IP Library › Granted Patent US 12,539,062
Granted Patent B2
US 12,539,062 · App. 18/480,446 · Granted Feb 3, 2026

Tissue oxygen saturation determined by Monte Carlo and iterative techniques

Inventors: Kate LeeAnn Bechtel (Pleasant Hill, CA); H. Keith Nishihara (Los Altos, CA)
Assignee: ViOptix, Inc.
A61B5/14551A61B5/0059A61B5/0075A61B5/14546A61B5/1455A61B5/14552A61B5/1459A61B5/1495A61B5/72A61B5/7246A61B5/7282A61B5/74A61B5/7405A61B5/742A61B5/7475A61B90/11A61B90/39A61M35/003A61B2090/065A61B2090/306A61B2090/395A61B2560/0431A61B2560/0475A61B2562/0271A61B2562/166
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,539,062
App. No.
18/480,446
Granted
Feb 3, 2026
Kind
B2
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.

Claims (42)

1 . A method comprising:

emitting light from a first light source and a second light source of a tissue oximetry device into a tissue;

using a plurality of detectors of the tissue oximetry device to detect reflected light from the tissue resulting from the emitted light;

using a processor, generating reflectance data points for the tissue based on detecting the light by the plurality of detectors;

for a first grid, determining a first subset of simulated reflectance curves from a plurality of simulated reflectance curves;

for the first grid, based on the first subset of simulated reflectance curves, fitting the reflectance data points to determine a fitting to one simulated reflectance curve of the first subset;

for a second grid, determining a second subset of simulated reflectance curves from the simulated reflectance curves based on the one simulated reflectance curve of the first subset determined during the first grid determination;

from the second grid determination, determining a peak surface array of absorption coefficients and reflection coefficients; and

using the reflection coefficients, determining an oxygen saturation of the tissue.

2 . The method of claim 1 wherein the plurality of simulated reflectance curves are stored in a memory of the tissue oximetry device.

3 . The method of claim 1 wherein the first grid is more coarse relative to the second grid.

4 . The method of claim 1 comprising:

from the second grid determination, determining an absorption coefficient and a reflectance coefficient for the reflectance data points by performing a weighted average of the absorption coefficients and reflection coefficients from the peak surface array,

wherein fitting the reflectance data points to a subset of simulated reflectance curves included in the first grid includes calculating a sum of squares error between the reflectance data points and each of the simulated reflectance curves of the first grid, and

the second subset of simulated reflectance curves are around the closest fitting one of the simulated reflectance curves included in the first grid.

5 . The method of claim 1 wherein a sensor head of the tissue oximetry device comprises an arrangement of source structures and detector structures,

the plurality of detector structures are arranged asymmetrically in the arrangement, asymmetric about a point on a line passing through the first and second source structures,

a first detector structure of the arrangement, wherein 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, and the first distance is greater than the second distance, and

a second detector structure of the arrangement, wherein 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, and the fourth distance is greater than the third distance.

6 . The method of claim 5 wherein the sensor head of the tissue oximetry device comprises

a third detector structure of the arrangement, wherein 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, and the sixth distance is different from the first distance and the second distance.

7 . The method of claim 6 wherein the sensor head of the tissue oximetry device comprises

a fourth detector structure of the arrangement, wherein 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, and fifth distances, and the eighth distance is different from the first, second, and sixth distances.

8 . The method of claim 7 wherein the first detector is nearest to the first light source relative to all other detectors, and the second detector is nearest to the second light source relative to all other detectors.

9 . The method of claim 7 wherein a ninth distance is between the first source structure and the second source structure, and the ninth distance is greater than the first, second, third, fourth, fifth, sixth, seventh, and eighth distances.

10 . The method of claim 7 wherein the first and second detector structures are on a first side of the line, while the third and fourth detector structures are on a second side of the line.

11 . The method of claim 7 wherein the processor of the tissue oximetry device is coupled to the first and second source structures, and the first, second, third, and fourth detector structures, and housed within an enclosure of the tissue oximetry device comprising the sensor head.

12 . The method of claim 11 comprising:

including a battery within the enclosure comprising the sensor head and processor, wherein the battery is coupled to the processor.

13 . The method of claim 1 wherein the processor is coupled to a nonvolatile memory, the nonvolatile memory is housed within an enclosure of the tissue oximetry device, and the simulated reflectance curves are stored in the nonvolatile memory stores.

14 . The method of claim 4 wherein a sensor head of the tissue oximetry device comprises an arrangement of source structures and detector structures,

the plurality of detector structures are arranged asymmetrically in the arrangement, asymmetric about a point on a line passing through the first and second source structures,

a first detector structure of the arrangement, wherein 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, and the first distance is greater than the second distance, and

a second detector structure of the arrangement, wherein 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, and the fourth distance is greater than the third distance.

15 . The method of claim 14 wherein the sensor head of the tissue oximetry device comprises

a third detector structure of the arrangement, wherein 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, and the sixth distance is different from the first distance and the second distance.

16 . The method of claim 15 wherein the sensor head of the tissue oximetry device comprises

a fourth detector structure of the arrangement, wherein 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, and fifth distances, and the eighth distance is different from the first, second, and sixth distances.

17 . The method of claim 16 wherein the first detector is nearest to the first light source relative to all other detectors, and the second detector is nearest to the second light source relative to all other detectors.

18 . The method of claim 16 wherein a ninth distance is between the first source structure and the second source structure, and the ninth distance is greater than the first, second, third, fourth, fifth, sixth, seventh, and eighth distances.

19 . The method of claim 16 wherein the first and second detector structures are on a first side of the line, while the third and fourth detector structures are on a second side of the line.

20 . The method of claim 16 wherein the processor of the tissue oximetry device is coupled to the first and second source structures, and the first, second, third, and fourth detector structures, and housed within an enclosure of the tissue oximetry device comprising the sensor head.

Continuity (10)
Continuation 16903315 · Jun 16, 2020
Division 15895904 · Feb 13, 2018
Division 15163565 · May 24, 2016
Continuation 13887220 · May 3, 2013
Provisional Application 61682146 · Aug 10, 2012
Provisional Application 61642399 · May 3, 2012
Provisional Application 61642389 · May 3, 2012
Provisional Application 61642395 · May 3, 2012
Provisional Application 61642393 · May 3, 2012
Related Publication 20240023842A1 · Jan 25, 2024
References Cited (71)
US 4223680A · Jobsis · 1980 [cited by applicant]
US 4286599A · Hahn et al. · 1981 [cited by applicant]
US 5088493A · Giannini et al. · 1992 [cited by applicant]
US 5218962A · Mannheimer et al. · 1993 [cited by applicant]
US 5517301A · Dave · 1996 [cited by applicant]
US 5517987A · Tsuchiya · 1996 [cited by applicant]
US 5690113A · Sliwa, Jr. et al. · 1997 [cited by applicant]
US 6056692A · Schwartz · 2000 [cited by applicant]
US 6070093A · Oosta et al. · 2000 [cited by applicant]
US 6078833A · Hueber · 2000 [cited by applicant]
US 6197034B1 · Gvozdic et al. · 2001 [cited by applicant]
US 6285904B1 · Weber et al. · 2001 [cited by applicant]
US 6453183B1 · Walker · 2002 [cited by applicant]
US 6516209B2 · Cheng et al. · 2003 [cited by applicant]
US 6549284B1 · Boas et al. · 2003 [cited by applicant]
US 6587701B1 · Stranc et al. · 2003 [cited by applicant]
US 6587703B2 · Cheng et al. · 2003 [cited by applicant]
US 6597931B1 · Cheng et al. · 2003 [cited by applicant]
US 6708048B1 · Chance · 2004 [cited by applicant]
US 6735458B2 · Cheng et al. · 2004 [cited by applicant]
US 6766188B2 · Soller · 2004 [cited by applicant]
US 6839580B2 · Zonios et al. · 2005 [cited by applicant]
US 7247142B1 · Elmandjra et al. · 2007 [cited by applicant]
US 7254427B2 · Cho et al. · 2007 [cited by applicant]
US 7344587B2 · Kahn et al. · 2008 [cited by applicant]
US D567949S · Lash et al. · 2008 [cited by applicant]
US 7355688B2 · Lash et al. · 2008 [cited by applicant]
US D568479S · Mao et al. · 2008 [cited by applicant]
US 7657293B2 · Lash et al. · 2010 [cited by applicant]
US 8798700B1 · Heaton et al. · 2014 [cited by applicant]
US 20020019587A1 · Cheng et al. · 2002 [cited by applicant]
US 20020179094A1 · Perlow · 2002 [cited by applicant]
US 20040111016A1 · Casscells et al. · 2004 [cited by applicant]
US 20040260161A1 · Melker · 2004 [cited by applicant]
US 20050177069A1 · Takizawa et al. · 2005 [cited by applicant]
US 20050250998A1 · Huiku · 2005 [cited by applicant]
US 20050277818A1 · Myers · 2005 [cited by applicant]
US 20060129037A1 · Kaufman et al. · 2006 [cited by applicant]
US 20070149886A1 · Kohls · 2007 [cited by applicant]
US 20080015422A1 · Wessel · 2008 [cited by applicant]
US 20080015424A1 · Bernreuter · 2008 [cited by applicant]
US 20080139908A1 · Kurth · 2008 [cited by applicant]
US 20080181715A1 · Cohen · 2008 [cited by applicant]
US 20080319290A1 · Mao et al. · 2008 [cited by applicant]
US 20090234209A1 · Lash et al. · 2009 [cited by applicant]
US 20090275805A1 · Lane et al. · 2009 [cited by applicant]
US 20100010486A1 · Mehta et al. · 2010 [cited by applicant]
US 20110028814A1 · Petersen et al. · 2011 [cited by applicant]
US 20110046458A1 · Pinedo et al. · 2011 [cited by applicant]
US 20110205535A1 · Soller et al. · 2011 [cited by applicant]
US 20110224518A1 · Tindi et al. · 2011 [cited by applicant]
US 20110237911A1 · Lamego et al. · 2011 [cited by applicant]
JP 05261088 · 1993 [cited by applicant]
JP 10216115A · 1998 [cited by applicant]
JP 11244268A · 1999 [cited by applicant]
JP 2006109964 · 2006 [cited by applicant]
KR 1020000075056 · 2000 [cited by applicant]
KR 1020090016744 · 2009 [cited by applicant]
WO 2011008382 · 2011 [cited by applicant]
Alexandrakis, et al., “Accuracy of the Diffusion Approximation in Determining the Optical Properties of a Two-Layer Turbid Medium,” Applied Optics, vol. 37, No. 31, Nov. 1, 1998, pp. 7403-7409. [cited by applicant]
Cen, et al., “Optimization of Inverse Algorithm for Estimating the Optical Properties of Biological Materials Using Spatially-Resolved Diffuse Reflectance,” Inverse Problems in Science and Engineering, vol. 18, No. 6, S… [cited by applicant]
Dam, et al., “Determination of Tissue Optical Properties from Diffuse Reflectance Profiles by Multivariate Calibration,” Applied Optics, vol. 37, No. 4, Feb. 1, 1998, pp. 772-778. [cited by applicant]
Farrell, et al., “Influence of Layered Tissue Architecture on Estimates of Tissue Optical Properties Obtained from Spatially Resolved Diffuse Reflectometry,” Applied Optics, vol. 37, No. 10, Apr. 1, 1998, pp. 1958-1972. [cited by applicant]
Fawzi, et al., “Determination of the Optical Properties of a Two-Layer Tissue Model by Detecting Photons Migrating at Progressively Increasing Depths,” Applied Optics, vol. 42, No. 31, Nov. 1, 2003, pp. 6398-6411. [cited by applicant]
Kienle, et al., “Spatially Resolved Absolute Diffuse Reflectance Measurements for Noninvasive Determination of the Optical Scattering and Absorption Coefficients of Biological Tissue,” Applied Optics, vol. 35, No. 13, M… [cited by applicant]
Nichols, et al., “Design and Testing of a White-Light, Steady-State Diffuse Reflectance Spectrometer for Determination of Optical Properties of Highly Scattering Systems,” Applied Optics, vol. 36, No. 1, Jan. 1, 1997, p… [cited by applicant]
Seo, et al., “Perturbation and Differential Monte Carlo Methods for Measurement of Optical Properties in a Layered Epithelial Tissue Model,” Journal of Biomedical Optics, vol. 12(1), 014030, Jan./Feb. 2007, pp. 1-15. [cited by applicant]
Tseng, et al., “In Vivo Determination of Skin Near-Infrared Optical Properties Using Diffuse Optical Spectroscopy,” Journal of Biomedical Optics, vol. 13(1), 014016, Jan./Feb. 2008, pp. 1-7. [cited by applicant]
Tseng, et al., “Analysis of a Diffusion-Model-Based Approach for Efficient Quantification of Superficial Tissue Properties,” Optics Letters, vol. 35, No. 22, Nov. 15, 2010, pp. 3739-3741. [cited by applicant]
Hueber, Dennis et al., “New Optical Probe Designs for Absolute (Self-Calibrating) NIR Tissue Hemoglobin Measurements,” in Proceedings of Optical Tomography and Spectroscopy of Tissue III, vol. 3597, 618-631(Jan. 1999). [cited by applicant]
Mittnacht, et al., “Methylene Blue Administration is Associated with Decreased Cerebral Oximetry Values,” Anesthesia & Analgesia, Aug. 2008, vol. 105, No. 2, pp. 549-550. [cited by applicant]