Comprehensive cardiovascular analysis with volumetric phase-contrast MRI

Patent metadata

Field	Value
Publication number	US-9513357-B2
Application number	US-201214118964-A
Country	US
Kind code	B2
Filing date	Jul 5, 2012
Priority date	Jul 7, 2011
Publication date	Dec 6, 2016
Grant date	Dec 6, 2016

Abstract

Processing techniques of volumetric anatomic and vector field data from volumetric phase-contrast MRI on a magnetic resonance imaging (MRI) system are provided to evaluate the physiology of the heart and vessels. This method includes the steps of: (1) correcting for phase-error in the source data, (2) visualizing the vector field superimposed on the anatomic data, (3) using this visualization to select and view planes in the volume, and (4) using these planes to delineate the boundaries of the heart and vessels so that measurements of the heart and vessels can be accurately obtained.

First claim

What is claimed is:

1. A method of operation in at least one component of a medical imaging system that employs volumetric phase-contrast magnetic resonance imaging (MRI) data, the method comprising:
receiving volumetric phase-contrast MRI data that includes a plurality of voxels;
identifying at least one set of voxels that represent static soft tissue;
generating via at least one computer at least one eddy current related phase offset based on the at least one set of voxels that represent static soft tissue; and
performing a phase error correction based at least in part on the generated at least one eddy current related phase offset,
wherein identifying at least one set of voxels that represent static soft tissue includes:
applying a first filter to the volumetric phase-contrast MRI data, the first filter based on an intensity value of a magnitude associated with the voxels of the volumetric phase-contrast MRI data;
applying a second filter to the volumetric phase-contrast MRI data, application of the second filter which excludes air and lung tissue from the volumetric phase-contrast MRI data; and
applying a third filter to the volumetric phase-contrast MRI data, application of the third filter which excludes blood and other moving tissue from the volumetric phase-contrast MRI data.

2. The method as set forth in claim 1 , wherein applying a first filter includes applying the first filter which is based on a maximum signal intensity across all of a plurality of temporal time points represented in the volumetric phase-contrast MRI data.

3. The method as set forth in claim 1 , further comprising receiving at least one user input indicative of at least one signal intensity threshold to suppress non-static tissue via application of the first filter.

4. The method as set forth in claim 1 , further comprising generating an average model across all temporal time points for an imaging volume represented in the volumetric phase-contrast MRI data.

5. The method as set forth in claim 4 , wherein generating an average model across all temporal time points includes individually computing a number of parameters of a three-dimensional model at each temporal time point, and computing an average of each of a number of coefficients of the three-dimensional model.

6. The method as set forth in claim 4 , wherein generating an average model across all temporal time points includes computing a number of parameters of a three-dimensional model by fitting a mean phase across all of the temporal time points for each static voxel in the imaging volume represented in the volumetric phase-contrast MRI data.

7. The method as set forth in claim 4 , wherein generating an average model across all temporal time points includes performing a least squares regression using static voxel data across all of the temporal time points represented in the volumetric phase-contrast MRI data.

8. A method of operation in at least one component of a medical imaging system that employs volumetric phase-contrast magnetic resonance imaging (MRI) data, the method comprising:
receiving volumetric phase-contrast MRI data that includes a plurality of voxels;
identifying at least one set of voxels that represent static soft tissue;
generating via at least one computer at least one eddy current related phase offset based on the at least one set of voxels that represent static soft tissue; and
performing a phase error correction based at least in part on the generated at least one eddy current related phase offset,
wherein identifying at least one set of voxels that represent static soft tissue includes:
applying a first filter to the volumetric phase-contrast MRI data, the first filter based on an intensity value of a magnitude associated with the voxels of the volumetric phase-contrast MRI data;
applying a second filter to the volumetric phase-contrast MRI data, application of the second filter which excludes air and lung tissue from the volumetric phase-contrast MRI data; and
applying a third filter to the volumetric phase-contrast MRI data, application of the third filter which excludes blood and other moving tissue from the volumetric phase-contrast MRI data, and

wherein applying a second filter to exclude air and lung tissue includes applying the second filter which is based on a relationship f 1 (m, {right arrow over (v)})=a(m)·b({right arrow over (v)})·[1−c({right arrow over (v)})], where m is magnitude image intensities, {right arrow over (v)} phase (velocity vector field), and a(m) an estimate of a relative likelihood that a given voxel is air or lung based on signal intensity alone.

9. The method as set forth in claim 8 , wherein

a
⁡

(
m
)

=

m
max

-

m
0

m
max

-

m
min

·

(

1
-

p
min

)

+

p
min

is computed based on a signal intensity of the
magnitude image at each location m 0 , and the function

b
⁡

(

v
⇀

)

=

stdev
⁡

(



v
⇀

0



)

mean
⁡

(



v
⇀

0



)

computed based on a velocity at each location.

10. The method as set forth in claim 8 , wherein

c
i

⁡

(

Assignees

• Hsiao Albert
• Vasanawala Shreyas S
• Alley Marcus T
• Univ Leland Stanford Junior

Inventors

• Hsiao Albert
• Vasanawala Shreyas S
• Alley Marcus T

Classifications

• G06T7/13

  Edge detection · CPC title

• G01R33/56518

  due to eddy currents, e.g. caused by switching of the gradient magnetic field · CPC title

• G01R33/56545

  caused by finite or discrete sampling, e.g. Gibbs ringing, truncation artefacts, phase aliasing artefacts · CPC title

• G06T2207/30048

  Heart; Cardiac · CPC title

• A61B5/0263

  using NMR · CPC title