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WO1999053288A2 - Logiciel interpretatif de l'immunoblot de lyme - Google Patents

Logiciel interpretatif de l'immunoblot de lyme Download PDF

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Publication number
WO1999053288A2
WO1999053288A2 PCT/US1999/008160 US9908160W WO9953288A2 WO 1999053288 A2 WO1999053288 A2 WO 1999053288A2 US 9908160 W US9908160 W US 9908160W WO 9953288 A2 WO9953288 A2 WO 9953288A2
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WO
WIPO (PCT)
Prior art keywords
band
immunoblot
bands
test specimen
processing
Prior art date
Application number
PCT/US1999/008160
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English (en)
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WO1999053288A3 (fr
WO1999053288A9 (fr
Inventor
Andrew E. Levin
A. Scott Oddo
Original Assignee
Immunetics, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Immunetics, Inc. filed Critical Immunetics, Inc.
Priority to AU36428/99A priority Critical patent/AU3642899A/en
Publication of WO1999053288A2 publication Critical patent/WO1999053288A2/fr
Publication of WO1999053288A9 publication Critical patent/WO1999053288A9/fr
Publication of WO1999053288A3 publication Critical patent/WO1999053288A3/fr

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Classifications

    • 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
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • 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
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/558—Immunoassay; Biospecific binding assay; Materials therefor using diffusion or migration of antigen or antibody
    • G01N33/561—Immunoelectrophoresis

Definitions

  • the invention relates generally to systems and methods for interpreting immunoblot test results, and more particularly to systems and methods that can generate an image of an immunoblot test and process the image to make a diagnosis for the tested condition or conditions
  • Binding assays are routinely used to screen for and diagnose a host of diseases and conditions, including Lyme disease, herpes, acquired immunodeficiency syndrome (ALDS), streptococcal infections, lupus and pregnancy
  • Such assays are relatively simple in theory, utilizing the binding affinity between two or more binding members to detect and/or quantify the presence of one of the members, referred to herein as the analyte Binding members comprise a wide range of substances, including antigens, antibodies, haptens, complimentary nucleic acid sequences, ligands, small molecules and receptors
  • Antigen-antibody binding member pairs used in immunoassays currently enjoy the most widespread use
  • a common format of a binding assay involves immobilizing a binding member specific for the analyte on a paper-like sheet or membrane The membrane is then contacted with the test sample and appropriate reagents under conditions allowing binding to occur between the immobilized binding member and any analyte in the sample, with means for detecting binding events also provided Often a labeled second binding member which binds to the first binding member-analyte complex is added to provide a detectable signal on the membrane.
  • the sandwich immunoassay is an example of one commonly used binding assay for antibody detection.
  • the antigen is immobilized on a solid substrate.
  • Antibody containing solution e.g., diluted serum
  • Antibodies specific to the antigen bind to it, and unbound antibodies are then removed by buffer washes.
  • a detection agent which may typically be a secondary antibody conjugated to an enzyme, is then incubated with the primary antibody-antigen complex.
  • ah enzyme substrate is added which is converted into a visual, detectable product whenever the enzyme is located.
  • Such multi-step sandwich immunoassays can be developed in many different ways depending on assay requirements.
  • the Western Blot is another example of a commonly used immunoassay.
  • the Western Blot method comprises a sequence of incubation and wash steps performed on a membrane bearing electrophoretically resolved antigen bands. Typically, the membrane is cut into narrow strips, each bearing the identical pattern of antigen bands. Strips are then processed in reagent solutions individually in narrow trays, each typically holding 0.5-2.0 ml. In the first step, the strip is incubated with a blocking solution containing a non-specific protein, e.g. , non-fat dry milk, bovine serum albumin, newborn calf serum or gelatin.
  • a non-specific protein e.g. , non-fat dry milk, bovine serum albumin, newborn calf serum or gelatin.
  • the strip After washing off excess blocking solution with a wash buffer, typically a physiological saline buffer containing a low percentage of detergent, the strip is then incubated with antibody solution.
  • Antibody solution may be diluted human or animal serum, cerebrospinal fluid, dried blood spot eluate, monoclonal antibody, to name a few. Unbound antibody is then washed off with buffer, and the strip is incubated in the detection reagent.
  • the detection reagent could be goat-anti-human IgG-alkaline phosphatase conjugate.
  • Unbound detection reagent is washed off with buffer, and finally the substrate (for alkaline phosphatase, a common substrate is 5-bromo-4-chloro-3-indolyl phosphate plus nitroblue tetrazolium) for the detection enzyme is added.
  • the conversion of the substrate to a visually detectable product is allowed to proceed until optimal visualization of bands, and then substrate is washed away
  • the strip is typically dried, providing a permanent record of the assay result
  • Bands on the strip indicating antibody reactivity can be compared with control strips to determine the specificity of the immunoreaction
  • a template is provided to help the clinician align the bands of the test strip with the bands that appear in the control strip.
  • a positive test result is defined as the appearance of certain combinations of specific bands For example, an HIV Western Blot test requires the presence of two bands to be considered positive, while a Lyme Western Blot test requires five out often bands to be positive for
  • IgG or two out of three bands to be positive for IgM
  • the band pattern provided by an immunoblot test does allow a diagnosis of a patient's condition, the blot itself is difficult to read and it can require considerable skill to determine whether the protein markers indicate the presence of disease
  • the interpretative criteria for many immunoblot assays is still somewhat undetermined
  • the interpretive criteria recommended for the Lyme IgG immunoblot were originally described in a study by Dressier, et al . These criteria define ten diagnostically significant bands.
  • the systems and processes described here can, inter alia, analyze the band pattern generated by an immunoassay test.
  • the test membrane is imaged and the generated image signal is processed to identify the band pattern carried on the surface of the membrane.
  • the band pattern can then be processed to determine whether the test specimen indicates a positive or negative result for the disease, or diseases, of interest.
  • the systems and methods described herein can apply a neural net processing system that employs interpretation criteria developed from training a neural net with actual samples of band patterns.
  • results of experiments indicate that the neural net system can perform comparably to a trained laboratory technician, thereby providing an automated system that can readily interpret immunoblot test specimens and do so in a less labor intensive manner.
  • the systems and methods described herein can be employed or modified to process other types of assays, including any assay that requires filtering a sample material through a filter membrane, such as direct or sandwich assays.
  • the systems and methods described above can be employed for use with any binding assay that detects the presence of analytes in any biological material, e.g. , an antibody or antigen analyte in human or animal serum, urine, stool, saliva or other body fluids, secretions or excretions.
  • the systems and methods described herein also can be used to screen for the presence of microbial organisms, including bacteria, viruses and fungi.
  • the device of the invention can additionally be used to screen or otherwise characterize binding specificities of monoclonal antibodies, antibodies of different species and antibodies produced by genetic engineering or other in vitro techniques.
  • the systems and methods described herein can include systems for analyzing immunoblot band patterns comprising an imaging system for generating an image signal representative of an immunoblot test specimen, a band identification mechanism for processing the image signal to identify the presence of bands and for generating a band pattern signal, and a band interpreter for processing the band pattern signal to generate a signal representative of a diagnosis indicated by the immunoblot band pattern.
  • the band interpreter can include a neural net processing system, such as the ARTMAP processing system.
  • the band interpreter can include means for processing information representative of a characteristic of a patient associated with the immunoblot test specimen. Such characteristics can include the stage of disease associated with the immunoblot test specimen, as well as certain demographic data about the patient associated with the test specimen such as age and sex.
  • the band interpreter can include a neural net component capable of processing an image signal to identify band patterns for a plurality of different diseases.
  • the image system can generate an intensity signal that is representative of intensity of a band that occurs on the surface of a membrane.
  • the band interpreter can process an intensity signal to generate a diagnosis signal where the diagnosis indicates whether the band pattern corresponds to a known category of band patterns associated with the presence or absence of a particular disease.
  • the band identification mechanism can include a processor for detecting bands on an immunoblot test specimen that has been generated through electrophoresis.
  • the band identification mechanism can include a processor for detecting bands on an immunoblot test specimen generated through stripping as well as for identifying immunoblot test specimens generated through an immunodot process.
  • the band identification mechanism includes an overlap processor for comparing band data from a reference specimen to band data from an immunoblot test specimen, and for generating the band pattern signal therefrom.
  • the band identification mechanism can include a keyband processor for identifying keyband signals within the image signal and for employing the keybands for generating the band pattern signal.
  • the invention can provide systems for determining the position of a band in an immunoblot test specimen.
  • These systems can comprise an imaging system for generating an image signal that is representative of an image of the immunoblot test specimen, and a keyband processor for processing the image signal to identify a keyband within the image signal, and for employing the keyband to generate a band pattern signal representative of locations of bands on the immunoblot test specimen.
  • the keyband processor can optionally include an alignment processor for employing the location of the keyband and a set of stored ratios to identify the position of known bands within the image signal.
  • the immunoblot test specimen can carry bands generated during a Western blot test for Lyme disease and wherein the keyband processor can identify keybands associated with the p66, p60 and p58 bands.
  • the keyband processor can identify keybands for the p21 and pi 8 bands and for the p39 and p41 bands.
  • Fig. 1 depicts a functional block diagram of one system according to the invention:
  • Fig. 2 depicts graphically a Western blot test result of the type that can be processed by the system depicted in Fig. 1 ;
  • Figs. 3a and 3b depict an image, and a set of intensity data, generated from an image such as that depicted in Fig. 2;
  • Fig. 4 provides a flow chart of a process for identifying the position of bands within an image such as the image depicted in Fig. 3;
  • Fig. 5 depicts a process for interpreting a band pattern such as the band patterns produced by the process depicted in Fig. 4;
  • Fig. 6 depicts an integrated system for performing an immunoblot assay and interpreting the results thereof.
  • the test membrane is imaged and the generated image signal is processes to located and identify the visible bands that appear on the surface of the test membrane.
  • the system can perform a pre-processing step to enhance the image. Such pre-processing can include steps to enhance contrast, adjust brightness, define the edges of the bands, filter out low intensity image components and other similar processing steps.
  • the system can generate a band pattern signal that is representative of the bands that reacted during the immunoblot assay.
  • the band pattern signal is processed to determine whether the test membrane indicates a positive or negative test result for the disease, or diseases, of interest.
  • the illustrated systems and methods are directed to systems and methods for processing immunoblot assays, it will be understood by one of ordinary skill in the art that these systems and methods can be employed or modified to provide systems that can perform other types of assays, including any assay that requires filtering a sample material through a filter membrane, such as direct or sandwich assays.
  • Fig. 1 depicts one system 10 for processing the test results of an immunoblot assay to determine whether the assay indicates the presence of a particular disease or diseases.
  • Fig. 1 depicts a system 10 that includes a data processing system 12, an imaging system 14, having disposed thereon an immunoblot test specimen 16, a video monitor 18, a printer 20, a band identification mechanism 22, and a band interpreter 24.
  • the elements depicted in Fig. 1 operate to generate an image of the immunoblot assay test specimen 16 and process the generated image to determine whether the test specimen 16 indicates a positive or negative response for a particular disease or diseases.
  • the imaging system 14 connects via a data path to the data processor 12, and the data processor 12 includes the band identification mechanism 22 and the band interpreter 24 for processing the image signal generated by the image system 14 to determine the results of the immunoblot assay.
  • the determined results can be displayed graphically on the monitor 18, and a paper copy of the results can be made by printing the results on the printer 20.
  • the depicted data processing system 12 can be a conventional data processing platform such as an IBM PC-compatible computer running the Windows operating systems, or a Sun workstation running a Unix operating system.
  • the data processing system 12 can comprise a dedicated processing system that includes an embedded programmable data processing system that can include the band identification mechanism and the band interpreter 24.
  • the data processing system can comprise a single board computer system that has been integrated into a system for performing an immunoblot assay, such as the CodaVision instrument, developed and manufactured by the Immunetics Company of Cambridge, Massachusetts, and which can, inter alia, perform Lyme immunoblot tests.
  • the single board computer (SBC) system can be any suitable SBC, including the SBCs sold by the Micro/Sys Company, which include microprocessors, data memory and program memory, as well as expandable bus configurations and an on-board operating system.
  • the data processing system can comprise a micro- controller system that can comprise the band identification system 22 and the band interpreter 24.
  • the micro controller system can also be embedded into an assay processing system, such as the above-mentioned CodaVision system.
  • the microcontroller can comprise any of the commercially available micro-controllers including the 8051 and 6811 class controllers.
  • the micro controllers can execute programs for implementing the image processing functions as well as for controlling the elements of the assay system, such as by executing motor control processes.
  • the data processing system can also include signal processing systems for performing the image processing. These systems can include any of the digital signal processors (DIPS) capable of implementing the image processing functions described herein, such as the DIPS) capable of implementing the image processing functions described herein, such as
  • DIPS based on the TMS320 core including those sold and manufactured by the Texas Instruments Company of Austin, Texas.
  • Fig. 1 graphically depicts the band identification mechanism 22 and the band interpreter 24 as functional block elements, it will be apparent to one of ordinary skill in the art that these elements can be realized as computer programs or portions of computer programs that are capable of running on the data processor platform 12 to thereby configure the data processor 12 as a system according to the invention.
  • Fig. 1 depicts the system 10 as an integrated unit of an imaging system 14 that couples to a data processing system 12, it will be apparent to those or ordinary skill in the art that this is only one embodiment, and that the invention can be embodied as a computer program that can process operate on an image file that includes image data representative of the surface of a membrane.
  • the imaging system 12 it is not necessary that the imaging system 12 be directly coupled to the data processing system 12, and instead the images generated by the imaging system 14 can be imported into the data processing system 12 by any suitable technique, including by file transfer over a computer network, or by storing the image file on a disk and mounting copying the disk into the file system of the data processing system 12.
  • the imaging system 14 can be remote from the data processing system 12.
  • the invention can include embodiments, wherein users at multiple remote sites create images of the membranes and deliver the images to a remote processing system that can identify and interpret the band patterns in the images.
  • the imaging system 14 is depicted in Fig. 1 as an optical scanner of the type commonly employed for creating an electronic image of a 2-dimensional recording of data, such as a drawing, body of text, or photograph.
  • One such scanner is the Apple One scanner manufactured and sold by the Apple Computer Company of Cupertino, California.
  • Digital images of the immunoblot assay can be captured employing the Ofoto flatbed scanner software of Light Source Computer Image, distributed by Apple Computer.
  • Another suitable scanner is the Scan Jet C, from Hewlett-Packard, Palo
  • Alto, California which can scan the image of the membrane to a TIFF file that can be imported into the data processing system 12.
  • the imaging system can include a CCD camera for taking an image of the surface of the immunoblot assay.
  • the CCD camera can be disposed above the membrane 16, and employed to capture an image of the band pattern on the membrane. The captured image can be transferred to the data processing system 12.
  • the CCD camera can be a stand alone device or can be part of an integrated computer imaging system.
  • a computer imaging system such as the PC Vision System manufactured and sold by the Imaging Technology Company of Woburn,
  • the CCD camera can be positioned above the membrane for taking an image thereof.
  • the immunoblot blot assay can be performed with materials that will enhance the image quality of images generated by the imaging system 14.
  • the immunoblot assay can be performed using materials that are photo-active or photo-responsive, contain certain colors, have selected surface characteristics that can increase or decrease reflectiveness of light, including light at the infrared wave length.
  • a light table, or other lighting system can be included that control the environmental light conditions that are in effect during the imaging step.
  • the imaging system 14 can be adapted or modified for imaging immunoblot blot test specimens.
  • the imaging systems can employ lenses, filters, or other devices for increasing the imaging systems effectiveness at generating an accurate image of the band pattern carried on the membrane surface.
  • the CCD cameras can detect a plurality of colors by the use of appropriate exciting sources and filters, and with the selection of photo-active or photo-responsive dyes, or analytes. Thus, systems can be employed that use multi-color imaging techniques to more clearly differentiate the bands on the membrane 16.
  • the CCD camera can generate a file in any format, such as the GIF, JPEG, TIFF, PBM, PGM, PPM, EPSF, XI 1 bitmap, Utah Raster Toolkit RLE, PDS/VICAR, Sun Rasterfile, BMP, PCX, PNG, IRIS RGB, XPM, Targa, XWD, possibly PostScript, and PM formats on workstations and terminals running the XI 1 Window System or any image file suitable for import into the data processing system 12.
  • the imaging system can include conversion filters that can convert an image signal of one format, such as EPSF, to another file format, such as PPM.
  • EPSF image signal of one format
  • PPM file format
  • the Western blot test can be conducted with a stain that has a color selected to be readily detected by the digital scanner.
  • a stain that has a color selected to be readily detected by the digital scanner.
  • blue stainings can be employed to provide protein bands with a bluish-purple color that is generally understood as being easily detected by commercial flatbed optical scanners.
  • a sheet of translucent colored plastic can be placed on the scanner to enhance the intensity of the acquired image. For example, in one practice an amber-colored acetate overhead transparency (No.
  • the imaging system will be able to generate an image of the immunoblot assay that captures the band patterns carried thereon.
  • an image of an immunoblot test specimen is depicted in Fig. 3 wherein an electronically recorded image of the band patterns of five strips, each having a band pattern thereon, is depicted.
  • the membrane 16 being imaged by the imaging system 14 can be a nitrocellulose membrane bearing electrophoretically resolved antigens of Borrelia burgdorferi was prepared by standard blotting procedures (e.g. , Towbin, H. , Stehelin, T. and Gordon, L , Proc. Nat. Acad. Sci. U.S.A. 76:4350-4354 (1979)), then washed 30 minutes in distilled water. Additional stripes of defined antigens may be applied to the membrane at this point by non-electrophoretic methods.
  • the nitrocellulose membrane can have a 0.2 ⁇ pore size and can be obtained from commercial suppliers such as Schleicher & Schuell (Keene, NH), Whatman, Inc.
  • the nitrocellulose membrane can be cut to fit the cassette, such as being cut to 2" wide x 4" long.
  • the wet membrane can be placed over an identically sized piece of dry filter paper.
  • a variety of filter papers may be used, but a paper specifically intended for wicking is optimal, such as #320 paper from Ahlstrom Filtration Inc.
  • the membrane 16 can be prepared by a typical multi-step binding assay, wherein each reagent or wash solution is added sequentially as soon as the previous solution has been fully aspirated through the membrane.
  • the sequence of solutions generally comprises, in order: blocking solution (e.g. , detergent Tween-20), primary antibody (diluted human serum), three washes with buffer containing phosphate- buffered saline and Tween-20 detergent, secondary antibody (e.g. , diluted anti-human IgG-alkaline phosphatase conjugate), three more buffer washes, distilled water, and enzyme substrate (e.g.
  • an analyte is bound to a binding member immobilized on the membrane, and a labeled second binding member is bound thereto to provide a detectable signal.
  • labels or indicator schemes which provide a detectable signal that analyte binding has occurred can be employed with the systems described herein, including, for example, direct labels such as fluorescent, radioactive and chromophoric labels. Labels which may require development or enzymatic reagents, such as horseradish peroxidase or alkaline phosphatase, can also be utilized. Additionally, indirect label vehicles such as Protein A or avidin/biotin methods, know to those skilled in the art, can also be adapted for use with the apparatus and methods described herein.
  • binding assays which can produce membranes that can be analyzed with the devices described herein include assays to detect the presence of antibodies specific for bacterial proteins of Borrelia burgdorferi which causes Lyme disease, for viral proteins of HSV which causes herpes, for viral HIV proteins implicated in acquired immunodeficiency syndrome (AIDS), for antigens specific to human chorionic gonadotropin (HCG) to detect pregnancy, for rheumatoid arthritis, and for a variety of bacterial and viral infections. It is also contemplated that the devices and processes of the invention be used to screen for toxins such as, e.g. , that of Clost ⁇ dium difficile, and to screen for specific nucleic acid sequences to detect, e.g.
  • the membrane 16 can be prepared by a striping process as known in the art for forming a pattern thereon that can be employed during an immunoblot test. Under any method of preparation, the membrane 16 can be prepared to detect one or more diseases, and the type of the disease dose not matter.
  • Fig. 1 further depicts a monitor element 18 that can be a conventional CRT monitor capable of displaying data to a system operator.
  • the CRT monitor 18 can connect to the data processor 12 via a data communication path that allows the data processor 12 to present to an operator information regarding the processing of the image signal collected from the imaging device 14.
  • Fig. 1 depicts that the system 10 can include an input device 28 depicted in Fig. 1 as a conventional keyboard that allows the operator to enter information into the data processor 12.
  • the input device 22 allows the operator to control the processing of the image signal as well as to provide the data processor 12 with information to be considered during the image processing operations.
  • an operator can employ the input device 22 to respond to a graphical user interface that is presented by a program executing on the data processor 12 and which prompts the operator to enter information associated with the immunoblot specimen 16.
  • information associated with the immunoblot specimen 16 can include identification information that identifies the patient or patients associated with the immunoblot assay test 16, as well as information regarding patient histories, such as demographic information about the patient including their age, sex, and the suspected stage of illness.
  • the information entered by the operator through the input device 22 can be employed by the data processor 12 to configure the band identification mechanism as well as the band inte ⁇ reter to more accurately process the image data generated by the imaging device 14.
  • the monitor element 18 depicted in Fig. 1 is shown as a CRT monitor of the type employed with a conventional workstation, it should be apparent to one of ordinary skill in the art that the monitor element can be an LCD display that can be incorporated into an integrated stand alone unit.
  • the depicted keyboard 28 shown in Fig. 1 as a conventional keyboard that can be employed with a workstation can alternatively be a keypad of the type commonly employed with dedicated hardware systems. The keypad can provide to an operator the necessary interface for operating a stand alone system that can process an assay as well as inte ⁇ ret the band patterns produced by the assay.
  • the monitor and keyboard can be absent and the system can be realized as a turn-key system capable of fully automated operation.
  • the results of the tests can be printed by the printer 20 and can optionally be printed as labels that can be affixed to the membranes processed and analyzed by the system.
  • the printer element 20 can therefore be understood as a system that can provide a hard copy of the data results can be generated for the operator.
  • the printer 20 can provide labels that can be attached to lab notebooks, specimen containers and test results and which report the findings identified by the system 10.
  • the system can include a barcode system for reading and generating barcode data that can be representative of a patient's information.
  • an image signal is depicted graphically of a type that can be generated by the imaging system 14 and can be transferred via an electronic data path to the data processor 12.
  • the scanner 14 runs software that provides a .jpg file or a .ppm file to the data processor 12.
  • Fig. 3a graphically depicts the image information that can be passed from the imaging system 14 to the data processor 12 in a .ppm file.
  • the .ppm file can include an image of the immunoblot assay specimen 16.
  • the image 30 depicted in Fig. 3a comprises five strips 32, 34, 38, 40 and 42, each of which is represented as of one Western blot assay.
  • Each strip can correspond to a test run for an individual patient, thereby providing an image of the band patterns produced by five patients being tested for a particular disease, or diseases.
  • the band identification mechanism 22 processes the image 30 to identify the bands, and the location of the bands with each strip in the image 30. To this end, the band identification mechanism 22 acts as a human operator that would look at the image 30 and visually determine the location of the bands within the strips 32 through 42. To simulate this procedure, the band identification mechanism 22 processes the image 30 to determine the pattern of grey- scale changes that occurs within each of the strips 32 through 42. The changes in grey-scale are representative of the band pattern which in turn is representative of whether the test indicates positive or negative for the particular disease or diseases for which the test was run.
  • Fig. 3b depicts that the image 30 can be subdivided into its individual strips.
  • the strip depicted in Fig. 3b corresponds to strip 42 of the image 30 shown in Fig. 3a.
  • Fig. 3b further shows that a centrally disposed axis 44 transverses the full length of the strip 42.
  • the axis 44 is representative of an image process carried out by the band identification mechanism 22 wherein the grey-scale level of the strip 42 is taken for each point, for the granularity of interest, along the length of the strip 42.
  • this sampling along the axis 44 helps eliminate or reduce errors in image processing that may arise from blurred, curved, or slanted bands that may appear within the strip 42.
  • Fig. 3B depicts a process wherein samples are taking along one centrally disposed axis
  • multiple axes that transversed the length of the strip can be employed for taking multiple samples of the grey-scales at the location of the bands.
  • These multiple samples can be processed, such as by a simple averaging process, to generate the grey-scale intensity level that will be associated with a particular location along the length of the strip 42.
  • Other techniques can be employed for determining the intensity at different locations on the strip 42, without departing from the scope of the invention.
  • the grey-scale level of the band pattern is detected by assigning grey-scale levels to each section of the test strip 42.
  • Fig. 3b shows that at the top of the strip 42 the grey-scale level is indicated as 32 and remains at 32 until it changes at the section 48 which has an indicated grey- scale level of 128.
  • the grey-scale level after section 48 returns to a grey-scale value of 32 in section 50 and remains so until it changes to the grey-scale level of 64 in section 52.
  • Fig. 3b depicts a technique wherein the band identification mechanism demarks the portions of the strip 42 wherein variations in the grey-scale level occur.
  • a threshold variation grey-scale value can be set such that a variation of a predetermined amount of grey-scale value, such as five points on a scale of 0 to 255 that must occur before a portion of the strip 42 will be deemed to have changed in grey-scale.
  • Fig. 3b shows that band intensity can be measured on the straight line 44 that is drawn along the center of each strip in the immunoblot test and can be recorded in optical intensity units (OU), or in other levels such as grey-scale levels.
  • Fig. 3b employs a system wherein the grey- scale is set to fall within a range of 0 to 255 with 0 being lightest in grey-scale and 255 being darkest.
  • the banded identification mechanism particularly if it is software, is readily calibrated so that the intensity in optical units or the grey-scale that corresponds to the white color or the black color is readily set. Once the band intensity values have been measured, the data can be stored by the data processor 12 for further processing.
  • the banded identification mechanism 22 can perform a step of preprocessing on the image signal.
  • the preprocessing step can adjust the generated image for increasing the contrast of the bands in the test strips against the background membrane of the test strip.
  • Other processing techniques can be employed for enhancing the brightness of the image signal, as well as for emphasizing the edges of the band within the test strip.
  • the band identification mechanism 22 can perform a homomo ⁇ hic imaging process wherein the image which can be represented discreetly by a two-dimensional sequence X(m,n) that can be processed to enhance the edges of the bands that occur within the test strips.
  • Other techniques can be employed for processing the image for more readily identifying the bands within the image and such techniques will be known to those of ordinary skills in the art. Moreover, such techniques are described in detail in Oppenheim et al. , Digital Signal Processing, Prentice-Hall (1975). Further filtering can be employed for removing from the image 30 bands that fall below a predetermined intensity level.
  • the band identification mechanism 22 as depicted in Fig. 1 is shown as a functional block element.
  • the band identification mechanism can be realized as a software component operating on a conventional data processing system such as a unix work station.
  • the band identification mechanism can be implemented as a C-language computer program, or a computer program written in any high level language including Fortran, Java or basic.
  • the band identification mechanism 22 can be realized as a computer program written in microcode or written in a high level language and compiled down to microcode that can be executed on the platform employed.
  • FIG. 4 depicts a flow chart of a process 70 for identifying the band pattern within the image signal provided to the band identification mechanism 22.
  • the particular process depicted by Fig. 4 is adapted for use with membranes that can have band patterns with an unknown amount of spread between the bands. As discussed above, such band spread can occur when a membrane is prepared using electrophoresis.
  • Employing this process makes the band separation depend in part on environmental conditions, such as temperature, and can lead to variations in separation between the bands of a band pattern, with band separation varying as much as several millimeters.
  • the process 70 searches through the intensity values in an intensity vector that can be generated by reading intensity values along a central axis extending through the strip, such as the process graphically depicted in Fig. 3B.
  • the keybands typically are readily identifiable within the intensity vector.
  • keybands can have particularly high intensity values, or a characteristic spatial frequency which can be detected by known image processing techniques.
  • Other characteristics that can lead to the identification of keybands can also be employed with the systems and processes described herein without departing from the scope of the invention. Analysis of band patterns of membranes prepared by electrophoresis have shown that the spread that occurs between bands is generally consistent.
  • band spread is generally evenly affected across the strip.
  • a portion of a strip can be identified as having a substantial amount of band spread, it is likely that band spread is substantial throughout the full length of the strip.
  • band spread between keybands can be determined and the relative amount of band spread for all bands in the band pattern can be ascertained.
  • band spread can be understood to vary in part as a function of molecular weight.
  • keybands can be located at different sections of the strip thereby providing keybands that are spatially proximate other bands of significance and therefore similar in molecular weight.
  • the band spread for keybands of a certain molecular weight can be employed for predicting the band spread of bands of significance having similar molecular weights.
  • a set of ratios can be generated and stored which can be employed for determining a position of a band in relation to the position of the keyband. For example, one band can be understood as being 2/3 as far down the strip as a particular keyband.
  • the relative position of bands of interest can be associated with positions of keybands by a lookup table that allows the location of keybands to be employed as an index into the lookup table. Therefore, if the position of keybands can be identified, the keyband information can be employed to generate a full set of likely locations for all bands of significance. Other techniques for identifying the location of bands within the strip can be employed without departing from the scope of the invention.
  • Figure 4 depicts a process 70 that begins with a step 72 wherein the process 70 reads in an intensity vector that is representative of the scale values that occurred along the center axis 44 that extends through the strip of the immunoblot blot assay. This is depicted in Figure 3B wherein the intensity levels are provided as gray scale values.
  • the process 70 proceeds to step 74 wherein the process determines whether or not a plurality of keybands is present within the intensity vector data.
  • Keybands are understood as bands which appear within the Western blot band pattern and which can be detected using signal processing techniques. For example, keybands can be selected which are bands that occur within a positive test and which have generally strong intensity levels and which typically have a detectable spatial frequency between the bands.
  • Such bands provide signals within the intensity vector that provide strong variations in intensity levels at a generally consistent spatial frequency from test to test.
  • One example of a set of keybands can be the bands that occur at 66 kd, 60 kd and 58 kd.
  • a further set of keybands for the lime disease Western blot assay can be the bands that can occur at 28 kd and 18 kd. Similarly, a third set of keybands can occur at 41 kd and 39 kd. An additional set of keybands for the lime disease
  • Western blot assay can include the bands at 34 kd and 31 kd.
  • the process can perform a signal processing technique that processes the intensity vector to identify within that vector a series of intensity values that correspond to the intensity values and spatial frequencies associated with the keybands.
  • Other techniques can also be employed for identifying the keybands within the intensity vector.
  • the vector can be convolved with a control pattern to identify the keybands within the intensity vector. Other techniques will be known to those of skill in the art.
  • step 88 visual inspection by an operator can be employed to determine whether keybands are present within the test results.
  • the process can proceed from step 74 to step 88 and terminate.
  • the system can require only the presence of keybands in a control strip that can be on the membrane surface, or can optionally, require that the keybands be found on each strip, or on a predetermined number of strips. If the keybands are not found, the system can indicate an error, such as by printing an error result to the monitor. Alternatively, if the system continues to process the signal, the system can flag the results of the test to indicate that the results may be suspect and can print a report of the keybands found and the keybands absent from the strip.
  • step 78 the process 70 determines the position of the keybands within the vector.
  • the position of keybands within the vector is determined by starting with a likely location within the vector for a particular keyband, and searching for the highest intensity level that occurs within that likely location.
  • the system can search in a window around the likely location, such as a window that corresponds to a typical width of the band of interest, and identify within that window the highest intensity value present. The location of the highest intensity value can be deemed to be the center of the band.
  • the width of that section of the vector can be measured and divided in half to find the center of that keyband. This process can be employed for each keyband until the center position of each keyband is established for the strip being analyzed. Once the position of the keyband has been established, the process can now determine the relative spread between bands within the test strip.
  • the process selects keybands associated with low molecular weights and high molecular weights to have keyband reference points at either end of the test strip.
  • the process 70 in step 82 can, in one practice, multiply the relative position of the keybands by predetermined ratios that describe the location of other bands within the test strip in relation to the position of the keybands. For example, the location of the band associated with the protein of 93 kd can be identified employing an equation such as:
  • the value returned by this equation can be employed as the exact location of the 93 kd protein or optionally can be employed as a first estimate of the location, and a moveable window can be slid across that location to identify the width of the P93 band, and the center location of the identified band can be employed as the exact location of the P93 band within the test strip.
  • intensity level in step 82, can be determined and associated with each band.
  • the locations associated with the bands of interest correspond to entries into the intensity vector originally read in to process 70 in step 72. Therefore, the location associated with the band can be employed as an entry point into the intensity vector wherein an intensity value is stored.
  • the intensity values can be read from the intensity vector and a vector of data points can be created which is representative of the band pattern. This is depicted by step by 84 which is shown as the last step of process 70 before the process 70 proceeds to step 88 and terminates.
  • Table 1 presents a pseudo-code representation of the process 70 described above
  • the pseudo-code can be representative of a C language computer program, C + + computer program or any high-level code that is capable of implementing the process described above.
  • Fig. 5 a process for inte ⁇ reting the band pattern is depicted graphically and shows that the band pattern identified by the band identification mechanism 22 such as by employment of the process 70 of Fig. 4, can then be inte ⁇ reted to determine whether the band pattern fits into a category that indicates the presence or absence of a particular disease or diseases. More specifically, Fig. 5 depicts an immunoblot blot membrane 92, a CCD camera 94, a band pattern 98, a plurality of positive categories 100, 102 and 104, and a match process that can lead to a diagnosis signal depicted in Fig. 5 as either a positive diagnosis signal 110 or a negative diagnosis signal 112.
  • the immunoblot blot membrane 92 can be a standard immunoblot blot membrane such as the membrane 16 depicted in Fig. 1.
  • the image of the membrane is captured as described above, and in Fig. 5 this is depicted by the CCD camera element 94 disposed above the immunoblot blot membrane 92.
  • the image signal generated by the CCD camera 94 can be processed by the band identification mechanism 22, which is not depicted in Fig. 5, but which is described above with reference to Figs. 1-4.
  • the band pattern generated by the system is depicted graphically in Fig. 5 as a band pattern on a strip. However, it will be understood that the band pattern can also be represented by a data vector such as the data vector produced by the band identification mechanism 22. Other formats for encoding the band pattern information can be employed with the systems and methods described herein.
  • the band pattern 98 can be processed by the band pattern inte ⁇ reter 24 which can attempt to match the determined band pattern 98 to one or more categories that have been determined to indicate the presence or absence of a particular disease or diseases.
  • the band inte ⁇ reter includes a neural network that can match the identified band pattern 98 against a set of known categories of band patterns.
  • the neural net allows the band inte ⁇ reter to inte ⁇ ret the immunoblot band pattern 98.
  • a neural net is coded with no explicit knowledge. Instead, the network is trained to develop knowledge through learning. What the network has learned can than be used to derive explicit rules. These rules may be consistent with or different from the existing criteria, and therefore can result in the generation of new or improved inte ⁇ retive criteria.
  • the band inte ⁇ reter includes a neural network that is based on the Adaptive Resonance Theory (ART) neural network for pattern recognition.
  • ART was inspired by the ability of human memory to build representations of objects in a category (birds, for example) that are adaptive enough to add new objects (e.g., a penguin) that fit the category without losing any of the previous objects in the category.
  • ART architectures are neural networks that self-organize stable recognition categories in real time in response to arbitrary sequences of input patterns.
  • the basic principles of adaptive resonance theory (ART) were introduced in Grossberg, "Adaptive pattern classification and universal recoding, II: Feedback, expectation, olfaction, and illusions.” Biological Cybernetics, 23 (1976) 187-202.
  • a class of adaptive resonance architectures has since been characterized as a system of ordinary differential equations by Carpenter and Grossberg, "Category learning and adaptive pattern recognition: A neural network model", Proceedings of the Third Army Conference on Applied Mathematics and Computing, ARO Report 86-1 (1985) 37-56, and "A massively parallel architecture for a self-organizing neural pattern recognition machine. " Computer Vision, Graphics, and Image Processing, 37 (1987) 54-1 15.
  • ART network is described in detail in these references, however for purposes of clarity, a brief description of the ART network will be provided.
  • new patterns are encoded, in part, by changing the weights or long term memory (LTM) traces of a bottom-up adaptive filter.
  • This filter can be contained in pathways leading from a feature representation field to a category representation field of short term memory.
  • STM short term memory
  • the long term memory (LTM) defines patterns learned from some number of input patterns, that is, over a relatively longer period of time. This bottom-up filtering property is shared by many other models of adaptive pattern recognition and associative learning.
  • any new input could create a new category at any time: plasticity, or the potential for change in the LTM, remains intact indefinitely. If at any time, for example, a new input were added to the previously learned set, the system would search the established categories. If an adequate match were found, the LTM category representation would be refined, if necessary, to incorporate the new pattern. If no match were found, a new category would be formed, with previously uncommitted LTM traces encoding the STM pattern established by the input. Nevertheless, the code does tend to stabilize as the category structure becomes increasingly complex, since then each new pattern becomes increasingly likely to fit into an established category.
  • the criterion for an adequate match between an input pattern and a chosen category template is adjustable.
  • the matching criterion is determined by a vigilance parameter that controls activation of the orienting subsystem. . All other things being equal, higher vigilance imposes a stricter matching criterion, which in turn partitions the input set into finer categories. Lower vigilance tolerates greater top-down/bottom-up mismatches at FI, leading in turn to coarser categories.
  • the matching criterion is self-scaling: a small mismatch may be tolerated if the input pattern is complex, while the same featural mismatch would trigger reset if the input represented only a few features. Additionally, Gain controls can act to adjust overall sensitivity to patterned inputs and to coordinate the separate, synchronous functions of the ART system.
  • a new neural network was developed using the ARTMAP system, to correctly identify the protein bands present in a Lyme IgG Western Blot.
  • the protein bands were identified, and a list of proteins present was entered into the network software.
  • the network was trained on a plurality of sets, with certain parameters set to seek a sensitivity and accuracy suitable for the application.
  • the ARTMAP software was provided with a set of 130 samples (94 positive and 36 negative) with a vigilance setting of 0.8.
  • the neural net can also be trained to consider patient information, such as patient history, existing medical conditions, age, sex, stage of illness, and other demographic information.
  • the neural net can employ this information to generate or refine classes and increase sensitivity.
  • the neural net can be trained to detect any type of disease for which images of membranes can be produced to allow for proper training. Additionally, the neural net can be trained to detect and distinguish multiple diseases, each of which can be tested for on a single membrane, or on separate membranes.
  • the system can be used in cooperation with, or relying on, a statistical processor.
  • certain keybands which can be identified based on unique characteristics (such as band strength and position, or Rf) can be used as reference points for determining the location of other bands.
  • An ideal image for each set of marker bands can be derived by taking a statistical average of all the marker bands. The ideal image can be compared with the actual image to find the position of the best match.
  • the variance, or other statistical measure, in the position of each protein band relative to the marker bands can be calculated by examining a data set of band patterns. These variances can then be used to generate probability curves for the locations of the non-marker protein bands and to define a region in which to search for each particular band.
  • a score can be generated for each protein band in the search region
  • the score is the product of the band intensity and the value of the band from the probability curve The greater the distance of a band from its ideal location or the lower its intensity, the lower its score.
  • the band with the highest score is defined to correspond to the protein.
  • the statistical method of band identification is not assay specific, however the marker band characteristics are specific to each antigen source. After the bands have been identified, the CDC/ASTPHLD interpretive criteria can be applied to determine the test result.
  • Fig. 6 depicts an overhead view of one integrated system that can generate immunoblot blot assay test results and inte ⁇ ret the results.
  • Fig. 6 depicts a system 120 that includes a housing 122. Within the housing 122 is a chamber wherein can sit a plurality of test beds 124, 126 and 128 each of which can carry a membrane fitted within a slotted cassette that allows a plurality of immunoblot blot assays to be performed.
  • One such system is the CodaVision system manufactured by the Immunetics Company of Cambridge, Massachusetts.
  • a moveable arm 134 can be disposed above the assay plates and can include a carrying arm 130 which can carry a pipette (not shown) that extends between the arm 130 and the assay cassettes 124, 126 and 128.
  • the pipette can deliver to the membrane materials needed for performing the immunoblot blot assay.
  • the arm further carries a CCD camera 132.
  • the arm 130 as in the Coda Vision system is capable of moving in an X and Y plane that allows full coverage of the surface area of all the assay cassettes 124, 126 and 128.
  • the arm 130 can move the camera 132 in a plane that provides for complete imaging of the assay cassettes 124, 126 and 128.
  • the membranes contained within the cassettes 124, 126 and 128 can be held in place during the imaging process.
  • a lighting system (not shown) can be employed for providing sufficient light onto the membrane at the proper angles to allow the CCD camera 132 to make accurate images of the membranes within the cassettes 124, 126 and 128.
  • system 120 can also include reservoirs 140 that can contain substrate material, analytes, wash materials, and other such materials necessary for implementing the immunoblot blot assay.
  • reservoirs 140 can contain substrate material, analytes, wash materials, and other such materials necessary for implementing the immunoblot blot assay.
  • the sample wheel 142 can be seated within the center of the chamber of the housing 120.
  • the sample wheel 142 can carry serological samples provided by patients that are to be tested for a disease or diseases of interest.
  • the housing 122 can carry on an exterior surface a keypad 148 and an LCD screen 144.
  • the keypad 148 can be employed for operating an embedded controller system that can operate the elements depicted in Fig. 6 to perform the immunoblot blot assay and to image and process the band patterns created by the assay. The results of the tests can be displayed on the LCD screen 144 to the clinician. Accordingly, the system depicted in Fig. 6 provides for one touch implementation of an immunoblot blot assay and the inte ⁇ retation thereof, and thereby reduces the number of manual steps necessary for implementing and inte ⁇ reting an immunoblot blot assay.
  • the systems and methods described above can be employed for use with any binding assay that detects the presence of analytes in any biological material, e.g. , an antibody or antigen analyte in human or animal serum, urine, stool, saliva or other body fluids, secretions or excretions.
  • the systems and methods described herein can also be used to screen for the presence of microbial organisms, including bacteria, viruses and fungi.
  • the device of the invention can additionally be used to screen or otherwise characterize binding specificities of monoclonal antibodies, antibodies of different species and antibodies produced by genetic engineering or other in vitro techniques.

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Abstract

On décrit des systèmes et des procédés automatisés pouvant être mis en oeuvre pour interpréter des immunoblots de Lyme. Ces programmes peuvent analyser les motifs en bandes produits par immunotransfert ('Western Blot test', par exemple), par numérisation de la membrane d'essai effectuée avec une caméra numérique, et par interprétation des résultats d'analyse (positifs ou négatifs). Selon le cas, on utilise soit une analyse statistique de données de bande, soit un ordinateur neuronal. Le programme statistique peut incorporer des algorithmes interprétatifs, tels que ceux reconnus par CDC/ASTPHLD pour les immunoblots de Lyme. L'ordinateur neuronal est doué de capacités d'apprentissage qui lui permettent d'améliorer ses performances et de mettre au point ses propres critères d'interprétation grâce à l'analyse d'un grand nombre d'échantillons positifs ou négatifs.
PCT/US1999/008160 1998-04-14 1999-04-14 Logiciel interpretatif de l'immunoblot de lyme WO1999053288A2 (fr)

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Cited By (6)

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WO2013089817A1 (fr) * 2011-12-16 2013-06-20 Li-Cor, Inc. Scanner d'imagerie à luminescence
DE102013008468A1 (de) 2013-05-21 2014-11-27 Euroimmun Medizinische Labordiagnostika Ag Verfahren zur automatisierten Auswertung von inkubierten lmmunoblotstreifen
EP2989446B1 (fr) * 2013-04-24 2018-10-03 Euroimmun Medizinische Labordiagnostika AG Procédé d'évaluation automatique des bandelettes des immunoblots incubeés
WO2020082029A1 (fr) * 2018-10-18 2020-04-23 The Regents Of The University Of California Dispositif et système de test sérodiagnostic pour la maladie de lyme à un stade précoce à l'aide d'un dosage immunologique multiplexé
EP3825691A1 (fr) 2019-11-25 2021-05-26 Roche Diabetes Care GmbH Procédé pour déterminer une concentration d'un analyte dans un fluide corporel
US20230274538A1 (en) * 2020-10-09 2023-08-31 The Trustees Of Columbia University In The City Of New York Adaptable Automated Interpretation of Rapid Diagnostic Tests Using Self-Supervised Learning and Few-Shot Learning

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5281517A (en) * 1985-11-04 1994-01-25 Cell Analysis Systems, Inc. Methods for immunoploidy analysis
US5585276A (en) * 1991-05-10 1996-12-17 Wisconsin Alumni Research Foundation Medium and method for blotting macromolecules
US5594808A (en) * 1993-06-11 1997-01-14 Ortho Diagnostic Systems Inc. Method and system for classifying agglutination reactions

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US8486644B2 (en) 2011-12-16 2013-07-16 Li-Cor, Inc. Chemiluminescence compact imaging scanner
US8722346B2 (en) 2011-12-16 2014-05-13 Li-Cor, Inc. Chemiluminescence compact imaging scanner
CN104115478A (zh) * 2011-12-16 2014-10-22 利-考股份有限公司 发光成像扫描仪
CN104115478B (zh) * 2011-12-16 2016-04-20 利-考股份有限公司 发光成像扫描仪
US9809842B2 (en) 2011-12-16 2017-11-07 Li-Cor, Inc. Chemiluminescence compact imaging scanner
WO2013089817A1 (fr) * 2011-12-16 2013-06-20 Li-Cor, Inc. Scanner d'imagerie à luminescence
US10914737B2 (en) 2013-04-24 2021-02-09 Euroimmun Medizinische Labordiagnostika Ag Method for automated evaluation of incubated immunoblot strips
EP2989446B1 (fr) * 2013-04-24 2018-10-03 Euroimmun Medizinische Labordiagnostika AG Procédé d'évaluation automatique des bandelettes des immunoblots incubeés
DE102013008468A1 (de) 2013-05-21 2014-11-27 Euroimmun Medizinische Labordiagnostika Ag Verfahren zur automatisierten Auswertung von inkubierten lmmunoblotstreifen
WO2020082029A1 (fr) * 2018-10-18 2020-04-23 The Regents Of The University Of California Dispositif et système de test sérodiagnostic pour la maladie de lyme à un stade précoce à l'aide d'un dosage immunologique multiplexé
US12013395B2 (en) 2018-10-18 2024-06-18 The Regents Of The University Of California Serodiagnostic testing device and system for early-stage Lyme disease using a multiplexed immunoassay
EP3825691A1 (fr) 2019-11-25 2021-05-26 Roche Diabetes Care GmbH Procédé pour déterminer une concentration d'un analyte dans un fluide corporel
WO2021105063A1 (fr) 2019-11-25 2021-06-03 F. Hoffmann-La Roche Ag Méthode de détermination d'une concentration d'un analyte dans un fluide corporel
EP4145128A1 (fr) 2019-11-25 2023-03-08 Roche Diabetes Care GmbH Procédé de détermination d'une concentration d'un analyte dans un fluide corporel
US12287327B2 (en) 2019-11-25 2025-04-29 Roche Diabetes Care, Inc. Method of determining a concentration of an analyte in a bodily fluid
US20230274538A1 (en) * 2020-10-09 2023-08-31 The Trustees Of Columbia University In The City Of New York Adaptable Automated Interpretation of Rapid Diagnostic Tests Using Self-Supervised Learning and Few-Shot Learning

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