US 9,955,924 B2Granted

Magnetic nanoparticle temperature imaging method and magnetic nanoparticle temperature imaging system

AssigneeHuazhong University of Science and Technology

InventorsWenzhong Liu, Shiqiang Pi, Wenping Mao, Jing Zhong, Le He

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Abstract

The present disclosure relates to methods and systems for magnetic nanoparticle temperature imaging. Particularly, the present methods involve applying different combinations of magnetic fields to magnetic nanoparticles placed in a one-dimensional space, collecting AC magnetization signals of the magnetic nanoparticles, and analyzing the collected signals to obtain in vivo temperature information of the one-dimensional space. Different exciting magnetic fields are applied to the magnetic nanoparticles, so that one-dimensional temperature imaging is transformed into single-point temperature measurement of each minizone, and one-dimensional temperature imaging can be precisely and quickly achieved without knowing the concentration distribution of the magnetic nanoparticles.

Claims10

Dependent claims

A method for magnetic nanoparticle temperature imaging, comprising steps of:

(1) positioning magnetic nanoparticles at a one-dimensional space of interest;
(2.1) applying a DC magnetic field Hdc=b and an AC excited magnetic field simultaneously to the one-dimensional space, and
(2.2) collecting a first AC magnetization signal of the magnetic nanoparticles via a data acquisition card, thereby obtaining amplitudes A1, A3 . . . A2j-1 of odd harmonics of the first AC magnetization signal, where a number of harmonics j≥2, and b is amplitude of the DC magnetic field;
(3.1) substituting a combined DC magnetic field
H
dc
′
=
{
b
x
<
x
1
f
⁡
(
x
)
x
1
≤
x
≤
x
1
+
Δ
⁢
⁢
x
-
b
x
>
x
1
+
Δ
⁢
⁢
x
for the DC magnetic field in step (2.1) while keeping the AC excited magnetic field in step (2.1) unchanged, where x represents position, x1 is starting position of a DC gradient magnetic field f(x) in the one-dimensional space, and Δx is width of the DC gradient magnetic field f(x), and
(3.2) collecting a second AC magnetization signal of the magnetic nanoparticles via the data acquisition card, thereby obtaining amplitudes B1, B3 . . . B2j-1 of odd harmonics of the second AC magnetization signal;
(4) calculating variations S1, S3 . . . S2j-1 between the amplitudes B1, B3 . . . B2j-1 of step (3.2) and the amplitudes A1, A3 . . . A2j-1 of step (2.2);
(5) calculating parameter y of an area of [x1, x1+Δx] according to equations between the variations and in-vivo temperature
S
1
=
∑
k
=
1
m
⁢
⁢
c
·
f
1
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
1
⁡
(
y
,
z
)
⁢
❘
z
=
b
⁢
⁢
S
3
=
∑
k
=
1
m
⁢
⁢
c
·
f
3
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
3
⁡
(
y
,
z
)
⁢
❘
z
=
b
⁢
⁢
⋮
⁢
⁢
⋮
⁢
⁢
⋮
S
2
⁢
⁢
j
-
1
=
∑
k
=
1
m
⁢
⁢
c
·
f
2
⁢
⁢
j
-
1
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
2
⁢
⁢
j
-
1
⁡
(
y
,
z
)
⁢
❘
z
=
b
thereby obtaining in-vivo temperature
T
=
M
s
k
0
·
y
of the area of [x1, x1+Δx], where c=NMS, N is concentration of the magnetic nanoparticles, Ms is effective atomic magnetic moment of the magnetic nanoparticles, k0 is Boltzmann's constant, magnetization of the magnetic nanoparticles is described by Langevin's function, c·f2j-1(y,z(rk)) is an amplitude of a (2j−1)th harmonic obtained by finite terms of Taylor series expansion of the Langevin's function, z(rk) is intensity of the DC magnetic field at a kth discrete point rk in the area of [x1, x1+Δx], and m is a number of discrete points in the area of [x1, x1+Δx], and
(6.1) changing the starting position of the DC gradient magnetic field f(x) relative to the one-dimensional space so that the DC gradient magnetic field f(x) with the width of Δx moves to a next area,
(6.2) repeating steps (3.1)˜(5) thereby obtaining in-vivo temperature of the next area until temperature measurement of the whole one-dimensional space is completed.

225 more elements

A system for magnetic nanoparticle temperature imaging, comprising:

a DC magnetic field generating device, operable for applying a DC magnetic field Hdc=b to a one-dimensional space where magnetic nanoparticles are positioned, where b is amplitude of the DC magnetic field;
a combined DC magnetic field generating device, operable for applying a combined DC magnetic field
H
dc
′
=
{
b
x
<
x
1
f
⁡
(
x
)
x
1
≤
x
≤
x
1
+
Δ
⁢
⁢
x
-
b
x
>
x
1
+
Δ
⁢
⁢
x
to the one-dimensional space, where x represents position, x1 is starting position of a DC gradient magnetic field f(x) in the one-dimensional space, and Δx is width of the DC gradient magnetic field f(x);
an AC excited magnetic field generating device, operable for applying an AC excited magnetic field to the one-dimensional space;
a magnetization collecting device, operable for collecting AC magnetization signals of the magnetic nanoparticles positioned at the one-dimensional space;
wherein the magnetization collecting device is a data acquisition card;
and
a processor, operable for processing a first AC magnetization signal collected by applying the DC magnetic field and the AC excited magnetic field simultaneously to the magnetic nanoparticles thereby obtaining amplitudes A1, A3 . . . A2j-1 of odd harmonics of the first AC magnetization signal, processing a second AC magnetization signal collected by applying the combined DC magnetic field and the AC excited magnetic field simultaneously to the magnetic nanoparticles thereby obtaining amplitudes B1, B3 . . . B2j-1 of odd harmonics of the second AC magnetization signal, calculating variations S1, S3 . . . S2j-1 between the amplitudes B1, B3 . . . B2j-1 and the amplitudes A1, A3 . . . A2j-1, and calculating parameter y of an area of [x1, x1+Δx] according to equations between the variations and in vivo temperature
S
1
=
∑
k
=
1
m
⁢
⁢
c
·
f
1
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
1
⁡
(
y
,
z
)
⁢
❘
z
=
b
⁢
⁢
S
3
=
∑
k
=
1
m
⁢
⁢
c
·
f
3
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
3
⁡
(
y
,
z
)
⁢
❘
z
=
b
⁢
⁢
⋮
⁢
⁢
⋮
⁢
⁢
⋮
S
2
⁢
⁢
j
-
1
=
∑
k
=
1
m
⁢
⁢
c
·
f
2
⁢
⁢
j
-
1
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
2
⁢
⁢
j
-
1
⁡
(
y
,
z
)
⁢
❘
z
=
b
thereby obtaining in-vivo temperature
T
=
M
s
k
0
·
y
of the area of [x1, x1+Δx], where c=NMS, N is concentration of the magnetic nanoparticles, Ms is effective atomic magnetic moment of the magnetic nanoparticles, k0 is Boltzmann's constant, magnetization of the magnetic nanoparticles is described by Langevin's function, c·f2j-1(y, z(rk)) is amplitude of a (2j−1)th harmonic obtained by finite terms of Taylor series expansion of the Langevin's function, z(rk) is intensity of the DC magnetic field at a kth discrete point rk in the area of [x1, x1+Δx], m is a number of discrete points in the area of [x1, x1+Δx], and a number of the harmonics j≥2.

223 more elements

A method for magnetic nanoparticle temperature imaging, comprising steps of:

(1) positioning magnetic nanoparticles at a one-dimensional space of interest;
(2.1) applying a DC magnetic field Hdc=b and an AC excited magnetic field simultaneously to the one-dimensional space, and
(2.2) collecting a first AC magnetization signal of the magnetic nanoparticles via a data acquisition card, thereby obtaining amplitudes A1, A3 . . . A2j-1 of odd harmonics of the first AC magnetization signal, where a number of harmonics j≥2, and b is amplitude of the DC magnetic field;
(3.1) substituting a combined DC magnetic field
H
dc
′
=
{
b
x
<
x
1
f
⁡
(
x
)
x
1
≤
x
≤
x
1
+
Δ
⁢
⁢
x
-
b
x
>
x
1
+
Δ
⁢
⁢
x
for the DC magnetic field in step (2.1) while keeping the AC excited magnetic field in step (2.1) unchanged, where x represents position, x1 is starting position of a DC gradient magnetic field f(x) in the one-dimensional space, and Δx is width of the DC gradient magnetic field f(x), wherein the DC gradient field is generated by one or more exciting coils;
and
(3.2) collecting a second AC magnetization signal of the magnetic nanoparticles via the data acquisition card, thereby obtaining amplitudes B1, B3 . . . B2j-1 of odd harmonics of the second AC magnetization signal;
(4) calculating variations S1, S3 . . . S2j-1 between the amplitudes B1, B3 . . . B2j-1 of step (3.2) and the amplitudes A1, A3 . . . A2j-1 of step (2.2);
(5) calculating parameter y of an area of [x1, x1+Δx] according to equations between the variations and in-vivo temperature
S
1
=
∑
k
=
1
m
⁢
⁢
c
·
f
1
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
1
⁡
(
y
,
z
)
⁢
❘
z
=
b
⁢
⁢
S
3
=
∑
k
=
1
m
⁢
⁢
c
·
f
3
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
3
⁡
(
y
,
z
)
⁢
❘
z
=
b
⁢
⁢
⋮
⁢
⁢
⋮
⁢
⁢
⋮
S
2
⁢
⁢
j
-
1
=
∑
k
=
1
m
⁢
⁢
c
·
f
2
⁢
⁢
j
-
1
⁡
(
y
,
z
⁡
(
r
k
)
)
-
∑
k
=
1
m
⁢
⁢
c
·
f
2
⁢
⁢
j
-
1
⁡
(
y
,
z
)
⁢
❘
z
=
b
thereby obtaining in-vivo temperature
T
=
M
s
k
0
·
y
of the area of [x1, x1+Δx], where c=NMS, N is concentration of the magnetic nanoparticles, Ms is effective atomic magnetic moment of the magnetic nanoparticles, k0 is Boltzmann's constant, magnetization of the magnetic nanoparticles is described by Langevin's function, c·f2j-1(y, z(rk)) is an amplitude of a (2j−1)th harmonic obtained by finite terms of Taylor series expansion of the Langevin's function, z(rk) is intensity of the DC magnetic field at a kth discrete point rk in the area of [x1, x1+Δx], and m is a number of discrete points in the area of [x1, x1+Δx];
and
(6.1) changing the starting position of the DC gradient magnetic field f(x) relative to the one-dimensional space via a motor or by changing current of the one or more exciting coils, so that the DC gradient magnetic field f(x) with the width of Δx moves to a next area,
(6.2) repeating steps (3.1)˜(5) thereby obtaining in-vivo temperature of the next area until temperature measurement of the whole one-dimensional space is completed,
(6.3) generating an image reflective of a plurality of positions in the one-dimensional space and corresponding temperature measurement at each of the plurality of positions.

228 more elements

Dependencies are inferred from the claim text.

Facts

Application: 14/431,777Filed 14 Apr 2014
Priority: CN 2014 1 01286591 Apr 2014
Published: US 2016/0296175 A113 Oct 2016
Granted: 1 May 2018
Term ends: Not estimatedThe source records don’t support an estimate.

Classification8 codes

A61B 5/7278
Specific aspects of physiological measurement analysis: artificial waveform generation or derivation, e.g. synthesizing signals from measured signals
A61B 5/01
Measuring for diagnostic purposes ; Identification of persons: measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for…
A61B 5/0515
Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves:…
G01K 7/36
Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using…: using…