Method of assessing tissue viability using near-infrared spectroscopy

• US 20040116814A1
• Filed: 12/16/2002
• Published: 06/17/2004
• Est. Priority Date: 04/03/1997
• Status: Active Grant

• Current Assignee: National Research Council Canada
• Original Assignee: National Research Council Canada
• Inventors: Mantsch, Henry H., Sowa, Michael G., Stranc, Miroslaw F.
• Granted Patent: US 7,729,747 B2
• Time in Patent Office: Days
• US Class Current: 600/473
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/413 Monitoring transplanted tissue or organ, e.g. for possible rejection reactions after a transplant
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00

Abstract

Prolonged and severe tissue hypoxia results in tissue necrosis in pedicled flaps. We demonstrate the potential of near-infrared spectroscopy for predicting viability of compromised tissue portions. This approach clearly identifies tissue regions with low oxygen supply, and also the severity of this challenge, in a rapid and non-invasive manner, with a high degree of reproducibility. Tissues remaining below a certain hemoglobin oxygen saturation threshold (oxygen saturation index <1) for prolonged periods (>6 h) became increasingly dehydrated, eventually becoming visibly necrotic. Tissues above this threshold (oxygen saturation index >1), despite being significantly hypoxic relative to the pre-elevation saturation values, remained viable over the 72 h post-elevation monitoring period. The magnitude of the drop in tissue oxygen saturation, as observed immediately following surgery, correlated with the final clinical outcome of the flap tissue. These results indicate the potential of near infrared spectroscopy and imaging to monitor tissue oxygenation status and assess tissue viability following reconstructive surgery. Early, nonsubjective detection of poor tissue oxygenation following surgery increases the likelihood that intervention aimed at saving the tissue will be successful.

Claims

1. A method of imaging variations in tissue oxygenation, perfusion or hydration comprising:

providing a tissue portion;

subjecting the tissue portion to spectral analysis, thereby providing an image;

separating the image into pixels;

determining the relative contributions of chromophores in the tissue portion to the resulting spectrum measured at representative pixels; and

grouping together pixels of the image with similar responses.

2. The method according to claim 1 wherein the chromophores are hemoglobin, oxyhemoglobin and water.

3. The method according to claim 1 wherein the spectral analysis comprises visible and near-infrared wavelengths.

4. The method according to claim 1 wherein the spectral analysis is carried out at least one of the following wavelengths:

430 nm, 550 nm, 565 nm, 760 nm, 830 nm, 980 nm and combinations thereof.

5. The method according to claim 1 wherein the image is preprocessed.

6. The method according to claim 5 wherein the image preprocessing comprises applying inverse contrast ratio transformation to the image.

7. The method according to claim 5 wherein the image preprocessing comprises optical density transformation.

8. The method according to claim 1 wherein the pixels are grouped using unsupervised classification means.

9. The method according to claim 8 wherein the pixels are grouped using fuzzy C-means cluster analysis.

10. The method according to claim 9 wherein the pixels are grouped by assigning a membership value from 0 to 1 to a pixel based on differential absorption.

11. The method according to claim 10 wherein pixels having a membership value of 1 have a first color while pixels having a membership value of 0 have a second color.

12. The method according to claim 1 wherein the pixels are grouped together using supervised classification means.

13. The method according to claim 8 wherein the unsupervised classification means comprises principal component analysis.

14. The method according to claim 2 wherein total hemoglobin is mapped.

15. The method according to claim 2 wherein tissue hydration is mapped.

16. The method according to claim 2 wherein oxygenated hemoglobin is mapped.

17. The method according to claim 2 wherein tissue oxygenation is mapped.

18. The method according to claim 1 wherein the image is statistically scaled.

19. The method according to claim 1 wherein the image is subjected to logarithmic residual correction.

20. The method according to claim 1 wherein the tissue is at risk or is compromised.

21. The method according to claim 12 wherein the supervised classification means comprises spectral discrimination based on a reference data set.