OPTICAL MEASUREMENT OF CELLULAR ENERGETICS

• US 20080200780A1
• Filed: 11/29/2007
• Published: 08/21/2008
• Est. Priority Date: 05/11/2006
• Status: Abandoned Application

• Current Assignee: University of Washington
• Original Assignee: University of Washington
• Inventors: Schenkman, Kenneth A., Burns, David H., Arakaki, Lorilee S.L., Feigl, Eric O., Ciesielski, Wayne A.
• Application Number:
  US11/947,242
• Publication Number:
  US 20080200780A1
• Time in Patent Office: Days
• US Class Current: 600/310
• 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 5/0062 Arrangements for scanning
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/1459 invasive, e.g. introduced into the body by a catheter A61B5/1464 takes precedence
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/4519 Muscles A61B5/389, A61B5/224 take precedence

Abstract

This document discloses, among other things, systems and methods for measuring a level of myoglobin, hemoglobin, and cytochrome using an optical probe coupled to a spectrometer. Multivariate analysis of the spectral data yields quantifiable cellular and mitochondrial characteristics.

Claims

1. A system comprising:

a data source configured to provide data corresponding to optical spectra for a tissue;

a data analyzer coupled to the source, the data analyzer configured to generate an estimate of a cellular energetic parameter using a multivariate curve resolution algorithm and using the data from the data source; and

an output device coupled to the data analyzer and configured to render an output based on the parameter.

2. The system of claim 1 wherein the data source includes a probe having an optical transmitter and an optical detector and wherein the optical detector is configured to provide spectral data using light from the optical transmitter.

3. The system of claim 2 wherein the probe provides data corresponding to reflectance spectra.

4. The system of claim 2 wherein the probe provides data corresponding to transmission spectra.

5. The system of claim 2 wherein the probe is configured for external use.

6. The system of claim 2 wherein the probe is configured for internal use.

7. The system of claim 1 wherein the data analyzer is configured to determine a concentration, saturation, oxygenation, oxidation, or a content.

8. The system of claim 1 wherein the data analyzer includes a processor having instructions for executing an iterative process.

9. The system of claim 8 wherein the iterative process includes an alternating least squares process.

10. A method comprising:

receiving data corresponding to optical spectra from a tissue sample;

alternately estimating concentrations of pure components for each tissue spectrum and estimating pure component spectra using an iterative process;

monitoring for convergence between two iterations; and

upon detecting convergence, calculating a cellular energetic parameter based on the estimated concentrations.

11. The method of claim 10 wherein estimating the pure component spectra includes determining a concentration.

12. The method of claim 10 wherein receiving data includes receiving data from an optical probe.

13. The method of claim 10 wherein receiving data includes receiving data corresponding to at least one of visible light and near infrared light.

14. The method of claim 10 wherein estimating the concentrations includes accessing stored information.

15. The method of claim 10 wherein alternately estimating includes executing a multivariate curve resolution algorithm.

16. The method of claim 15 wherein executing the multivariate curve resolution algorithm includes using alternating least squares optimization.

17. The method of claim 10 wherein monitoring for convergence includes comparing a stored value and a difference between two pure component spectra.

18. The method of claim 10 wherein calculating the cellular energetic parameter includes calculating at least one of myoglobin saturation, hemoglobin saturation, and cytochrome oxidation.

19. A device comprising:

a portable housing;

a user interface coupled to the portable housing, the interface having at least one user operable switch and an output device;

a processor disposed in the housing and coupled to the user interface; and

a probe coupled to the processor, the probe having an illumination source and an optical receiver element, the optical receiver element configured to generate data using a specimen tissue and using the illumination source; and

wherein the processor is configured to execute an algorithm for implementing multivariate curve resolution analysis, the processor having access to a memory with instructions stored thereon for performing the analysis using the data and further wherein the processor is configured to generate at least one cellular energetic parameter using a result from the analysis.

20. The device of claim 19 wherein the user interface includes at least one of a keyboard and a pointing device and further wherein the output device includes a display.

21. The device of claim 19 wherein the processor is configured to implement multivariate curve resolution using alternating least squares optimization.

22. The device of claim 19 further including a battery coupled to the processor.

23. The device of claim 19 wherein the probe is configured to generate data corresponding to at least one of visible light and near infrared light.