Variable density incoherent spatiotemporal acquisition (VISTA) for highly accelerated magnetic resonance imaging

Patent metadata

Field	Value
Publication number	US-9939509-B2
Application number	US-201514593322-A
Country	US
Kind code	B2
Filing date	Jan 9, 2015
Priority date	Jan 28, 2014
Publication date	Apr 10, 2018
Grant date	Apr 10, 2018

Abstract

A pseudo-random, incoherent sampling technique, called Variable density Incoherent Spatiotemporal Acquisition (VISTA) is disclosed, which is based on minimal Riesz energy problem. Compared with other pseudorandom methods (e.g., PDS), VISTA has the unique ability to incorporate a variety of problem-specific constraints. In this study, VISTA was applied to real-time CMR, where it not only provided an incoherent sampling with variable density but also ensured a constant temporal resolution and a fully sampled time-averaged data.

First claim

What is claimed:

1. A method of Variable density Incoherent Spatiotemporal Acquisition (VISTA) for generating magnetic resonance imaging (MRI) sampling location of N data samples on an n-dimensional (nD) grid, comprising;
initializing a location of N k-space samples on the nD grid;
iteratively minimizing a cost function U to update the location of samples;
enforcing application specific constraints on the distribution of samples in each iteration;
generating a sampling pattern at each iteration; and
storing each sampling pattern as a lookup table, whereby MR images are reconstructed from the data collected using the lookup table.

2. The method of claim 1 , if the convergence has not occurred, repeating the minimizing and enforcing.

3. The method of claim 1 , wherein a deterministic, random, or pseudorandom sampling is used as the initializing.

4. The method of claim 1 , where the number of samples, N, is predefined by the user.

5. The method of claim 1 , wherein gradient projections are applied to enforce application-specific constraints.

6. The method of claim 1 , wherein a constraint is enforced such that averaging the samples along one of the n dimensions yields fully sampled data in (n−1)-dimensional domain.

7. The method of claim 1 , wherein the location of samples is rounded to the nearest location on a Cartesian grid.

8. The method of claim 1 , wherein partial-Fourier sampling is embedded into the VISTA framework by imposing antipodal symmetry on the sampling pattern.

9. The method of claim 1 , further comprising different sampling domains, including: 3D spatial MRI (with 2D VISTA in k y -k z domain); 2D cine at rest and stress (with 2D VISTA in k y -t domain); 3D cine at rest and stress (with 3D VISTA in k y -k z -t domain); 2D and 3D multi-direction flow imaging (with 3D VISTA in k y -t-velocity encoding domain and 4D VISTA in k y -k z t-velocity encoding domain, respectively); 2D myocardial perfusion (with 2D VISTA in k y -t domain); 3D myocardial perfusion (with 3D VISTA in k y -k z -t domain); 3D dynamic angiography (with 3D VISTA in k y -k z -t domain); and 2D and 3D MR elastography (with 2D VISTA in k y -phase offset domain and 3D VISTA in k y -k z -phase offset domain, respectively).

10. The method of claim 1 , for 2D and 3D single-point acquisition for electron paramagnetic resonance imaging.

11. The method of claim 1 , further comprising sampling in Cartesian and non-Cartesian domains, where one or more dimensions represent a variable other than space or time.

12. The method of claim 1 , wherein the resulting sampling pattern is used for iterative or non-iterative image reconstruction methods.

13. The method of claim 1 , wherein the distribution is obtained before full convergence is reached.

14. The method in claim 1 , wherein a sample represents multiple k-space lines obtained by EPI sequence or an arm of a spiral or radial acquisition.

15. The method if claim 1 , wherein one or more transmit and receive coils are used for acquisition.

16. The method of claim 1 , wherein the cost function is represented by:

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Assignees

• Ohio State Innovation Foundation

Inventors

• Ahmad Rizwan
• Simonetti Orlando P
• Ding Yu

Classifications

• G01R33/56325

  Cine imaging · CPC title

• G01R33/5619 Primary

  by temporal sharing of data, e.g. keyhole, block regional interpolation scheme for k-Space [BRISK] · CPC title

• G01R33/4824

  using a non-Cartesian trajectory · CPC title

• G01R33/482

  using a Cartesian trajectory · CPC title

• G01R33/5608

  Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels (image data processing or generation, in general G06T) · CPC title