IP Library Granted Patent US 10,548,505
Granted Patent B2
US 10,548,505 · App. 15/070,116 · Granted Feb 4, 2020

System and method for real-time MRI-guided object navigation

Inventors: Eva Rothgang (Nürnberg, DE); Arne Hengerer (Möhrendorf, DE); Lars Lauer (Neunkirchen, DE); Jan Fritz (Baltimore, MD); Paul Bottomley (Columbia, MD); Wesley David Gilson (Northbeach, MD); Robert Grimm (Nürnberg, DE)
Assignees: Siemens Healthcare GmbH; The Johns Hopkins University
A61B5/055
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Quick Facts
Patent No.
US 10,548,505
App. No.
15/070,116
Filed
Mar 15, 2016
Granted
Feb 4, 2020
Kind
B2
Art Unit
3793
USPC
600/417
Abstract

A magnetic resonance method and system are provided for magnetic resonance (MR) image-guided insertion of an object into a biological tissue along a predetermined trajectory. The trajectory provides a path between a starting point and a target site within the tissue. Sufficiently high resolution images can be generated in real time to precisely guide the needle placement. A compressed sensing approach is used to generate the images based on minimization of a cost function, where the cost function is based on the predetermined needle path, artifact effects associated with the needle, the negligible changes in the images away from the trajectory, and the limited differences between successive images. The improved combination of spatial and temporal resolution facilitates an insertion procedure that can be continuously adjusted to accurately follow a predetermined trajectory in the tissue, without interruptions to obtain verification images.

Claims (145)

1. A method for directing an object from a starting point to a target site in a biological tissue using real-time magnetic resonance imaging (MRI) guidance, comprising the steps of:

generating a high-resolution planning image of a region of the biological tissue that includes the starting point and the target site;

determining a trajectory from the starting point to the target site using the planning image;

generating and displaying a series of images of the region of the biological tissue and of an artifact based on the position of the object using a compressed sensing technique, wherein the series of images is generated and displayed substantially in real time;

wherein each image of the series of images is generated using a compressed sensing technique based on minimization of a cost function that includes:

a difference between the current image and the corresponding raw image data based on a particular MRI sampling operator;

a difference between the current image and a sum of a baseline image and a predicted artifact; and

a difference between the current image and the most recent image.

2. The method of claim 1 , further comprising:

introducing a distal end of the object into the starting point in a direction substantially corresponding to the direction of the trajectory; and

advancing the object further into the biological tissue along the trajectory toward the target site, wherein a direction of the advancement is based on the displayed series of images.

3. The method of claim 1 , wherein the cost function is denoted as ƒ(x t ) and has the form:

f

(

x

t

)

=

1

2

Ax

t

-

y

2

2

+

λ

1

x

t

-

(

x

ref

+

x

^

Needle

,

t

)

1

+

λ

2

x

t

-

x

t

-

1

1

wherein x t represents the current image being computed at time t, A represents an MRI sampling operator, y represents measured (raw) k-space data, X ref represents a predicted image without the presence of needle artifacts, {circumflex over (x)} Needle,t represents a predicted needle artifact, x t-1 represents the previous image that was computed at time t- 1 , and λ 1 and λ 2 are weighting coefficients.

4. The method of claim 3 , wherein a value for λ 1 is between 0.5 and 1.5.

5. The method of claim 3 , wherein a value for λ 2 is between 0.5 and 1.5.

6. The method of claim 1 , wherein each image of the series of images includes a representation of the trajectory.

7. The method of claim 1 , wherein the series of images is generated at a rate that is between 0.5 and 15 images per second.

8. The method of claim 1 , wherein each image of the series of images has an in-plane resolution that is between 0.5 mm and 2 mm.

9. The method of claim 1 , wherein each image of the series of images is generated using a radial sampling trajectory in k-space.

10. The method of claim 1 , wherein each image of the series of images is generated using a spiral sampling trajectory in k-space.

11. The method of claim 1 , wherein each image of the series of images is generated using a steady-state free precession technique.

12. The method of claim 1 , wherein each image of the series of images is generated using a balanced steady-state free precession technique.

13. An MRI system configured to facilitate directing an object from a starting point to a target site in a biological tissue using real-time magnetic resonance imaging (MRI) guidance, comprising:

a radio frequency (RF) signal generator and a magnetic field gradient generator which are together configured to provide an imaging protocol comprising a plurality of imaging pulse sequences that further comprise a plurality of RF pulse sequences and magnetic field gradient sequences for acquisition of image data; and

an image processing unit configured to generate a series of images based on the image data,

wherein the MRI system is configured to:

generate a high-resolution planning image of a region of the biological tissue that includes the starting point and the target site;

determine a trajectory from the starting point to the target site based on the planning image; and

generate and display the series of images of the region of the biological tissue and of an artifact using a compressed sensing technique, wherein each image is based on a current position of the object, and wherein the series of images is generated and displayed substantially in real time;

wherein each image of the series of images is generated using a compressed sensing technique based on minimization of a cost function that includes:

a difference between the current image and the corresponding raw image data based on a particular MRI sampling operator;

a difference between the current image and a sum of a baseline image and a predicted artifact; and

a difference between the current image and the most recent image.

14. The system of claim 13 , wherein the cost function is denoted as ƒ(x t ) and has the form:

f

(

x

t

)

=

1

2

Ax

t

-

y

2

2

+

λ

1

x

t

-

(

x

ref

+

x

^

Needle

,

t

)

1

+

λ

2

x

t

-

x

t

-

1

1

wherein x t represents the current image being computed at time t, A represents an MRI sampling operator, y represents measured (raw) k-space data, x ref represents a predicted image without the presence of needle artifacts, {circumflex over (x)} Needle,t represents a predicted needle artifact, x t-1 represents the previous image that was computed at time t- 1 , and λ 1 and λ 2 are weighting coefficients.

15. The system of claim 14 , wherein at least one of λ 1 and λ 2 has a value that is between 0.5 and 1.5.

16. The system of claim 13 , wherein each image of the series of images includes a representation of the trajectory.

17. The system of claim 13 , wherein the system is configured to generate the series of images at a rate that is between 0.5 and 15 images per second.

18. The system of claim 13 , wherein the system is configured to generate each image of the series of images with an in-plane resolution that is between 0.5 mm and 2 mm.

19. The system of claim 13 , wherein the system is configured to generate each image of the series of images using at least one of a spiral sampling trajectory or a radial sampling trajectory in k-space.

20. The system of claim 13 , wherein the system is configured to generate each image of the series of images using a steady-state free precession technique.

Assignments (10)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 20, 2023
From: SIEMENS HEALTHCARE GMBH
To: SIEMENS HEALTHINEERS AG
Reel/Frame 066267/0346 →
CONFIRMATORY LICENSE Recorded Dec 17, 2018
From: JOHNS HOPKINS UNIVERSITY
To: NATIONAL INSTITUTES OF HEALTH (NIH), U.S. DEPT. OF HEALTH AND HUMAN SERVICES (DHHS), U.S. GOVERNMENT
Reel/Frame 047928/0220 →
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY NAME AND ADDRESS PREVIOUSLY RECORDED AT REEL: 043482 FRAME: 0539. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT OF RIGHTS . Recorded Jul 9, 2018
From: SIEMENS CORPORATION
To: SIEMENS HEALTHCARE GMBH
Reel/Frame 046507/0026 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 20, 2018
From: FRITZ, JAN; BOTTOMLEY, PAUL
To: THE JOHN HOPKINS UNIVERSITY
Reel/Frame 045283/0542 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 8, 2017
From: SIEMENS AKTIENGESELLSCHAFT
To: SIEMENS HEALTHCARE GMBH
Reel/Frame 044064/0549 →
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY DATA PREVIOUSLY RECORDED ON REEL 038778 FRAME 0020. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Oct 11, 2017
From: ROTHGANG, EVA; HENGERER, ARNE; LAUER, LARS; GRIMM, ROBERT
To: SIEMENS AKTIENGESELLSCHAFT
Reel/Frame 044174/0083 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 5, 2017
From: SIEMENS CORPORATION
To: SIEMENS AKTIENGESELLSCHAFT
Reel/Frame 043482/0539 →
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY DATA PREVIOUSLY RECORDED ON REEL 038760 FRAME 0648. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT OF INVENTOR RIGHTS. Recorded Aug 30, 2017
From: GILSON, WESLEY DAVID
To: SIEMENS CORPORATION
Reel/Frame 043721/0564 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 2, 2016
From: ROTHGANG, EVA; HENGERER, ARNE; LAUER, LARS; GRIMM, ROBERT
To: SIEMENS HEALTHCARE GMBH
Reel/Frame 038778/0020 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 1, 2016
From: GILSON, WESLEY DAVID
To: SIEMENS MEDICAL SOLUTIONS USA, INC.
Reel/Frame 038760/0648 →
Continuity (1)
Related Publication 20170269174A1 · Sep 21, 2017