IP Library › Granted Patent US 11,385,311
Granted Patent B2
US 11,385,311 · App. 16/858,848 · Granted Jul 12, 2022

System and method for improved magnetic resonance fingerprinting using inner product space

Inventors: Debra McGivney (Bay Village, OH); Mark A. Griswold (Shaker Heights, OH)
Assignee: Case Western Reserve University
G01R33/4828G01R33/5608G01R33/5614
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Quick Facts
Patent No.
US 11,385,311
App. No.
16/858,848
Granted
Jul 12, 2022
Kind
B2
Abstract

A system and method is provided for improved magnetic resonance fingerprinting (MRF) data dictionary matching using an MRF dictionary having entries with an inner product storing tissue properties.

Claims (151)

1. A method for generating a map of a tissue property in a subject using magnetic resonance fingerprinting (MRF) data, the method comprising:

accessing MRF data formed by acquiring a series of signal evolutions from tissue of a subject in a region of interest while performing an MRF process using a nuclear magnetic resonance (NMR) or magnetic resonance imaging (MRI) system;

accessing an MRF dictionary having entries that are a function of a tissue property vector given by q,d=d(q), wherein a given voxel is represented by q 0 , an acquired MRF signal evolution from the given voxel is given by s=d(q 0 )+e, where s is the MRF signal evolution and e is a noise term;

comparing the MRF data to the MRF dictionary to identify at least one tissue property of the region of interest by comparing inner product values between s and entries in the MRF dictionary; and

generating the map of the at least one tissue property based on the tissue in the region of interest of the subject.

2. The method of claim 1 , wherein identifying the tissue property is achieved upon finding a maximum in absolute value from the comparing of the inner product values between s and entries in the MRF dictionary.

3. The method of claim 1 , wherein the inner product can be approximated as a quadratic function.

4. The method of claim 1 , wherein the signal evolutions are described by:

S

⁢

⁢

E

=

∑

s

=

1

N

S

⁢

∏

i

=

1

N

A

⁢

∑

j

=

1

N

RF

⁢

R

i

⁡

(

α

)

⁢

R

RF

ij

⁡

(

α

,

ϕ

)

⁢

R

⁡

(

G

)

⁢

E

i

⁡

(

T

1

,

T

2

,

D

)

⁢

M

0

where SE is a signal evolution; N S is a number of spins; N A is a number of sequence blocks in a pulse sequence of the MRF process; N RF is a number of RF pulses in a sequence block in the pulse sequence; α is a flip angle in the pulse sequence; ϕ is a phase angle; R i (α) is a rotation due to off resonance; R RF ij (α,ϕ) is a rotation due to RF differences; R(G) is a rotation due to a magnetic field gradient; T 1 is a longitudinal, or spin-lattice, relaxation time; T 2 is a transverse, or spin-spin, relaxation time; D is diffusion relaxation; E i (T 1 ,T 2 ,D) is a signal decay due to relaxation differences; and M 0 is the magnetization in the default or natural alignment to which spins align when placed in a static magnetic field.

5. A magnetic resonance fingerprinting (MRF) system comprising:

a magnet system configured to generate a polarizing magnetic field about at least a portion of a subject;

a magnetic gradient system including a plurality of magnetic gradient coils configured to apply at least one 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 from the subject using a coil array;

a computer system programmed to:

control the magnetic gradient system and the RF system to perform an MRF process to acquire MRF data formed by acquiring a series of signal evolutions from tissue of a subject in a region of interest;

access an MRF dictionary having entries that are a function of a tissue property vector given by q,d=d(q), wherein a given voxel is represented by q 0 , an acquired MRF signal evolution from the given voxel is given by s=d(q 0 )+e, where s is the MRF signal evolution and e is a noise term;

compare the MRF data to the MRF dictionary to identify a tissue property of the region of interest by comparing inner product values between s and each entry in the MRF dictionary; and

generate the map of the tissue property based on the tissue in the region of interest of the subject.

6. The system of claim 5 , wherein identifying the tissue property is achieved upon finding a maximum in absolute value from the comparing of the inner product values between s and entries in the MRF dictionary.

7. The system of claim 5 , wherein the inner product can be approximated as a quadratic function.

8. The system of claim 5 , wherein MRF process includes performing an MRF pulse sequence designed to elicit the series of signal evolutions.

9. The system of claim 8 , wherein the MRF pulse sequence includes a fast imaging with steady-state free precession (FISP) or balanced steady-state free precession (bSSFP) pulse sequence.

10. The system of claim 8 , wherein the signal evolutions are described by:

S

⁢

E

=

∑

s

=

1

N

S

⁢

∏

i

=

1

N

A

⁢

∑

j

=

1

N

RF

⁢

R

i

⁡

(

α

)

⁢

R

RF

ij

⁡

(

α

,

ϕ

)

⁢

R

⁡

(

G

)

⁢

E

i

⁡

(

T

1

,

T

2

,

D

)

⁢

M

0

where SE is a signal evolution; N S is a number of spins; N A is a number of sequence blocks in the pulse sequence; N RF is a number of RF pulses in a sequence block in the pulse sequence; α is a flip angle in the pulse sequence; ϕ is a phase angle; R i (α) is a rotation due to off resonance; R RF ij (α,ϕ) is a rotation due to RF differences; R(G) is a rotation due to a magnetic field gradient; T 1 is a longitudinal, or spin-lattice, relaxation time; T 2 is a transverse, or spin-spin, relaxation time; D is diffusion relaxation; E i (T 1 ,T 2 ,D) is a signal decay due to relaxation differences; and M 0 is the magnetization in the default or natural alignment to which spins align when placed in a static magnetic field.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 9, 2022
From: MCGIVNEY, DEBRA; GRISWOLD, MARK A.
To: CASE WESTERN RESERVE UNIVERSITY
Reel/Frame 059211/0301 →
Continuity (2)
Provisional Application 62838867 · Apr 25, 2019
Related Publication 20200341089A1 · Oct 29, 2020