Field of view increase in magnetic resonance imaging using nonlinear gradients and generalized iterative reconstruction

• US 10,459,051 B2
• Filed: 01/05/2017
• Issued: 10/29/2019
• Est. Priority Date: 01/05/2017
• Status: Active Grant

• Current Assignee: The General Hospital Corporation (Mass General Brigham, Inc.), Siemens Healthineers AG (Siemens AG)
• Original Assignee: Siemens Healthcare GMBH (Siemens AG)
• Inventors: Heberlein, Keith Aaron, Stockmann, Jason
• Primary Examiner(s): LaBalle, Clayton E.
• Assistant Examiner(s): Wenderoth, Frederick
• Application Number:
  US15/399,015
• Publication Number:
  US 20180188342A1
• Time in Patent Office: 1,027 Days
• Field of Search: 399309
• CPC Class Codes: G01R 33/481 MR combined with positron emission tomography [PET] or single photon emission computed tomography [SPECT]
• CPC Class Codes: G01R 33/4824 using a non-Cartesian trajectory
• CPC Class Codes: G01R 33/56572 caused by a distortion of a gradient magnetic field, e.g. non-linearity of a gradient magnetic field G01R33/56509, G01R33/56518, G01R33/56536 take precedence

Abstract

A method for increasing field of view (FOV) in magnetic resonance imaging includes determining linear field gradients of associated with a gradient coil of a magnetic resonance (MR) scanner and using the MR scanner to acquire a k-space dataset representative of a patient using a plurality of readout gradient amplitudes. An extended FOV image is generated based on the k-space dataset using an iterative reconstruction process to solve a forward model that incorporates a measurement of gradient distortion as a deviation from the linear field gradients.

Claims

1. A method for increasing field of view (FOV) in magnetic resonance imaging, the method comprising:

determining linear field gradients of associated with a gradient coil of a magnetic resonance (MR) scanner;

using the MR scanner to acquire a k-space dataset representative of a patient using a plurality of readout gradient amplitudes;

generating an extended FOV image based on the k-space dataset using an iterative reconstruction process that applies a forward model to convert the k-space data set to image space, wherein the forward model incorporates a measurement of gradient distortion as a deviation from the linear field gradients.

2. The method of claim 1, wherein the MR scanner acquires the k-space dataset using multiple projections of a non-Cartesian trajectory.

3. The method of claim 2, wherein the non-Cartesian trajectory is a spiral sampling trajectory.

4. The method of claim 2, wherein the non-Cartesian trajectory is a radial sampling trajectory.

5. The method of claim 1, wherein the linear field gradients of associated with the gradient coil of the MR scanner comprise a plurality of spatially varying functions.

6. The method of claim 1, wherein the iterative reconstruction process comprises a process implementing the Kaczmarz algorithm.

7. The method of claim 1, further comprising:

generating a full body model of the patient based on the extended FOV image.

8. The method of claim 7, further comprising:

using the full body model to perform a PET reconstruction of a patient image.

9. A system for increasing field of view (FOV) in magnetic resonance imaging, the system comprising:

a plurality of coils configured to acquire a k-space dataset representative of a patient using a plurality of readout gradient amplitudes;

a control computer configured to reconstruct an extended FOV image of the patient based on the k-space dataset using a process comprising;

determining linear field gradients associated with the plurality of coils, and

generating the extended FOV image based on the k-space dataset using an iterative reconstruction process that applies a forward model to convert the k-space data set from image space to projection space, wherein the forward model incorporates a measurement of gradient distortion as a deviation from the linear field gradients.

10. The system of claim 9, wherein the plurality of coils acquires the k-space dataset using multiple projections of a non-Cartesian trajectory.

11. The system of claim 10, wherein the non-Cartesian trajectory is a spiral sampling trajectory.

12. The system of claim 10, wherein the non-Cartesian trajectory is a radial sampling trajectory.

13. The system of claim 9, wherein the plurality of coils comprises volume coils.

14. The system of claim 9, wherein the plurality of coils comprise a phased array of coils and generation of the extended FOV image utilizes a plurality of sensitivity maps associated with the plurality of coils.

15. The system of claim 9, wherein the linear field gradients of associated with the plurality of coils comprise a plurality of spatially varying functions.

16. The system of claim 9, wherein the iterative reconstruction process implements the Kaczmarz algorithm.

17. The system of claim 9, further comprising:

a computer configured to generate a full body model of the patient based on the extended FOV image.

18. The system of claim 17, further comprising:

a positron emission tomography (PET) scanner configured to perform a PET acquisition of the patient using the full body model.

19. A system for performing extended FOV imaging, the system comprising:

a MRI scanner configured to acquire a k-space dataset representative of a patient using a plurality of readout gradient amplitudes;

one or more computers configured to;

generate an extended FOV image based on the k-space dataset using an iterative reconstruction process that applies a forward model to convert the k-space data set to image space, wherein the forward model incorporates a measurement of gradient distortion as a deviation from linear field gradients associated with the MRI scanner, and

generate a full body model of the patient based on the extended FOV image; and

a PET scanner configured to perform a PET acquisition of the patient using the full body model.

20. The system of claim 19, wherein the MRI scanner and the PET scanner are co-located in a single hybrid scanning device.