# US 7,609,060 B2 · Non iterative shimming in magnetic resonance imaging in the presence of high LIPID levels

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- Number: US 7,609,060 B2
- Document ID: US7609060B2
- Status: Granted
- Kind: B2
- Application number: 12/080,510
- Filed: 2008-04-03
- Published: 2008-10-23
- Granted: 2009-10-27
- Earliest claimed: 2007-04-20
- Assignees: Albert Einstein College of Medicine of Yeshiva University
- Inventors: Hoby P. Hetherington; Jullie W. Pan
- Web page: https://patentgrep.com/patent/US7609060B2

## CPC

- G01R 33/56563: {caused by a distortion of the main magnetic field B0, e.g. temporal variation of the magnitude or spatial inhomogeneity of B0 (G01R33/56509, G01R33/56518, G01R33/56536 take precedence)}
- G01R 33/243: {Spatial mapping of the polarizing magnetic field}
- G01R 33/3875: using correction coil assemblies, e.g. active shimming
- G01R 33/4828: {Resolving the MR signals of different chemical species, e.g. water-fat imaging}
- G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12)

## Abstract

For the brain, a variety of automated non-iterative shimming methods using phase evolution derived B0 maps have been reported. These methods assume that there is only a single chemical species contributing to the image. Although true in the brain, lipid contributions from skin, bone marrow and structural fat, may approach or exceed the concentration of water in other organs. In these instances, standard B0 mapping methods cannot be used due to contributions arising from the lipids. To overcome these limitations the present invention discloses a multi-point B0 mapping method combined with Dixon imaging to provide fully automated shimming of the human calf.

## Claims

### Claim 1

A method for mapping the inhomogeneity of a magnetic field within an object in an MRI system, said object containing a first and a second material comprising the steps of:
a. acquiring a plurality of images with said MRI system at a corresponding plurality of evolution times,
b. calculating the phase contribution to the plurality of images due to the second material,
c. removing said contribution from each of said plurality of images to obtain a phase map reflective of the inhomogeneity of said magnetic field,
d. unwrapping aliasing present in the phase maps of images having relatively longer evolution times by reference to phase maps of images having relatively shorter evolution times, and
e. generating a single map of magnetic field inhomogeneity from the unwrapped results,
wherein said plurality of images comprises a first image set of at least three images separated by a predetermined evolution time interval, Δt, and a second image set of n≧3 images each having evolution times respectively corresponding to ascending evolution delays Δt1-Δtn, said evolution delays measured relative to a reference image corresponding to evolution delay Δt0=0,
wherein the predetermined evolution time interval Δt is a function of the chemical shift between said first and second material, and Δt is defined by the equation Δt=½Δv where Δv is the chemical shift between said first and second material in Hertz,
wherein the step of calculating the phase contribution to the plurality of images due to the second material comprises calculating a Dixon image from the images in said first image set, and
wherein the step of unwrapping aliasing is performed on images in the second image set.

### Claim 2 (depends on 1)

The method of claim 1, wherein said first image set and said second image set intersect.

### Claim 3 (depends on 1)

The method of claim 1, wherein said first material is water and said second material has a Larmor frequency different from that of water.

### Claim 4 (depends on 3)

The method of claim 3, wherein said second material is a lipid.

### Claim 5 (depends on 4)

The method of claim 4, wherein said second material is human fat tissue.

### Claim 6 (depends on 1)

The method of claim 1, wherein the step of unwrapping aliasing further comprises using the phase map of a base image to predict and correct for aliasing in a target image where said target image has a larger evolution delay than that of the base image.

### Claim 7 (depends on 6)

The method of claim 6, wherein said predicting of aliasing in the target image comprises the steps of:
a. calculating a frequency map based on the respective evolution delays of the base image and the target image, and
b. identifying regions in the target image, based on said frequency map, wherein:
i. wrapping is not predicted to occur,
ii. wrapping is predicted to occur, and
iii. wrapping cannot be predicted.

### Claim 8 (depends on 7)

The method of claim 7, wherein said correcting of said aliasing in the target image comprises the steps of:
c. measuring the phase difference between the base image and the target image as a function of their respective evolution delays and calculating the frequency based on the phase difference, in regions of the target image where wrapping is not predicted to occur, and
d. correcting the phase and calculating the frequency based on the corrected phase in regions of the target image where wrapping is predicted to occur.

### Claim 9 (depends on 8)

The method of claim 8, wherein the step of correcting of said aliasing further comprises retaining the current frequency value observed in the base image in regions of the target image where wrapping cannot be predicted to occur.

### Claim 10 (depends on 9)

The method of claim 9, wherein the current frequency value is selectively retained when the calculated frequencies in the base and target image are significantly different.

### Claim 11 (depends on 10)

The method of claim 10, wherein the evolution delay of the target image is longer than the evolution delay of the base image by a factor of two.

### Claim 12 (depends on 10)

The method of claim 10, wherein the first image set and the second image set are selected to minimize differential T2 relaxation between the first material and the second material.

### Claim 13 (depends on 10)

The method of claim 10, wherein the first image set and the second image set intersect.

### Claim 14 (depends on 10)

The method of claim 10, wherein the second material comprises a plurality of compounds having different Larmor frequencies.

### Claim 15 (depends on 14)

The method of claim 14, wherein said chemical shift is calculated based on an estimated Larmor frequency model corresponding to the composition of the second material.

### Claim 16 (depends on 10)

The method of claim 10 further comprising using information from said map to compensate for inhomogeneity in the magnetic field within said MRI system.

### Claim 17 (depends on 16)

The method of claim 16, wherein said information is uploaded to shimming coils to compensate for said inhomogeneity in said magnetic field.