IP Library Granted Patent US 9,618,593
Granted Patent B2
US 9,618,593 · App. 14/217,517 · Granted Apr 11, 2017

Phase enhanced UTE with improved fat suppression

Inventor: Ravi Teja Seethamraju (Malden, MA)
Assignee: Siemens Healthcare GmbH
G01R33/4816G01R33/50G01R33/5607G01R33/5616
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Quick Facts
Patent No.
US 9,618,593
App. No.
14/217,517
Granted
Apr 11, 2017
Kind
B2
Abstract

A computer-implemented method of performing magnetic resonance imaging with ultra-short echo time pulse sequences includes defining short T2 threshold limits for enhancement. A multi-echo ultra-short echo time response is acquired and a complex dataset is determined based on the multi-echo ultra-short echo time response. A plurality of phase components is identified from the complex dataset, wherein each phase component is associated with a T2 relaxation time within the short T2 threshold limits. A plurality of frequency components is also identified from the complex dataset, wherein each frequency component is associated with the T2 relaxation time within the short T2 threshold limits. Next, a magnitude dataset is derived from the complex dataset and a fitting algorithm is applied to the magnitude dataset to yield a plurality of magnitude components, wherein each magnitude component is associated with the T2 relaxation time within the short T2 threshold limits. A plurality of phase masks are created based on the plurality of phase components and the plurality of frequency components. These phase masks are applied to the magnitude dataset to obtain a combined dataset. Then, an image based on the combined dataset may be presented on a display.

Claims (67)

1. A computer-implemented method of performing magnetic resonance imaging with ultra-short echo time pulse sequences, the method comprising:

defining short T2 threshold limits for enhancement;

acquiring a multi-echo ultra-short echo time response;

determining a complex dataset based on the multi-echo ultra-short echo time response;

identifying a plurality of phase components from the complex dataset, wherein each phase component is associated with a T2 relaxation time within the short T2 threshold limits;

identifying a plurality of frequency components from the complex dataset, wherein each frequency component is associated with the T2 relaxation time within the short T2 threshold limits;

deriving a magnitude dataset from the complex dataset;

applying a fitting algorithm to the magnitude dataset to yield a plurality of magnitude components, wherein each magnitude component is associated with the T2 relaxation time within the short T2 threshold limits;

creating a plurality of phase masks based on the plurality of phase components and the plurality of frequency components;

applying the plurality of phase masks to the magnitude dataset to obtain a combined dataset; and

presenting an image on a display based on the combined dataset.

2. The method of claim 1 , wherein the short T2 threshold limits are defined based on user input.

3. The method of claim 2 , wherein the method further comprises:

identifying a user-selected anatomical area of interest based on user input;

determining an empirical T2 relaxation time associated with the user-selected anatomical area of interest,

wherein the short T2 threshold limits are defined based on the empirical T2 relaxation time.

4. The method of claim 3 , wherein the user-selected anatomical area of interest includes one or more of bone, marrow, or cartilage.

5. The method of claim 1 , wherein the plurality of phase components are identified from the complex dataset according to a process comprising:

identifying a first signal from a first echo in the multi-echo ultra-short echo time response;

identifying a second signal from a later echo in the multi-echo ultra-short echo time response, the later echo following the first echo in the multi-echo ultra-short echo time response;

applying a predetermined weighting value to the second signal, yielding a weighted second signal and

subtracting the weighted second signal from the first signal to identify the plurality of phase components.

6. The method of claim 5 , wherein the later echo immediately follows the first echo in the multi-echo ultra-short echo time response.

7. The method of claim 1 , wherein the fitting algorithm is a biexponential signal decay fitting algorithm utilizing a multivariate constrained nonlinear optimization method.

8. The method of claim 1 , wherein applying the plurality of phase masks to the magnitude dataset to obtain the combined dataset comprises:

determining a number of preferred multiplications; and

multiplying the plurality of phase masks by the magnitude dataset for the number of preferred multiplications to yield the combined dataset.

9. A method for performing phase enhanced UTE with improved fat suppression, the method comprising:

applying a multi-echo gradient echo sequence comprising a first echo set to an ultra-short echo time to an anatomic area of interest;

obtaining a complex data set in response to application of the multi-echo gradient echo sequence;

determining a magnitude data set based on the complex data set;

applying a fitting algorithm to the magnitude data set to obtain a T2* map;

creating a first phase mask based on a first portion of the T2* map comprising first components of the magnitude data set associated with a first echo in the multi-echo gradient echo sequence;

creating a second phase mask based a second portion of the T2* map comprising second components of the magnitude data set associated with a second echo in the multi-echo gradient echo sequence;

determining a suppression mask based on a remaining portion the T2* map which excludes the first portion and the second portion;

applying the suppression mask to the T2* map to remove one or more magnitude values from the T2* map, yielding a filtered T2* map;

determining a weighted combination of the first phase mask and the second phase mask; and

multiplying the filtered T2* map by the weighted combination of the first phase mask and the second phase mask to yield an enhanced image data set.

10. The method of claim 9 , further comprising:

selecting a first species of anatomy for image enhancement; and

selecting a second species of anatomy for image suppression.

11. The method of claim 10 , further comprising:

determining the ultra-short echo time for the first echo set based on the first species of anatomy.

12. The method of claim 10 , wherein the first species of anatomy includes one or more of bone, marrow, or cartilage.

13. The method of claim 10 , wherein the second species of anatomy is selected automatically based on selection of the first species of anatomy.

14. The method of claim 10 , wherein the second species of anatomy comprises fat.

15. The method of claim 9 , further comprising:

presenting an image on a display based on the enhanced image data set.

16. The method of claim 9 , wherein the fitting algorithm is a bi-exponential signal decay fitting algorithm utilizing a multivariate constrained nonlinear optimization method.

17. The method of claim 9 , wherein multiplying the filtered T2* map by the weighted combination of the first phase mask and the second phase mask to yield the enhanced image data set comprises:

determining a number of preferred multiplications; and

multiplying the filtered T2* map by the weighted combination of the first phase mask and the second phase mask for the number of preferred multiplications to yield the enhanced image data set.

18. A system for performing magnetic resonance imaging with ultra-short echo time pulse sequences, the system comprising:

a magnetic resonance imaging device configured to:

apply a multi-echo gradient echo sequence to an anatomic area of interest, and

acquire a multi-echo ultra-short echo time response following application of the multi-echo gradient echo sequence to an anatomic area; and

an image data processor configured to:

define one or more short T2 threshold limits,

determine a complex dataset based on the multi-echo ultra-short echo time response,

identify a plurality of phase components from the complex dataset, wherein each phase component is associated with a T2 relaxation time within the short T2 threshold limits,

create a phase mask based on the plurality of phase components, derive a magnitude dataset based on the complex dataset,

apply a fitting algorithm to the magnitude dataset to yield a plurality of magnitude components, wherein each magnitude component is associated with the T2 relaxation time within the short T2 threshold limits, and

apply the phase mask to the magnitude dataset to obtain a combined dataset.

19. The system of claim 18 , further comprising:

display configured to present an image based on the combined dataset.

20. The system of claim 18 , further comprising:

a user input device configured to select a species of anatomy for image enhancement, wherein the short T2 threshold limits are defined based on the species.

Assignments (4)
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE PREVIOUSLY RECORDED AT REEL: 066088 FRAME: 0256. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Jan 17, 2024
From: SIEMENS HEALTHCARE GMBH
To: SIEMENS HEALTHINEERS AG
Reel/Frame 071178/0246 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 20, 2023
From: SIEMENS HEALTHCARE GMBH
To: SIEMENS HEALTHINEERS AG
Reel/Frame 066088/0256 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 20, 2017
From: SIEMENS MEDICAL SOLUTIONS USA, INC.
To: SIEMENS HEALTHCARE GMBH
Reel/Frame 041292/0663 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 18, 2014
From: SEETHAMRAJU, RAVI TEJA
To: SIEMENS MEDICAL SOLUTIONS USA, INC.
Reel/Frame 032458/0715 →
Continuity (1)
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