Systems and methods for free-breathing cine DENSE MRI using self-navigation
Some aspects of the present disclosure relate to systems and methods for free-breathing cine DENSE MRI using self-navigation. In one embodiment, a method includes acquiring magnetic resonance data for an area of interest of a subject, wherein the acquiring comprises performing sampling with phase-cycled, cine displacement encoding with stimulated echoes (DENSE) during free-breathing of the subject; identifying, from the acquired magnetic resonance data, a plurality of phase-cycling data pairs corresponding to matched respiratory phases of the free-breathing of the subject; reconstructing, from the plurality of phase-cycling data pairs, a plurality of intermediate self-navigation images; performing motion correction by estimating, from the plurality of intermediate self-navigation images, the respiratory position associated with the plurality of phase-cycling data pairs; and reconstructing a plurality of motion-corrected cine DENSE images of the area of interest of the subject.
1. A method comprising:
acquiring magnetic resonance data for an area of interest of a subject, wherein the acquiring comprises performing sampling with phase-cycled, cine displacement encoding with stimulated echoes (DENSE) during free-breathing of the subject;
identifying, from the acquired magnetic resonance data, a plurality of phase-cycling data pairs corresponding to matched respiratory phases of the free-breathing of the subject;
reconstructing, from the plurality of phase-cycling data pairs, a plurality of intermediate self-navigation images of the area of interest of the subject;
performing motion correction by estimating, from the plurality of intermediate self-navigation images, the respiratory position associated with the plurality of phase-cycling data pairs; and
reconstructing a plurality of motion-corrected cine DENSE images of the area of interest of the subject.
2. The method of claim 1 , wherein identifying the plurality of phase-cycling data pairs corresponding to matched respiratory phases includes determining whether a plurality of phase-cycling data meet match-making criterion associated with respiratory motion of the subject.
3. The method of claim 2 , wherein the match-making criterion includes a residual T1 relaxation echo energy determined by subtracting the plurality of phase-cycling data to identify phase-cycling data pairs at matched respiratory phases.
4. The method of claim 3 , wherein phase-cycling data at matched respiratory phases have a lower residual T1 relaxation echo energy than phase-cycling data at different respiratory phases.
5. The method of claim 1 , wherein identifying the plurality of phase-cycling data pairs corresponding to matched respiratory phases comprises reconstructing a plurality of pre-subtraction intermediate self-navigation images.
6. The method of claim 5 , further comprising performing principal component analysis (PCA)-based filtering to suppress a T1 relaxation echo.
7. The method of claim 5 , further comprising performing motion estimation between a plurality of pre-subtraction intermediate self-navigation images to identify a plurality of phase-cycling data pairs corresponding to matched respiratory phases.
8. The method of claim 1 , wherein performing motion correction by estimating, from the plurality of intermediate self-navigation images, the respiratory position associated with the plurality of phase-cycling data pairs includes using slice-selective radiofrequency pulses such that the stimulated echo generates a signal from a region focused on the area of interest of the subject.
9. A system comprising:
a data acquisition device configured to acquire magnetic resonance data for an area of interest of a subject, wherein the acquiring comprises performing sampling with phase-cycled, cine displacement encoding with stimulated echoes (DENSE) during free-breathing of the subject;
one or more processors coupled to the data acquisition device and configured to cause the system to perform functions including:
identifying, from the acquired magnetic resonance data, a plurality of phase-cycling data pairs corresponding to matched respiratory phases of the free-breathing of the subject;
reconstructing, from the plurality of phase-cycling data pairs, a plurality of intermediate self-navigation images of the area of interest of the subject;
performing motion correction by estimating, from the plurality of intermediate self-navigation images, the respiratory position associated with the plurality of phase-cycling data pairs; and
reconstructing a plurality of motion-corrected cine DENSE images of the area of interest of the subject.
10. The system of claim 9 , wherein the data acquisition device comprises a magnetic resonance imaging (MRI) device.
11. The system of claim 9 , wherein identifying the plurality of phase-cycling data pairs corresponding to matched respiratory phases includes determining whether a plurality of phase-cycling data meet match-making criterion associated with respiratory motion of the subject.
12. The system of claim 11 , wherein the match-making criterion includes a residual T1 relaxation echo energy determined by subtracting the plurality of phase-cycling data to identify phase-cycling data pairs at matched respiratory phases.
13. The system of claim 12 , wherein phase-cycling data at matched respiratory phases have a lower residual T1-relaxation echo energy than phase-cycling data at different respiratory phases.
14. The system of claim 9 , wherein identifying the plurality of phase-cycling data pairs corresponding to matched respiratory phases comprises reconstructing a plurality of pre-subtraction intermediate self-navigation images.
15. The system of claim 14 , wherein the one or more processors are configured to cause the system to perform further functions that comprise performing principal component analysis (PCA)-based filtering to suppress a T1 relaxation echo.
16. The system of claim 14 , wherein the one or more processors are configured to cause the system to perform further functions that comprise performing motion estimation between a plurality of pre-subtraction intermediate self-navigation images to identify a plurality of phase-cycling data pairs corresponding to matched respiratory phases.
17. The system of claim 9 , wherein performing motion correction by estimating, from the plurality of intermediate self-navigation images, the respiratory position associated with the plurality of phase-cycling data pairs includes using slice-selective radiofrequency pulses such that the stimulated echo generates a signal from a region focused on the area of interest of the subject.
18. A non-transitory computer-readable medium having stored instructions that, when executed by one or more processors, cause one or more computing devices to perform functions that comprise:
acquiring magnetic resonance data for an area of interest of a subject, wherein the acquiring comprises performing sampling with phase-cycled, cine displacement encoding with stimulated echoes (DENSE) during free-breathing of the subject;
identifying, from the acquired magnetic resonance data, a plurality of phase-cycling data pairs corresponding to matched respiratory phases of the free-breathing of the subject;
reconstructing, from the plurality of phase-cycling data pairs, a plurality of intermediate self-navigation images of the area of interest of the subject;
performing motion correction by estimating, from the plurality of intermediate self-navigation images, the respiratory position associated with the plurality of phase-cycling data pairs; and
reconstructing a plurality of motion-corrected cine DENSE images of the area of interest of the subject.
19. The non-transitory computer-readable medium of claim 18 , wherein identifying the plurality of phase-cycling data pairs corresponding to matched respiratory phases includes determining whether a plurality of phase-cycling data meet match-making criterion associated with respiratory motion of the subject.
20. The non-transitory computer-readable medium of claim 19 , wherein the match-making criterion includes a residual T1 relaxation echo energy determined by subtracting the plurality of phase-cycling data to identify phase-cycling data pairs at matched respiratory phases.
21. The non-transitory computer-readable medium of claim 20 , wherein phase-cycling data at matched respiratory phases have a lower residual T1-relaxation echo energy than phase-cycling data at different respiratory phases.
22. The non-transitory computer-readable medium of claim 18 , wherein identifying the plurality of phase-cycling data pairs corresponding to matched respiratory phases comprises reconstructing a plurality of pre-subtraction intermediate self-navigation images.
23. The non-transitory computer-readable medium of claim 22 , wherein the instructions, when executed by the one or more processors, cause the one or more computing devices to perform further functions that comprise performing principal component analysis (PCA)-based filtering to suppress a T1 relaxation echo.
24. The non-transitory computer-readable medium of claim 22 , wherein the instructions, when executed by the one or more processors, cause the one or more computing devices to perform further functions that comprise performing motion estimation between a plurality of pre-subtraction intermediate self-navigation images to identify a plurality of phase-cycling data pairs corresponding to matched respiratory phases.
25. The non-transitory computer-readable medium of claim 18 , wherein performing motion correction by estimating, from the plurality of intermediate self-navigation images, the respiratory position associated with the plurality of phase-cycling data pairs includes using slice-selective radiofrequency pulses such that the stimulated echo generates a signal from a region focused on the area of interest of the subject.