CN107121653A - The method that fat presses down water process magnetic resonance spectrum imaging data is pressed down based on frequency domain - Google Patents
The method that fat presses down water process magnetic resonance spectrum imaging data is pressed down based on frequency domain Download PDFInfo
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 49
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000001228 spectrum Methods 0.000 title claims abstract description 12
- 238000003384 imaging method Methods 0.000 title abstract description 4
- 150000002632 lipids Chemical class 0.000 claims abstract description 49
- 230000001629 suppression Effects 0.000 claims abstract description 21
- 238000013139 quantization Methods 0.000 claims abstract description 9
- 239000000178 monomer Substances 0.000 claims abstract description 7
- 239000002207 metabolite Substances 0.000 claims description 30
- 230000005764 inhibitory process Effects 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 13
- 230000002503 metabolic effect Effects 0.000 claims description 5
- 230000003595 spectral effect Effects 0.000 claims description 5
- 238000005070 sampling Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 238000000354 decomposition reaction Methods 0.000 abstract description 3
- 238000001914 filtration Methods 0.000 abstract description 3
- 238000002059 diagnostic imaging Methods 0.000 abstract description 2
- 230000006978 adaptation Effects 0.000 abstract 1
- 229910002114 biscuit porcelain Inorganic materials 0.000 abstract 1
- 239000000126 substance Substances 0.000 description 8
- 125000003473 lipid group Chemical group 0.000 description 6
- 239000011159 matrix material Substances 0.000 description 6
- 230000002401 inhibitory effect Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 150000001875 compounds Chemical class 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 2
- 239000013558 reference substance Substances 0.000 description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 206010028980 Neoplasm Diseases 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
- CZDYPVPMEAXLPK-UHFFFAOYSA-N tetramethylsilane Chemical compound C[Si](C)(C)C CZDYPVPMEAXLPK-UHFFFAOYSA-N 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R33/00—Arrangements or instruments for measuring magnetic variables
- G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
- G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
- G01R33/48—NMR imaging systems
- G01R33/54—Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
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- High Energy & Nuclear Physics (AREA)
- Condensed Matter Physics & Semiconductors (AREA)
- General Physics & Mathematics (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Abstract
The invention provides a kind of magnetic resonance spectrum imaging data frequency domain suppression fat suppression method for treating water, belong to medical imaging field.This method includes：The monomer biscuit porcelain resonance wave time spectrum numeric field data collected is subjected to one-dimensional Fourier transform, frequency domain FID signal is obtained；Four lipid peaks and a water signal frequency range are determined according to priori；Using nonlinear parameter attenuation coefficient in the method estimation wave spectrum Model in Time Domain of singular value decomposition；Spectrum peak frequency and previous quantized obtained attenuation coefficient in priori, linear dimensions amplitude, phase are estimated by amplitude phase automatic adaptation FIR filtering method method；Change frequency range, circulation performs above two steps, until four groups of lipids and water signal parameter quantify to complete；By time domain FID models and lipid and water signal quantization parametric configuration lipid and water time-domain signal；One-dimensional Fourier transform is carried out to time-domain signal, makees poor in frequency domain and original spectroscopic signal, the Magnetic Resonance Spectrum frequency domain data pressed down after fat suppression water process is obtained.
Description
Technical Field
The present invention relates to the field of medical imaging.
Background
The water-suppressing sequence and the lipid-suppressing sequence are generally applied to inhibit in the MRSI data acquisition stage at present, and the inhibition is incomplete in this way, and residual components exist, so that trace metabolites are submerged in the water signal and the lipid signal. With the development of medical research, diseases can be diagnosed and tumors can be graded through information such as the ratio of metabolite content, and lipid and water inhibition through pretreatment in the research cannot meet the requirement.
Disclosure of Invention
The invention mainly aims to provide a method for fat and water suppression based on frequency domain MRSI data, which solves the problem of incomplete water and fat suppression of an acquisition sequence, combines a fat and water suppression process into a quantitative MRSI data processing process, meets the requirements of simultaneous quantification and fat and water suppression, and further can shorten the overall processing time. Therefore, the invention adopts the following technical scheme:
(1) converting the acquired single element MRSI time domain data into a frequency domain FID signal;
(2) selecting an inhibition treatment frequency range of metabolites needing to be inhibited, wherein the metabolites needing to be inhibited are lipid and water;
(3) selecting a suppression processing frequency range of the metabolite to be suppressed from the suppression processing frequency ranges selected in the step (2), and estimating the nonlinear parameter attenuation coefficient d in the FID time domain modelk(ii) a According to fkAnd attenuation coefficient dkEstimating the amplitude a of the linear parameterkPhase phik(ii) a K is the number of the quantitative spectrum peaks, i.e. the number of the metabolic species, ak、φk、dk、fkRespectively the amplitude, phase, attenuation coefficient and frequency of the metabolite to be inhibited;
(4) selecting another inhibition treatment frequency range of the metabolite to be inhibited according to the inhibition treatment frequency range of the metabolite to be inhibited selected in the step (2), and circularly executing the step (3) until the parameter a of the inhibition treatment frequency range of the metabolite to be inhibited selected in the step (2)k、φk、dk、fkThe equalization is completed;
(5) lipid and water parameters a obtained from FID time domain model and steps (3) and (4)k、φk、 dk、fkConstructing lipid and water time domain signals;
(6) converting the lipid and water time domain signals obtained in the step (5), and subtracting the original monomer MRSI signals in a frequency domain to obtain monomer MRSI frequency domain data after lipid and water inhibition treatment;
wherein, the step (1) and the step (2) are not separated in sequence.
Further, the FID time domain model adopts the formula (1)
In the formula, ynIs the n-th numberAccording to the data of the point,as part of a model function, enFor the complex noise portion, N is the number of sampled data points,tnΔ t is the sampling time interval, K is the number of the quantization spectral peaks, i.e. the number of the metabolic species, ak、φk、dk、fkThe amplitude, phase, attenuation coefficient and frequency of the metabolite, respectively.
Further, the transformation in step (1) and step (6) adopts one-dimensional Fourier transform.
Further, in the step (2), the frequency range is 0.2 ppm, the lipid peak 1 is 0.8-1.0 ppm, the lipid peak 2 is 1.2-1.4 ppm, the lipid peak 3 is 1.4-1.6 ppm, the lipid peak 4 is 5.8-6.1 ppm, and the water peak is 4.6-4.8 ppm; in the step (3) and the step (4), f of the lipid peak 1k0.9ppm, lipid peak 2 fk1.3ppm, lipid peak 3 fk1.5ppm, lipid peak 4 fk5.9ppm, water peak fkIt was 4.7 ppm.
Lipid and water are also present as metabolites in human tissue, and most of the lipid and water signals are removed but remain after the collection stage. The invention provides a fat and water inhibiting method based on frequency selection, which can be simultaneously carried out with frequency domain MRSI data parameter quantization processing.
Drawings
FIG. 1 is a flow chart of the present invention.
FIG. 2 is a frequency domain diagram of MRSI raw data
FIG. 3 is a frequency domain data graph before and after the MRSI data fat and water suppression treatment.
FIG. 4 is a frequency domain data diagram of the fat and water suppression processing of MRSI data.
FIG. 5 is a diagram illustrating the suppression effect of the conventional method
Detailed Description
As shown in fig. 1, the present invention provides a method for suppressing fat and water based on frequency-selective magnetic resonance spectrum data, comprising the following steps:
1. converting the acquired single element MRSI time domain data into a frequency domain FID signal by adopting one-dimensional Fourier transform to obtain frequency domain data Yk。
2. Dividing the frequency range of the selected lipid and the frequency range of the water signal.
In the field of magnetic resonance spectroscopy imaging, metabolites are distinguished by applying different chemical shifts of the metabolites. Chemical shifts are represented graphically, with each spectral line or group of spectral lines corresponding to a particular metabolite. In order to make the chemical shifts manifest independently of the field strength, the chemical shifts are usually expressed in relative values in parts per million (ppm):
wherein f isrefFor the resonance frequency of the reference substance, tetramethylsilane is generally selected as the reference substance for the hydrogen resonance spectrum.
Using the results of previous studies, the chemical shift range of metabolites requiring inhibition was divided. From a priori knowledge, the lipid resonance peaks in the MRSI data appear in the form of multiple peaks at 0.9ppm, 1.3ppm, 1.5ppm and 6ppm respectively, and the water peak appears at 4.7 ppm. The frequency range is 0.2 ppm, the lipid peak is 1: 0.8-1.0 ppm, the lipid peak is 2: 1.2-1.4 ppm, the lipid peak is 3: 1.4-1.6 ppm, the lipid peak is 4: 5.8-6.1 ppm, the water peak: 4.6-4.8 ppm.
From a priori knowledge, a portion of the data of interest is selected:
Y＝[YkYk+1... Yk+M](3)
3. the FID time domain model is selected, and in this embodiment, the formula (1) is selected as the FID time domain model, but the method of the present invention is also applicable to other FID time domain models.
Estimating nonlinear parameter attenuation coefficient d in FID time domain model of formula (1)k；
In the formula, ynFor the nth data point data, the data point is,as part of a model function, enFor the complex noise portion, N is the number of sampled data points,tnΔ t is the sampling time interval, K is the number of the quantization spectral peaks, i.e. the number of the metabolic species, ak、φk、dk、fkThe four parameters are respectively the amplitude, the phase, the attenuation coefficient and the frequency of the metabolite, and are closely related to physiological and biochemical information such as the species and the concentration of the compound. f. ofkRepresents the chemical shift of the metabolite, different kinds of metabolites have different chemical shifts, and there is a one-to-one correspondence relationship, and from this parameter, the type of the compound can be judged. a iskThe content of the metabolite is generally judged according to the value of the parameter in direct proportion to the concentration of the metabolite. dkRepresenting the activity of the molecule, in relation to the chemical environment in which the molecule is located, from which parameters the pH profile of the tissue can be judged.
Mathematically, equation (1) can be rewritten as:
wherein,
the quantization method based on frequency selection can be divided into two parts, a nonlinear parameter estimation part and a linear parameter estimation part, as shown in formula (1), and the frequency fkAnd attenuation coefficient dkAs a non-linear parameter, amplitude akAnd phase phikIs a linear parameter.
Estimating nonlinear parameter attenuation coefficient by using the method of Singular Value Decomposition (SVD) on the selected interested data in the step (2)The process is as follows:
the equation can be shown:
here, ,
wherein,
in the formula (5), it is relatively complicated,the parts outside the region of interest are shown, the expression is similar to A, X, the components are noise, and the components are not much related to the implementation of the following algorithm and are not shown in detail. S is a user parameter, M is required to be larger than or equal to n + S, n is the number of quantization components contained in the region of interest, and S is an integer part of M/3 in general.
Definition ofOrthogonal projection on null space for U:
the noise term in equation (5) is much smaller than AX, andwithin the region of interest is much smaller than AX, i.e. the third and fourth terms are negligible, so equation (4) reduces to:
both sides are multiplied simultaneouslyObtaining:
as M is more than or equal to n + S and some additional regularity conditions, the following are obtained:
assuming that S ≧ n, this condition is easily fulfilled, and the following equations (3.27), (3.28):
effrank here refers to the effective rank.
To pairSingular value decomposition is carried out:
wherein W ∈ CS×nByAnd n columns of the left singular vector corresponding to larger n singular values are formed, and T and V are a singular value matrix and a right singular matrix respectively.
According to the formulas (15) and (16):
A≈WP (17)
here, P is a non-singular transformation matrix. From the column space shift invariance of matrix a, one can derive:
A↑＝A↓Z (18)
A↑、A↓respectively, the first row and the last row of the matrix A are deleted, and Z is represented by Z1,…znA diagonal matrix is formed.
Obtained from formulae (17), (18):
Wu≈WlΛ (19)
wherein Λ ═ PZP-1，WlIs the first S-1 line of W, WuThe last S-1 line of W Λ has the same eigenvalue as Z, and therefore the pole of the signal is obtained by equation (18) — from the pole of the signalThen the non-linear parameter d can be obtainedk。
4. According toAnd the attenuation coefficient d obtained by quantization in the step (2)kEstimating the amplitude a of the linear parameterkPhase phikHere, an amplitude phase adaptive FIR filtering (APES) method is applied, which is implemented as follows:
this part is for the linear parameter akAnd phikEstimation, the invention applies a more accurate Amplitude Phase adaptive FIR filtering method (APES), which has been proven to be more accurate in estimating Amplitude and Phase than FFT and Capon methods.
Order to
yq(l)＝[y(l) y(l+1) … y(l+P-1)]Τ,l＝0,1,…,L-1 (20)
Where L is N-P +1, and P is a set parameter, which is not limited in its selection but is an important parameter that may affect the design of the subsequent filter, and the set of the parameter is analyzed in this study to obtain the optimal parameter set.
The coefficient vector of the FIR filter is h (z). To arrive at time domain data ynAfter passing, the components of interest (whose parameters correspond to c and z) are retained, rather than the components of interest being filtered out as much as possible, the transfer function of the filter needs to satisfy the following two conditions:
wherein s (z) ═ 1 z1… zP-1]TThe two conditions are solved as follows:
here, the
Q(z)＝R-G(d)Z(z)Z*(z) (26)
In the above formula, f, d, c and z have the same meanings as in formula (4)) The medium spectrum parameters correspond. Here, the prior knowledge in step (2) is applied for each lipid or water frequency fkFThe linear parameter a of the component of interest is estimated by integrating the equations (22) to (27)kAnd phik。
(5) Changing the lipid frequency range, and circularly executing 3 and 4 steps until the frequency range of the lipid and the frequency range a of the water signal selected in the step (2)k、φk、dkCompleting parameter equalization;
(6) constructing lipid and water time domain signals by using the FID time domain model and the lipid and water signal quantization parameters in the formula (1);
(7) converting the lipid and water time domain signal obtained in the step (6), and subtracting the original monomer MRSI signal from the frequency domain to obtain monomer MRSI frequency domain data after lipid-inhibiting and water-inhibiting treatment;
the processing results of the above examples are shown in fig. 3 and fig. 4, and fig. 1 is a frequency domain graph of the raw collected data, which shows that the lipid signal and the water signal of the non-coincident peak part are completely inhibited by the method of the present invention, such as the lipid peak at 6ppm (-83 Hz). The lipid signals with overlapped parts are also greatly inhibited, such as three lipid peaks at 0.9ppm, 1.3ppm and 1.5ppm (242Hz, 216Hz and 203Hz), although partial residual lipid signals are still treated by the method, and partial residual lipid signals are still treated by the method, which is indicated by arrows in figure 4, but the residual signal values are small, and the research on other metabolites cannot be influenced. Two formants, i.e. two metabolites are included, can be clearly resolved. Fig. 5 shows the results of disturbing signal suppression of MRSI data by the conventional method, which suppresses only water signals but not lipid signals. The comparison shows that the method is more beneficial to inhibiting interference components and is beneficial to observing and analyzing MRSI data.
Claims (4)
1. The method for processing MRSI data based on fat and water suppression in a frequency domain is characterized by comprising the following steps:
(1) converting the acquired single element MRSI time domain data into a frequency domain FID signal;
(2) selecting an inhibition treatment frequency range of metabolites needing to be inhibited, wherein the metabolites needing to be inhibited are lipid and water;
(3) selecting a suppression processing frequency range of the metabolite to be suppressed from the suppression processing frequency ranges selected in the step (2), and estimating a nonlinear parameter attenuation system in the FID time domain modelNumber dk(ii) a According to fkAnd attenuation coefficient dkEstimating the amplitude a of the linear parameterkPhase phik(ii) a K is the number of the quantitative spectrum peaks, i.e. the number of the metabolic species, ak、φk、dk、fkRespectively the amplitude, phase, attenuation coefficient and frequency of the metabolite to be inhibited;
(4) selecting another inhibition treatment frequency range of the metabolite to be inhibited according to the inhibition treatment frequency range of the metabolite to be inhibited selected in the step (2), and circularly executing the step (3) until the parameter a of the inhibition treatment frequency range of the metabolite to be inhibited selected in the step (2)k、φk、dk、fkThe equalization is completed;
(5) lipid and water parameters a obtained from FID time domain model and steps (3) and (4)k、φk、dk、fkConstructing lipid and water time domain signals;
(6) converting the lipid and water time domain signals obtained in the step (5), and subtracting the original monomer MRSI signals in a frequency domain to obtain monomer MRSI frequency domain data after lipid and water inhibition treatment;
wherein, the step (1) and the step (2) are not separated in sequence.
2. The method for fat and water suppression based MRSI data processing based on frequency domain as claimed in claim 1, wherein said FID time domain model adopts formula (1)
<mrow> <msub> <mi>y</mi> <mi>n</mi> </msub> <mo>=</mo> <msub> <mover> <mi>y</mi> <mo>&OverBar;</mo> </mover> <mi>n</mi> </msub> <mo>+</mo> <msub> <mi>e</mi> <mi>n</mi> </msub> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msub> <mi>a</mi> <mi>k</mi> </msub> <msup> <mi>e</mi> <mrow> <msub> <mi>j&phi;</mi> <mi>k</mi> </msub> </mrow> </msup> <msup> <mi>e</mi> <mrow> <mrow> <mo>(</mo> <mrow> <mo>-</mo> <msub> <mi>d</mi> <mi>k</mi> </msub> <mo>+</mo> <mi>j</mi> <mn>2</mn> <msub> <mi>&pi;f</mi> <mi>k</mi> </msub> </mrow> <mo>)</mo> </mrow> <msub> <mi>t</mi> <mi>n</mi> </msub> </mrow> </msup> <mo>+</mo> <msub> <mi>e</mi> <mi>n</mi> </msub> <mo>,</mo> <mi>n</mi> <mo>=</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo>,</mo> <mo>...</mo> <mo>,</mo> <mi>N</mi> <mo>-</mo> <mn>1</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>
In the formula, ynFor the nth data point data, the data point is,as part of a model function, enFor the complex noise portion, N is the number of sampled data points,tnΔ t is the sampling time interval, K is the number of the quantization spectral peaks, i.e. the number of the metabolic species, ak、φk、dk、fkThe amplitude, phase, attenuation coefficient and frequency of the metabolite, respectively.
3. The method for fat and water suppression based MRSI data processing according to claim 1, wherein the transformation in step (1) and step (6) is one-dimensional Fourier transform.
4. The method for treating MRSI based on frequency domain lipid and water suppression as claimed in claim 1, wherein in step (2), the frequency range is 0.2 ppm, the lipid peak 1 is 0.8 to 1.0ppm, the lipid peak 2 is 1.2 to 1.4ppm, the lipid peak 3 is 1.4 to 1.6ppm, the lipid peak 4 is 5.8 to 6.1ppm, and the water peak is 4.6 to 4.8 ppm;
in the step (3) and the step (4), f of the lipid peak 1k0.9ppm, lipid peak 2 fk1.3ppm, lipid peak 3 fk1.5ppm, lipid peak 4 fk5.9ppm, water peak fkIt was 4.7 ppm.
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| CN111460934A (en) * | 2020-03-18 | 2020-07-28 | 深圳市贝斯达医疗股份有限公司 | Method and system for calculating center frequency of superconducting high-field magnetic resonance |
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