IP Library Granted Patent US 11,221,388
Granted Patent B1
US 11,221,388 · App. 16/442,358 · Granted Jan 11, 2022

Compensation of magnetic field inhomogeneity in MR spectroscopic imaging using dynamic k-space expansion in combination with parallel imaging

Inventor: Stefan Posse (Albuquerque, NM)
Assignee: UNM Rainforest Innovations
G01R33/56572A61B5/0042A61B5/055G01R33/4818
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,221,388
App. No.
16/442,358
Granted
Jan 11, 2022
Kind
B1
Abstract

A method for the compensation of magnetic field inhomogeneity in magnetic resonance spectroscopic imaging comprising the steps of using dynamic k-space expansion in combination with parallel imaging.

Claims (12)

1. A method for the compensation of magnetic field inhomogeneity in magnetic resonance spectroscopic imaging comprising the steps of using dynamic k-space expansion in combination with parallel imaging; said k-space is expanded with increasing spectral encoding time t, resulting in spectral line narrowing in proportion to the expansion of k-space; and minimizing gradient switching by tailoring the expansion and density of k-t-space sampling to the dispersion and density of signal trajectories in k-t-space.

2. The system and method of claim 1 wherein said expansion of the k-space with spectral encoding time includes interleaving progressively larger spatial encoding gradient moments.

3. The method of claim 1 wherein expanding the k-space is accomplished by extending high speed image encoding modules, including echo-planar and spiral encoding modules.

4. The method of claim 1 wherein said k-space is undersampled regularly and compressed sensing is used to reconstruct the missing data.

5. The method of claim 1 wherein said k-space is under sampled randomly and compressed sensing is used to reconstruct the missing data.

6. The method of claim 1 wherein said expansion of k-t-space is linear and employs readout gradient moment with stepwise increases (2G l δt) every second gradient using a constant gradient duration δ, up to the limits of the gradient performance.

7. The method of claim 1 wherein single-shot phase encoding using gradient blips with linearly increasing gradient moment G l *t are selectively interleaved into the readout, with a corresponding increase of the effective spectral dwell time.

8. The method of claim 7 wherein said interleaving starts at the edges of the original k y -k z -space and progressively inserts single-shot phase encoding into more central k y -k z -space encodings as time t increases.

9. The method of claim 1 wherein the k-space dimensions are tailored to the orientation and amplitude distribution of local Gradients G l based on B 0 gradient maps.

10. The method of claim 1 further including the step of compensating local gradients in a selected brain region and simultaneously acquiring signals from the rest of the brain without compensation.

11. A method for the compensation of magnetic field inhomogeneity in magnetic resonance spectroscopic imaging comprising the steps of using dynamic k-space expansion in combination with parallel imaging; and said k-space is expanded with increasing spectral encoding time t, resulting in spectral line narrowing in proportion to the expansion of k-space; and wherein said k-space is undersampled regularly and partial parallel imaging is used to reconstruct the missing data.

12. A method for the compensation of magnetic field inhomogeneity in magnetic resonance spectroscopic imaging comprising the steps of using dynamic k-space expansion in combination with parallel imaging; and said k-space is expanded with increasing spectral encoding time t, resulting in spectral line narrowing in proportion to the expansion of k-space; and wherein said k-space is under sampled randomly and compressed sensing is used to reconstruct the missing data.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 2, 2022
From: POSSE, STEFAN
To: THE REGENTS OF THE UNIVERSITY OF NEW MEXICO
Reel/Frame 058865/0531 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 2, 2022
From: THE REGENTS OF THE UNIVERSITY OF NEW MEXICO
To: UNM RAINFOREST INNOVATIONS
Reel/Frame 058865/0674 →
Continuity (1)
Provisional Application 62685746 · Jun 15, 2018
Cited By (1)
US 12,484,782