Monte carlo and iterative methods for determination of tissue oxygen saturation

Patent metadata

Field	Value
Publication number	US-9345439-B2
Application number	US-201313887220-A
Country	US
Kind code	B2
Filing date	May 3, 2013
Priority date	May 3, 2012
Publication date	May 24, 2016
Grant date	May 24, 2016

Abstract

A method for determining oxygen saturation includes emitting light from sources into tissue; detecting the light by detectors subsequent to reflection; and generating reflectance data based on detecting the light. The method includes determining a first subset of simulated reflectance curves from a set of simulated reflectance curves stored in a tissue oximetry device for a coarse grid; and fitting the reflectance data points to the first subset of simulated reflectance curves to determine a closest fitting one of the simulated reflectance curves. The method includes determining a second subset of simulated reflectance curves for a fine grid based on the closest fitting one of the simulated reflectance curves; determining a peak of absorption and reflection coefficients from the fine grid; and determining an absorption and a reflectance coefficient for the reflectance data points by performing a weighted average of the absorption coefficients and reflection coefficients from the peak.

First claim

The invention claimed is:

1. A method for determining oxygen saturation of tissue via a tissue oximetry device comprising:
emitting light having at least two wavelengths into tissue from a first source structure and a second source structure that are optically coupled respectively to the first and second light sources;
detecting the light by a plurality of detector structures subsequent to reflection of the light from the tissue, wherein the plurality of detector structures comprises a first detector structure, a second detector structure, a third detector structure, and a fourth detector structure,
the first and second source structures and the first, second, third, and fourth detector structures are arranged in a circular arrangement on a probe face of the tissue oximetry device,
a first distance is from the first detector structure to the first source structure,
a second distance is from the first detector structure to the second source structure,
the first distance is greater than the second distance,
a third distance is from the second detector structure to the first source structure,
a fourth distance is from the second detector structure to the second source structure,
the fourth distance is greater than the third distance,
a fifth distance is from the third detector structure to the first source structure,
a sixth distance is from the third detector structure to the second source structure,
the fifth distance is different from the first distance and the second distance,
the sixth distance is different from the first distance and the second distance,
a seventh distance is from the fourth detector structure to the first source structure,
an eighth distance is from the fourth detector structure to the second source structure,
the seventh distance is different from the first, second, fifth, and sixth distances,
the eighth distance is different from the first, second, fifth, and sixth distances,
the first distance is greater than the second, third, fifth, sixth, seventh, and eighth distances, and
the second distance is less than the fifth, sixth, seventh, and eight distances;
generating digital reflectance data points for the tissue from detected light;
retrieving a plurality of simulated data points from a memory of the tissue oximetry device for each simulated reflectance curve in a set of simulated reflectance curves, wherein the simulated data points are simulated reflectance intensities of the simulated reflectance curves for the first, second, third, fourth, fifth, sixth, seventh, and eighth distances;
from the simulated data points, for the simulated reflectance intensities for the first, second, third, fourth, fifth, sixth, seventh, and eighth distances, for the set of simulated reflectance curves, selecting, by a processor of the tissue oximetry device, a first of the simulated reflectance curves as a first selected simulated reflectance curve;
from first simulated data points of the plurality of simulated data points for simulated reflectance intensities for the first, second, third, fourth, fifth, sixth, seventh, and eighth distances, wherein the first simulated data points are for the first of the simulated reflectance curves, selecting, by the processor of the tissue oximetry device, a second of the simulated reflectance curves that is an first interval value away from the first of the simulated reflectance curves as a second selected simulated reflectance curve;
from second simulated data points of the plurality of simulated data points for simulated reflectance intensities for the first, second, third, fourth, fifth, sixth, seventh, and eighth distances, wherein the second simulated data points are for the second of the simulated reflectance curves, selecting, by the processor of the tissue oximetry device, a third of the simulated reflectance curves that is a second interval value away from the second of the simulated reflectance curves as a second selected simulated reflectance curve, wherein the first, second, and third selected simulated reflectance curves comprise a first subset of the simulated reflectance curves included in a coarse grid of the simulated reflectance curves;
fitting, by the processor of the tissue oximetry device via a least-error fit process, the digital reflectance data points to the first subset of simulated reflectance curves included in the coarse grid to determine a closest fitting one of the simulated reflectance curves included in the coarse grid;
defining, by the processor of the tissue oximetry device, a second subset of simulated reflectance curves from the set of simulated reflectance curves stored in the memory of the tissue oximetry device for a fine grid based on the closest fitting one of the simulated reflectance curves included in the coarse grid;
positioning, by the processor of the tissue oximetry device, the closest one of the simulated reflectance curves at a center of the fine grid of the second subset of simulated reflectance curves;
determining, by the processor of the tissue oximetry device, a peak surface array of absorption coefficients and scattering coefficients from the fine grid;
calculating, by the processor of the tissue oximetry device, a weighted average of the absorption coefficients and scattering coefficients from the peak surface array to determine a set of absorption coefficients and a set of scattering coefficients for the reflectance data points, wherein the absorption coefficients and the scattering coefficients for the reflectance data points are independent from each other; and
determining an oxygen saturation value for the tissue based on the set of absorption coefficients from the light having at least two wavelengths; and
outputting, by the processor of the tissue oximetry device, a value indicative of the oxygen saturation value from the tissue oximetry device.

2. The method of claim 1 wherein the weighted average is a centroid calculation.

3. The method of claim 1 wherein fitting the reflectance data points to a subset of simulated reflectance curves included in the coarse grid includes calculating a sum of squares error between the reflectance data points and each of the simulated reflectance curves of the coarse grid.

4. The method of claim 1 wherein the second subset of simulated reflectance curves are around the closest fitting one of the simulated reflectance curves included in the coarse grid.

5. The method of claim 4 wherein the first subset of simulated reflectance curves includes at least ten of the simulated reflectance curves stored in the memory of the tissue oximetry device.

6. The method of claim 4 wherein the second subset of simulated reflectance curves includes at least ten of the simulated reflectance curves stored in the memory of the tissue oximetry device.

7. The method of claim 1 wherein the interval of steps includes steps through scattering coefficients μ′ s and steps through absorption coefficients μ a of the simulated reflectance curves stored in the memory of the tissue oximetry device.

8. The method of claim 1 further comprising applying a correction function to the reflectance data points based on gain corrections stored in the memory of the tissue oximetry device for source structure-detector structure pairs.

9. The method of claim 1 further comprising:
calculating a log of the reflectance data points;
calculating a log of the simulated reflectance curves;
dividing the log of the reflectance data points by a square root of the of source structure-detector structure distances of the source structures and the detector structures of the tissue oximetry device; and
dividing the log of the simulated reflectance curves by the square root of the source structure-detector structu

Assignees

• Vioptix Inc

Inventors

• Bechtel Kate Leeann
• Nishihara H Keith

Classifications

• A61B5/742

  using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339) · CPC title

• A61B5/14551 Primary

  for measuring blood gases · CPC title

• A61B2090/306

  using optical fibres · CPC title

• A61B5/1495 Primary

  Calibrating or testing of in-vivo probes · CPC title

• A61B2560/0431

  Portable apparatus, e.g. comprising a handle or case · CPC title