CN109256023B - Measuring method of lung airway microstructure model - Google Patents
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- 210000004072 lung Anatomy 0.000 title claims abstract description 45
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- QYSGYZVSCZSLHT-UHFFFAOYSA-N octafluoropropane Chemical compound FC(F)(F)C(F)(F)C(F)(F)F QYSGYZVSCZSLHT-UHFFFAOYSA-N 0.000 claims description 3
- 229960004065 perflutren Drugs 0.000 claims description 3
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Abstract
The invention discloses a measuring method of a lung airway microstructure model, which comprises the steps of collecting inert gas to obtain position information of a lung of an imaging object, sucking the inert gas into the lung by the imaging object to obtain original data of diffusion weighted magnetic resonance undersampling imaging of a multi-diffusion sensitive factor of the imaging object, processing the original data of the diffusion weighted magnetic resonance undersampling imaging of the multi-diffusion sensitive factor of the imaging object according to a nonlinear iterative reconstruction algorithm to obtain a diffusion weighted magnetic resonance imaging measuring signal S of the multi-diffusion sensitive factor of the imaging object, and carrying out nonlinear fitting according to the diffusion weighted magnetic resonance imaging measuring signal S and the multi-diffusion sensitive factor b of the imaging object to obtain a radius R and an outer radius R of an alveolar passageway. The lung airway microstructure model disclosed by the invention is tightly filled in space and conforms to the topological property of a lung microstructure. Multiple microstructure parameters of the lung can be obtained noninvasively, and the lung can be evaluated comprehensively.
Description
Technical Field
The invention relates to the technical field of magnetic resonance imaging, in particular to a measuring method of a lung airway microstructure model. The magnetic resonance imaging device is suitable for the research of lung airway diseases of magnetic resonance imaging with hyperpolarized gas as a contrast agent, such as chronic obstructive pulmonary diseases, asthma, molecular images and the like.
Background
The lung is the main respiratory organ of the human body, and the physiological state of the lung affects the health condition of the human body. The pulmonary imaging examination commonly used in clinic includes chest radiography, CT, nuclear imaging (SPECT, PET), etc., but these methods all have ionizing radiation or radioactivity and are not suitable for frequent examination in a short period. Magnetic Resonance Imaging (MRI) is free of ionizing radiation or radioactivity and is capable of Imaging most tissues and organs of the human body. But the lungs areThe cavity structure, whose water proton density is about 1000 times lower than that of muscle tissue, therefore the lungs are blind in magnetic resonance imaging. In conventional magnetic resonance imaging, according to a phenomenon that nuclear magnetic resonance occurs when an observation nucleus in a sample is excited by a radio frequency pulse (RF pulse) in a magnetic field, a gradient coil is used to spatially encode the sample, and an electronic system is used to receive a magnetic resonance signal generated by the sample, perform frequency spectrum conversion on the magnetic resonance signal, and reconstruct a magnetic resonance image. Conventional MRI is mostly used for H atoms in water or lipids. For inert gas atoms, spin-exchange optical pumping is generally used to make the magnetization vector at non-thermal equilibrium much higher than that at steady state, i.e. the inert gas nuclei acquire higher polarizability, which is called hyperpolarized gas technology. H gas and inert gas have nuclear spin polarization degree of 10 at room temperature-6And the hyperpolarization technology can increase the nuclear spin polarization degree of the inert gas by 4-5 orders of magnitude so as to make up the factor of lower atomic density and realize the hyperpolarization gas magnetic resonance imaging. This makes pulmonary magnetic resonance imaging possible.
The lung is mainly composed of the lung parenchyma and the lung interstitium. The lung parenchyma mainly comprises bronchi and alveoli at all levels, and the topological structure of the lung airway approaches to a two-dimensional structure along with the increase of the bronchi level. Based on the information of lung tissue sections, Weibel and the like propose a lung bronchus model (Weibel model) which considers that a lung acinus is composed of a cylindrical alveolus channel and alveolus wrapped around the alveolus channel, and the model can better explain the change of the lung airway microstructure caused by lung pathological changes. In hyperpolarized gas pulmonary magnetic resonance imaging, diffusion-weighted magnetic resonance imaging (DWI) can be used to characterize pulmonary airway microstructure information. The DWI-based lung airway microstructure model comprises a Q space model, a DKI model, a single chamber model, a cylinder model and the like. The cylinder model is based on a Weibel model and is further developed, and parameters such as the inner diameter, the outer diameter, the average alveolar length, the alveolar surface volume ratio and the like of the pulmonary airway microstructure can be extracted, so that the cylinder model is more applied to research. The model is based on a cylinder, the topological property of the model determines that the space filling rate is not the highest, but the lung airway microstructure is tightly filled, so that a new lung airway microstructure model needs to be developed.
Disclosure of Invention
The invention aims to solve the problems and provides a measuring method of a lung airway microstructure model.
In order to achieve the purpose, the invention adopts the following technical scheme:
a measuring method of a lung airway microstructure model comprises the following steps:
step 1, collecting inert gas, storing the collected inert gas in a gaseous state or a solid state,
step 2, carrying out chest proton MR imaging on the imaging object to obtain the position information of the lung of the imaging object
Step 3, the imaging object inhales inert gas into the lung,
step 4, setting a multiple diffusion sensitive factor b, then performing two-dimensional multiple diffusion sensitive factor diffusion weighted magnetic resonance imaging or three-dimensional multiple diffusion sensitive factor diffusion weighted magnetic resonance imaging based on undersampling on the imaging object according to the position information of the imaging object lung obtained in the step 2 to obtain the original data of the imaging object multiple diffusion sensitive factor diffusion weighted magnetic resonance undersampling imaging,
step 5, processing the original data of the imaging object multi-diffusion sensitive factor diffusion weighted magnetic resonance undersampling imaging obtained in the step 4 according to a nonlinear iterative reconstruction algorithm to obtain a multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging measurement signal S of the imaging object, defining the multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging measurement signal S of the imaging object as S (R, R, b),
step 6, diffusion weighting the multi-diffusion sensitivity factor diffusion weighting magnetic resonance imaging measurement signal S and the multi-diffusion sensitivity factor b of the imaging object obtained in the step 5 according to the function S (R, R, b) ═ exp (-b multiplied by D)T)×(π/(b×Dan))0.5The radius R and the outer radius R of the alveolar channel are obtained by nonlinear fitting, where Dan＝DL-DTCoefficient of lateral diffusion DT＝a1+a2×(r/R)+a3×(r/R)2Longitudinal diffusion coefficient DL＝a4×exp(a5×(1-r/R)a6) A1, a2, a3, a4, a5 and a6 are all real numbers, the multiple diffusion sensitive factor b is a real number, and b is more than or equal to 0.
Step 7, calculating to obtain the alveolar depth h, the alveolar length L, the alveolar surface area Sa, the alveolar volume Va, the alveolar density Na, the alveolar surface volume ratio SVR and the alveolar average linear intercept Lm according to the alveolar internal radius R and the alveolar external radius R obtained in the step 6, wherein,
h＝R-r，
L＝2×R/3，
Sa＝(14×(30.5/9)×R-2r)×L+2×(7×30.5/27×R2-π/6×r2)，
Va＝7×(30.5/27)×R2×L，
Na＝1/Va，
SVR＝Sa/Va，
Lm＝4/SVR。
the inert gas is hyperpolarized as described above13C or hyperpolarisation3He or hyperpolarization83Kr or hyperpolarization129Xe or hyperpolarization131Xe or perfluoropropane or sulfur hexafluoride.
Compared with the prior art, the invention has the following beneficial effects:
1. the lung airway microstructure model is tightly filled in space and conforms to the topological property of lung microstructure.
2. A plurality of microstructure parameters of the lung are obtained noninvasively in a two-dimensional or three-dimensional multi-diffusion sensitive factor diffusion weighting magnetic resonance imaging mode, and comprehensive evaluation on the lung is facilitated.
3. The diffusion weighted magnetic resonance imaging is accelerated by using a compressed sensing mode, and the imaging time is shortened.
Drawings
Fig. 1 is a schematic structural diagram of a pulmonary airway microstructure model. Wherein:
(a) the pulmonary alveolus simplified model is composed of a cylindrical alveolar channel in the middle area and a plurality of pulmonary alveolus wrapped outside the alveolar channel, each pulmonary alveolus is opened towards the alveolar channel, and the pulmonary alveolus is separated by alveolar walls and pulmonary interstitium.
(b) The cross section of a single alveolar channel is in the shape, and the model is formed by closely connecting 6 identical regular hexagonal prisms in an annular shape, wherein R is the inner radius of the alveolar channel, h is the depth of an alveolar, and R is the outer radius of the alveolar channel.
(c) Is the longitudinal cross-sectional shape of a single alveolar channel, where L is the single alveolar length.
FIG. 2 is a schematic diagram of a K-space sampling template for DWI. Wherein:
(a) a K space sampling template for two-dimensional multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging,
(b) the method is a K space sampling template for three-dimensional multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging.
Detailed Description
The present invention will be described in further detail with reference to examples for the purpose of facilitating understanding and practice of the invention by those of ordinary skill in the art, and it is to be understood that the present invention has been described in the illustrative embodiments and is not to be construed as limited thereto.
The utility model provides a pulmonary airway micro-structure model, the same circumference of alveolus passageway includes 6 the same alveolus, and the alveolus is the regular hexagonal prism, and the axial direction of alveolus is parallel with the axial direction of the alveolus passageway of junction, and 6 alveolus of same circumference are the inseparable amalgamation of annular, and one side edge face opening that the alveolus faced alveolus passageway and with alveolus passageway intercommunication.
Defining the radius of an alveolar channel as r; the vertical distance between two opposite lateral edges of each alveolus is the depth of the alveolus, and the depth of the alveolus is defined as h; the length of the alveolus along the axial direction of the alveolus channel is the length of the alveolus, and the length of the alveolus is defined as L; the sum of the alveolar depth h and the radius R of the alveolar channel is defined as the outer radius R.
A measuring method of a lung airway microstructure model comprises the following steps:
step 1, collecting inert gas, and taking the inert gas as a contrast agent. The collected inert gas is stored in a gaseous or solid state, wherein the solid state is sublimed to be gaseous when in use. Inert gases including hyperpolarization13C or hyperpolarisation3He or hyperpolarization83Kr orHyperpolarisation of129Xe or hyperpolarization131Xe, perfluoropropane, sulfur hexafluoride, or the like.
And 2, carrying out chest proton MR imaging on the imaging object to obtain the position information of the lung of the imaging object. Wherein the sequence used for thoracic proton MR imaging is a TSE sequence.
And 3, the imaging object inhales inert gas into the lung. The inhalation method comprises main trachea cannula inhalation, nasal inhalation, oral inhalation and the like.
And 4, setting a multi-diffusion sensitive factor b, and then performing under-sampling-based two-dimensional multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging or three-dimensional multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging on the imaging object according to the position information of the imaging object lung obtained in the step 2 to obtain original data of the imaging object multi-diffusion sensitive factor diffusion weighted magnetic resonance under-sampling imaging.
The method comprises the steps of randomly generating an undersampling track according to a variable density weighting function, wherein the sampling density of a K space central area corresponding to the undersampling track is higher than that of a K space peripheral area corresponding to the undersampling track.
During two-dimensional multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging, variable density random undersampling is carried out in the phase encoding direction, and the expression of a variable density weighting function f (x) is as follows: f (x) ═ 1/((2 × pi)0.5×σ1))×exp(-((x-M/2)2/(σ1×M)2/2)), where σ1M, x are positive real numbers and M is more than or equal to x and more than or equal to 1.
During three-dimensional multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging, variable density random undersampling is carried out in the phase encoding direction and the slice selection encoding direction, and the expression of a variable density weighting function f (x, y) is as follows: f (x, y) ═ 1/(2 × pi × σ1×σ2))×exp(-((x-M/2)2/(σ1×M)2+(y-N/2)2/(σ2×N)2) /2) where σ1≥0，σ2More than or equal to 0, M, N, x and y are positive real numbers, wherein M is more than or equal to x and more than or equal to 1, and N is more than or equal to y and more than or equal to 1.
And 5, processing the original data of the imaging object multi-diffusion sensitive factor diffusion weighted magnetic resonance undersampling imaging obtained in the step 4 according to a nonlinear iterative reconstruction algorithm to obtain a multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging measurement signal S of the imaging object, and defining the multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging measurement signal S of the imaging object as S (R, R, b).
Step 6, diffusion weighting the multi-diffusion sensitivity factor diffusion weighting magnetic resonance imaging measurement signal S and the multi-diffusion sensitivity factor b of the imaging object obtained in the step 5 according to the function S (R, R, b) ═ exp (-b multiplied by D)T)×(π/(b×Dan))0.5The radius R and the outer radius R of the alveolar channel are obtained by nonlinear fitting. Wherein Dan＝DL-DTCoefficient of lateral diffusion DT＝a1+a2×(r/R)+a3×(r/R)2Longitudinal diffusion coefficient DL＝a4×exp(a5×(1-r/R)a6) A1, a2, a3, a4, a5 and a6 are all real numbers, the multiple diffusion sensitive factor b is a real number, and b is more than or equal to 0.
And 7, calculating parameters such as alveolar depth h, alveolar length L, alveolar surface area Sa, alveolar volume Va, alveolar density Na, alveolar surface volume ratio SVR, alveolar average linear intercept Lm and the like according to the alveolar internal radius R and the alveolar external radius R obtained in the step 6. Wherein,
h＝R-r，
L＝2×R/3，
Sa＝(14×(30.5/9)×R-2r)×L+2×(7×30.5/27×R2-π/6×r2)，
Va＝7×(30.5/27)×R2×L，
Na＝1/Va，
SVR＝Sa/Va，
Lm＝4/SVR。
the specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (2)
1. A method for measuring a lung airway microstructure model is characterized by comprising the following steps:
step 1, collecting inert gas, storing the collected inert gas in a gaseous state or a solid state,
step 2, carrying out chest proton MR imaging on the imaging object to obtain the position information of the lung of the imaging object
Step 3, the imaging object inhales inert gas into the lung,
step 4, setting a multiple diffusion sensitive factor b, then performing two-dimensional multiple diffusion sensitive factor diffusion weighted magnetic resonance imaging or three-dimensional multiple diffusion sensitive factor diffusion weighted magnetic resonance imaging based on undersampling on the imaging object according to the position information of the imaging object lung obtained in the step 2 to obtain the original data of the imaging object multiple diffusion sensitive factor diffusion weighted magnetic resonance undersampling imaging,
step 5, processing the original data of the imaging object multi-diffusion sensitive factor diffusion weighted magnetic resonance undersampling imaging obtained in the step 4 according to a nonlinear iterative reconstruction algorithm to obtain a multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging measurement signal S of the imaging object, defining the multi-diffusion sensitive factor diffusion weighted magnetic resonance imaging measurement signal S of the imaging object as S (R, R, b),
step 6, diffusion weighting the multi-diffusion sensitivity factor diffusion weighting magnetic resonance imaging measurement signal S and the multi-diffusion sensitivity factor b of the imaging object obtained in the step 5 according to the function S (R, R, b) = exp (-b multiplied by D)T)×(π/(b×Dan))0.5The radius R and the outer radius R of the alveolar channel are obtained by nonlinear fitting, where Dan=DL-DTCoefficient of lateral diffusion DT= a1+a2×(r/R)+a3×(r/R)2Longitudinal diffusion coefficient DL= a4× exp(a5×(1- r/R)a6) A1, a2, a3, a4, a5 and a6 are all real numbers, the multiple diffusion sensitive factor b is a real number, and b is more than or equal to 0,
further comprising step 7, specifically:
calculating to obtain the depth h of the alveolus, the length L of the alveolus, the surface area Sa of the alveolus, the volume Va of the alveolus, the density Na of the alveolus, the surface volume ratio SVR of the alveolus and the average linear intercept Lm of the alveolus according to the inner radius R of the alveolus and the outer radius R of the alveolus obtained in the step 6, wherein,
h=R-r，
L=2×R/3，
Sa=(14×(30.5/9)×R-2r)×L+2×(7×30.5/27×R2-π/6×r2)，
Va=7×(30.5/27)×R2×L，
Na=1/Va，
SVR=Sa/Va，
Lm=4/SVR。
2. the method of claim 1, wherein the inert gas is hyperpolarized13C or hyperpolarisation3He or hyperpolarization83Kr or hyperpolarization129Xe or hyperpolarization131Xe or perfluoropropane or sulfur hexafluoride.
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