans un échantillon d'urine WO2021205483A1 (fr)

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