Automated methods and systems for vascular plaque detection and analysis

• US 20050043614A1
• Filed: 08/21/2004
• Published: 02/24/2005
• Est. Priority Date: 08/21/2003
• Status: Active Grant

• Current Assignee: Ischem Corporation
• Original Assignee: Ischem Corporation
• Inventors: Huizenga, Joel T., Anderson, Russell W., Brotherton, Thomas Woodley
• Granted Patent: US 7,657,299 B2
• Time in Patent Office: Days
• US Class Current: 600/427
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/7235 Details of waveform analysis A61B5/349 takes precedence
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 6/00 Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment instruments measuring radiation intensity for application in the field of nuclear medicine, e.g. in vivo counting, G01T1/161; apparatus for taking X-ray photographs G03B42/02
• CPC Class Codes: C23F 11/08 in other liquids
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 2210/41 Medical
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 2201/032 of protuberances, polyps nodules, etc.

Abstract

Automated methods and systems for the detection and analysis of plaque in one or more regions of a patient'"'"'s vasculature are described.

Claims

1. An automated method of assessing a degree of atherosclerosis in at least a portion of a patient'"'"'s vasculature, comprising computationally processing processable data from at least one cross section of at least one blood vessel of a patient'"'"'s vasculature derived from a medical imaging system to determine if the blood vessel comprises at least one tissue correlated with the presence of plaque, thereby assessing the degree of atherosclerosis in at least a portion of the patient'"'"'s vasculature.

13. An automated method according to claim 1 wherein the processable data are computationally processed to determine whether the blood vessel, in the region of the cross section, comprises artery and plaque.

14. An automated method according to claim 13 wherein determining tissue types is accomplished by comparing by computer different tissue types identified in the data to a plurality of statistical classifiers.

15. An automated method according to claim 14 wherein the statistical classifiers are developed using known outcome data by a process selected from the group consisting of logistic regression, decision trees, non-parametric regression, Fisher discriminant analysis, Bayesian network modeling, and a fuzzy logic system.

16. An automated method according to claim 15 wherein at least one of the plurality of stored tissue classifier elements was determined by a process selected from the group consisting of post-operative histological examination, direct tissue inspection, and labeling by one or more experts.

17. An automated method according to claim 14 wherein the processable data are computationally processed to determine whether the blood vessel, in the region of the cross section, further comprises at least one tissue selected from the group consisting of adventitia, a calcium deposit, a cholesterol deposit, fibrous plaque, and thrombus.

18. An automated method according to claim 17 wherein determining tissue types is accomplished by comparing by computer different tissue types identified in the data to a plurality of statistical classifiers.

34. A computer program product comprising a computer usable medium having computer readable program code embodied therein, wherein the computer readable program code is configured to implement an automated method according to claim 1 on a computer adapted to execute the computer readable program code.

40. A system for analyzing whether a blood vessel of a patient'"'"'s vasculature contains plaque, the system comprising:

a. a computer adapted to execute the computer readable program code embodied in a computer program product according to claim 34;

b. a computer data storage system in communication with the computer, wherein the computer data storage system is configured to send to, receive from, and/or store data processed by the computer; and

c. operably connected to the computer, a communications interface for receiving data to be processed by, or for sending data after processing by, the computer.

2. An automated method of determining whether a blood vessel of a patient'"'"'s vasculature contains plaque, comprising computationally processing processable data from at least one cross section of a blood vessel of a patient'"'"'s vasculature derived from a medical imaging system to determine if the blood vessel comprises at least one tissue correlated with the presence of plaque, in which event the blood vessel is determined to contain plaque.

3. An automated method according to claim 2 wherein the medical imaging system is a non-invasive imaging system.

4. An automated method according to claim 3 wherein the non-invasive imaging system comprises one or more instruments selected from the group consisting of an MRI instrument, a CT instrument, a PET instrument, a thermography instrument, and an ultrasound instrument to generate raw image data from which the processable data are derived.

5. An automated method according to claim 2 wherein the medical imaging system comprises an MRI instrument to generate raw magnetic resonance data from which processable magnetic resonance data are derived.

6. An automated method according to claim 5 wherein a plurality of different radio frequency pulse sequence series are employed, wherein each of the different radio frequency pulse sequence series allows raw magnetic resonance data to be generated for a subset of different tissues that may be present in the blood vessel.

7. An automated method according to claim 6 wherein at least one of the different radio frequency pulse sequence series results in the generation of raw magnetic resonance data selected from the group consisting of T1-weighted data, T2-weighted data, PDW-weighted data, and TOF-weighted data.

8. An automated method according to claim 2 wherein the blood vessel comprises a portion of the vasculature supplying blood to an organ selected from the group consisting of a brain and a heart.

9. An automated method according to claim 2 wherein the blood vessel is selected from the group consisting of a carotid artery and a coronary artery.

10. An automated method according to claim 2 wherein the patient is human.

11. An automated method according to claim 2 wherein the processable data are generated by pre-processing raw data generated by the medical imaging system.

12. An automated method according to claim 11 further comprising normalizing the processable data prior to computationally processing the processable data.

19. An automated method according to claim 6 wherein the components comprising the processable magnetic resonance data are computationally brought into registration.

20. An automated method according to claim 19 wherein registration is accomplished by aligning the components comprising the processable magnetic resonance data about a representation that represents a landmark selected from the group consisting of a vessel lumen centroid and a vessel branch point.

21. An automated method according to claim 20 wherein the landmark is selected from the group consisting of a physical landmark and a computational landmark.

22. An automated method according to claim 2 comprising computationally processing processable data of a plurality of spaced cross sections of the blood vessel.

23. An automated method according to claim 22 further comprising computationally rendering a three-dimensional model of the blood vessel over at least a portion of the region bounded by the most distantly spaced cross sections of the blood vessel.

24. An automated method according to claim 2 further comprising generating an output file comprising data resulting from the computationally processing.

25. An automated method according to claim 24 wherein the output file further comprises a computationally rendered three-dimensional model of the blood vessel over at least a portion of the region bounded by most distantly spaced cross sections of the blood vessel.

26. An automated method according to claim 23 further comprising computationally determining plaque volume present in the three-dimensional model of the blood vessel.

27. An automated method according to claim 23 further comprising computationally determining composition of plaque present in the three-dimensional model of the blood vessel.

28. An automated method according to claim 27 further comprising computationally distinguishing whether the plaque is a vulnerable plaque or a stable plaque.

29. An automated method of assessing effectiveness of a therapeutic regimen, comprising:

a. determining a plaque burden in a patient using an automated method according to claim 26;

b. delivering to the patient a therapeutic regimen comprising administration of a drug expected to stabilize or reduce the plaque burden in a patient over the course of the therapeutic regimen; and

c. during and/or at the end of the therapeutic regimen determining whether the plaque burden in the patient has stabilized or been reduced, thereby allowing assessment of the effectiveness of the therapeutic regimen.

30. An automated method according to claim 24 wherein the drug is an investigational drug.

31. A method of treating a patient having vulnerable plaque in a blood vessel, comprising:

a. determining that a patient has a vulnerable plaque in a blood vessel using an automated method according to claim 27;

and

b. delivering to the patient a therapeutic regimen designed to stabilize or reduce vulnerability of the vulnerable plaque to rupture over the course of the therapeutic regimen, thereby treating the patient.

32. A method according to claim 31 wherein therapeutic regimen comprises administration of a drug that stabilizes or reduces vulnerability of the plaque to rupture.

33. A method according to claim 32 wherein the drug is selected from the group consisting of statins, anti-inflammatory drugs, and anti-coagulant drugs.

35. An automated method for analyzing patient data obtained using a medical imaging system to determine whether a blood vessel of the patient contains plaque, comprising:

a. obtaining processable data of at least one cross section of a blood vessel of a patient'"'"'s vasculature, wherein the processable data are derived from raw data collected using a medical imaging system;

b. communicating the processable data to a computer configured to receive and computationally process the processable data to determine whether the blood vessel in the region of the cross section(s) comprises at least one tissue correlated with the presence of plaque, in which event the blood vessel is determined to contain plaque; and

C. using the computer to computationally process the processable data and determine whether the blood vessel contains plaque.

36. An automated method according to claim 35 wherein the medical imaging system and the computer are located at different locations.

37. An automated method according to claim 36 wherein the computer resides in a computational center physically removed from each of a plurality of imaging centers which each comprises a medical imaging system capable of generating raw data from which processable data can be derived.

38. An automated method according to claim 37 wherein at least one of the imaging centers communicates raw data to the computational center via a telecommunications link.

39. An automated method according to claim 35 further comprising communicating results of the analysis to an address specified as being affiliated with medical imaging system used to collect the raw data.