Method for rapid-multicontrast brain imaging

Patent metadata

Field	Value
Publication number	US-9454709-B2
Application number	US-201414539061-A
Country	US
Kind code	B2
Filing date	Nov 12, 2014
Priority date	Nov 12, 2014
Publication date	Sep 27, 2016
Grant date	Sep 27, 2016

Abstract

A method for providing an image of a subject is provided. The plurality of Cartesian points is divided into a first group and a second group, wherein all of the Cartesian points in the first group have a k r that is less than or equal to k r of all of the Cartesian points in the second group. The second group is divided into N subgroups. An inversion recovery radio frequency is applied to the subject. K-space data for the first group of Cartesian points for M different time periods is acquired, wherein k-space data is acquired for only one sub-group sequentially and cyclically for the M different time periods. For each time period i of the M different time periods, acquired k-space data for the first group of Cartesian points at time period i and k-space data from N consecutive subgroups of Cartesian points.

First claim

What is claimed is:

1. A method for providing an image of a subject in a magnetic resonance imaging MRI system, comprising:
defining a plurality of Cartesian points on a k y -k z plane with a center, wherein each of the plurality of Cartesian points has a k r , wherein k r is a distance from a Cartesian point of the plurality of Cartesian points to the center;
dividing the plurality of Cartesian points into a first group (Group A) and a second group (Group B), wherein all of the Cartesian points in the first group have a k r that is less than or equal to k r of all of the Cartesian points in the second group;
dividing the second group into N subgroups, wherein N is a whole number greater than or equal to two, wherein the subgroups have an incoherent point spread function;
applying an inversion recovery (IR) radio frequency to the subject such that a net longitudinal magnetization in the subject is substantially inverted and begins to relax back to equilibrium;
acquiring k-space data for the first group of Cartesian points for M different time periods, wherein k-space data is acquired for only one sub-group for each time period of the M different time periods, and wherein k-space data is acquired for each subgroup sequentially and cyclically for the M different time periods;
for each time period i of the M different time periods, using acquired k-space data for the first group of Cartesian points at time period i and k-space data from N consecutive subgroups of Cartesian points where one of the N consecutive subgroups is the subgroup that is acquired during time period i to create image data of the subject for first time period i.

2. The method, as recited in claim 1 , further comprising:
for each time period i for the M different time periods, using the image data for time period i to create an image for time period i; and
displaying the image for time period.

3. The method, as recited in claim 1 , wherein the image data from a plurality of time periods are combined to create a relaxation map.

4. The method, as recited in claim 1 , wherein the first plurality of Cartesian points are within a radial sector of the circle, and wherein the Cartesian points within the first group are all Cartesian points in the radial sector at or within a radius of R from the center of the circle and wherein the Cartesian points within the second group are all Cartesian points in the radial sector at or beyond the radius of R from the center of the circle.

5. The method, as recited in claim 1 , wherein the Cartesian points within the first group are Cartesian points in the circle at or within a radius of r from the center of the circle and wherein the Cartesian points within the second group are Cartesian points in the circle at or beyond the radius of r from the center of the circle.

6. The method, as recited in claim 1 , wherein Cartesian points in each subgroup are dispersed as much as possible.

7. The method, as recited in claim 1 , wherein the Cartesian points in each subgroup are chosen by at least one of dithered spiral interleaving, random selection, or pseudo-random selection.

8. The method, as recited in claim 1 , further comprising:
for each time period i for the M different time periods, using the image data for time period i to create an image for time period i, which provides a plurality of images;
displaying the plurality of images; and
using the plurality of images to provide multicontrast images.

9. The method, as recited in claim 8 , wherein the Cartesian points in each subgroup are chosen by at least one of dithered spiral interleaving, random selection, or pseudo-random selection.

10. The method, as recited in claim 9 , wherein N is between 3 and 6 inclusive.

11. The method, as recited in claim 10 , wherein M is a multiple of N.

12. The method, as recited in claim 11 , wherein Cartesian points in each subgroup are dispersed as much as possible.

13. The method, as recited in claim 12 , wherein the multicontrast images are multicontrast images of a brain.

14. The method, as recited in claim 12 , wherein the first plurality of Cartesian points are within a radial sector of the circle, and wherein the Cartesian points within the first group are all Cartesian points in the radial sector at or within a radius of R from the center of the circle and wherein the Cartesian points within the second group are all Cartesian points in the radial sector at or beyond the radius of R from the center of the circle.

15. The method, as recited in claim 12 , wherein the Cartesian points within the first group are Cartesian points in the circle at or within a radius of r from the center of the circle and wherein the Cartesian points within the second group are Cartesian points in the circle at or beyond the radius of r from the center of the circle.

16. The method, as recited in claim 1 , wherein N is between 3 and 6 inclusive.

17. The method, as recited in claim 1 , wherein M is a multiple of N.

18. The method, as recited in claim 1 , wherein the N subgroups are interleaved.

Assignees

• Univ Leland Stanford Junior

Inventors

• Saranathan Manojkumar
• Rutt Brian K
• Rioux James A

Classifications

• G01R33/482

  using a Cartesian trajectory · CPC title

• A61B2576/026

  for the brain · CPC title

• G01R33/561

  by reduction of the scanning time, i.e. fast acquiring systems, e.g. using echo-planar pulse sequences · CPC title

• A61B5/742

  using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339) · CPC title

• G06T2207/20076

  Probabilistic image processing · CPC title