Methods and apparatus for relative perfusion and/or viability

• US 20070244389A1
• Filed: 04/13/2006
• Published: 10/18/2007
• Est. Priority Date: 04/13/2006
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Licato, Paul, Hoppel, Bernice, Callister, Tracy, Broadie, Amy
• Granted Patent: US 8,626,263 B2
• Time in Patent Office: Days
• US Class Current: 600/425
• CPC Class Codes: A61B 6/507 for determination of haemodynamic parameters, e.g. perfusion CT
• CPC Class Codes: A61B 6/508 for non-human patients
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 2207/30104 Vascular flow; Blood flow; Perfusion
• CPC Class Codes: G06T 7/0012 Biomedical image inspection

Abstract

A method of evaluating tissue of an organ includes performing at least one of classification processing and clustering processing to obtain a processed dataset to visualize at least one of the imaging agent, blood, the contrast agent, and the biomedical agent distribution in the tissue, a relative regional uptake of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent in the tissue, relative regional flow of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent and the clearance or persistence of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent within the tissue and the characterization of elemental components of disease.

Claims

1. A method of evaluating tissue of an organ, said method comprising:

accessing image data from an imaging modality acquisition system wherein the image data comprises at least one of a three dimensional single or multiple cardiac phase dataset or a three dimensional multi-temporal phase dataset of a feature of interest in an organ or tissue wherein the data is acquired in conjunction with at least one of an imaging agent, blood, a contrast agent, and a biomedical agent, wherein the data can be acquired in a state of cardiac stress or in non- cardiac stress state; and

a three dimensional segmentation is performed on said data for isolation of tissue or organ to allow for more accurate processing; and

performing classification processing to obtain at least one of a processed dataset to visualize at least one of the imaging agent, blood, the contrast agent, and the biomedical agent distribution in the tissue, a relative regional uptake of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent in the tissue, relative regional flow of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent and the clearance or persistence of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent within the tissue.

2. The method of claim 1 wherein said performing comprises at least one of a z-scoring of the tissue, a statistical analysis, at least one t-test, a multivariate analysis, a classifier based analysis, an exclusive clustering algorithm, an overlapping and fuzzy clustering algorithm, a partitioning algorithm, a probabilistic clustering, a hierarchical clustering, a K-means analysis, a fuzzy C-means analysis, an expectation maximization analysis, a density based algorithm, a grid-based algorithm and a model based algorithm and combinations thereof.

3. The method of claim 1 further comprising delivering one or two injections to provide classification information of perfusion or viability.

4. The method of claim 1 wherein the organ is one of a heart, a liver, a brain, a vasculature, and a kidney.

5. The method of claim 1 wherein the feature of interest comprises at least one of a volume of ischemic tissue, an area of ischemic tissue infarct, a percentage of ischemic tissue within the organ, an organ wall motion, a relative blood flow to the tissue, a microvasculature density, a microvasculature pattern, at least one calcification, a stroke volume, a mass volume, a percent stenosis, an agent distribution within the organ, an agent clearance throughout the organ, an agent distribution in the tissue, a whole organ uptake of agent, a regional uptake of agent, a regional washout of agent, a regional accumulation of agent, a regional persistence of agent, a regional clearance of agent, a whole organ washout of agent, a clearance in the tissue over a plurality of phases, a thrombosis, a mass shape, and combinations thereof.

6. The method of claim 1 further comprising performing a visualization of the feature of the processed dataset using a three or four dimensional display of the processed dataset represented by color, texture or pattern as an overlay of the processed dataset for comparison with an originally collected dataset, a curved reformat of the processed dataset, a lumen view of the processed dataset, and combinations thereof.

7. The method of claim 1 further comprising performing visualization for preferred presentation to the user including visualization of deficit or hyper intense areas in a 3D dimensional display.

8. The method of claim 1 further comprising performing a visualization of the feature of the processed dataset as a time course in response to physiological motion of the organ or the passage of the imaging agent through the organ of interest over time

9. The method of claim 1, wherein the imaging modality acquisition system is one of a single energy CT system and a multi-energy CT system.

10. The method of claim 1 wherein the dataset is configured to be reconstructed in an angiographic view for disease evaluation, reformatted for an optimal view or functional characteristics, statistically analyzed cluster view for disease component analysis and statistically analyzed for imaging agent wash-in, clearance, distribution, accumulation either regionally or globally and combinations thereof.

11. A method in accordance with claim 1 wherein said performing at least one of statistical processing and clustering processing to obtain a processed dataset to visualize further comprises performing a statistical or a clustering processing to visualize and characterize components of the tissue or organ for evaluation of disease with or without the injection of imaging agent.

12. A method in accordance with claim 11 wherein said imaging modality acquisition system is of a first modality, said method further comprises sending at least some data to a imaging modality acquisition system of a second or third or fourth modality different than the first or any such combination of modalities.

13. A method in accordance with claim 12 wherein the first modality is CT, and the second modality is PET or SPECT or MRI or Ultrasound.

14. A method of evaluating components of a disease, said method comprising:

accessing image data from any imaging modality system wherein the image data comprises of three dimensional, single or multi-phase dataset of data; and

statistical or clustering processing to visualize and characterize the components of the tissue or organ for evaluation of disease.

15. The method of claim 14 wherein the processing includes at least one of z-scoring of the tissue, statistical analysis, t-tests, multivariate analysis, classifier based analysis, exclusive clustering algorithms, overlapping and fuzzy clustering algorithms, partitioning algorithms, probabilistic clustering, hierarchical clustering, K-means, fuzzy C-means, Expectation maximization, density based algorithms, grid-based algorithms or model based algorithms and combination thereof.

16. The method of claim 14 further comprising performing a volumetric analysis of elemental and structural components as relative amounts to each other as well as through a systemic analysis for determination of disease characterization.

17. The method of claim 14 further comprising performing a visualization of a feature of the processed dataset using a three or four dimensional display of the processed dataset represented by color, texture or pattern as an overlay of the processed dataset for comparison with an originally collected dataset, a curved reformat of the processed dataset, a lumen view of the processed dataset, and combinations thereof.

18. The method of claim 14 further comprising differentiating between anatomical differences as well as various components of disease.

19. An imaging system comprising:

an acquisition device configured to receive energy regarding a patient; and

a computer coupled to said acquisition device, said computer configured to do at least one of;

a) access image data from the acquisition device, wherein the image data comprises of three dimensional, single or multi-phase dataset of data; and

classifying or clustering processing to visualize and characterize the components of the tissue or organ for evaluation of disease; and

b) access image data from the acquisition device, wherein the image data comprises of three dimensional, single or multi-phase dataset of data of a feature of interest in an organ including tissue wherein the data is acquired in conjunction with at least one of an imaging agent, blood, a contrast agent, and a biomedical agent; and

perform at least one of classsifying processing or clustering processing to obtain a processed dataset to visualize at least one of the imaging agent, blood, the contrast agent, and the biomedical agent distribution in the tissue, a relative regional uptake of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent in the tissue, relative regional flow of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent and the clearance or persistence of the at least one of the imaging agent, blood, the contrast agent, and the biomedical agent within the tissue.

20. A system in accordance with claim 19 wherein said computer configured to do both of a) and b).

21. A system in accordance with claim 19 wherein said system is a CT system, said acquisition device is a radiation detector, and said computer further configured to send data to a imaging system of a modality or modalities other than CT.

22. A system in accordance with claim 19 wherein said computer further configured to perform at least one of a z-scoring of the tissue, a statistical analysis, at least one t-test, a multivariate analysis, a classifier based analysis, a exclusive clustering algorithm, an overlapping and fuzzy clustering algorithm, a partitioning algorithm, a probabilistic clustering, a hierarchical clustering, a K-means analysis, a fuzzy C-means analysis, an expectation maximization analysis, a density based algorithm, a grid-based algorithm and a model based algorithm and combinations thereof.