Dynamic StO2 measurements and analysis

• US 20070093701A1
• Filed: 10/26/2005
• Published: 04/26/2007
• Est. Priority Date: 10/26/2005
• Status: Active Grant

• Current Assignee: Hutchinson Technology Incorporated (TDK Corporation)
• Original Assignee: Hutchinson Technology Incorporated (TDK Corporation)
• Inventors: Jones, Jeffrey, Myers, Dean
• Granted Patent: US 7,536,214 B2
• Time in Patent Office: Days
• US Class Current: 600/323
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/0295 using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives

Abstract

A method of analyzing a patient'"'"'s tissue oxygenation capabilities includes measuring a tissue chromophore whose light absorption properties depend on the oxygenation state of the tissue and generating data representative of tissue oxygenation before, during and after a controlled ischemia event. From this data characterizing data, including ischemia onset slope, ischemia onset response time, ischemia recovery slope, ischemia recovery response time or hyperemia is automatically determined. This characterizing data is related to corresponding characterizing data determined from a control population. The relationship may be displayed on a graphical display.

Claims

1. A method for analyzing data related to tissue oxygenation, comprising the steps of:

taking an initial measurement to collect data on a tissue chromophore whose light absorption properties depend on the oxygenation state of the tissue;

restricting blood flow for a first predetermined period in the region where the initial measurement was made while continuing to measure the tissue chromophore;

un-restricting the blood flow after the first predetermined period while continuing to measure the tissue chromophore; and

using the data collected during the measurements, automatically determining within the data an ischemia start point and an ischemia end point of the first predetermined period.

2. The method of claim 1, wherein the step of determining within the data an ischemia end point further comprises:

smoothing the data;

transforming the data into second derivative points of the tissue chromophore measurement;

identifying peaks in the data, by identifying second derivative points that exceed an average of local second derivative points by a first predetermined amount;

identifying valleys in the data, by identifying second derivative points that are less than an average of local second derivative points by a second predetermined amount;

identifying peaks that precede valleys within a predetermined time interval to determine a valid peak;

generating a curve fitting on the second derivative points between each valid peak and its related valley, to produce a correlation coefficient versus the actual second derivative data;

comparing the correlation coefficient to a predetermined threshold;

determining that the valley represents the ischemia end point if a first predetermined relationship exists between the correlation coefficient and the predetermined threshold; and

determining that the valley does not represent the ischemia endpoint otherwise.

3. The method of claim 2, wherein the step of determining within the data an ischemia start point further comprises identifying a data point that precedes the ischemia end point by the first predetermined period.

4. The method of claim 3, comprising the further steps of:

selecting data points occurring in a second predetermined time period after the ischemia start point;

generating a curve fitting on the selected data points;

selecting from time or a measurement number to use as an independent variable; and

generating a correlation coefficient representative of a slope of onset of ischemia.

5. The method of claim 3, comprising the further steps of:

for a time interval beginning at the ischemia start point and ending at the ischemia end point, fitting the data points to a non-linear exponential response curve equation of CA_fit=(a₁+b₁*{1−

exp[(−

time+b₂)/b₃]}) where CA_fit=fitted data points, a₁=baseline data point value just before the ischemia start point, b₁=minimum data point value occurring between the ischemia start point and the ischemia end point minus a₁, b₂=time delay between the ischemia start point and when the data points in the time interval begin a significant decrease, and b₃=0.633; and

determining the elapsed time between (a₁) and (a₁+EQ[minimum(CA_fit)−

a₁]) where EQ represents a fraction equilibrium time between 0 and 1; and

for EQ=0.95 the resultant elapsed time is the 95% equilibrium response time for the tissue chromophore amount to reach an ischemia minimum, which is representative of an ischemia onset time.

6. The method of claim 2, comprising the further step of determining a recovery maximum point by identifying a maximum data point following the ischemia endpoint.

7. The method of claim 6, comprising the further step of determining a recovery end point by identifying a minimum data point occurring after the recovery maximum point.

8. The method of claim 7, comprising the further steps of:

selecting data points occurring between the ischemia end point and the recovery end point;

generating a curve fitting on the selected data points;

selecting from time or a measurement number to use as an independent variable; and

generating a correlation coefficient representative of a slope of recovery from ischemia.

9. The method of claim 7, comprising the further steps of:

identifying a minimum data point occurring between the recovery maximum point and the recovery end point; and

integrating the data points occurring in a time interval between the ischemia end point and the recovery end point for data points greater than the minimum data point.

10. The method of claim 6, comprising the further steps of:

for a time interval beginning at the ischemia end point and ending at the recovery maximum point, fitting data points to a non-linear exponential response curve equation CA_fit=(a₁+c₁*{1−

exp[(−

time+c₂)/c₃]}), where CA_fit=fitted data points, a₁=baseline data point just before the ischemia start point, c₁=maximum tissue chromophore value occurring between the ischemia endpoint and the recovery maximum point minus a₁, c₂=time delay between ischemia start point and when data points in the time interval begin a significant increase, and c₃=0.633; and

determining an elapsed time between (a₁) and (a₁+EQ[maximum(CA_fit)−

a₁]) where EQ represents a fraction equilibrium time between 0 and 1; and

for EQ=0.95 the resultant elapsed time is the 95% equilibrium response time for the tissue chromophore amount to reach its maximum recovery point which is representative of an ischemia recovery time.

11. The method of claim 1, wherein the tissue chromophore is one of StO₂, oxyhemoglobin, deoxyhemoglobin and total hemoglobin in the tissue.

12. The method of claim 1, comprising the further step of adjusting the data by a total amount of hemoglobin in the patient'"'"'s tissue.

13. A method of analyzing a patient'"'"'s tissue oxygenation capabilities, comprising the steps of:

measuring a tissue chromophore whose light absorption properties depend on an oxygenation state of the tissue and generating data representative of the patient'"'"'s tissue oxygenation before, during and after a controlled ischemia event; and

automatically determining from said data characterizing data related to tissue oxygenation.

14. The method of claim 13, wherein the tissue chromophore is one of StO₂, oxyhemoglobin, deoxyhemoglobin and total amount of hemoglobin in the tissue.

15. The method of claim 13, comprising the further step of displaying at least one of said measurement data and characterizing data on a display.

16. The method of claim 13, comprising the further step of relating said patient characterizing data to corresponding characterizing data determined from a control population.

17. The method of claim 16, comprising the further step of displaying said relationship on a display.

18. The method of claim 17, wherein the relationship is displayed as a distribution meter plot in which the control population characterizing data is fit to a distribution curve.

19. The method of claim 18, wherein the distribution curve is a log normal probability density function.

20. The method of claim 18, wherein patient characterizing data is plotted on the distribution curve showing the patient characterizing data relative to a distribution center and spread of the control population characterizing data.

21. The method of claim 20, wherein the distribution center and spread of the control population characterizing data is one of mean or median and standard deviation or percentile.

22. The method of claim 17, wherein the relationship is displayed as a distribution statistic trend plot in which the patient characterizing data is scatter plotted or line graphed versus time.

23. The method of claim 22, wherein the distribution statistic trend plot shows the distance of patient characterizing data relative to a distribution of the control population characterizing data.

24. The method of claim 23, wherein the distribution position includes one of percentile, t, z or f value, p-value, curve area left or right of the characterizing data, difference between patient characterizing data and control population mean, or standard deviation.

25. The method of claim 17, wherein the relationship is displayed as an analysis trend plot relative to the control population characterizing data.

26. The method of claim 17, wherein the patient characterizing data is plotted on a scatter plot or a line graph versus time with normal limits shown as constant lines representing the center and spread of the control population characterizing data.

27. The method of claim 16, wherein the control population is known to be healthy.

28. The method of claim 16, wherein the control population is known to be unhealthy.

29. The method of claim 16, wherein the control population shares at least a first selected attribute of the patient.

30. The method of claim 29, wherein the at least first selected attribute is one of sex, age range, weight range or health attribute.

31. The method of claim 16, comprising the further steps of determining that an ischemic response of the patient is normal if a predetermined relationship exists between the patient characterizing data and the control population characterizing data and determining that the patient ischemic response is abnormal otherwise.

32. The method of claim 31, wherein the first predetermined relationship comprises the patient characterizing data being within about the 5^th to the 95^th percentile of the control population characterizing data.

33. The method of claim 31, wherein the first predetermined relationship comprises the patient characterizing data being within about two standard deviations of the control population characterizing data.

34. The method of claim 16, comprising the further steps of determining that an ischemic response of the patient is healthy if a first predetermined relationship exists between the patient characterizing data and the control population characterizing data and determining that the patient ischemic response is unhealthy otherwise.

35. The method of claim 34, wherein the first predetermined relationship comprises the patient characterizing data being within about the 5^th to the 95^th percentile of the control population characterizing data.

36. The method of claim 34, wherein the first predetermined relationship comprises the patient characterizing data being within a range of two standard deviations of the control population characterizing data.

37. The method of claim 13, comprising the further step of repeating the method periodically for an extended period of time.

38. The method of claim 13, comprising the further step of indicating when patient characterizing data is outside of a pre-determined range of values.

39. The method of claim 38, wherein the step of indicating further comprises the step of indicating by at least one of audible, visual or sensory signals.

40. The method of claim 13, wherein the characterizing data is one of ischemia onset slope, ischemia onset response time, ischemia recovery slope, ischemia recovery response time or hyperemia.

41. The method of claim 13, wherein determining from said data characterizing data related to tissue oxygenation comprises the further steps of:

selecting data points occurring in a predetermined time period after an ischemia start point;

generating a curve fitting on the selected data points;

selecting from time or a measurement number to use as an independent variable; and

generating a correlation coefficient representative of a slope of onset of ischemia.

42. The method of claim 13, wherein determining from said data characterizing data related to tissue oxygenation comprises the further steps of:

for a time interval beginning at an ischemia start point and ending at an ischemia end point, fitting the data points to a non-linear exponential response curve equation of CA_fit=(a₁+b₁*{1−

exp[(−

time+b₂)/b₃]}) where CA_fit=fitted data points, a1=baseline data point value just before the ischemia start point, b₁=minimum data point value occurring between the ischemia start point and the ischemia end point minus a₁, b₂=time delay between the ischemia start point and when the data points in the time interval begin a significant decrease, and b₃=0.633; and

determining the elapsed time between (a₁) and (a₁+EQ[minimum(CA_fit)−

a₁]) where EQ represents a fraction equilibrium time between 0 and 1; and

for EQ=0.95 a resultant elapsed time is the 95% equilibrium response time for the tissue chromophore amount to reach an ischemia minimum, which is representative of an ischemia onset time.

43. The method of claim 13, wherein determining from said data characterizing data related to tissue oxygenation comprises the further steps of:

selecting data points occurring between an ischemia end point and a recovery end point;

generating a curve fitting on the selected data points;

selecting from time or a measurement number to use as an independent variable; and

generating a correlation coefficient representative of a slope of recovery from ischemia.

44. The method of claim 13, wherein determining from said data characterizing data related to tissue oxygenation comprises the further steps of:

for a time interval beginning at an ischemia end point and ending at a recovery maximum point, fitting data points to a non-linear exponential response curve equation CA_fit=(a₁+c₁*{1−

exp[(−

time+c₂)/c₃]}), where CA_fit=fitted data points, a1=baseline data point just before an ischemia start point, c₁=maximum tissue chromophore value occurring between the ischemia endpoint and recovery maximum point minus a₁, c₂=time delay between the ischemia start point and when data points in the time interval begin a significant increase, and c₃=0.633; and

determining an elapsed time between (a₁) and (a₁+EQ[maximum(CA_fit)−

a₁]) with EQ representing a fraction equilibrium time between 0 and 1; and

for EQ=0.95 the resultant elapsed time is the 95% equilibrium response time for the tissue chromophore amount to reach its maximum recovery point which is representative of an ischemia recovery time.

45. The method of claim 13, wherein determining from said data characterizing data related to tissue oxygenation comprises the further steps of:

determining a recovery maximum point and a recovery end point;

identifying a minimum data point occurring between the recovery maximum point and the recovery end point; and

integrating the data points occurring in a time interval between an ischemia end point and the recovery end point for data points greater than the minimum data point.

46. The method of claim 13, wherein determining from said data characterizing data related to tissue oxygenation further comprises the step of adjusting said characterizing data by the total amount of hemoglobin in the patient'"'"'s tissue.

47. An apparatus for analyzing a patient'"'"'s tissue oxygenation capabilities, the apparatus comprising:

a software program for installation on a processor, wherein the software program is adapted to;

input data from measurements of a tissue chromophore whose light absorption properties depend on the oxygenation state of the tissue before, during and after a controlled ischemic event; and

determine from said data characterizing data related to tissue oxygenation.

48. The apparatus of claim 47, wherein the characterizing data is one of ischemia onset slope, ischemia onset response time, ischemia recovery slope, ischemia recovery response time and hyperemia.

49. The apparatus of claim 47, wherein the software program is further adapted to relate said patient characterizing data to corresponding characterizing data determined from a control population.

50. The apparatus of claim 49, wherein the software program is further adapted to determine that an ischemic response of the patient is normal if a predetermined relationship exists between the patient characterizing data and the corresponding characterizing data of the control population and determine that the patient ischemic response is abnormal otherwise.

51. The apparatus of claim 49, wherein the software program is further adapted to determine that an ischemic response of the patient is healthy if a predetermined relationship exists between the patient characterizing data and the corresponding characterizing data of the control population and to determine that the patient ischemic response is unhealthy otherwise.

52. The apparatus of claim 49, wherein the software program is further adapted to generate a display of said relationship.