Point of care diagnostic systems

• US 20040241752A1
• Filed: 06/25/2004
• Published: 12/02/2004
• Est. Priority Date: 02/03/1998
• Status: Active Grant

• Current Assignee: Cytyc Corporation (Hologic Incorporated)
• Original Assignee: Cytyc Corporation (Hologic Incorporated)
• Inventors: Senyei, Andrew E., Martinez, Ricardo, Anderson, Emory V., Marzolf, Gail, Nemec, Edward, Pong, Ronald, Jones, Lynn, Lapointe, Jerome, DeSieno, Duane, Hussa, Robert O.
• Granted Patent: US 7,270,970 B2
• Time in Patent Office: Days
• US Class Current: 435/7.1
• CPC Class Codes: G01N 21/474 Details of optical heads therefor, e.g. using optical fibres
• CPC Class Codes: G01N 21/8483 Investigating reagent band test-element handling not specific to a test method G01N33/4875; analytical elements specific to chemical analysis of biological material G01N33/52; autometer with reagent band G01N35/04
• CPC Class Codes: G01N 2333/78 Connective tissue peptides, e.g. collagen, elastin, laminin, fibronectin, vitronectin, cold insoluble globulin [CIG]
• CPC Class Codes: G01N 2800/368 Pregnancy complicated by disease or abnormalities of pregnancy, e.g. preeclampsia, preterm labour
• CPC Class Codes: G01N 33/54388 based on lateral flow
• CPC Class Codes: G01N 33/558 using diffusion or migration of antigen or antibody immunochromatographic test strips G01N33/54387
• CPC Class Codes: G01N 33/6887 from muscle, cartilage or connective tissue
• CPC Class Codes: G01N 33/689 related to pregnancy or the gonads
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
• CPC Class Codes: Y10S 436/811 Test for named disease, body condition or organ function
• CPC Class Codes: Y10S 436/814 Pregnancy

Abstract

Systems and methods for medical diagnosis or risk assessment for a patient are provided. These systems and methods are designed to be employed at the point of care, such as in emergency rooms and operating rooms, or in any situation in which a rapid and accurate result is desired. The systems and methods process patient data, particularly data from point of care diagnostic tests or assays, including immunoassays, electrocardiograms, X-rays and other such tests, and provide an indication of a medical condition or risk or absence thereof. The systems include an instrument for reading or evaluating the test data and software for converting the data into diagnostic or risk assessment information.

Claims

1. A method for determining results from an immunoassay, comprising:

(a) testing a patient sample for the presence of a target analyte indicative of a condition or risk of having the condition by reacting the sample with antibodies specific for the analyte in a sandwich assay performed on a test strip, in which one of the antibodies is labeled with a detectable label;

(b) detecting the signal produced by the label in a reflectance reader containing a reader head, wherein the reader head is parallel to the surface of the test strip; and

(c) processing the data obtained from the reflectance signal obtained from reading the test strip into a result indicative of the presence or absence or a threshold concentration of analyte in a sample.

2. The method of claim 1, further comprising a step of transmitting light onto the surface of the test strip at an angle normal to the surface, wherein the detecting step includes measuring light reflected normally from the surface, wherein the reflected light measurement is indicative of the presence of the analyte.

3. The method of claim 1, further comprising a step of uniformly illuminating the surface of the test strip, wherein the detecting step includes measuring light reflected normally from the surface, wherein the reflected light measurement is indicative of the presence of the analyte.

4. The method of claim 1, wherein the results are qualitative.

5. The method of claim 1, wherein the results are quantitative

6. The method of claim 1, wherein the data is input into a neural network trained for assessing risk related to or diagnosing the condition.

7. The method of claim 6, wherein the analyte is fetal fibronectin (fFN).

8. The method of claim 7, wherein the condition is pregnancy-related or the method assesses fertility status.

9. The method of claim 7, wherein the condition is a fertility-related disorder.

10. The method of claim 7, wherein the risk of ectopic pregnancy, pre-eclampsia, infertility, preterm labor, imminent delivery, term induction or fetal membrane rupture is assessed.

11. The method of claim 1, wherein the immunoassay detects fetal fibronectin (fFN) in a sample.

12. The method of claim 1, wherein the reflectance reader contains a charge coupled device (CCD).

13. The method of claim 1, wherein the processing step further comprises a step of forming an array of points containing a number of rows (n) corresponding to the number of points at which readings were taken along the test strip, and a number of columns (m) corresponding to the number of reflectance readings taken at each point.

14. The method of claim 13, wherein:

the processing step further converts the array into a result indicative of the presence or absence or a threshold concentration of an analyte in a sample; and

conversion is effected by data processing software employing data reduction and curve fitting algorithms.

15. A method for reading a surface of a test strip comprising an image, comprising:

(a) measuring a first amount of light reflected from the surface comprising the image;

(b) uniformly illuminating the surface with light of a first wavelength, and measuring a second amount of light reflected from the surface;

(c) uniformly illuminating the surface with light of a second wavelength, and measuring a third amount of light reflected from the surface; and

(d) determining a parameter correlated with an intensity or shape of the image.

16. A method for determining results from an immunoassay, comprising:

(a) testing a patient sample for the presence of a target analyte indicative of a condition or risk of having the condition by applying the sample to a lateral flow immunoassay test strip that comprises antibodies specific for the analyte, wherein one of the antibodies is labeled with a detectable label, wherein the immunoassay test strip comprises;

(i) a conjugate pad which serves as a sample application component;

(ii) a porous or bibulous member which is capable of transporting a liquid sample along the test strip and serves as a solid support upon which immunoreactions occur; and

(iii) an absorbent pad, which serves to draw liquid continuously through the device, wherein;

the materials of the membrane system form a single fluid flow pathway and the test strip is designed to be read by the reader;

(b) either before or after reacting the sample with the antibodies, inserting the test strip into a computer-controlled reflectance reader that measures light reflected from the surface of the test strip; and

(c) detecting the signal produced by the label in a reflectance reader, wherein the intensity of reflected signal in the test region or detection zone of the test strip is correlated with an amount of analyte present in the test sample.

17. A method for determining results from an immunoassay, comprising:

(a) testing a patient sample for the presence of a target analyte indicative of a condition or risk of having the condition by reacting the sample with antibodies specific for the analyte in a sandwich assay performed on a test strip, in which one of the antibodies is labeled with a detectable label; and

(b) detecting a reflectance signal produced by the label in a reflectance reader, wherein;

the reflectance reader includes a reader head that comprises;

(i) a reader head body;

(ii) a light emitting diode (LED);

(iii) a first fiberoptic bundle optically coupled to the light emitting diode;

(iv) a photodetector;

(v) a second fiberoptic bundle optically coupled to the photodetector; and

(vi) an aperture in the reader head body;

wherein the fiberoptic conductor ends of the first fiberoptic bundle and the fiberoptic conductor ends of the second fiberoptic bundle arranged in a substantially co-planar relationship to form a planar surface, and the planar surface is substantially parallel to a plane at an upper surface of the test strip during reflectance signal detection, whereby light is conducted by fiberoptic bundles to the photodetector, which generates the reflectance signal indicative of an amount of reflected light;

wherein the reflectance signal is indicative of the presence of the analyte.

18. The method of claim 17, wherein the fiberoptic conductor ends of the first fiberoptic bundle and the fiberoptic conductor ends of the second fiberoptic bundle are arranged in a sigmoidal distribution in the aperture.

19. The method of claim 17, wherein the reader head further comprises a third fiberoptic bundle optically connected to a second light emitting diode, wherein the fiberoptic conductor ends of the third fiberoptic bundle are arranged in a substantially co-planar relationship with the fiberoptic conductor ends of the first fiberoptic bundle and the fiberoptic conductor ends of the second fiberoptic bundle.

20. The method of claim 19, wherein the fiberoptic conductor ends of the first fiberoptic bundle and the fiberoptic conductor ends of the second fiberoptic bundle and the fiberoptic conductor ends of the third fiberoptic bundle are arranged in a sigmoidal distribution in the aperture.

21. A method for determining results from a test strip, comprising:

(a) measuring light reflected normally from the surface of the test strip to obtain a reflectance signal, wherein the reflectance signal is indicative of the presence of the analyte; and

(b) processing the data obtained from the reflectance signal using data processing software employing data reduction and curve fitting algorithms and/or a trained neural network to convert the reflectance signal into a result indicative of the presence or absence or a threshold concentration of analyte in a sample by a process that comprises;

(i) reducing an image to a set of derived parameters that can be used to reconstruct the image within a specified degree of tolerance;

(ii) inputting the derived parameters into a classification means; and

(iii) determining the classification of the image based on the output of the classification means.

22. A method of classifying an image, comprising:

(a) reducing the image to a set of derived parameters that can be used to reconstruct the image within a specified degree of tolerance;

(b) inputting the derived parameters into a classification means; and

(c) determining the classification of the image based on the output of the classification means.

23. A method for determining results from a test strip, comprising:

(a) scanning the test strip in a reflectance reader to obtain a scanned image; and

(b) processing the scanned image with data processing software employing data reduction algorithms and/or a trained neural network to convert the scanned image into data indicative of the presence or absence of a threshold concentration of analyte in the sample.

24. The method of claim 23, wherein the processing step further comprises:

reducing the image to a set of derived parameters that can be used to reconstruct the image within a specified degree of tolerance;

inputting the derived parameters into a classification means; and

determining the classification of the image based on the output of the classification means.