# US 10,310,047 B2 · Systems and methods for free-breathing cine DENSE MRI using self-navigation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,310,047 B2 - Document ID: US10310047B2 - Status: Granted - Kind: B2 - Application number: 15/493,825 - Filed: 2017-04-21 - Published: 2017-10-26 - Granted: 2019-06-04 - Earliest claimed: 2016-04-21 - Assignees: University of Virginia Patent Foundation - Applicants: University of Virginia Patent Foundation - Inventors: Xiaoying Cai; Frederick H. Epstein; Xiaodong Zhong - Web page: https://patentgrep.com/patent/US10310047B2 ## CPC - G01R 33/5676: {Gating or triggering based on an MR signal, e.g. involving one or more navigator echoes for motion monitoring and correction} - G01R 33/56316: {involving phase contrast techniques} - G01R 33/56325: {Cine imaging} - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) ## Abstract 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. ## Claims ### Claim 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. ### Claim 2 (depends on 1) 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. ### Claim 3 (depends on 2) 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. ### Claim 4 (depends on 3) 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. ### Claim 5 (depends on 1) 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. ### Claim 6 (depends on 5) The method of claim 5, further comprising performing principal component analysis (PCA)-based filtering to suppress a T1 relaxation echo. ### Claim 7 (depends on 5) 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. ### Claim 8 (depends on 1) 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. ### Claim 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. ### Claim 10 (depends on 9) The system of claim 9, wherein the data acquisition device comprises a magnetic resonance imaging (MRI) device. ### Claim 11 (depends on 9) 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. ### Claim 12 (depends on 11) 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. ### Claim 13 (depends on 12) 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. ### Claim 14 (depends on 9) 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. ### Claim 15 (depends on 14) 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. ### Claim 16 (depends on 14) 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. ### Claim 17 (depends on 9) 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. ### Claim 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. ### Claim 19 (depends on 18) 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. ### Claim 20 (depends on 19) 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. ### Claim 21 (depends on 20) 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. ### Claim 22 (depends on 18) 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. ### Claim 23 (depends on 22) 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. ### Claim 24 (depends on 22) 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. ### Claim 25 (depends on 18) 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.