Method for automated exclusion of deep venous thrombosis

• US 6,447,460 B1
• Filed: 04/05/1999
• Issued: 09/10/2002
• Est. Priority Date: 12/09/1998
• Status: Expired due to Fees

• Current Assignee: Huntleigh Technology, Inc.
• Original Assignee: KCI Licensing Incorporated (3M Company)
• Inventors: Xu, Tianning, Tumey, David M., Zheng, X. Lu
• Primary Examiner(s): O'Connor, Cary
• Assistant Examiner(s): MARMOR II, CHARLES ALAN
• Application Number:
  US09/286,190
• Time in Patent Office: 1,254 Days
• Field of Search: 600/473, 600/474, 600/481, 600/482, 600/485, 600/504, 600/507, 600/408, 600/549, 600/555, 128/920, 128/925, 374/100, 374/112
• US Class Current: 600/549
• CPC Class Codes: A61B 5/015 By temperature mapping of body part
• CPC Class Codes: A61B 5/6828 Leg
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00

Abstract

An automated screening tool for the exclusion of deep venous thrombosis generally comprises a sensor array for gathering thermal data from the lower limbs of a patient suspected of DVT; a processor for automated analysis of the gathered data; and a display device for reporting the exclusion or non-exclusion of DVT. In the preferred embodiment of the present invention, a microprocessor based system is utilized to control the gathering of thermal data and, thereafter, the reporting of the gathered data to the processor. According to the preferred method for use of the present invention, the gathered thermal data is utilized, alone or in combination with other indicators, as a factor for exclusion of DVT based upon an implemented algorithm.

According to the preferred embodiment of the present invention, a neural network or genetic algorithm is implemented within the processor in order to make an entirely objective determination relative the presence of DVT. This feature makes the present invention particularly adapted to multiple risk factor analysis, wherein factors such as calf circumference; positive Homan sign; colorimetry reading of the limbs; recent surgery or trauma; history of DVT, phlebitic syndrome or venous insufficiency; or presently uncannulated veins may be considered along with thermographic data.

Claims

1. A diagnostic method for the automated and objective exclusion of deep venous thrombosis (DVT) in a patient'"'"'s limb, said diagnostic method comprising the steps of:

obtaining a sensed thermal characteristic of the patient'"'"'s limb;

converting said thermal characteristic to a processor compatible format; and

processing said format in an automated and objective analysis, said analysis being adapted to exclude the patient for DVT based upon said sensed thermal characteristic.

2. The diagnostic method as recited in claim 1, wherein said obtaining a sensed thermal characteristic step comprises using a thermistor to measure said thermal characteristic.

3. The diagnostic method as recited in claim 1, wherein said obtaining a sensed thermal characteristic step comprises using a plurality of thermistors to measure said thermal characteristic, said plurality of thermistors forming an array of sensors.

4. The diagnostic method as recited in claim 3, wherein said array of sensors is adapted for disposition along the posterior region of the patient'"'"'s calf region.

5. The diagnostic method as recited in claim 4, wherein said array is adapted to dispose said sensors at predetermined intervals one to another.

6. The diagnostic method as recited in claim 5, wherein said array comprises a flexible strip, said sensors being disposed at predetermined positions along one side of said flexible strip and said one side being provided with an adhesive for application to the patient'"'"'s calf.

7. The diagnostic method as recited in claim 3, wherein said converting said thermal characteristic step comprises using an acquisition device in independent communication with each said sensor, said acquisition device being adapted to convert said thermal characteristic measured by each said sensor to said processor compatible format.

8. The diagnostic method as recited in claim 7, wherein:

said acquisition device comprises an analog multiplexor and an amplifier; and

said acquisition device is adapted to independently amplify through said amplifier said thermal characteristic measured by each said sensor of said array.

9. The diagnostic method as recited in claim 7, wherein said acquisition device comprises a microprocessor, said microprocessor being adapted to control:

acquisition of said thermal characteristic;

conversion of said thermal characteristic to said processor compatible format; and

presentation of said format to a processor for said automated and objective analysis.

10. The diagnostic method as recited in claim 9, wherein said acquisition device further comprises:

an analog to digital converter for converting said thermal characteristic to said processor compatible format; and

a serial communication channel for transmission of said format to said processor, said serial communication channel comprising an opto-coupler adapted for electrical isolation of said acquisition device from said processor.

11. The diagnostic method as recited in claim 1, wherein said processing said format step comprises using a genetic algorithm to objectively determine whether said thermal characteristic indicates exclusion of the patient for DVT.

12. The diagnostic method as recited in claim 1, wherein said processing said format step comprises using a neural network to objectively determine whether said thermal characteristic indicates exclusion of the patient for DVT.

13. The diagnostic method as recited in claim 1, wherein said processing said format step comprises performing a multiple risk factor analysis.

14. The diagnostic method as recited in claim 13, wherein said performing a multiple risk factor analysis step comprises analyzing said format and at least one other indicator of DVT, said analyzing step being conducted in an entirely objective manner.

15. The diagnostic method as recited in claim 14, wherein said analyzing step comprises using a neural network for indicating exclusion of the patient for DVT.

16. The diagnostic method as recited in claim 15, wherein said neural network comprises a bias factor for patient safety.

17. The diagnostic method as recited in claim 13, wherein said performing a multiple risk factor analysis step comprises analyzing said format and a plurality of other indicators of DVT.

18. The diagnostic method as recited in claim 1, said diagnostic method further comprising reporting excludability of the patient for DVT.

19. The diagnostic method as recited in claim 18, wherein said reporting excludability step comprises displaying a result on a monitor.

20. The diagnostic method as recited in claim 18, wherein said reporting excludability step comprises recording computational data in a magnetic medium.