CEREBRAL VASCULAR REACTIVITY MONITORING

• US 20100030054A1
• Filed: 07/29/2008
• Published: 02/04/2010
• Est. Priority Date: 07/29/2008
• Status: Active Grant

• Current Assignee: Johns Hopkins University, Raba Equity Partners II, LLC
• Original Assignee: Raba Equity Partners II, LLC
• Inventors: BARUCH, Robert A., BRADY, Ken M.
• Granted Patent: US 7,744,541 B2
• Time in Patent Office: Days
• US Class Current: 600/368
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/031 Intracranial pressure
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/14553 specially adapted for cerebral tissue
• CPC Class Codes: A61B 5/4076 Diagnosing or monitoring particular conditions of the nervous system A61B5/4821, A61B5/4824 take precedence

Abstract

A monitoring device may include logic to receive arterial blood pressure data associated with a patient and receive tissue hemoglobin data associated with the patient. The logic may also calculate a linear correlation between the arterial blood pressure data and the tissue hemoglobin data. The correlation may be used to assess vascular reactivity.

Claims

1. A method, comprising:

receiving arterial blood pressure data associated with a patient;

receiving tissue hemoglobin data associated with the patient;

calculating a mean value for the arterial blood pressure data every first period of time;

calculating a mean value for the tissue hemoglobin data every first period of time; and

calculating a linear correlation between the mean value of the arterial blood pressure data and the mean value for the tissue hemoglobin data.

2. The method of claim 1, wherein the calculating a linear correlation comprises:

comparing a predetermined number of the mean values of the arterial blood pressure data and the tissue hemoglobin data, and

generating a hemoglobin volume value every second period of time.

3. The method of claim 2, further comprising:

outputting a plurality of linear correlation values, the plurality of linear correlation values corresponding to a continuous hemoglobin volume index.

4. The method of claim 2, further comprising:

plotting the hemoglobin volume values against arterial blood pressure or a cerebral perfusion pressure associated with the patient.

5. The method of claim 4, further comprising:

determining, based on the plotting, a range of at least one of arterial blood pressure or cerebral perfusion pressure at which autoregulation for the patient is functioning properly.

6. The method of claim 2, wherein the calculating a linear correlation comprises calculating a Pearson coefficient.

7. The method of claim 6, wherein the calculating a Pearson coefficient comprises comparing paired samples of the arterial blood pressure and the tissue hemoglobin data taken over overlapping periods of time and repeating the comparing at least once every 60 seconds to generate a linear correlation coefficient at least once every 60 seconds.

8. The method of claim 1, further comprising:

comparing the linear correlation to a pressure reactivity value, the pressure reactivity value being based on an intra-cranial pressure of the patient; and

determining a range of autoregulation for the patient based on a result of the comparing.

9. A monitoring device, comprising:

logic configured to;

receive arterial blood pressure data associated with a patient,

receive tissue hemoglobin data associated with the patient, and

calculate a linear correlation between mean values of the arterial blood pressure data and mean values of the tissue hemoglobin data.

10. The monitoring device of claim 9, wherein the logic is further configured to calculate a linear correlation value every first period of time, and wherein a plurality of linear correlation values comprise an index that corresponds to a hemoglobin volume index of the patient over a period of time.

11. The monitoring device of claim 10, wherein the logic is further configured to:

determine a range of autoregulation for the patient based on the linear correlation values.

12. The monitoring device of claim 9, wherein the logic is further configured to:

calculate the linear correlation every predetermined period of time, and

associate each linear correlation value to at least one of the arterial blood pressure or a cerebral perfusion pressure of the patient.

13. The monitoring device of claim 12, wherein the logic is further configured to:

generate a graphical representation of the linear correlation values as a function of the arterial blood pressure or the cerebral perfusion pressure, the monitoring device further comprising;

an output device configured to display the graphical representation.

14. The monitoring device of claim 9, wherein when calculating a linear correlation, the logic is configured to calculate a Pearson coefficient.

15. The monitoring device of claim 14, wherein when calculating a Pearson coefficient, the logic is configured to compare paired samples of the arterial blood pressure and the tissue hemoglobin data taken over approximately a five minute period of time.

16. The monitoring device of claim 15, wherein the logic is further configured to calculate a Pearson coefficient at least once per minute, wherein the Pearson coefficients correspond to data taken during overlapping five minute periods of time.

17. A computer-readable medium having stored thereon sequences of instructions which, when executed by at least one processor, cause the at least one processor to:

receive arterial blood pressure data associated with a patient;

receive tissue hemoglobin data associated with the patient; and

calculate a linear correlation between mean values of the arterial blood pressure data and mean values of the tissue hemoglobin data.

18. The computer-readable medium of claim 17, wherein when calculating a linear correlation, the instructions cause the at least one processor to calculate a Pearson coefficient.

19. The computer-readable medium of claim 18, wherein when calculating a Pearson coefficient, the instructions cause the at least one processor to:

compare approximately 30 paired samples of the arterial blood pressure and the tissue hemoglobin data taken over a five minute period.

20. The computer-readable medium of claim 17, further comprising instructions for causing the at least one processor to:

generate a graphical representation of linear correlation values as a function of the arterial blood pressure or cerebral perfusion pressure of the patient; and

output the graphical representation to a display device.

21. A system, comprising:

means for receiving arterial blood pressure data associated with a patient;

means for receiving hemoglobin data associated with the patient;

means for calculating a mean value for the arterial blood pressure data every first period of time;

means for calculating a mean value for the hemoglobin data every first period of time; and

means for calculating a linear correlation between the mean value of the arterial blood pressure data and the mean value for the hemoglobin data.