IMAGING-BASED DIAGNOSTIC APPARATUS AND METHODS FOR QUANTIFYING CEREBRAL VASCULAR RESERVE

• US 20120220858A1
• Filed: 02/24/2012
• Published: 08/30/2012
• Est. Priority Date: 02/25/2011
• Status: Active Grant

• Current Assignee: Northwestern University
• Original Assignee: Northwestern University
• Inventors: Carroll, Timothy J., Hurley, Michael, Vakil, Parmede, Menon, Rajiv, Jonathan, Sumeeth Vijay, Qian, Renee, Ansari, Sameer
• Granted Patent: US 9,140,771 B2
• Time in Patent Office: Days
• US Class Current: 600/420
• CPC Class Codes: A61B 2576/026 for the brain
• CPC Class Codes: A61B 5/0042 for the brain
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: G01R 33/5602 by filtering or weighting based on different relaxation times within the sample, e.g. T1 weighting using an inversion pulse
• CPC Class Codes: G01R 33/5616 using gradient refocusing, e.g. EPI
• CPC Class Codes: G01R 33/56366 Perfusion imaging
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing

Abstract

In one aspect of the disclosure, an MRI-based system includes an MRI scanner having a first axis and a first plane perpendicular to the first axis, a pulse sequence module configured to provide a 3D pulse sequence to the MRI scanner, and a control module configured to instruct the MRI scanner to conduct radial k-space samples having N second planes that each are perpendicular to the first plane and through which the first axis passes, N being an integer greater than 1. The 3D pulse sequence instructs the MRI scanner to a radio-frequency (RF) pulse, conduct a gradient readout in the first plane, and conduct a gradient readout in one of the N second planes.

Claims

1. An MRI-based system, comprising:

an MRI scanner having a first axis and a first plane perpendicular to the first axis;

a pulse sequence module configured to provide a 3D pulse sequence to the MRI scanner; and

a control module configured to instruct the MRI scanner to conduct radial k-space samples having N second planes that each are perpendicular to the first plane and through which the first axis passes, N being an integer greater than 1,

wherein the 3D pulse sequence instructs the MRI scanner to

generate a radio-frequency (RF) pulse;

conduct a gradient readout in the first plane; and

conduct a gradient readout in one of the N second planes.

2. The MRI-based system of claim 1, wherein the control module is configured to instruct the MRI scanner to conduct an echo-planar readout along the first axis.

3. The MRI-based system of claim 2, wherein the control module is configured to instruct the MRI scanner to sample a 3D k-space volume over a plurality of sample points sampling a line perpendicular to the first axis.

4. The MRI-based system of claim 1, wherein the control module is configured to instruct the MRI scanner to acquire k-space samples through a 3D k-space volume at oblique angles so as to trace out samples oriented radially in the N second planes.

5. The MRI-based system of claim 1, wherein the control module is configured to instruct the MRI scanner to conduct a first set of N consecutive gradient readouts for the N second planes.

6. The MRI-based system of claim 5, wherein the MRI scanner is configured to have a raw sampling window from about 10,000 ms to about 10 seconds.

7. The MRI-based system of claim 5, comprising an imaging module configured to construct a first 3D image frame using readout results of the first set of readouts.

8. The MRI-based system of claim 7, wherein the imaging module is configured to construct images with a spatial resolution about 2.5 mm×

0.825 mm×

0.825 mm.

9. The MRI-based system of claim 7, wherein the imaging module is configured to construct 3D images at a rate of about 0.6 second/frame.

10. The MRI-based system of claim 5, wherein the control module is configured to instruct the MRI scanner to conduct a second set of N consecutive gradient readouts for the N second planes.

11. The MRI-based system of claim 10, wherein the imaging module is configured to construct a second 3D image frame using readout results of the second set of readouts.

12. The MRI-based system of claim 10, wherein the imaging module is configured to construct a third 3D image frame using the readout results of the last M of N second planes from the first set of readouts and the readout results of the first (N-M) of N second planes from the second set of readouts, M being an integer greater than 0 and less than N.

13. The MRI-based system of claim 5, wherein the imaging module is configured to combine two 3D images representing co-registered perfusion images to construct a Cerebro-vascular Reserve (CVR) image based on the relation:

CVR=(Stress−

Rest)/Rest×

100%.

14. The MRI-based system of claim 1, comprising a quantification module configured to quantify levels of a patient'"'"'s vascular reserve and construct a respective score representing each of the levels.

15. The MRI-based system of claim 14, wherein the quantification module is configured to implement the following calibration equation:

16. A method, comprising:

instructing an MRI scanner having a first axis and a first plane perpendicular to the first axis to conduct radial k-space samples having N second planes that each are perpendicular to the first plane and through which the first axis passes, N being an integer greater than 1; and

instructing the MRI scanner with a 3D pulse sequence to

generate a radio-frequency (RF) pulse,

conduct a gradient readout in the first plane, and

conduct a gradient readout in one of the N second planes.

17. The method of claim 16, comprising instructing the MRI scanner to conduct an echo-planar readout along the first axis.

18. The method of claim 16, comprising instructing the MRI scanner to sample a 3D k-space volume over a plurality of sample points sampling a line perpendicular to the first axis volume into a plurality of slices each perpendicular to the first axis.

19. The method of claim 16, comprising instructing the MRI scanner to acquire k-space samples through a 3D k-space volume at oblique angles so as to trace out samples oriented radially in the N second planes.

20. The method of claim 16, comprising instructing the MRI scanner to conduct a first set of N consecutive gradient readouts for the N second planes.

21. The method of claim 20, comprising instructing the MRI scanner to have a raw sampling window from about 10,000 ms to about 10 seconds.

22. The method of claim 20, comprising generating a first 3D image frame using readout results of the first set of readouts.

23. The method of claim 22, comprising acquiring images with a spatial resolution about 2.5 mm×

0.825 mm×

0.825 mm.

24. The method of claim 22, comprising constructing 3D images at a rate of about 0.6 second/frame.

25. The method of claim 20, comprising instructing the MRI scanner to conduct a second set of N consecutive gradient readouts for the N second planes.

26. The method of claim 25, comprising generating a second 3D image frame using readout results of the second set of readouts.

27. The method of claim 25, comprising generating a third 3D image frame using the readout results of the last M of N second planes from the first set of readouts and the readout results of the first (N-M) of N second planes from the second set of readouts, M being an integer greater than 0 and less than N.

28. The method of claim 20, comprising combining two 3D images representing co-registered perfusion images to construct a Cerebro-vascular Reserve (CVR) image based on the relation:

CVR=(Stress−

Rest)/Rest×

100%.

29. The method of claim 16, comprising quantifying levels of a patient'"'"'s vascular reserve and generating a respective score representing each of the levels.

30. The MRI-based system of claim 29, comprising quantifying the levels by implementing the following calibration equation: