System and method for combined chemical species separation and high resolution R2* mapping with magnetic resonance imaging

Patent metadata

Field	Value
Publication number	US-9329250-B2
Application number	US-201313803360-A
Country	US
Kind code	B2
Filing date	Mar 14, 2013
Priority date	Mar 14, 2013
Publication date	May 3, 2016
Grant date	May 3, 2016

Abstract

Described here is a system and method for estimating apparent transverse relaxation rate, R 2 *, while simultaneously performing chemical species separation (e.g., water-fat separation) using magnetic resonance imaging (“MRI”). A homodyne reconstruction of k-space datasets acquired using a partial k-space acquisition is used and the chemical species separation of the resultant images takes into account the spectral complexity of the chemical species in addition to magnetic resonance signal decay associated with transverse relaxation. Full resolution maps of R 2 * are thus capable of being produced while also allowing for the production of images depicting the separated chemical species that are corrected for transverse relaxation associated signal decays.

First claim

The invention claimed is:

1. A method for producing a quantitative map of transverse relaxation rate while separating signal contributions from at least two chemical species using a magnetic resonance imaging (MRI) system, the steps of the method comprising:
a) acquiring k-space data with the MRI system using a partial k-space acquisition that samples a fraction of k-space, the k-space data corresponding to magnetic resonance signals formed at least at three different echo times;
b) producing low-pass filtered data by applying a low-pass filter to the k-space data acquired in step a);
c) reconstructing low resolution images from the low-pass filtered data;
d) fitting the low resolution images to a signal model to estimate a low resolution field map, a first low resolution image depicting signal contributions from a first chemical species separated from a second chemical species, and a second low resolution image depicting signal contributions from the second chemical species separated from the first chemical species;
e) applying a weighting to the k-space data acquired in step a);
f) reconstructing weighted images from the weighted k-space data;
g) demodulating the weighted images using the low resolution field map, first low resolution image, and second low resolution estimated in step d);
h) estimating a transverse relaxation rate, R 2 *, map by fitting the images demodulated in step g) to a signal model that accounts for the demodulation performed in step g), the R 2 * map having a higher spatial resolution than the low resolution images reconstructed in step c); and
i) fitting the weighted images reconstructed in step f), the low resolution field map estimated in step d), and the R 2 * map estimated in step h) to a signal model to produce a first image depicting signal contributions from the first chemical species separated from a second chemical species, and a second image depicting signal contributions from the second chemical species separated from the first chemical species, the first and second images having a higher spatial resolution than the first and second low resolution images.

2. The method as recited in claim 1 in which step g) includes demodulating contributions from the low resolution field map and from a phase of signal contributions from the first chemical species and a phase of signal contributions from the second chemical species.

3. The method as recited in claim 2 in which step g) includes calculating a common phase of signal contributions from the first chemical species and the second chemical species.

4. The method as recited in claim 3 in which the common phase is estimated by combining a phase component of the first low resolution image and a phase component of the second low resolution image.

5. The method as recited in claim 1 in which step e) includes multiplying the acquired k-space data by a weighting function.

6. The method as recited in claim 5 in which the weighting function is a Hanning window function.

7. The method as recited in claim 1 in which the first chemical species is water and the second chemical species is fat, and the signal models fit to in steps d), h), and i) model fat as having multiple spectral peaks.

8. A magnetic resonance imaging (MRI) system, comprising:
a magnet system configured to generate a polarizing magnetic field about at least a portion of a subject arranged in the MRI system;
a plurality of gradient coils configured to apply a magnetic gradient field to the polarizing magnetic field;
a radio frequency (RF) system configured to apply an RF field to the subject and to receive magnetic resonance signals therefrom;
a computer system programmed to:
direct the plurality of gradient coils and the RF system to acquire k-space data by sampling k-space using a partial k-space acquisition that samples a fraction of k-space, the k-space data corresponding to magnetic resonance signals formed at least at three different echo times;
produce low-pass filtered data by applying a low-pass filter to the acquired k-space data;
reconstruct low resolution images from the low-pass filtered data;
fit the low resolution images to a signal model to estimate:
a low resolution field map;
a first low resolution image depicting signal contributions from a first chemical species separated from a second chemical species; and
a second low resolution image depicting signal contributions from the second chemical species separated from the first chemical species;

apply a weighting to the acquired k-space data;
reconstruct weighted images from the weighted k-space data;
demodulate the weighted images using the low resolution field map, first low resolution image, and second low resolution;
estimate a transverse relaxation rate map by fitting the demodulated images to a signal model that accounts for the demodulation, the transverse relaxation rate map having a higher spatial resolution than the reconstructed low resolution images;
fit the weighted images, the low resolution field map, and the transverse relaxation rate map to a signal model to produce:
a first image depicting signal contributions from the first chemical species separated from a second chemical species; and
a second image depicting signal contributions from the second chemical species separated from the first chemical species;

wherein the first and second images have a higher spatial resolution than the first and second low resolution images.

9. The MRI system as recited in claim 8 in which the computer system is programmed to demodulate the weighted images by demodulating contributions from the low resolution field map and from a phase of signal contributions from the first chemical species and a phase of signal contributions from the second chemical species.

10. The MRI system as recited in claim 9 in which the computer system is programmed to demodulate the weighted imaged by first calculating a common phase of signal contributions from the first chemical species and the second chemical species and using that common phase to demodulate the weighted images.

11. The MRI system as recited in claim 10 in which the computer system is programmed to estimate the common phase by combining a phase component of the first low resolution image and a phase component of the second low resolution image.

12. The MRI system as recited in claim 8 in which the computer system is programmed to apply a weighting to the acquired k-space data by multiplying the acquired k-space data by a weighting function.

13. The MRI system as recited in claim 12 in which the computer system is programmed to select a Hanning window function as the weighting function.

Assignees

• Wisconsin Alumni Res Found
• Wisconsin Alumni Resesarch Foundation

Inventors

• Taviani Valentina
• Hernando Diego
• Reeder Scott Brian

Classifications

• G01R33/4828 Primary

  Resolving the MR signals of different chemical species, e.g. water-fat imaging · CPC title

• G01R33/561

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

• G01R33/50

  based on the determination of relaxation times {, e.g. T1 measurement by IR sequences; T2 measurement by multiple-echo sequences} · CPC title