WO2009052607A1

WO2009052607A1 - Method and apparatus for microvascular oxygenation imaging

Info

Publication number: WO2009052607A1
Application number: PCT/CA2008/001837
Authority: WO
Inventors: Yasser Sherif Fawzy
Original assignee: Perceptronix Medical Inc.
Priority date: 2007-10-24
Filing date: 2008-10-17
Publication date: 2009-04-30

Abstract

The present invention relates to an apparatus and method for quantifying the tissue de-oxygenated blood index (dHbi) directly from image data for improving image contrast and detection of suspicious/cancer lesions and/or other kind of pathologies. The tissue de-oxygenated index (dHBi) is defined using a diffusion approximation model analysis as a de-oxygenated blood volume multiplied by a scattering amplitude (kHbi). The present invention also relates to a new method and device for real time measurement of the tissue oxygenation index (TOI).

Description

Method and Apparatus for Microvascular Oxygenation Imaging

BACKGROUND OF THE INVENTION This application claims priority from United States Provisional Patent

Application No. 60/982,252, filed October 24, 2007.

FIELD OF THE INVENTION

The present invention relates to an apparatus and a method for quantifying tissue microvascular properties, namely tissue blood volume fraction and blood oxygenation directly from the image data. The quantified information is then used for enhancing image contrast and thereby increasing the visual sensitivity to cancer lesions. The present invention also relates to a method and apparatus used for quantifying the tissue/mucosa oxygenation levels directly from the image data to detect and monitor early changes in the mucosa oxygen supply and perfusion for applications like ischemia and micro-vascular surgery.

BACKGROUND OF THE INVENTION

Imaging is capturing electromagnetic radiation either reflected or emitted from an object of interest in a manner which preserves or otherwise represents the spatial distribution of said radiation from within an object. In the field of medical imaging, light is utilized to illuminate body tissues (internal organs) and returns as diagnostic or otherwise useful image. The light beam projected into the sample is absorbed, reflected, scattered, and transmitted or back-reflected through the sample material and then the back-reflected (back-scattered) light is collected and directed to the detector optics. Various optical apparati such as microscopes, endoscopes, cameras etc. support viewing or analyzing the images. Generally in endoscopy conventional white light reflectance imaging is used to view surface morphology and assess the internal organs based on appearance. Clinicians may detect various diseases such as cancer by observing features in white light reflectance images such as the tissue color and surface morphology. While changes in the physical appearance (color and morphology) of tissue using white light is useful, to accomplish more reliable and earlier detection of diseases, such as cancer, a number of research groups have investigated the use of tissue autofluorescence to improve the detection sensitivity of cancerous lesions. Just as certain morphological changes in tissue may be associated with disease, chemical changes may also be exploited for disease detection especially for early detection of disease. When tissue is illuminated (or excited) with specific wavelengths of ultraviolet (UV) or visible light, biological molecules (fluorophores) will absorb the energy and emit it as fluorescent light at longer wavelengths (green/red wavelength region). These wavelengths of light are selected based on their ability to stimulate certain chemicals in tissue that are associated with disease or disease processes. Images or spectra from these emissions (fluorescence) may be captured for observation and/or analysis. Diseased tissue has considerably different fluorescent signals than healthy tissue so the spectra of fluorescent emissions can be used as a diagnostic tool. Abnormal tissues such as diseased or cancerous tissues tend to emit significantly lower intensities of such autofluorescence light at green wavelengths than normal tissues. Abnormal tissues therefore tend to appear darker in a corresponding fluorescence image of the tissues at green wavelengths. Although fluorescence imaging provides increased sensitivity to diseases such as cancer, the increase in detection sensitivity compared to white light reflectance imaging was at the cost of the decreased detection specificity. The result was increased medical costs related to the enlarged number of biopsies resulting from by the increased number of false positives.

Another imaging method utilizes near infrared light to measure tissue oxygenation in healthy and diseased tissue. It is known that cancerous tissues exhibit hypoxia caused by increased oxygen consumption due to rapid growth of cancerous cells. However, other unrelated chromophores tend to overwhelm and obscure the effects of hypoxia at visible imaging wavelengths interfering with the ability of conventional imaging systems to detect tissue oxygenation status. Biological tissue is a turbid medium which absorbs and scatters incident light. When light impinges on tissue, it is typically multiple elasticaliy scattered but at the same time absorption and fluorescence can occur, too. Further scattering and absorption can occur before light exits the tissue surface containing compositional and structural information of the tissue. This information can be used for detection of pre-cancers and early cancers that are accompanied by local metabolic and architectural changes at the cellular and subcellular level. For example, changes in the nuciear-to-cytoplasm ratio of cells and changes in chromatin texture are detectable. These changes affect the elastic scattering properties of tissue. One of the most prominent features used by pathologists to diagnose cancerous tissue is the presence of enlarged and crowded nuclei. When a beam of light reaches the tissue under investigation, part of it will be specularly reflected by the surface, while the rest is refracted and transmitted into the tissue. The light transmitted into the tissue will be scattered and absorbed. After multiple scattering, some of the transmitted light will return to the tissue surface and be detectable. The part of the light that is scattered within the tissue is called diffuse reflectance light. Light scattering by biological tissues are caused by refractive index variations inside the tissue at the boundaries of various microstructures such as the cell nucleus and collagen bundles. Thus, tissue scattering property varies with a tissue's microstructure properties and morphology, which are often accompanied with tissue pathological changes. For example, when normal tissue becomes cancerous, the nuclear size of the cells and the epithelial layer thickness increase as does the total volume occupied by the cells (micro-scatterers). Such changes in the tissue microstructure and morphology have been found to cause intrinsic differences in the light-scattering properties of the normal and cancerous lesions. Recent studies have shown that vascularization related changes and morphological related changes are very important features for early cancer detection. For example, Published Patent Application No. WO 2006/076810 to Fawzy et al., Method And Apparatus For Measuring Cancerous Changes From Reflectance Spectral Measurements Obtained During Endoscopic Imaging, the disclosure of which is incorporated herein, discloses a new method and an apparatus for early cancer detection from diffuse reflectance spectra (DRS) measured during in vivo endoscopic imaging and obtaining quantitative information about the tissue absorption-related properties and/or scattering-related properties directly from measured diffuse reflectance spectra (DRS). However, this method requires spectral measurement in addition to the imaging mode and is applicable only for fiber endoscopes.

A ratio of oxyhemoglobin and deoxyhemoglobin can be inferred and used to determine tissue oxygenation status, which is very useful for cancer detection and prognostication. It can also be used to derive information about scatterers in the tissue, such as the size distribution of cell nucleus and average cell density. In many cases quantification of chromophore concentration is desired, and requires the ability to separate the effects of absorption from those of scattering. Also, the absorption properties and scattering properties of the light at the living body tissue differ according to the wavelength of the illuminated light. This difference is due to a distribution of different absorbent material such as blood vessels in the depth direction. Longer wavelengths of illumination light as infrared light provide information from deeper part of the tissue while shorter wavelengths of illumination light give information of the tissue near the surface. So, thick blood vessels that are at deep positions are detected in the longer wavelengths band image such as red or infrared band image while the blood vessel networks such as capillaries that exists near the surface of mucous membrane are detected in the blue band image. Detection of the changes that occur near the tissue surface is essential for early cancer detection. Thus, there is a need for developing method for obtaining tissue information of desired depth and accurate measurement of tissue oxygenated status.

An interesting and practical approach is to quantify morphological related and vascularization related changes directly from the image and obtain improved visualization of early cancer lesions and/or other kind of pathologies. In United States Patent No. 5,512,940 to Takasugi et. al., Image Processing Apparatus, Endoscope Image Sensing and Processing Apparatus, and Image Processing Method for Performing Different Displays Depending upon Subject Quantity, the inventors disclose a method for image enhancement and improved visualization by calculating the Index of Hemoglobin (iHb) and using this information to improve cancer lesions detection. The basic principle of this method is that the image red color tones depend on the quantity of the blood (hemoglobin), thus by quantifying the blood (or Hemoglobin) concentration the slight changes in the red color tones can be potentially enhanced. However, the method does not quantify the oxygenated part versus the de-oxygenated part of the mucosa/tissue blood. Thus, the method basically provides image contrast enhancement by utilizing color quantification.

On the other-hand the present invention is based on quantifying both the de-oxygenated and the oxygenated parts of the mucosa blood which would provide additional functional/diagnostic information that has minimal effect on image coloration but could improve the detection and localization of cancerous related changes and/or other related pathologies. Different pathologies including the lung cancer modify the amount of deoxygenated blood within the tissue. However, the effect of such changes on the image redness color is weak and can not be obtained from simple color quantification. Accordingly, the present invention discloses image contrast enhancement method and apparatus based on actual tissue properties quantification (morphological and vascular) directly from the image data. The use of quantified de-oxygenated blood provides improved diagnostic accuracy for cancer detection with superior classification when compared to the prior art.

In addition, present invention describes a method and an apparatus for accurate imaging of tissue/mucosa oxygenation to improve diagnostic accuracy of current imaging systems to even slight changes in the mucosa/tissue oxygen supply and perfusion.

BRIEF SUMMARY OF THE INVENTION

The present invention is a method and apparatus for quantitative processing of images of a tissue, such as for real-time measurements of cancerous changes in a tissue. The preferred method comprises the steps of illuminating the tissue and producing at least two images at different spectral bands, analyzing the images to determine a tissue microvascular oxygenation parameter for each desired pixel of a image; and quantifying changes in a tissue oxygenation and adjusting image contrast based on the microvascular oxygenation parameter. The preferred apparatus of the invention comprises a light source for illuminating the tissue and producing at least two images at different spectral bands, an image-detecting device for receiving the images; and an image processing device for analyzing the images to determine a tissue microvascular oxygenation parameter for each desired pixel of a image, wherein the processing device quantifies changes in tissue oxygenation and adjusts image contrast based on the determined microvascular oxygenation parameter. In some embodiments, a diffusion-approximation model is used. BRIEF DESCRIPTION OF THE DRAWINGS

The organization and manner of the structure and operation of the invention, together with further objects and advantages thereof, may best be understood by reference to the following description, taken in connection with the accompanying drawings, wherein like reference numerals identify like elements in which:

FIG. 1 is a block diagram of a preferred embodiment of the present invention;

FIG. 2 is a block diagram of another embodiment of the present invention; FIG. 3 is a graph illustrating spectral properties of illumination light according to one embodiment of the present invention;

FIG. 4 is a graph illustrating spectral properties of illumination light according to another embodiment of the present invention;

FIG. 5 is a flow diagram of the method for quantitative image enhancement based on quantifying the deoxygenated blood of the present invention;

FIG. 6 is a flow diagram of a modeling approach of the present invention;

FIG. 7 is an illustration of an deoxygenated threshold imaging approach;

Fig. 8 is a flow diagram for Quantification of Tissue Oxygenation Index - TOI using model analysis;

FIG 9 is a graph showing deoxygenated blood fraction by pathology result for visually suspicious sites;

FIG. 10 is a graph showing difference in deoxygenated blood fraction between visually suspicious and normal sites by pathology results; FIG. 11 is a graph showing difference between the tissue image a) before and b) after quantification of mucosa oxygenation using pseudo color map.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE INVENTION

While the invention may be susceptible to embodiments in different forms, there is shown in the drawings, and herein will be described in detail, specific embodiments with the understanding that the present disclosure is to be considered an exemplification of the principles of the invention, and is not intended to limit the invention to that as illustrated and described herein.

As shown in FIG. 1 a system 10 for imaging and image processing used in the present invention is configured of a light source 1 for supplying illumination light to an optical device such as an endoscope 4 adapted for insertion into the patient, a rotating filter 2 for turning the illumination light into plurality of wavelength bands, a detecting device 7 for capturing image signals, and processing unit 5 for receiving image signals from the detector 7 and processing and analyzing the image signals according to the method described herein and generating an enhanced image. The generated image is then provided to a display device 9 for viewing or further analyzing.

The light source 1 provides white light of the visible light region and may be a single unit or be comprised of a combination of light sources to deliver the desired illumination. The preferable light source is a Xenon lamp, but in other embodiments a mercury lamp, a tungsten halogen lamp, a metal halide lamp, a laser, laser diodes (LDs), or an LED are used. The light emitted from the light source 1 is modulated into a plurality of illuminating segments by the rotating filter 2 consisting of plurality of filters modulating the illumination light that passes through them into light band segments with specific spectral properties. The frame sequence light bands coming from the filter are collected by a condenser lens and directed into a light guide 8 disposed within the endoscope 4. The illumination bands conveyed by light guide interrogate the investigated subject sequentially and the returning light is captured by the detecting device 7. The detecting device 7 is preferably CCD but also could be an intensified CCD, a CID, a CMOS, or any other pixelated detector. The detecting device could be mounted either on a distal end of the endoscope or at the proximal end of the endoscope. If the detector 7 is at the proximal end of the endoscope then the returned light will be carried to the detecting device by an imaging guide disposed within the endoscope.

Image signals from the detector 7 are received by a processing unit 5 that performs the calculations and processes the signals to generate improved image. The processing unit 5 is a computer or a microprocessor, preferably a personal computer. The processing unit 5 outputs its results to any output means desired by the user, such as a monitor, an LCD screen, or a printer, or conveys the results to another computer for further analysis, or uses the results for its own internal calculations and analysis. Control unit 6 controls the rotation of the filter and coordinates and synchronizes the detecting device and rotating filter.

The rotating filter 2 is a wheel driven by a motor 3 that contains various filters that separates the white light into a plurality of light segments with specific spectral properties. It may further include light blocking strips to separate the light segments. For example, the rotating filter could be RGB filter that provides light segments in a blue, green and red wavelength range as shown in FIG. 3. The light segments from the filter sequentially reach the investigating subject and the light reflected from the subject is captured by the detecting device 7. In another embodiment of the present invention the rotating filter contains filters that generate narrow-band illumination light as shown in FIG. 4. While Fig. 4 depicts spectrum properties of narrow-band illumination light of the present invention, the present invention is not limited to the described set of narrow-band illumination light. The generated narrow-band illumination light has spectral properties that enable extraction of tissue information from a desired depth, e.g., longer wavelengths (red, NIR) provide information from deeper part while shorter wavelengths provide information of the tissue near the surface. The obtained narrow-band illumination light segments impinge onto the subject and the return light is captured by the detecting device 7. The detected image signals are then processed by the processing unit and an image is displayed on a desired output means such as monitor 9.

In one embodiment, a light source 1 is placed near the distal end of the endoscope. For example, by placing at least one LED and preferably plurality of LEDs or LDs at the end of the endoscope, the light guide for carrying illumination light can be eliminated. Accordingly, the plurality of LEDs or LDs may be electronically switched at high rates to provide plurality of illumination segments with specific spectral properties eliminating the need of rotating filter. In yet another embodiment the light sources, detecting device and other expensive optics may be disposed on a removable tip which can be changed from patient to patient, as described in detail in United States Published Patent Application No. 2006/0217594, to Ferguson, Endoscopy Device with Removable Tip, the disclosure of which is incorporated herein by reference.

FIG. 2 describes another embodiment of the present invention in which the subject is illuminated simultaneously with a broad band visible illumination light from light source unit 21 , through light guide 22 in endoscope 24. Returned radiation is captured by a detecting device 28 employing a plurality of CCDs (30, 31 , 32), preferably three for detecting band images such as blue, green and/or red/NIR images with a specific spectral properties defined by properties of the band pass filters disposed in front of each of the CCDs. The detecting device according to this embodiment is preferably mounted on the proximal end of the endoscope but could also be disposed at the distal tip of the endoscope. Reflected light carried by an image guide disposed within the endoscope is directed to the detecting device 28. The detector 28 further comprises a plurality of beam separating devices such as dichroic mirrors (26) and (27) or some other optical device such as beam splitters. The detector 28 also comprises band pass filters 34b, 34g, 34r disposed in a close proximity in front of the CCDs to further optically processed the light that is then captured by the CCDs.

These multispectral narrow-band images are fed to the processing unit 25 for further analyses and processing in accordance to the method described herein. The generated image is visualized on a display device 29. The images are viewed on any type of video image display device(s), such as a standard CRT monitor, an LCD flat panel display, or a projector. A different detector configuration utilizing a single CCD sensor with patterned filter coating could also be used. The CCD may be mounted at the distal tip of an endoscope or outside the endoscope probe. Returned light from the subject is focused by a lens onto CCD sensor. The different adjacent pixels on the CCD sensor are designed to capture images at different spectral bands corresponding with the band pass filter coating. The CCD sensor output signals (narrow band or RGB) are further processed and analyzed by the processing unit 25.

FIG. 5 describes steps of the method of the present invention for quantitative image processing. The subject under investigation is illuminated either sequentially with at least two wavelength bands or simultaneously with broad band illumination as described in relation with Fig. 1 and Fig. 2 herein. In case of simultaneous broad band illumination, the reflected light is modulated into at least two narrow-band images. Further analyses yield information about morphological and microvascular properties of investigated subject. To achieve this result, light distribution was modelled as a function of the tissue optical properties, namely μ_a(λ) (absorption coefficient) and μ_s(λ) (scattering coefficient). The absorption coefficient was expressed in terms of microvascular absorption related parameters such as de-oxygenated blood volume fraction and tissue oxygenation, and the scattering coefficient was expressed in term of tissue scatter related parameters such as a scattering amplitude. Image signals captured by the detector are processed and analysed to calculate the De- oxygenated Tissue Index (dHbi) which quantify the amount of de-oxygenated blood volume within the tissue. The dHBi is defined using diffusion approximation model analysis as de-oxygenated blood volume multiplied by scattering amplitude (/cHbi).

The quantification of the blood volume fraction and the tissue-oxygenation is obtained using the modelling approach described by FIG. 6. The original image composed of at least two narrow-band images is further analyzed using diffusion- approximation model for obtaining information about tissue microvascular properties.

The absorption coefficient μ_a(λ) and scattering coefficient μ_s(λ) were modeled using the following diffusion-approximation model:

▼ ²l_d(r) - μ²e_ff l_d(r) = -3μ_s μ_trS(r) (1 )

R_d = l_d(z)/2ASo(1-r_s)|₂=o where μtr = μ_a +μ_s μ² _eff =3μ_aμtr

I_d : is the diffuse fluence rate Rd : is the measured diffuse reflectance

A: is constant depends on the tissue-air refractive index mismatch r_ε : specular reflectance So : The source power

For plane wave irradiation (1-D) geometry the source term S(r) can be described by the following equation

S(z)= S_o exp (μ_rz) (2) where z; is a tissue depth

Solving the above model for plane-wave (1-D) irradiation for the quantity, X(λ) = μ_s(λ)/μ_a(λ), we obtain the following linear model: c1 *X(λ)^*[1 +X(λ)]^1/2 - c2*[1 +X(λ)]^1/2 + c3*X(λ) - c4 = 0 (3) where; c1 = 3 + A[1+2^*Rd(λ)] c2 = 4*A*Rd(λ) c3 = A[3+2^*A^*Rd(λ)] c4 = 4*A2*Rd(λ)

Solving for the roots of the above linear model we determine X(λ). To increase the model analysis performance the scattering coefficient was accounted for by assuming: μ_s(λ)= (1//c)^*(1-/7*λ) (4)

Where, h is constant for the same tissue, and is the inverse scattering amplitude k and is independent of the wavelength.

Thus;

/φ_a(λ) = (1-/7* λ)/X(λ) (5)

Assuming the blood is the main absorber, the deoxygenated blood volume fraction multiplied by the scattering amplitude (/cHbi) is thus obtained from the least-square solving of the following:

[ /cHbO2i , /cHbi ] = [E_HbO2i , EJHbi]^"1 * /cμai (6) Where

/cHbO2 and /cHb are the oxygenated and deoxygenated blood fraction respectively ;

E_HbO2 and E_Hb are the molar coefficient for the oxygenated and deoxygenated blood respectively; and i : is an index for the wavelength

The dHbi is then calculated for each desired pixel of the image and is used to quantify the changes in the mucosa oxygenation levels and by comparing the areas with lower/higher dHBi and the image background to adjust the image contrast according to any of the methods described herein below.

According to one method, the threshold parameter is determined as an average deoxygenated index for the whole image. The concept of image enhancement based on calculating the de-oxygenation index through the image is shown by FIG. 7. The de-oxygenated index is calculated for each desired pixel of the original image and area(s) that have high deoxygenated index are identified (FIG. 7a). Then, an average de-oxygenated index for the whole image is determined and use as a threshold parameter to enhance image contrast by applying it to each desired pixel of the image. The pixels with dHbi less than the threshold parameter are assigned with more pink colour. The pixels with dHbi higher than the threshold parameter are assigned with more white colour. As shown by FIG. 7b, the area(s) with high de-oxygenated index adjusted with the threshold parameter as described above are visually more visible and easily differentiable from the rest of the image while keeping the image natural colour. Figure 11 shows another method for characterizing the changes in the de- oxygenated index and adjusting the image contrast so that the pixels with equal dHbi are assigned with a same colour. This is so called Pseudo colour map of the image. According to another method, the inventor of the present invention uses an empirical threshold parameter that was determined from a clinical and experimental data from a number of images obtained from a number of patients and from a number of biopsies. So, determined threshold parameter is then applied to each desired pixel of an image to adjust the image contrast. This is so called global approach and is tissue dependent because is based on the available experimental data.

In addition, the oxygenated /cHbO2 and deoxygenated blood fraction /cHb determined according to the model analysis described herein (equation 6) can also be used to determine tissue oxygenation index, which in addition can be used to determine tissue oxygenation status.

The Tissue Oxygenation Index (TOI) is obtained from the following model:

TOI = /cHbO2i//cHbi+/eHbO2i (7)

FIG. 8 shows the steps of the method for quantification of Tissue

Oxygenation Index (TOI) using the model analysis of the present invention. Original image data are processed using the diffusion approximation model of the present invention, and oxygenated and deoxygenated blood volume fractions are calculated as described herein (equation 6). Using these two quantities, the Tissue Oxygenation Index (TOI) can be calculated as per equation 7 and use it for determining tissue oxygenating status.

Tissue oxygenation status and micro-vasculature parameters play central role in detection and monitoring of ischemia and tissue viability as well as tumor physiology and cancer treatment. Routine evaluation of the pre-therapeutic tissue oxygenation status is of prime importance in establishing individual therapeutic strategies including combined radiotherapy, chemotherapy and photodynamic therapy. Another area where measurement of tissue oxygenation status can serve as an important endpoint is the assessment of the efficacy of the newly developed hypoxia- or angiogenesis-targeted therapies. However, in-vivo measurement of tumor oxygenation is a challenging procedure especially for difficult to access (endoscopic) lesions such as the lung.

The present invention provides direct and real-time measurement of tumor hypoxia-related parameters in non-invasive manner, during routine endoscopy procedure. Ischemia detection is related to the detection of the area of tissues that is hypoxic or has deficiency in oxygen supply. The method of the present invention is used to detect the presence of ischemia by calculating the tissue oxygenation index (TOI) through different areas within the image. It is well known that the normal tissue has TOI value between 65%-75% and the TOI value of the hypoxic is usually 55% or less. By indentifying the areas with lower than normal TOI and adjust the image contrast an improved, accurate detection of ischemia is achieved.

The present invention could also apply in establishing surrogate endpoints for assessment of efficacy of hypoxia- or angiogenesis-targeted drugs and compounds. In addition, the apparatus and method of the present invention play important role in the design of in vivo clinical trials (Phase Il and III) and in assessment of clinical response and for defining an end point to the newly developed anti-angiogenic and hypoxia targeted drugs, especially for those developed for early/small tumors (<1cm). In addition, analysis of tumor oxygen status predicts the response to oxygen-targeting drugs.

With advances in curative endobronchial therapy for early lung cancer, these quantified physiological measurements of microenvironment and oxygenation of the lesion will play an important role in assessment of the success of endobronchial treatments, such as photodynamic therapy (PDT), and in establishing of individual therapeutic strategies. In addition the spectrally estimated micro-vascular and oxygenation parameters can be of prime importance for monitoring tissue vitality and ischemia during endoscopy.

In our study we have performed in vivo measurements on normal bronchial mucosa and both benign and malignant bronchial mucosa lesions on 421 patients and have obtained images from visually suspicious tissues, as summarized in Table 1.

Table 1

The images were analyzed according to the model analysis of the present invention and tissue microvascular and morphological properties were determined. In addition, 346 biopsies ware obtained to classify each measured tissue site into hyperplasia/metaplasia, dysplasia and carcinoma in situ (CISyCancer. The pathology examination of biopsies revealed that 123 were from normal tissue sites, 127 were hyperplasia/metaplasia, 13 were dysplasia, and 72 were CIS/cancer lesions. The results are shown in Table 2. Table 2 - Pathology Grades by Site for Analyzable, Suspicious Biopsies

As shown on FIG. 9 the deoxygenated index demonstrates significant statistical changes between the grades of the lesions, namely the de-oxygenated index has significantly higher value in malignant lesions than in normal tissue.

FIG. 10 shows difference in the deoxygenated blood fraction between visually suspicious sites and normal, distant sites. As can been seen, the difference in the deoxygenated blood fraction between suspicious sites and normal, distant sites for normal tissues is lower than the difference in the deoxygenated blood fraction between suspicious sites and normal, distant sites for malignant tissues, suggesting the potential of using the deoxygenated blood imaging for detecting suspicious lesions. We have also found very good statistical correlation between the Tissue De-oxygenated Index and the G/B image ratio which suggests that G/B ratio can be used for approximating the Tissue De-oxygenated Index.

The method of the present invention for improving the contrast and the sensitivity of the WL endoscopy to mucosa perfusion and oxygen supply could be also used in the other endoscopic applications such as a detection and monitoring of ischemia in the other tissue sites (e.g. colon and/or the stomach such as the mesenteric ischemia and the gut ischemia); monitoring tissue and/or graft viability; micro-vascular surgery and assessment of perfusion in rectal anastomosis.

While preferred embodiments of present invention are shown and described, it is envisioned that those skilled in the art may devise various modifications of the present invention without departing from the spirit and scope.

Claims

CLAIMS We claim:

1. A method for quantitatively processing images of a tissue, the method comprising the steps of: illuminating the tissue and producing at least two images at different spectral bands; analyzing said images to determine a tissue microvascular oxygenation parameter for each desired pixel of a image; and adjusting image contrast based on said tissue microvascular oxygenation parameter.

2. The method of claim 1 , wherein said images are analyzed using a diffusion-approximation model.

3. The method of claim 1 , wherein said microvascular oxygenation parameter is selected from a de-oxygenated index (dHBi) and a tissue oxygenation index (TOI).

4. The method of claim 3, wherein said dHBi is determined by multiplying the de-oxygenated blood volume fraction and scattering amplitude.

5. The method of claim 3, wherein the TOI is determined based on oxygenated and de-oxygenated blood volume fractions.

6. The method of claim 3, wherein said TOI is used to determine tissue oxygenating status.

7. The method of claim 1 , wherein the step of adjusting image contrast further comprises comparing image areas with a lower and higher value of the oxygenated parameter with the rest of the image.

8. The method of claim 7, further comprising a step of mapping areas of the image with equal oxygenated parameter with a same colour.

9. The method of claim 1 , further comprising a step of determining a threshold of said microvascular oxygenation parameter.

10. The method of claim 9, wherein said threshold is applied to each desired pixel of the images for adjusting image contrast.

11. The method of claim 9, wherein said threshold is an average value of the oxygenation parameter for the images.

12. The method of claim 11 , wherein the image contrast is adjusted by adding white colour to image areas having higher oxygenated parameter than the threshold and adding pink colour to image areas with lower oxygenated parameter than the threshold.

13. The method of claim 1 , further comprising a step of detecting ischemia.

14. The method of claim 1 , further comprising a step of monitoring ischemia.

15. The method of claim 1 , further comprising a step of monitoring tissue viability.

16. The method of claim 1 , further comprising measuring cancerous changes.

17. An apparatus for quantitative processing images of a tissue, comprising: a light source for illuminating the tissue and producing at least two images at different spectral bands; an image detecting device for receiving said images; and an image processing device for analyzing said images to determine a tissue microvascular oxygenation parameter for each desired pixel of a image, wherein said processing device quantifies changes in tissue oxygenation and adjusts image contrast based on the determined microvascular oxygenation parameter.

18. The apparatus of claim 17, wherein said processing device is configured to detect ischemia.

19. The apparatus of claim 17, wherein said processing device is configured to monitor ischemia.

20. The apparatus of claim 17, wherein said processing devices is configured to monitor tissue viability.

21. The apparatus of claim 17, wherein said processing device is configured to measure cancerous changes.