METHOD FOR GENERATING QUANTITATIVE IMAGES OF THE FLOW POTENTIAL OF A REGION UNDER INVESTIGATION

• US 20090074267A1
• Filed: 09/08/2008
• Published: 03/19/2009
• Est. Priority Date: 09/17/2007
• Status: Abandoned Application

• Current Assignee: AMID SRL
• Original Assignee: AMID SRL
• Inventors: Tonti, Giovanni, Marchese, Emidio, Pedrizzetti, Gianni
• Application Number:
  US12/206,104
• Publication Number:
  US 20090074267A1
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 6/481 involving the use of contrast agents
• CPC Class Codes: A61B 6/503 for diagnosis of the heart
• CPC Class Codes: A61B 6/504 for diagnosis of blood vessels, e.g. by angiography
• CPC Class Codes: A61B 6/507 for determination of haemodynamic parameters, e.g. perfusion CT
• CPC Class Codes: A61B 6/5235 combining images from the same or different ionising radiation imaging techniques, e.g. PET and CT
• CPC Class Codes: A61B 8/06 Measuring blood flow measuring volume flow in general G01F, e.g. G01F1/66, G01F1/72; measuring speed of fluids in general G01P5/00
• CPC Class Codes: A61B 8/0883 for diagnosis of the heart
• CPC Class Codes: A61B 8/0891 for diagnosis of blood vessels
• CPC Class Codes: A61B 8/5238 for combining image data of patient, e.g. merging several images from different acquisition modes into one image for image registration algorithms G06T7/30

Abstract

The invention relates to a method for generating images representative of the flow potential of a permeable body. The following steps are part of the disclosed method. First, providing a first sequence of digital images of the body perfused by a fluid at a rest condition. Then extracting a first quantification image of the spatial distribution of flow of the fluid in the body at the rest condition, the first quantification image being defined by pixel values. Next, providing a second sequence of digital images of the body perfused by the fluid at a stress condition. Then extracting a second quantification image of the spatial distribution of flow of the fluid in the body at the stress condition, the second quantification image being defined by pixel values. Then, combining the two quantification images to obtain an image defined by pixel values.

Claims

1. A method for generating images representatives of the flow potential of a permeable body comprising the following steps:

providing a first sequence of digital images of the body perfused by a fluid at a rest condition;

extracting at least one first quantification image of the spatial distribution of flow of said fluid in said body at said rest condition, said at least one first quantification image being defined by pixel values having an appearance scale univocally correlated to a parameter representative of the perfusion at said rest condition;

providing a second sequence of digital images of the body perfused by the fluid at a stress condition, wherein at such stress condition the perfusion is forced to be increased with respect to the rest condition;

extracting at least one second quantification image of the spatial distribution of flow of said fluid in said body at said stress condition, said at least one second quantification image being defined by pixel values having an appearance scale univocally correlated to a parameter representative of the perfusion at said stress condition; and

combining the two quantification images to obtain at least an image defined by pixel values having an appearance scale univocally correlated to a combination of corresponding pixels of the two quantification images.

2. The method according to claim 1, wherein the two quantification images are aligned so that pixel values of one image can be compared to homologous pixel values of the other image.

3. The method according to claim 2, wherein the step of aligning the images comprises deforming at least one of said images to allow cross reference points identified on both images to overlap.

4. The method according to claim 2, wherein said two quantification images are aligned manually using optimal-likelihood-based processing.

5. The method according to claim 2, wherein said two quantification images are aligned automatically using optimal-likelihood-based processing.

6. The method according to claim 1, wherein the two quantification images are combined through a non-linear software device.

7. The method according to claim 1, wherein the two quantification images are combined through a hardware device.

8. The method according to claim 1, wherein the step of combining the two quantification images comprises calculating the ratio of pixel values of the second image to corresponding pixel values of the first image or vice versa to obtain an image where some or all the pixels have values corresponding to such ratio.

9. The method according to claim 1, and further including the step of defining at least one threshold to determine which pixels of the generated image(s) are a combination of the corresponding pixels of the first and second image and/or which pixels of the generated image(s) correspond to pixels related to only one of the two images and/or are filtered out.

10. The method according to claim 9, wherein values below said at least one threshold are corrected to filter noise in the generated image.

11. The method according to claim 1, wherein the step of extracting at least one quantification image from each sequence of images comprises one or more steps selected from the group consisting of extracting the last frame of the sequence, extracting a frame of the sequence at an intermediate time, extracting the image of the sequence having the maximum brightness, and determining a parametric image.

12. The method according to claim 11, wherein the step of determining a parametric image comprises the following substeps:

defining an evaluation function for each sequence of images, said evaluation function having at least one parameter;

calculating for each pixel or group of pixels of each sequence the value of said parameter for best fitting said evaluation function with a curve representing the values of said pixels or group of pixels obtained from such sequence of images; and

constructing a parametric image for each sequence of images by defining a pixel appearance scale univocally correlated to said at least one parameter.

13. The method according to claim 12, wherein said estimation function is of the form y(t)=A(1−

e<sup>−

Bt</sup>), where y(t) is the pixel value depending from time, t is the time at which the pixel value has been determined in the image and A and B are parameters giving the best fit of said estimation function.

14. The method according to claim 13, wherein said parameters are imaged in a two-dimensional or a three-dimensional image, or in any known representation of a function of one, two, or more variables.

15. The method according to claim 1, wherein the pixel values comprise the brightness of black and white digital images or one or more variables of colour digital images like hue, saturation, colour or the like.

16. The method according to claim 1, wherein more quantification images are extracted from each sequence of images, more images being generated by combining corresponding images at rest and stress condition.

17. The method according to claim 16, wherein one image is generated, such image being the ratio of two images extracted/calculated from a combination of images extracted and/or calculated respectively from the sequence of images at stress and from the sequence of images at rest.

18. The method according to claim 17, wherein the generated image is displayed overlaid with the image of the first and/or the second sequence of images and/or with the corresponding quantification image.

19. The method according to claim 1 wherein the sequences of images are echographic or MRI or SPECT or PET or X-Ray images or the like.

20. The method according to claim 1 wherein the images of the sequences are obtained with one or more imaging modes selected from the group consisting of:

Doppler, power Doppler, B-mode, Harmonic imaging, Contrast imaging.

21. The method according to claim 1 wherein the permeable body is a biological tissue, the sequences of images being representative of the spatial distribution of blood flow in such tissue.

22. The method according to claim 21, wherein the permeable body is the heart, the sequences of images being representative of the blood perfusion in the myocardium.

23. The method according to claim 22, wherein the pixels of the images of the sequences have brightness values related to the concentration of a contrast media perfusing the myocardium at the time the images are taken.

24. The method according to claim 23, wherein, for each sequence of images representative of a condition of the heart, a perfusion image is determined, such perfusion image giving a synthetic spatial representation of the perfusion process of at least part of the myocardium at such condition.

25. The method according to claim 24, wherein one or more differential perfusion images representative of the capacity of the myocardium to react to a demand for an increased blood flow are determined by combining perfusion images obtained from sequences of images of the myocardium at rest and hyperemic condition.

26. The method according to claim 22, wherein, for each sequence of images representative of a condition of the heart, a perfusion image is determined, such perfusion image giving a synthetic spatial representation of the perfusion process of at least part of the myocardium at such condition.

27. The method according to claim 26, wherein one or more differential perfusion images representative of the capacity of the myocardium to react to a demand for an increased blood flow are determined by combining perfusion images obtained from sequences of images of the myocardium at rest and hyperemic condition.