Target site component quantification method, device and magnetic resonance imaging system

Abstract

Embodiments of the present invention disclose a method, apparatus, and magnetic resonance imaging system for quantifying components of a target site. The method comprises: performing an MR scan of the target site using a MOLLI sequence to obtain a T1 map of the target site; calculating the signal intensity of each voxel in the target site at each inversion time based on the T1 value of each voxel in the T1 map of the target site; calculating the signal intensity of each component in the target site at each inversion time based on the T1 value of each component in the target site; and calculating the content of each component in each voxel in the target site based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components in the target site at the same inversion time. Embodiments of the present invention improve the speed and accuracy of quantifying components in the target site.

Description

Technical Field

[0001] The present invention relates to the technical field of MRI (Magnetic Resonance Imaging), and in particular to a method and device for quantitatively determining components of a target site and an MRI system. Background Art

[0002] Many heart diseases lead to fat deposition, fibrosis, and edema within the myocardium. Fat deposition occurs when myocardial cells are replaced by fat cells; fibrosis occurs when myocardial cells are replaced by fibers, leading to an increase in extracellular free water; and edema also leads to an increase in myocardial free water. The proportion of fat deposition, fibrosis, and edema correlates with the severity of disease progression. Therefore, quantification of fat and free water within the myocardium is highly helpful for disease diagnosis and aids in disease risk stratification. The Modified Look-Locker Inversion Recovery (MOLLI) sequence is commonly used to quantify myocardial T1 (longitudinal relaxation time), which is related to myocardial volume. It indirectly reflects changes in fat, free water, and bound water content within the myocardium caused by fat deposition, fibrosis, or edema. Due to the partial volume effect, the longitudinal magnetization recovery process of each voxel is composed of contributions from multiple components, such as bound water, fat, and free water in myocardial cells. Therefore, the T1 value fitted by MOLLI is a mixture of the various components within the voxel.

[0003] Currently, 1H MRS (1H MR spectroscopy) is considered the gold standard for fat and water quantification. Current studies have shown the potential for intramyocardial fat and water quantification using 1H MRS. However, the inevitable motion of the heart during scanning may introduce signals from surrounding tissues that do not belong to the myocardium, resulting in unreliable measurements of myocardial fat content. Furthermore, this method cannot distinguish between free and bound water within a voxel. Furthermore, the use of diaphragm navigation results in relatively long scan times of approximately 2 minutes.

[0004] Currently, other methods have shown their ability to quantify intramyocardial fat, such as two-echo or four-echo DIXON, MRF (Magnetic Resonance Fingerprint), and CMR multitasking. However, these methods have the following limitations:

[0005] First, these methods are generally very sensitive to the inhomogeneity of the B0 field, among which the DIXON and MRF methods are particularly sensitive to motion.

[0006] Second, the current two-echo or four-echo DIXON method is inaccurate in estimating fat content. This is because the DIXON method generally requires more than six echoes to calibrate the quantitative results to accurately quantify fat content. However, the acquisition window duration of ECG trigger (Electro Cardio Gram trigger) cardiac imaging is very short, making it impossible to acquire too many echoes between two R waves of an ECG gate.

[0007] Third, the fat and water images obtained by the DIXON method may contain errors, for example, areas that are actually fat are counted as water, or vice versa. This is caused by the changes in water and fat content and the inhomogeneity of the B0 field.

[0008] Fourth, the spatial resolution of the MRF method is low, which may lead to partial volume effects. The MRF method can obtain T1 / T2 / T2* values ​​and fat fraction in the myocardium simultaneously in a single scan. However, the MRF method requires a long breath-holding time of about 18 seconds, which is a challenge for many patients. At the same time, due to the limited breath-holding time, the spatial resolution is also low, which may lead to partial volume effects. Recently, a free-breathing CMR multitasking method has emerged that can simultaneously achieve T1 / T2 / T2* value and fat fraction mapping of the myocardium. However, its scanning time and image reconstruction time are very long, and, similar to the MRF method, its spatial resolution is limited, which may also lead to partial volume problems. Summary of the Invention

[0009] In view of this, the embodiments of the present invention provide, on the one hand, a method for quantifying components of a target site, and, on the other hand, a device and an MRI system for quantifying components of a target site, so as to improve the speed and accuracy of quantifying components of a target site.

[0010] A method for quantitatively determining components of a target site, comprising:

[0011] The target area is scanned by magnetic resonance imaging (MR) using the improved Locke-Locke inversion recovery (MOLLI) sequence to obtain a longitudinal relaxation time (T1) map of the target area.

[0012] Calculate the signal intensity of each voxel at each inversion time based on the T1 value of each voxel in the T1 map of the target site;

[0013] According to the T1 value of each component at the target site, the signal intensity of each component at the target site at each inversion time is calculated;

[0014] For each voxel of the target site, the content of each component of the voxel is calculated based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of each component of the target site at the same inversion time.

[0015] The calculation of the content of each component of the voxel according to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of each component of the target part at the same inversion time includes:

[0016] Based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target area at the same inversion time, an equation for the signal intensity of the voxel at each inversion time is constructed. The constructed overdetermined equations are solved to obtain the content of each component of the voxel.

[0017] Calculating the signal intensity of each voxel at each inversion time based on the T1 value of each voxel in the T1 map of the target site includes:

[0018] For each voxel of the target site, the signal intensity of the voxel at each inversion time is calculated based on the T1 value of the voxel in the T1 map of the target site and the preset net magnetization intensity;

[0019] Calculating the signal intensity of each component at each inversion time according to the T1 value of each component at the target site includes:

[0020] For each component of the target site, the signal intensity of the component at each inversion time is calculated according to the T1 value of the component and the preset net magnetization intensity.

[0021] Calculating the signal intensity of the voxel at each inversion time based on the T1 value of the voxel in the T1 map of the target site and the preset net magnetization intensity includes:

[0022]

[0023] Calculating the signal intensity of the component at each reversal time based on the T1 value of the component and the preset net magnetization intensity includes:

[0024]

[0025] Among them, S i,j is the signal intensity of the i-th voxel at the target site at the j-th inversion time, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, S k,jis the signal intensity of the kth component of the target site at the jth inversion time, T1 k is the T1 value of the kth component of the target site.

[0026] According to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target part at the same inversion time, an overdetermined set of equations for the signal intensity of the voxel at each inversion time is constructed, including:

[0027] according to

[0028]

[0029] Construct an equation for the signal intensity of the voxel at each inversion time;

[0030] in,

[0031]

[0032]

[0033] S i,j is the signal intensity of the i-th voxel at the target site at the j-th inversion time, 1≤j≤J, J is the total number of inversion times, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, S k,j is the signal intensity of the kth component of the target site at the jth inversion time, 1≤k≤K, K is the total number of component categories in the target site, T1 k is the T1 value of the kth component of the target site, α k is the content of the kth component in the i-th voxel of the target area, 0≤α k ≤1.

[0034] The solving of the constructed overdetermined equations comprises:

[0035] The constructed overdetermined system of equations is solved by using a fitting method, an optimization method based on linear constraints, or a method based on a lookup table.

[0036] The target part is the heart, and the components of the target part are: fat, free water, and bound water.

[0037] A component quantification device for a target site, comprising:

[0038] A T1 map acquisition module is used to perform magnetic resonance MR scanning on the target part using an improved Locke-Locke inversion recovery MOLLI sequence to obtain a longitudinal relaxation time T1 map of the target part;

[0039] a voxel signal intensity calculation module, for calculating the signal intensity of each voxel of the target part at each inversion time according to the T1 value of each voxel in the T1 map of the target part;

[0040] A component signal intensity calculation module is used to calculate the signal intensity of each component at the target site at each inversion time based on the T1 value of each component at the target site;

[0041] The component quantification module is used to calculate the content of each component of each voxel in the target area according to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target area at the same inversion time.

[0042] The component quantification module calculates the content of each component of the voxel according to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target part at the same inversion time, including:

[0043] Based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target area at the same inversion time, an equation for the signal intensity of the voxel at each inversion time is constructed. The constructed overdetermined equations are solved to obtain the content of each component of the voxel.

[0044] The component quantification module calculates the signal intensity of each voxel in the target part at each inversion time according to the T1 value of each voxel in the T1 map of the target part, including:

[0045] For each voxel of the target site, the signal intensity of the voxel at each inversion time is calculated based on the T1 value of the voxel in the T1 map of the target site and the preset net magnetization intensity;

[0046] The component quantification module calculates the signal intensity of each component at the target site at each reversal time based on the T1 value of each component at the target site, including:

[0047] For each component of the target site, the signal intensity of the component at each inversion time is calculated according to the T1 value of the component and the preset net magnetization intensity.

[0048] The component quantification module calculates the signal intensity of the voxel at each inversion time based on the T1 value of the voxel in the T1 map of the target site and the preset net magnetization intensity, including:

[0049]

[0050] The component quantification module calculates the signal intensity of the component at each reversal time according to the T1 value of the component and the preset net magnetization intensity, including:

[0051]

[0052] Among them, S i,j is the signal intensity of the i-th voxel at the target site at the j-th inversion time, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, S k,j is the signal intensity of the kth component of the target site at the jth inversion time, T1 k is the T1 value of the kth component of the target site.

[0053] The component quantification module constructs an equation for the signal intensity of the voxel at each inversion time based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target site at the same inversion time, including:

[0054] according to

[0055]

[0056] Construct an equation for the signal intensity of the voxel at each inversion time;

[0057] in,

[0058]

[0059]

[0060] S i,j is the signal intensity of the i-th voxel at the target site at the j-th inversion time, 1≤j≤J, J is the total number of inversion times, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, S k,j is the signal intensity of the kth component of the target site at the jth inversion time, 1≤k≤K, K is the total number of component categories in the target site, T1 k is the T1 value of the kth component of the target site, α k is the content of the kth component in the i-th voxel of the target area, 0≤α k ≤1.

[0061] The component quantification module solves the constructed overdetermined equations, including:

[0062] The constructed overdetermined system of equations is solved by using a fitting method, an optimization method based on linear constraints, or a method based on a lookup table.

[0063] A magnetic resonance imaging system comprises any one of the above target site component quantification devices.

[0064] In the above embodiment, a T1 map of the target site is obtained by a MOLLI sequence, and then the signal intensity of each voxel of the target site at each inversion time is calculated based on the T1 map, and the signal intensity of each component of the target site at each inversion time is calculated based on the T1 value of each component of the target site. Then, based on the principle that the signal intensity of any voxel at any inversion time is equal to the weighted sum of the signal intensities of each component of the target site at the same inversion time, the content of each component in each voxel is calculated, thereby improving the speed and accuracy of component quantification at the target site. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, so that those skilled in the art will understand the above and other features and advantages of the present invention more clearly. In the accompanying drawings:

[0066] Figure 1 A flow chart of a method for quantifying components of a target site provided by one embodiment of the present invention;

[0067] Figure 2 Schematic diagram of a one-dimensional voxel model consisting of three components A, B, and C;

[0068] Figure 3 Schematic diagram of the signal intensity-inversion time change curves of components A, B, C and voxels 1, 2, and 3;

[0069] Figure 4 is α i =0.2, β i =0.2,γ i =0.6, the signal intensity-inversion time variation curve of voxel i obtained according to formula (10);

[0070] Figure 5 is α i =0.3, β i =0.3,γ i =0.4, the signal intensity-inversion time variation curve of voxel i obtained according to formula (10);

[0071] Figure 6 is α i =0.4, β i =0.2,γ i =0.4, the signal intensity-inversion time variation curve of voxel i obtained according to formula (10);

[0072] Figure 7 This is an example diagram of experimental results of obtaining component contents of myocardium using an embodiment of the present invention;

[0073] Figure 8 This is a schematic diagram of the structure of a component quantification device for a target site provided by an embodiment of the present invention.

[0074] The accompanying drawings are numerals as follows:

[0075]

[0076] DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail with reference to the following examples.

[0078] Figure 1 This is a flow chart of a method for quantifying components of a target site according to one embodiment of the present invention. The specific steps are as follows:

[0079] Step 101: Perform MR scanning on the target part using the MOLLI sequence to obtain a T1 mapping image of the target part.

[0080] Step 102: Calculate the signal intensity of each voxel of the target site at each inversion time based on the T1 value of each voxel in the T1 map of the target site.

[0081] Step 103: Calculate the signal intensity of each component in the target site at each inversion time according to the T1 value of each component in the target site.

[0082] Step 104 : For each voxel of the target site, the content of each component of the voxel is calculated based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of each component of the target site at the same inversion time.

[0083] In the above embodiment, a T1 map of the target site is obtained by using the MOLLI sequence, and then the signal intensity of each voxel of the target site at each inversion time is calculated based on the T1 map, and the signal intensity of each component of the target site at each inversion time is calculated based on the T1 value of each component of the target site. Then, based on the principle that the signal intensity of any voxel at any inversion time is equal to the weighted sum of the signal intensities of each component of the target site at the same inversion time, the content of each component of each voxel is calculated, thereby:

[0084] First, the component quantification of each voxel in the target area is achieved;

[0085] Second, the T1 map obtained by the MOLLI sequence is accurate and robust, thereby improving the accuracy of the content of each component of the target site calculated based on the T1 map;

[0086] 3. Insensitivity to B0 field inhomogeneity and motion. This is because MOLLI uses adiabatic pulses, motion correction, and multiple correction methods, making it insensitive to B0 field inhomogeneity and motion. The embodiments of the present invention perform component quantification of the target area based on the MOLLI sequence, thereby inheriting the advantage of MOLLI's insensitivity to B0 field inhomogeneity and motion.

[0087] Fourth, the time required to acquire a T1 map using the MOLLI sequence is typically less than 10 seconds per layer. Therefore, the target site component quantification method provided by the embodiments of the present invention has a shorter acquisition time and places fewer restrictions on subjects. Furthermore, the embodiments of the present invention calculate the content of each component in a voxel based on the principle that the signal intensity of a voxel at any inversion time is equal to the weighted sum of the signal intensities of each component in the target site at the same inversion time. This allows for faster calculations and shorter reconstruction times.

[0088] 5. Since the embodiment of the present invention utilizes the partial volume effect to simulate the water and fat content, the component quantification result will not be affected by the partial volume effect.

[0089] 6. The embodiment of the present invention can be extended to quantify any number of components in a target area.

[0090] In an optional embodiment, in step 104, the content of each component of the voxel is calculated based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target part at the same inversion time, including: constructing an equation for the signal intensity of the voxel at each inversion time based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target part at the same inversion time, and solving the constructed overdetermined equations to obtain the content of each component of the voxel.

[0091] In an optional embodiment, in step 104, the signal intensity of each voxel in the target region at each inversion time is calculated based on the T1 value of each voxel in the T1 map of the target region, including: for each voxel in the target region, the signal intensity of the voxel at each inversion time is calculated based on the T1 value of the voxel in the T1 map of the target region and a preset net magnetization intensity;

[0092] In step 104, the signal intensity of each component in the target site at each inversion time is calculated based on the T1 value of each component in the target site, including: for each component in the target site, the signal intensity of the component at each inversion time is calculated based on the T1 value of the component and the preset net magnetization intensity.

[0093] In an optional embodiment, in step 104, the signal intensity of the voxel at each inversion time is calculated based on the T1 value of the voxel in the T1 map of the target site and a preset net magnetization intensity, including:

[0094]

[0095] In step 104, the signal intensity of the component at each reversal time is calculated based on the T1 value of the component and the preset net magnetization intensity, including:

[0096]

[0097] Among them, S i,j is the signal intensity of the i-th voxel in the target area at the j-th inversion time, 1≤i≤I, I is the total number of voxels in the target area, 1≤j≤J, J is the total number of inversion times; M0 is the preset net magnetization intensity; TI j is the jth reversal time; T1 i is the T1 value of the i-th voxel of the target area; S k,j is the signal intensity of the kth component of the target site at the jth inversion time, 1≤k≤K, K is the total number of component categories in the target site; T1 k is the T1 value of the kth component of the target site.

[0098] The T1 value of each component can be obtained through experience or experiments.

[0099] In an optional embodiment, in step 104, based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target site at the same inversion time, an equation for the signal intensity of the voxel at each inversion time is constructed, including:

[0100] according to

[0101]

[0102] Construct an equation for the signal intensity of the voxel at each inversion time;

[0103] Among them, S i,j As shown in formula (1), S k,j As shown in formula (2). k is the content of the kth component in the i-th voxel of the target area, 0≤α k ≤1.

[0104] For example, with a step size of 1 ms, and J inversion times of 1 ms, 2 ms, 3 ms, ..., (J-1) ms, and J ms, for the i-th voxel of the target area, a total of J equations are obtained: in, Solving the overdetermined system of equations composed of these J equations, we can get the content α of each component in the voxel k , 1≤k≤K.

[0105] In an optional embodiment, in step 104, solving the constructed overdetermined system of equations includes: solving the constructed overdetermined system of equations using a fitting method, an optimization method based on linear constraints, or a method based on a lookup table.

[0106] In an optional embodiment, the target site is the heart, and the components of the target site are: fat, free water, and bound water.

[0107] In practical applications, the types of components contained in the target site can be determined by experimental measurement or empirical setting.

[0108] Figure 2 Schematic diagram of a 1D voxel model consisting of three components A, B, and C, where 21 is voxel 1, 22 is voxel 2, and 23 is voxel 3.

[0109] The contents of components A, B, and C in voxel 1 are α1, β1, and γ1, respectively;

[0110] The contents of components A, B, and C in voxel 2 are α2, β2, and γ2, respectively;

[0111] The contents of components A, B, and C in voxel 3 are α3, β3, and γ3, respectively;

[0112] Δx is the size of voxels 1, 2, and 3 in the X direction, then:

[0113] The sizes of components A, B, and C in voxel 1 can be expressed as: α1·Δx, β1·Δx, γ1·Δx, respectively. The size of voxel 1 can be expressed as:

[0114] α1·Δx+β1·Δx+γ1·Δx=Δx (4)

[0115] The sizes of components A, B, and C in voxel 2 can be expressed as: α2·Δx, β2·Δx, γ2·Δx, respectively. The size of voxel 2 can be expressed as:

[0116] α2·Δx+β2·Δx+γ2·Δx=Δx (5)

[0117] The sizes of components A, B, and C in voxel 3 can be expressed as: α3·Δx, β3·Δx, γ3·Δx, respectively. The size of voxel 3 can be expressed as:

[0118] α3·Δx+β3·Δx+γ3·Δx=Δx (6)

[0119] Figure 3 Figure 3 is a schematic diagram of the signal intensity-inversion time curves for components A, B, C, and voxels 1, 2, and 3. Curve 31 corresponds to component A, curve 32 corresponds to component B, curve 33 corresponds to component C, curve 34 corresponds to voxel 1, curve 35 corresponds to voxel 2, and curve 36 corresponds to voxel 3. It can be seen that the signal intensities of different components and different voxels at different inversion times are different.

[0120] In the present embodiment, the signal intensity of the components is simulated by T1 values ​​using methods such as the Bloch equation or the extended phase map. To reduce the complexity of the model, a simple exponential model (i.e., formulas (1) and (2)) is used to describe the signal intensity of the components and voxels at different inversion times.

[0121] Partial volume models such as Figure 3 When the point spread effect of image reconstruction is ignored, the signal S of voxel i is i are the signal contributions S from components A, B, and C respectively A,i 、S B,i 、S C,i The sum of , that is:

[0122] S i =S A,i +S B,i +S C,i (7)

[0123] Among them, S A,i 、S B,i 、S C,i Can be expressed as:

[0124]

[0125] S A 、S B 、S C are the signals of components A, B, and C respectively, then:

[0126] S i =α i ·S A +β i ·S B +γ i ·S C (9)

[0127] αi , β i , γ i are the contents of components A, B, and C in voxel i, respectively.

[0128] according to Figure 3 It can be seen that the signal intensity of the same voxel and the same component at different inversion times is different, so formula (9) can be further expressed as:

[0129] S i,j =α i ·S A,j +β i ·S B,j +γ i ·S C,j (10)

[0130] Among them, S i,j is the signal intensity of voxel i at the jth inversion time, α i , β i , γ i are the contents of components A, B, and C in voxel i, respectively, i +β i +γ i =1, S A,j 、S B,j 、S C,j are the signal intensities of components A, B, and C at the jth inversion time, respectively.

[0131] Figure 4 is α i =0.2, β i =0.2,γ i = 0.6, the signal intensity-inversion time variation curve of voxel i is obtained according to formula (10). Among them, 41 is the signal intensity-inversion time variation curve of voxel i, 31, 32, 33 and Figure 3 The same are the signal intensity-reversal time change curves of components A, B, and C, respectively.

[0132] Figure 5 is α i =0.3, β i =0.3,γ i = 0.4, the signal intensity-inversion time variation curve of voxel i is obtained according to formula (10). Among them, 51 is the signal intensity-inversion time variation curve of voxel i, 31, 32, 33 and Figure 3 The same are the signal intensity-reversal time change curves of components A, B, and C, respectively.

[0133] Figure 6 is α i =0.4, β i =0.2,γi = 0.4, the signal intensity-inversion time variation curve of voxel i is obtained according to formula (10). Among them, 61 is the signal intensity-inversion time variation curve of voxel i, 31, 32, 33 and Figure 3 The same are the signal intensity-reversal time change curves of components A, B, and C, respectively.

[0134] It can be seen that α i , β i , γ i Essentially an approximation of the partial volume effects of components A, B, and C.

[0135] Formula (10) gives the case where voxel i contains three components. In practical applications, some voxels may contain two or more components. For example, a certain voxel contains five components: saturated fat, unsaturated fat, deposited iron, bound water, and free water. Considering the universality of formula (10), it is expanded to formula (3).

[0136] Figure 7 This is an example diagram of experimental results of obtaining the component content of myocardium using an embodiment of the present invention.

[0137] Figure a is a T1 map of the body membrane acquired using the MOLLI sequence;

[0138] FIG. b shows the PDFF (Proton Density Fat Fraction) of various regions of the body membrane calculated based on FIG. a and using the method provided by an embodiment of the present invention. The PDFF represented by different grayscales is shown in the color card on the right side of FIG. b.

[0139] Figure c is a T1 map of the volunteer's heart acquired using the MOLLI sequence;

[0140] FIG. d shows the free water fraction (i.e., content) of various regions of the myocardium calculated based on FIG. c and using the method provided by an embodiment of the present invention, wherein the free water fraction represented by different grayscales is shown in the color chart on the right side of FIG. d ;

[0141] Figure e shows the fat fraction (i.e., content) of various myocardial regions calculated based on Figure c and using the method provided by an embodiment of the present invention, wherein the fat fraction represented by different grayscales is shown in the color card on the right side of Figure e;

[0142] FIG. f shows the bound water fraction (i.e., content) of various regions of the myocardium calculated based on FIG. c and using the method provided by an embodiment of the present invention, wherein the bound water fraction represented by different grayscales is shown in the color card on the right side of FIG. f.

[0143] For regions of interest 71-76 in FIG. a, the PDFF of each region of the body membrane calculated according to FIG. a and using the method provided by an embodiment of the present invention, the PDFF obtained using the existing HISTO (high-speed T2-corrected multiecho acquisition at 1H MR spectroscopy) method, and the fat content designed when configuring the body membrane are as follows:

[0144] Region of interest 71: 0.15%, 0.75%, 0%;

[0145] Region of interest 72: 3.82%, 4.76%, 5%;

[0146] Region of interest 73: 16.60%, 14.72%, 25%;

[0147] Region of interest 74: 46.7%, 43.34%, 45%;

[0148] Region of interest 75: 77.46%, 66.63%, 75%;

[0149] Region of interest 76: 91.58%, 92.02%, 100%.

[0150] Figure 8 This is a schematic diagram of the structure of a target site component quantification device 80 provided in an embodiment of the present invention. The device mainly includes: a T1 map acquisition module 81, a voxel signal intensity calculation module 82, a component signal intensity calculation module 83 and a component quantification module 84, wherein:

[0151] The T1 map acquisition module 81 is configured to perform MR scanning on the target part using the MOLLI sequence to obtain the T1 map of the target part, and send the T1 map of the target part to the voxel signal intensity calculation module 82 .

[0152] The voxel signal intensity calculation module 82 is used to calculate the signal intensity of each voxel in the target part at each inversion time based on the T1 value of each voxel in the T1 map of the target part, and send the signal intensity of each voxel in the target part at each inversion time to the component quantification module 84.

[0153] The component signal intensity calculation module 83 is used to calculate the signal intensity of each component in the target site at each inversion time according to the T1 value of each component in the target site, and send the signal intensity of each component in the target site at each inversion time to the component quantification module 84.

[0154] The component quantification module 84 is configured to calculate the content of each component of each voxel in the target area according to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target area at the same inversion time.

[0155] In an optional embodiment, the component quantification module 84 calculates the content of each component of the voxel based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target site at the same inversion time, including: constructing an equation for the signal intensity of the voxel at each inversion time based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target site at the same inversion time, solving the constructed overdetermined equations, and obtaining the content of each component of the voxel.

[0156] In an optional embodiment, the component quantification module 84 calculates the signal intensity of each voxel in the target site at each inversion time based on the T1 value of each voxel in the T1 map of the target site, including: for each voxel in the target site, calculating the signal intensity of the voxel at each inversion time based on the T1 value of the voxel in the T1 map of the target site and a preset net magnetization intensity;

[0157] The component quantification module 84 calculates the signal intensity of each component in the target site at each inversion time based on the T1 value of each component in the target site, including: for each component in the target site, calculating the signal intensity of the component at each inversion time based on the T1 value of the component and the preset net magnetization intensity.

[0158] In an optional embodiment, the component quantification module 84 calculates the signal intensity of the voxel at each inversion time based on the T1 value of the voxel in the T1 map of the target site and the preset net magnetization intensity, including:

[0159]

[0160] The component quantification module 84 calculates the signal intensity of the component at each reversal time based on the T1 value of the component and the preset net magnetization intensity, including:

[0161]

[0162] Among them, S i,j is the signal intensity of the i-th voxel at the target site at the j-th inversion time, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, C k,j is the signal intensity of the kth component of the target site at the jth inversion time, T1k is the T1 value of the kth component of the target site.

[0163] In an optional embodiment, the component quantification module 84 constructs an equation for the signal intensity of the voxel at each inversion time based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target site at the same inversion time, including:

[0164] according to

[0165]

[0166] Construct an equation for the signal intensity of the voxel at each inversion time;

[0167] in,

[0168]

[0169]

[0170] S i,j is the signal intensity of the i-th voxel at the target site at the j-th inversion time, 1≤j≤J, J is the total number of inversion times, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, C k,j is the signal intensity of the kth component of the target site at the jth inversion time, 1≤k≤K, K is the total number of component categories in the target site, T1 k is the T1 value of the kth component of the target site, α k is the content of the kth component in the i-th voxel of the target area, 0≤α k ≤1.

[0171] In an optional embodiment, the component quantification module 84 solves the constructed overdetermined equations, including: solving the constructed overdetermined equations by using a fitting method, an optimization method based on linear constraints, or a lookup table-based method.

[0172] In an optional embodiment, the T1 map acquisition module 81 performs an MR scan on the target part using a MOLLI sequence, including: performing an MR scan on the heart using a MOLLI sequence;

[0173] The component signal intensity calculation module 83 is specifically configured to calculate the signal intensity of the fat, free water, and bound water in the target area at each inversion time based on the T1 values ​​of the fat, free water, and bound water in the target area, and send the signal intensity of the fat, free water, and bound water in the target area at each inversion time to the component quantification module 84;

[0174] The component quantification module 84 is specifically used to calculate the content of fat, free water and bound water in each voxel of the target area based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of fat, free water and bound water in the target area at the same inversion time.

[0175] The embodiment of the present invention further provides a magnetic resonance imaging system, which may include the target site component quantification device 80 provided in the above embodiment.

[0176] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for quantifying components of a target site, characterized in that: include: The target area is scanned by magnetic resonance imaging (MR) using the improved Locke-Locke inversion recovery (MOLLI) sequence to obtain a longitudinal relaxation time (T1) map of the target area. Calculate the signal intensity of each voxel at each inversion time based on the T1 value of each voxel in the T1 map of the target site; According to the T1 value of each component at the target site, the signal intensity of each component at the target site at each inversion time is calculated; For each voxel of the target site, the content of each component of the voxel is calculated based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of each component of the target site at the same inversion time.

2. The method according to claim 1, characterized in that The calculation of the content of each component of the voxel according to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of each component of the target part at the same inversion time includes: Based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target area at the same inversion time, an equation for the signal intensity of the voxel at each inversion time is constructed. The constructed overdetermined equations are solved to obtain the content of each component of the voxel.

3. The method according to claim 1 or 2, characterized in that Calculating the signal intensity of each voxel at each inversion time based on the T1 value of each voxel in the T1 map of the target site includes: For each voxel of the target site, the signal intensity of the voxel at each inversion time is calculated based on the T1 value of the voxel in the T1 map of the target site and the preset net magnetization intensity; Calculating the signal intensity of each component at each inversion time according to the T1 value of each component at the target site includes: For each component of the target site, the signal intensity of the component at each inversion time is calculated according to the T1 value of the component and the preset net magnetization intensity.

4. The method according to claim 3, characterized in that Calculating the signal intensity of the voxel at each inversion time based on the T1 value of the voxel in the T1 map of the target site and the preset net magnetization intensity includes: Calculating the signal intensity of the component at each reversal time based on the T1 value of the component and the preset net magnetization intensity includes: Among them, S i,j is the signal intensity of the i-th voxel at the j-th inversion time of the target site, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, S k,j is the signal intensity of the kth component of the target site at the jth inversion time, T1 k is the T1 value of the kth component of the target site.

5. The method according to claim 2, characterized in that According to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target part at the same inversion time, an overdetermined set of equations for the signal intensity of the voxel at each inversion time is constructed, including: according to Construct an equation for the signal intensity of the voxel at each inversion time; in, S i,j is the signal intensity of the i-th voxel at the target site at the j-th inversion time, 1≤j≤J, J is the total number of inversion times, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, S k,j is the signal intensity of the kth component of the target site at the jth inversion time, 1≤k≤K, K is the total number of component categories in the target site, T1 k is the T1 value of the kth component of the target site, α k is the content of the kth component in the i-th voxel of the target area, 0≤α k ≤1.

6. The method according to claim 2 or 5, characterized in that The solving of the constructed overdetermined equations comprises: The constructed overdetermined system of equations is solved by using a fitting method, an optimization method based on linear constraints, or a method based on a lookup table.

7. The method according to claim 1, characterized in that The target part is the heart, and the components of the target part are: fat, free water, and bound water.

8. A component quantification device (80) for a target site, characterized in that: include: A T1 map acquisition module (81) is used to perform magnetic resonance MR scanning on the target part using an improved Locke-Locke inversion recovery MOLLI sequence to obtain a longitudinal relaxation time T1 map of the target part; a voxel signal intensity calculation module (82), configured to calculate the signal intensity of each voxel of the target part at each inversion time based on the T1 value of each voxel in the T1 map of the target part; a component signal intensity calculation module (83), for calculating the signal intensity of each component at the target site at each inversion time based on the T1 value of each component at the target site; The component quantification module (84) is used to calculate the content of each component of each voxel in the target part according to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target part at the same inversion time.

9. The device (80) according to claim 8, characterized in that The component quantification module (84) calculates the content of each component of the voxel according to the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of each component of the target part at the same inversion time, including: Based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target area at the same inversion time, an equation for the signal intensity of the voxel at each inversion time is constructed. The constructed overdetermined equations are solved to obtain the content of each component of the voxel.

10. The device (80) according to claim 8 or 9, characterized in that The component quantification module (84) calculates the signal intensity of each voxel of the target part at each inversion time according to the T1 value of each voxel in the T1 mapping image of the target part, including: For each voxel of the target site, the signal intensity of the voxel at each inversion time is calculated based on the T1 value of the voxel in the T1 map of the target site and the preset net magnetization intensity; The component quantification module (84) calculates the signal intensity of each component at the target site at each inversion time according to the T1 value of each component at the target site, including: For each component of the target site, the signal intensity of the component at each inversion time is calculated according to the T1 value of the component and the preset net magnetization intensity.

11. The device (80) according to claim 10, characterized in that The component quantification module (84) calculates the signal intensity of the voxel at each inversion time according to the T1 value of the voxel in the T1 mapping image of the target part and the preset net magnetization intensity, including: The component quantification module (84) calculates the signal intensity of the component at each reversal time according to the T1 value of the component and the preset net magnetization intensity, including: Among them, S i,j is the signal intensity of the i-th voxel at the j-th inversion time of the target site, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, S k,j is the signal intensity of the kth component of the target site at the jth inversion time, T1 k is the T1 value of the kth component of the target site.

12. The device (80) according to claim 9, characterized in that The component quantification module (84) constructs an equation for the signal intensity of the voxel at each inversion time based on the principle that the signal intensity of the voxel at any inversion time is equal to the weighted sum of the signal intensities of the components of the target site at the same inversion time, including: according to Construct an equation for the signal intensity of the voxel at each inversion time; in, S i,j is the signal intensity of the i-th voxel at the target site at the j-th inversion time, 1≤j≤J, J is the total number of inversion times, M0 is the preset net magnetization intensity, TI j is the jth reversal time, T1 i is the T1 value of the i-th voxel of the target part, S k,j is the signal intensity of the kth component of the target site at the jth inversion time, 1≤k≤K, K is the total number of component categories in the target site, T1 k is the T1 value of the kth component of the target site, α k is the content of the kth component in the i-th voxel of the target area, 0≤α k ≤1.

13. The device (80) according to claim 9 or 12, characterized in that The component quantification module (84) solves the constructed overdetermined equations, including: The constructed overdetermined system of equations is solved by using a fitting method, an optimization method based on linear constraints, or a method based on a lookup table.

14. A magnetic resonance imaging system, characterized in that: A target site component quantification device (80) comprising any one of claims 8 to 13.

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