Decision support systems and methods for assessing vascular health

• US 6,699,193 B2
• Filed: 10/01/2001
• Issued: 03/02/2004
• Est. Priority Date: 09/29/2000
• Status: Expired due to Fees

• Current Assignee: New Health Sciences, Inc.
• Original Assignee: New Health Sciences, Inc.
• Inventors: Davidson, John, Crutchfield, Kevin, Fitall, Simon, Mozayeni, Robert
• Primary Examiner(s): Lateef, Marvin M.
• Assistant Examiner(s): Jain, Ruby
• Application Number:
  US09/966,366
• Publication Number:
  US 20020062078A1
• Time in Patent Office: 883 Days
• Field of Search: 600/453-456, 600/504-506, 600/513, 600/457, 600/301, 600/300, 738/612.5, 514/2
• US Class Current: 600/454
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/4076 Diagnosing or monitoring particular conditions of the nervous system A61B5/4821, A61B5/4824 take precedence
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• 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
• CPC Class Codes: A61B 8/06 Measuring blood flow measuring volume flow in general G01F, e.g. G01F1/66, G01F1/72; measuring speed of fluids in general G01P5/00
• CPC Class Codes: A61B 8/56 Details of data transmission or power supply
• CPC Class Codes: G01S 15/8915 using a transducer array
• CPC Class Codes: G01S 15/8979 Combined Doppler and pulse-echo imaging systems
• CPC Class Codes: G01S 7/52036 using analysis of echo signal for target characterisation
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 70/60 relating to pathologies

Abstract

The present invention relates generally to systems and methods for assessing blood flow in blood vessels, for assessing vascular health, for conducting clinical trials, for screening therapeutic interventions for adverse effects, and for assessing the effects of risk factors, therapies and substances, including therapeutic substances, on blood vessels, especially cerebral blood vessels, all achieved by measuring various parameters of blood flow in one or more vessels and analyzing the results in a defined manner. The relevant parameters of blood flow include mean flow velocity, systolic acceleration, and pulsatility index. By measuring and analyzing these parameters, one can ascertain the vascular health of a particular vessel, multiple vessels and an individual. Such measurements can also determine whether a substance has an effect, either deleterious or advantageous, on vascular health. The present invention further provides an expert system for achieving the above.

Claims

1. A method of assessing vascular health in a human or an animal, the method of assessing vascular health comprising the steps of:

measuring information concerning flow velocity within a subject'"'"'s blood vessels;

obtaining a mean flow velocity value for each measured vessel;

obtaining a systolic acceleration value for each measured vessel;

inputting the measured information into a processor containing at least one algorithm wherein the processor performs correlations of at least one mean flow velocity value, and at least one systolic acceleration value, and performs comparisons to analyze vascular health; and

outputting an assessment indicative of the subject'"'"'s vascular health.

2. The method according to claim 1, further comprising the steps of:

obtaining at least one pulsatility index value; and

inputting the at least one pulsatility index value into the processor,

wherein the processor performs a correlation of the pulsatility index value with at least one previously inputted value.

3. The method according to claim 1 wherein the vessel is an artery.

4. The method according to claim 3, wherein the artery supplies a central nervous system.

5. The method according to claim 3, wherein the artery is selected from the group consisting of a common carotid artery, an internal carotid artery, an external carotid artery, a middle cerebral artery, an anterior cerebral artery, a posterior cerebral artery, an anterior communicating artery, a posterior communicating artery, a vertebral artery, a basilar artery, and branches thereof.

6. The method according to claim 1, wherein the vessel is an intracranial vessel.

7. The method according to claim 1, wherein ultrasound energy is used to collect the information concerning flow velocity.

8. The method according to claim 7, wherein a Doppler probe is used to collect the information concerning flow velocity.

9. A method of determining effects of a substance on a vessel comprising application of the method according to claim 1 before and after administration of the substance.

10. The method according to claim 9 wherein the substance is a drug.

11. The method according to claim 10 wherein the substance is a vasoactive drug.

12. The method according to claim 10 wherein the substance is suspected of having vascular activity.

13. The method according to claim 1 wherein the human or the animal has a vascular disease or a condition that affects vascular function.

14. The method according to claim 1 wherein the human or the animal is suspected of having a vascular disease or a condition that affects vascular function.

15. The method according to claim 1, wherein the human or the animal is analyzed at a time of normal and at a time of abnormal health.

16. A method of analyzing vascular structure in a human or animal, the method of analyzing comprising the steps of:

inputting blood flow measurements of a subject to derive systolic acceleration into a processor;

applying algorithms that correlate the subject'"'"'s blood flow measurements including calculations based on the subject'"'"'s systolic acceleration and at least one additional parameter; and

outputting an analysis of the subject.

17. The method of analyzing vascular structure in a human or animal according to claim 16, further comprising the step of outputting intermediate calculations of the algorithms.

18. The method of analyzing vascular structure in a human or animal according to claim 17, wherein the algorithms are modifiable bases on an analysis by a health professional.

19. The method of analyzing vascular structure in a human or animal according to claim 16, wherein the algorithms include calculations based on the subject'"'"'s index of pulsatility.

20. The method of analyzing vascular structure in a human or animal according to claim 19, wherein the algorithms further include calculations based on the subject'"'"'s mean blood flow velocity.

21. The method of analyzing vascular structure in a human or animal according to claim 20, wherein the measurements of the subject come from at least three blood vessels.

22. The method of analyzing vascular structure in a human or animal according to claim 20, wherein the measurements of the subject are intracranial.

23. A method of assessing vascular health of a subject through analysis of multiple vascular measurements of multiple vascular segments, the method of assessing comprising the steps of:

obtaining blood flow parameters from multiple vascular measurements;

inputting patient data and data regarding related pathologies;

accessing a correlating system embodying a process of reasoning from blood flow parameters, patient data, and data regarding related pathologies to an assessment of vascular health; and

outputting an assessment of the subject'"'"'s vascular health.

24. The method according to claim 23 wherein the vascular measurements comprise data collected via ultrasound energy.

25. The method according to claim 24 wherein the vascular measurements are collected using a Doppler probe.

26. The method according to claim 25 wherein the vascular measurements comprise transcranial Doppler data.

27. The method according to claim 23 wherein the blood flow parameters comprise mean flow velocity and systolic acceleration.

28. The method according to claim 27 wherein a data set comprising mean flow velocity and the systolic acceleration comprise a characterization of vascular health, and

the method further comprising the step of comparing the characterization of vascular health of the subject to a set of characterizations of vascular health of a reference population.

29. The method according to claim 28 wherein the system comprises a Bayesian belief network.

30. The method according to claim 27 wherein the blood flow parameters further comprise a pulsatility index.

31. The method according to claim 30 wherein a data set comprising mean flow velocity, systolic acceleration, and pulsatility index comprise a characterization of vascular heath, and

the method further comprising the step of comparing the characterization of vascular health of the subject to a set of characterizations of vascular health of a reference population.

32. The method according to claim 31 wherein the system comprises a Bayesian belief network.

33. The method of claim 32 wherein the system accepts and incorporates input from a user regarding relationships and probabilities within a process of reasoning.

34. The method according to claim 23 wherein the system comprises a transparent Bayesian belief network.

35. The method according to claim 23 wherein an artery is one subject of the multiple vascular measurements.

36. The method according to claim 35, wherein the artery supplies a central nervous system.

37. The method according to claim 35, wherein the artery is selected from the group consisting of a common carotid artery, an internal carotid artery, an external carotid artery, a middle cerebral artery, an anterior cerebral artery, a posterior cerebral artery, an anterior communicating artery, a posterior communicating artery, a vertebral artery, a basilar artery, and branches thereof.

38. The method according to claim 23 wherein an intracranial vessel is the subject of the vascular measurements.

39. The method according to claim 23 wherein the vascular measurements comprise data from at least three blood vessels.

40. The method of claim 39 wherein the blood vessels are intracranial vessels associated with the cerebrovasculature.

41. The method of claim 23 wherein the system accepts and incorporates input from a user regarding relationships and probabilities within a process of reasoning.