Method and apparatus for automated tracking of vessel movement using MR imaging
A system and method is disclosed for tracking a moving object using magnetic resonance imaging. The technique includes acquiring a scout image scan having a number of image frames and extracting non-linear motion parameters from the number of image frames of the scout image scan. The technique includes prospectively shifting slice location using the non-linear motion parameters between slice locations while acquiring a series of MR images. The system and method are particularly useful in tracking coronary artery movement during the cardiac cycle to acquire the non-linear components of coronary artery movement during a diastolic portion of the R-R interval.
1. A magnetic resonance (MR) imaging apparatus comprising:
a plurality of gradient coils positioned about a bore of a magnet;
an RF transceiver system and an RF switch controlled by a pulse module to transmit RF pulses to an RF coil assembly and receive MR signals therefrom; and
a controller programmed to:
cause acquisition of a series of scout images;
determine a non-linear motion of an anatomy of interest among the series of scout images; and
adjust a position of an acquisition slice during MR image acquisition based on the non-linear motion of the anatomy of interest.
2. The MR apparatus of claim 1 wherein the controller is further programmed to define a region of interest (ROI) within a reference image of the series of scout images, the ROI containing the anatomy of interest.
3. The MR apparatus of claim 2 wherein the controller is further programmed to determine the non-linear motion of the anatomy of interest by cross-correlating positions of the ROI between the reference image and additional images of the series of scout images.
4. The MR apparatus of claim 3 wherein the controller is further programmed to define the region of interest and cross-correlate positions thereof for all images of the series of scout images.
5. The MR apparatus of claim 3 wherein the controller is further programmed to cross-correlate the positions of the ROI by using the reference image as a convolution kernel and convolving the more than three of the series of scout images with the convolution kernel.
6. The MR apparatus of claim 5 wherein the controller is further programmed to identify a number of displacement values of central convolution peaks from cross-correlating the positions of the ROI.
7. The MR apparatus of claim 6 wherein the controller is further programmed to determine the motion of the anatomy of interest from the displacement values and adjust the position of the acquisition slice by modifying a slice selection gradient of the MR image acquisition according to the displacement values.
8. A method of coronary MR imaging comprising:
identifying a region of interest (ROI) in a reference scout image generated by a magnetic resonance (MR) apparatus; and
in a computer operational with the MR apparatus:
(A) cross-correlating positions of the ROI between the reference scout image and each of a series of scout images acquired by the MR apparatus during an R-R interval;
(B) determining a plurality of cross-correlation maps from the cross-correlated positions of the ROI, wherein the plurality of cross-correlation maps define a non-linear motion of the anatomy of interest; and
(C) applying the cross-correlation maps to define a plurality of acquisition slices during MR imaging of the region of interest.
9. The method of claim 8 further comprising:
acquiring a plurality of CINE scout images from a CINE scout scan; and
selecting the reference image as an image of the plurality of CINE scout images in which the ROI is most discernible.
10. The method of claim 8 wherein cross-correlating positions of the ROI includes Fourier transforming the reference scout image and determining a kernel set therefrom.
11. The method of claim 10 wherein cross-correlating positions of the ROI further includes creating a mask of the ROI and determining a weighting set therefrom.
12. The method of claim 11 wherein cross-correlating positions of the ROI further includes multiplying the kernel set and the weighting set by a raw data image to result in a kernel product and a weighting product, and calculating a cross-correlation image from a ratio of the magnitudes of the kernel product and the weighting product.
13. The method of claim 8 wherein the plurality of cross-correlation maps define a non-linear motion of the anatomy of interest during one phase of motion of the anatomy of interest.
14. The method of claim 8 further comprising tracking motion of a coronary artery by positioning the number of acquisition slices to maintain the coronary artery in a field of view of each acquisition slice.
15. A non-transitory computer readable storage medium having stored thereon a set of instructions which, when executed by a computer, cause the computer to:
identify a region of interest (ROI) in a series of scout images;
extract a plurality of motion parameters from the series of scout images, wherein the plurality of motion parameters define non-linear motion of the ROI; and
adjust an acquisition slice location during MR imaging using the plurality of motion parameters.
16. The computer readable storage medium of claim 15 wherein the set of instructions further causes the computer to:
cross-correlate a position of the ROI in one image of the series of scout images with positions of the ROI in other images of the series of scout images; and
generate a cross-correlation map from the cross-correlated positions of the ROI.
17. The computer readable storage medium of claim 16 wherein the set of instructions further causes the computer to cross-correlate the positions of the ROI using the one image of the series of scout images as a convolution kernel and convolving the other images of the series of scout images with the convolution kernel.
18. The computer readable storage medium of claim 15 wherein the set of instructions further causes the computer to extract the plurality of motion parameters during one phase of motion of an anatomy of interest.
19. The computer readable storage medium of claim 15 wherein the set of instructions further causes the computer to identify a displacement of a central intensity maximum of the ROI in the series of scout images.
20. The computer readable storage medium of claim 15 wherein the set of instructions further causes the computer to adjust the acquisition slice location by modifying a slice selection gradient.