Methods for collecting and analyzing thermal data based on breast surface temperature to determine suspect conditions

• US 8,226,572 B2
• Filed: 08/27/2009
• Issued: 07/24/2012
• Est. Priority Date: 08/27/2008
• Status: Active Grant

• Current Assignee: Cyrcadia, Inc., First Clearing LLC (Wells Fargo & Company)
• Original Assignee: Lifeline Biotechnologies, Inc.
• Inventors: Keith, Louis G., Holmes, Jimmy D., Ng, Yin Kwee, Reeves, William H., Acharya U, Rajendra
• Primary Examiner(s): Hindenburg, Max
• Assistant Examiner(s): DANEGA, RENEE A
• Application Number:
  US12/583,951
• Publication Number:
  US 20100056945A1
• Time in Patent Office: 1,062 Days
• Field of Search: 600/549
• US Class Current: 600/549
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A portable computing device or microprocessor/storage system including temperature sensors used to collect temperature readings of a breast tissue of a subject. The device would collect data from the sensors at regular time intervals over a period of time. All of the generated temperature data is stored in the portable computing or storage device. The sensors are placed on the greatest areas of interest on the breast, based on where most cancers develop, by using a sensor placeholder. The sensor placeholder would be lobate shaped, with the sensor placeholder aligning with the glandular regions of the breast where cancers are most likely to develop. The temperature data is then analyzed by one or more classifier systems and classified as either suspect or non-suspect tissue.

Claims

1. A method for classifying breast tissue of a subject as suspect tissue or non-suspect tissue, comprising the steps of:

placing a plurality of temperature sensors on a breast of the subject at a set of predetermined positions;

sensing a set of temperature readings from the plurality of temperature sensors over a predetermined period; and

sending the set of temperature readings to an ensemble of classifier systems including two or more classifier systems, the ensemble of classifier systems deriving two or more output labels from the set of temperature readings identifying the breast tissue as suspect tissue or non-suspect tissue, and combining the two or more output labels into a single diagnosis identifying the breast tissue as suspect tissue or non-suspect tissue, wherein a weight of each label from the two or more output labels determines a relative contribution of the label towards the single diagnosis, the ensemble of classifier systems trained using one or more actual temperature readings including an above average temperature reading corresponding to suspect tissue, an average temperature reading corresponding to non-suspect tissue, and an anomalous temperature reading corresponding to non-suspect tissue.

2. The method as recited in claim 1, wherein suspect tissue includes cancerous tissue, benign tissue, and suspected cancerous tissue.

3. The method as recited in claim 1, wherein the predetermined period is 24 hours or less.

4. The method as recited in claim 1, wherein the plurality of temperature sensors are divided into a first group and a second group, wherein the step of placing includes the steps of:

placing each of the temperature sensors in the first group of temperature sensors in a predetermined position among the set of predetermined positions on a left breast of the subject; and

placing each of the temperature sensors in the second group of temperature sensors in a predetermined position among the set of predetermined positions on a right breast of the subject.

5. The method as recited in claim 1, wherein the plurality of temperature sensors are divided into a first group and a second group, wherein the step of placing includes the steps of:

placing one temperature sensor from the first group below a nipple of a left breast of the subject and one temperature sensor from the second group below a nipple of a right breast of the subject;

placing one temperature sensor from the first group in an upper outer quadrant of the left breast and one temperature sensor from the second group in an upper outer quadrant of the right breast;

placing one temperature sensor from the first group in an upper outer quadrant toward axilla associated with the left breast and one temperature sensor from the second group in an upper outer quadrant toward axilla associated with the right breast;

placing one temperature sensor from the first group on an upper areola of the left breast and one temperature sensor from the second group on an upper areola of the right breast;

placing one temperature sensor from the first group on a vertical midline above a horizontal midline of the left breast and one temperature sensor from the second group on a vertical midline above a horizontal midline of the right breast;

placing one temperature sensor from the first group in an upper inner quadrant of the left breast and one temperature sensor from the second group in an upper inner quadrant of the right breast;

placing one temperature sensor from the first group in an ambient temperature zone of the left breast and one temperature sensor from the second group in an ambient temperature zone of the right breast; and

placing one temperature sensor from the first group in a flexible position of the left breast and one temperature sensor from the second group in a flexible position of the right breast.

6. The method as recited in claim 5, wherein the flexible position of the left breast and the flexible position of the right breast includes in an area of concern, near a palpable lesion, and in a contralateral position.

7. The method as recited in claim 1, wherein the set of predetermined positions is determined by a substantially lobate shaped sensor placeholder with a set of four appendages, each appendage among the four appendages forming a series of holes within each appendage and forming a central hole, and wherein the step of placing include placing each temperature sensor among the plurality of temperature sensors in a different hole among the series of holes.

8. The method as recited in claim 7, wherein the plurality of temperature sensors are divided into a first group and a second group, wherein the step of placing includes the steps of:

placing the central hole of a first sensor placeholder over a nipple of a left breast of the subject with three appendages among the four appendages positioned above the nipple of the left breast;

placing the central hole of a second sensor placeholder over a nipple of a right breast of the subject with three appendages among the four appendages positioned above the nipple of the right breast;

placing one temperature sensor from the first group within a hole among the series of holes of a first appendage of the first sensor placeholder and below a nipple of the left breast and one temperature sensor from the second group within a hole among the series of holes of a first appendage of the second sensor placeholder and below a nipple of the right breast;

placing one temperature sensor from the first group within a hole among the series of holes of a second appendage of the first sensor placeholder and in an upper outer quadrant of the left breast and one temperature sensor from the second group within a hole among the series of holes of a second appendage of the second placeholder and in an upper outer quadrant of the right breast;

placing one temperature sensor from the first group within a second hole among the series of holes of a second appendage of the first sensor placeholder and in an upper outer quadrant toward axilla associated with the left breast and one temperature sensor from the second group within a second hole among the series of holes of a second appendage of the second sensor placeholder and in an upper outer quadrant toward axilla associated with the right breast;

placing one temperature sensor from the first group within a hole among the series of holes of a third appendage of the first sensor placeholder and on an upper areola of the left breast and one temperature sensor from the second group within a hole among the series of holes of a third appendage of the second sensor placeholder and on an upper areola of the right breast;

placing one temperature sensor from the first group within a second hole among the series of holes of a third appendage of the first sensor placeholder and on a vertical midline above a horizontal midline of the left breast and one temperature sensor from the second group within a second hole among the series of holes of a third appendage of the second sensor placeholder and on a vertical midline above a horizontal midline of the right breast;

placing one temperature sensor from the first group within a hole among the series of holes of a fourth appendage of the first sensor placeholder and in an upper inner quadrant of the left breast and one temperature sensor from the second group within a hole among the series of holes of a fourth appendage of the second sensor placeholder and in an upper inner quadrant of the right breast;

placing one temperature sensor from the first group within a hole among the series of holes of the set of four appendages of the first sensor placeholder and in an ambient temperature zone of the left breast and one temperature sensor from the second group within a hole among the series of holes of the set of four appendages of the second sensor placeholder and in an ambient temperature zone of the right breast; and

placing one temperature sensor from the first group within a hole among the series of holes of the set of four appendages of the first sensor placeholder and in a flexible position of the left breast and one temperature sensor from the second group within a hole among the series of holes of the set of four appendages of the second sensor placeholder and in a flexible position of the right breast.

9. The method as recited in claim 1, further comprising the step of assigning the weight of each label from the two or more output labels.

10. The method as recited in claim 1, further comprising the step of enabling a user to select one or more classifiers among the ensemble of classifier systems to use for the step of deriving.

11. A method for classifying breast tissue of a subject as suspect tissue or non-suspect tissue, comprising the steps of:

receiving a set of temperature readings from a plurality of temperature sensors positioned over a breast of the subject, the set of temperature readings including temperature readings over a predetermined period of time;

inputting the set of temperature readings into an ensemble of classifier systems including two or more classifier systems;

deriving two or more output labels based on the set of temperature readings identifying the breast tissue as suspect tissue or non-suspect tissue with the ensemble of classifier systems, the ensemble of classifier systems trained using one or more actual temperature readings including an above average temperature reading corresponding to suspect tissue, an average temperature reading corresponding to non-suspect tissue, and an anomalous temperature reading corresponding to non-suspect tissue; and

combining the two or more output labels into a single diagnosis identifying the breast tissue as suspect tissue or non-suspect tissue, wherein a weight of each label from the two or more output labels determines a relative contribution of the label towards the single diagnosis.

12. The method as recited in claim 11, wherein suspect tissue includes cancerous tissue, benign tissue, and suspected cancerous tissue.

13. The method as recited in claim 11, further comprising the step of training the ensemble of classifier systems using the one or more actual temperature readings corresponding to one or more known output labels using one or more of supervised learning, unsupervised learning, or reinforcement learning.

14. The method as recited in claim 11, wherein the ensemble of classifier systems includes a neural network.

15. The method as recited in claim 14, further comprising the step of training the neural network using one or more actual temperature readings corresponding to one or more known output labels using either back-propagation or neuroevolution.

16. The method as recited in claim 11, wherein the ensemble of classifier systems includes one or more of a back-propagation neural network, a neural network trained with neuroevolution, a radial basis function, a Gaussian mixture model, a fuzzy network, a neural network, and a support vector machine.

17. The method as recited in claim 11, wherein the predetermined period is 24 hours or less.

18. The method as recited in claim 11, further comprising the step of storing the set of temperature readings before inputting the set of temperature readings into the ensemble of classifier systems.

19. The method as recited in claim 11, further comprising the step of filtering the set of temperature readings to remove one or more anomalous temperature readings before the step of deriving.

20. The method as recited in claim 19, wherein the one or more anomalous temperature readings include one or more temperature readings from a temperature sensor that have an elevated temperature for a short period of time.

21. The method as recited in claim 19, wherein the one or more anomalous temperature readings include a series of temperature readings from a temperature sensor that decrease in temperature over a period of time.

22. The method as recited in claim 19, wherein the one or more anomalous temperature readings include one or more temperature readings from a temperature sensor that have a lower temperature for a period of time.

23. The method as recited in claim 11, further comprising the step of providing a user of the ensemble of classifier systems with a visual indication of the two or more output labels and the single diagnosis.

24. The method as recited in claim 11, further comprising the step of providing a user of the ensemble of classifier systems with a visual indication of a stage of breast cancer for the breast tissue identified as suspect tissue.

25. The method as recited in claim 24, wherein the visual indication includes a color indication.

26. The method as recited in claim 11, further comprising the step of enabling a user to select one or more classifiers among the ensemble of classifier systems to use for the step of deriving.

27. The method as recited in claim 11, further comprising the step of assigning the weight of each label from the two or more output labels.