METHOD OF ASSESSING TISSUE VIABILITY USING NEAR-INFRARED SPECTROSCOPY

• US 20090216098A1
• Filed: 02/24/2009
• Published: 08/27/2009
• Est. Priority Date: 04/03/1997
• Status: Active Grant

• Current Assignee: National Research Council Canada
• Original Assignee: National Research Council Canada
• Inventors: Stranc, Miroslaw F., Sowa, Michael G. R., Mantsch, Henry H.
• Granted Patent: US 8,060,188 B2
• Time in Patent Office: Days
• US Class Current: 600/328
• 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 non-invasive method for imaging variations in tissue viability, the method comprising:

providing a tissue portion;

illuminating the tissue portion with a spectral output of a light source; and

capturing a multispectral image of the tissue portion, the multispectral image having of a series of images at respective wavelength channels chosen for differential absorption of the spectral output by oxygenated hemoglobin and deoxygenated hemoglobin.

2. The non-invasive method according to claim 1 wherein capturing a multispectral image comprises capturing the series of images at respective wavelength channels chosen for differential absorption of the spectral output by oxygenated hemoglobin, deoxygenated hemoglobin, and water.

3. The non-invasive method according to claim 1 wherein capturing the series of images further comprises capturing images at respective wavelength channels that correspond to absorption band maxima or isobestic points for oxygenated hemoglobin, deoxygenated hemoglobin, and water within the visible and near infrared spectrum.

4. The non-invasive method according to claim 3 wherein capturing images at respective wavelength channels that correspond to absorption band maxima for deoxygenated hemoglobin comprises capturing images at least one of:

430 nm, 565 nm and 760 nm.

5. The non-invasive method according to claim 3 wherein capturing images at respective wavelength channels that correspond to isobestic points for deoxygenated hemoglobin and oxygenated hemoglobin comprises capturing images at least one of:

550 nm and 830 nm.

6. The non-invasive method according to claim 3 wherein capturing images at respective wavelength channels that correspond to absorption band maxima for water comprises capturing an image at 980 nm.

7. The non-invasive method according to claim 1 wherein capturing a multispectral image further comprises capturing a series of images at respective wavelength channels of 430 nm, 530 nm, 565 nm, 760 nm, 830 nm, and 980 nm.

8. The non-invasive method according to claim 1 further comprising grouping together pixels of the multispectral image with similar responses.

9. The non-invasive method according to claim 8 wherein grouping together pixels further comprises applying a component analysis to identify uncorrelated features of the multispectral image.

10. The non-invasive method according to claim 8 wherein grouping together pixels further comprises applying a cluster analysis to the multispectral image.

11. The non-invasive method according to claim 1 further comprising preprocessing the images to improve a contrast of the images.

12. The non-invasive method according to claim 11 wherein preprocessing comprises applying a median filter to the images.

13. The non-invasive method according to claim 11 wherein preprocessing comprises applying a log residual correction to the images.

14. The non-invasive method according to claim 11 wherein preprocessing comprises applying a normalization to the images.

15. The non-invasive method according to claim 11 wherein preprocessing comprises subtracting estimated topographical and illumination factors from the images.

16. The non-invasive method according to claim 11 wherein preprocessing comprises applying a statistical scaling to the images.