Method for measuring hepatic venous pressure gradient, measuring system, electronic device and medium

Abstract

The application discloses a kind of hepatic venous pressure gradient measurement method, measurement system, electronic equipment and medium, the measurement method includes: the blood vessel model of liver is constructed;By the way of fluid mechanics, the blood flow of hepatic vein under normal circumstances and the blood flow of hepatic vein under the condition of obstruction are simulated in blood vessel model based on the same preset boundary condition, to calculate the hepatic vein free pressure and hepatic vein wedge pressure at the first preset position of hepatic vein respectively;According to hepatic vein free pressure and hepatic vein wedge pressure obtains hepatic venous pressure gradient.The application can use the calculation of CFD, in the case of non-invasive, based on the liver image of the user to be detected shot, accurately and quickly get accurate virtual hepatic venous pressure gradient, can replace the invasive measurement of hepatic venous pressure gradient, provides accurate data for clinical portal hypertension etc..

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data measurement, in particular to a hepatic venous pressure gradient measurement method, a measurement system, an electronic device and a medium. BACKGROUND

[0002] Portal hypertension, as one of the important manifestations of liver disease syndrome, is asymptomatic in the early stage of the disease, but in the late stage, it will have a series of serious complications such as refractory ascites, portal hypertensive gastropathy, hepatopulmonary syndrome, etc., which greatly reduces the quality of life of patients.

[0003] Hepatic venous pressure gradient (HVPG) can be used as a reference for portal hypertension.

[0004] However, the measurement of HVPG still uses invasive methods at present, by puncturing the probe into the body through the jugular vein, passing through the internal jugular vein, superior vena cava, right atrium, inferior vena cava into the hepatic vein in turn, measuring the free hepatic venous pressure (FHVP) and the wedged hepatic venous pressure (WHVP) respectively, and calculating the difference between the two to obtain HVPG (HVPG=WHVP-FHVP). However, this method as an invasive measurement is not only complicated to operate, but also requires a physician with professional training to implement, and has certain infection risk, etc., and the cost is high, therefore, it is urgent to find a non-invasive alternative method to measure the hepatic venous pressure gradient.

[0005] In recent years, various non-invasive measurement methods have emerged in the field of non-invasive assessment of portal pressure, but each has certain limitations. For example, the HVPG non-invasive measurement based on transient elastography (TE) assesses the degree of cirrhosis associated with hepatic portal hypertension by measuring liver stiffness value, but the results of this method are not reliable for patients with obesity or intercostal space stenosis, etc. Some researchers have found that some serum markers can assist in measurement, such as prothrombin index (PI), aspartate aminotransferase (AST) and alanine amino-transferase (ALT) ratio (AST to ALT ratio, AAR), etc. These methods have a wider range of application, but the accuracy is often lower. SUMMARY

[0006] The technical problem solved by the present application is to provide a measurement method and system for measuring a hepatic vein pressure gradient, which are convenient and have high accuracy, so as to overcome the low accuracy and complex measurement means of the prior art.

[0007] The present application solves the above technical problems by the following technical solutions:

[0008] The present application provides a measurement method for a hepatic vein pressure gradient, which comprises the following steps:

[0009] A blood vessel model of a liver is constructed, which comprises a hepatic vein and a portal vein connected to each other;

[0010] The blood flow of the hepatic vein under normal conditions and the blood flow of the hepatic vein under occlusion conditions are simulated in the blood vessel model based on the same preset boundary conditions by means of fluid mechanics, so as to calculate the hepatic vein free pressure and the hepatic vein wedge pressure at a first preset position of the hepatic vein, respectively.

[0011] The hepatic vein pressure gradient is obtained according to the hepatic vein free pressure and the hepatic vein wedge pressure.

[0012] Preferably, the step of constructing the blood vessel model of the liver specifically comprises the following steps:

[0013] A blood vessel image of the liver is obtained, which comprises a hepatic vein and a portal vein;

[0014] A blood vessel contour is extracted from the blood vessel image;

[0015] The hepatic vein and the portal vein in the blood vessel contour are connected to construct a blood vessel model;

[0016] And / or,

[0017] The preset boundary conditions comprise a velocity boundary condition and a pressure boundary condition, and the measurement method further comprises the following steps:

[0018] The blood flow velocity of blood at the entrance of the hepatic vein is measured, and the blood flow velocity is taken as the velocity boundary condition;

[0019] The pressure boundary condition at the exit of the hepatic vein is preset.

[0020] Preferably, the measurement method specifically comprises at least one of the following steps:

[0021] The step of obtaining the blood vessel image of the liver specifically comprises scanning the liver under a 3T magnetic field using a three-dimensional multiple gradient echo magnetic resonance sequence to obtain the blood vessel image of the liver;

[0022] The step of extracting the blood vessel contour from the blood vessel image specifically comprises: extracting the blood vessel contour in the blood vessel image by a pre-trained deep neural network.

[0023] The step of measuring the blood flow velocity of the blood at the entrance of the hepatic vein specifically comprises: measuring the blood flow velocity at the entrance of the hepatic vein using a phase-contrast gradient echo sequence.

[0024] Preferably, the hepatic vein comprises a main hepatic vein and a plurality of hepatic vein branches connected to the main hepatic vein, and the hepatic portal vein comprises a main hepatic portal vein and a plurality of hepatic portal vein branches connected to the main hepatic portal vein.

[0025] The step of connecting the hepatic vein and the hepatic portal vein in the blood vessel contour to construct a blood vessel model specifically comprises:

[0026] The hepatic vein branches are connected to the corresponding hepatic portal vein branches.

[0027] Preferably, the step of connecting the hepatic vein branches to the corresponding hepatic portal vein branches specifically comprises the steps of:

[0028] When the included angle between the hepatic vein branch to be connected and the corresponding hepatic portal vein branch is greater than a first preset angle, the hepatic vein branch is extended along the blood vessel direction to the corresponding hepatic portal vein branch, and the corresponding hepatic portal vein branch is extended along the blood vessel direction to the hepatic vein branch to connect the hepatic vein branch to the corresponding hepatic portal vein branch.

[0029] When the included angle between the hepatic vein branch to be connected and the corresponding hepatic portal vein branch is less than the first preset angle, after the hepatic vein branch is extended along the blood vessel direction to the corresponding hepatic portal vein branch, and the corresponding hepatic portal vein branch is extended along the blood vessel direction to the hepatic vein branch to connect the hepatic vein branch to the corresponding hepatic portal vein branch, the connection is taken as a new blood vessel port, and the corresponding hepatic vein branch or the corresponding hepatic portal vein branch is connected.

[0030] Preferably, after the step of connecting the hepatic vein branches to the corresponding hepatic portal vein branches, the method further comprises the steps of:

[0031] The connected blood vessels are smoothed.

[0032] Preferably, the steps of respectively simulating the blood flow in the hepatic vein under normal conditions and the blood flow in the hepatic vein under a blocked condition specifically comprise:

[0033] The zero point and the first measured blood flow velocity in the hepatic vein under normal conditions are connected by a smoothing function, and the blood flow in the hepatic vein under normal conditions is simulated.

[0034] connecting a zero point with the first measured blood flow velocity of the hepatic vein under the occlusion condition by a smoothing function, and simulating blood flow in the hepatic vein under the occlusion condition.

[0035] The application further provides a hepatic vein pressure gradient measurement system, comprising a model construction module, a pressure calculation module and a pressure gradient acquisition module.

[0036] The model construction module is configured to construct a blood vessel model of the liver, wherein the blood vessel model comprises the hepatic vein and the hepatic portal vein connected with each other.

[0037] The pressure calculation module is configured to simulate blood flow in the hepatic vein under a normal condition and blood flow in the hepatic vein under an occlusion condition in the blood vessel model based on the same preset boundary condition by fluid mechanics, so as to calculate the hepatic vein free pressure and the hepatic vein wedge pressure at the first preset position of the hepatic vein, respectively.

[0038] The pressure gradient acquisition module is configured to acquire the hepatic vein pressure gradient according to the hepatic vein free pressure and the hepatic vein wedge pressure.

[0039] Preferably, the model construction module is specifically configured to acquire a blood vessel image of the liver, wherein the blood vessel image comprises the hepatic vein and the hepatic portal vein.

[0040] The blood vessel contour is extracted from the blood vessel image.

[0041] The hepatic vein and the hepatic portal vein in the blood vessel contour are connected to construct the blood vessel model.

[0042] And / or,

[0043] The preset boundary condition comprises a velocity boundary condition and a pressure boundary condition, and the measurement system further comprises a boundary setting module configured to measure the blood flow velocity of blood at the entrance of the hepatic vein and take the blood flow velocity as the velocity boundary condition, and preset the pressure boundary condition at the exit of the hepatic vein.

[0044] Preferably, the model construction module is specifically configured to scan the liver under a 3T magnetic field by using a three-dimensional multiple gradient echo magnetic resonance sequence to acquire the blood vessel image of the liver.

[0045] Preferably, the model construction module is specifically configured to extract the blood vessel contour in the blood vessel image by using a pre-trained deep neural network.

[0046] Preferably, the boundary setting module is specifically configured to measure the blood flow velocity at the entrance of the hepatic vein by using a phase-contrast gradient echo sequence.

[0047] Preferably, the hepatic vein includes a main hepatic vein trunk and a plurality of hepatic vein branches connected to the main hepatic vein trunk, and the portal vein includes a main hepatic portal vein trunk and a plurality of portal vein branches connected to the main hepatic portal vein trunk;

[0048] The model building module is specifically used to connect the hepatic vein branches with the corresponding portal vein branches.

[0049] Preferably, the model construction module is specifically configured to, when an angle between a hepatic vein branch to be connected and a corresponding portal vein branch is greater than a first preset angle, extend the hepatic vein branch along the blood vessel direction toward the corresponding portal vein branch, and extend the corresponding portal vein branch along the blood vessel direction toward the hepatic vein branch so as to connect the hepatic vein branch with the corresponding portal vein branch;

[0050] When the angle between the hepatic vein branch to be connected and the corresponding portal vein branch is less than a first preset angle, the hepatic vein branch is extended along the blood vessel direction toward the corresponding portal vein branch, and the corresponding portal vein branch is extended along the blood vessel direction toward the hepatic vein branch to connect the hepatic vein branch with the corresponding portal vein branch, and the connection point is used as a new blood vessel port to connect to the corresponding hepatic vein branch or the corresponding portal vein branch.

[0051] Preferably, the model building module is further configured to connect the hepatic vein branch with the corresponding portal vein branch and then perform smoothing on the connected blood vessels.

[0052] Preferably, the pressure calculation module is specifically used to connect the zero point and the first measured blood flow velocity of the simulated hepatic vein under normal conditions through a smooth function, and simulate the blood flow in the hepatic vein under normal conditions;

[0053] A zero point and a first measured blood flow velocity of the simulated hepatic vein under occlusion are connected by a smoothing function, and the blood flow in the hepatic vein under the occlusion condition is simulated.

[0054] The present invention also provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-described method for measuring the hepatic venous pressure gradient when executing the computer program.

[0055] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the above-mentioned method for measuring the hepatic venous pressure gradient.

[0056] The positive progress effect of the present application is that: the present application can use the calculation of CFD (Computational Fluid Dynamics), based on the photographed liver image of the to-be-detected user, obtain the accurate virtual hepatic vein pressure gradient in a non-invasive manner, can replace the invasive measurement of the hepatic vein pressure gradient, provide auxiliary diagnosis basis for clinical portal hypertension, etc., is beneficial to timely find the disease in the early stage of various liver diseases, and treat as early as possible. Further, the present application uses one-stop MRI (based on nuclear magnetic resonance imaging) measurement, facilitates the measurement process, and simplifies the measurement steps. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 The flowchart of the measurement method of the hepatic vein pressure gradient in embodiment 1 of the present application.

[0058] Figure 2 The flowchart of the specific implementation mode of step 101 in embodiment 1.

[0059] Figure 3 The schematic diagram of the whole processing process of the measurement method in embodiment 1.

[0060] Figures 4-7 The schematic diagram of the photographed blood vessel image in embodiment 1.

[0061] Figure 8 The schematic diagram of the extracted hepatic vein in embodiment 1.

[0062] Figure 9 The schematic diagram of the extracted portal vein in embodiment 1.

[0063] Figure 10 The schematic diagram of the connection between the hepatic vein and the portal vein in embodiment 1.

[0064] Figure 11 The schematic diagram of the blood vessel contour in embodiment 1.

[0065] Figure 12 The schematic diagram of the data of the blood flow velocity at the entrance of the hepatic vein in embodiment 1.

[0066] Figure 13 The schematic diagram of the smoothing function of the connection between the zero point and the first velocity measurement data in embodiment 1.

[0067] Figure 14 The schematic diagram of the blood flow velocity periodic function in embodiment 1.

[0068] Figure 15 The schematic diagram of the blood vessel contour of the marked partial region in embodiment 1.

[0069] Figure 16 The schematic diagram of the blood pressure data after the partial region is enlarged.

[0070] Figure 17 a schematic diagram of pressure distribution of blood flow of a first user in a normal state.

[0071] Figure 18 a schematic diagram of pressure distribution of blood flow of the first user after occlusion of the hepatic vein.

[0072] Figure 19 a schematic diagram of pressure distribution of blood flow of a second user in a normal state.

[0073] Figure 20 a schematic diagram of pressure distribution of blood flow of the second user after occlusion of the hepatic vein.

[0074] Figure 21 a schematic diagram of four head-to-tail vHVPG versus time periodic functions of a final measurement.

[0075] Figure 22 a schematic diagram of a module of a measurement system of the hepatic vein pressure gradient in Embodiment 2.

[0076] Figure 23 a schematic diagram of a module of the electronic device of Embodiment 3. DETAILED DESCRIPTION

[0077] The present application is further illustrated by the following embodiments, but the present application is not limited in the scope of the embodiments.

[0078] Embodiment 1

[0079] This embodiment provides a measurement method of the hepatic vein pressure gradient, as shown in the following. Figure 1 The measurement method comprises the following steps:

[0080] Step 101, constructing a blood vessel model of the liver.

[0081] The blood vessel model comprises the hepatic vein and the hepatic portal vein connected with each other.

[0082] The constructed blood vessel model of the liver is a blood vessel model of the liver of a user to be tested, and the specific construction method can be selected according to actual needs.

[0083] In a specific embodiment, as shown in the following, step 101 can specifically construct the blood vessel model by the following steps: Figure 2

[0084] Step 1011, acquiring a blood vessel image of the liver.

[0085] ​In this embodiment, a three-dimensional multiple gradient echo magnetic resonance sequence is specifically used to scan the liver under a 3T magnetic field, so that a clear image of the main blood vessels of the liver can be obtained, wherein the main blood vessels of the liver include the hepatic vein and the portal vein, and more specifically, the hepatic vein includes the main stem of the hepatic vein and a plurality of hepatic vein branches connected thereto, and the portal vein includes the main stem of the portal vein and a plurality of portal vein branches connected thereto.

[0086] It should be understood that in other embodiments, other ways can also be selected according to actual needs to obtain the blood vessel contour image of the liver.

[0087] Step 1012, extracting the blood vessel contour from the blood vessel image.

[0088] In this embodiment, the blood vessel contour in the blood vessel image is automatically extracted by a pre-trained deep neural network, wherein the neural network model is a model specially trained for extracting the blood vessel contour, and the specific model training method can be obtained according to the prior art, and this embodiment does not limit this.

[0089] Step 1013, connecting the hepatic vein and the portal vein in the blood vessel contour to construct a blood vessel model.

[0090] In this embodiment, the hepatic vein branches and the corresponding portal vein branches are connected, so that a more realistic connection of the liver blood vessels can be simulated, and it should be understood that in other embodiments, the main stem of the hepatic vein and the main stem of the portal vein can also be directly connected.

[0091] In this embodiment, the blood vessel connection in step 1013 can be performed in the following manner:

[0092] When the included angle between the hepatic vein branch to be connected and the corresponding portal vein branch is greater than the first preset angle, the hepatic vein branch is extended along the blood vessel direction to the corresponding portal vein branch, and the corresponding portal vein branch is extended along the blood vessel direction to the hepatic vein branch to connect the hepatic vein branch and the corresponding portal vein branch;

[0093] When the included angle between the hepatic vein branch to be connected and the corresponding portal vein branch is less than the first preset angle, after the hepatic vein branch is extended along the blood vessel direction to the corresponding portal vein branch, and the corresponding portal vein branch is extended along the blood vessel direction to the hepatic vein branch to connect the hepatic vein branch and the corresponding portal vein branch, the connection is taken as a new blood vessel port, and the corresponding hepatic vein branch or the corresponding portal vein branch is connected.

[0094] It should be understood that in the actually acquired blood vessel image, there are some capillaries between the hepatic portal vein branches and the hepatic vein branches, which are relatively thin and difficult to accurately shoot clearly. The connection relationship between these capillaries in the blood vessel contour extracted based on the blood vessel image may not be clear. Therefore, in order to simulate the connection relationship between the real blood vessels, in the embodiment, different connection relationships are simulated according to the different angles between the hepatic vein branches and the hepatic portal vein branches, so that the connection between the blood vessels is more in line with the complex blood vessel connection relationship in the real situation, and the finally calculated data is more accurate.

[0095] It should be understood that the first preset angle can be selected according to actual conditions.

[0096] Further, after connecting the blood vessels, the embodiment can further include the step of: performing smoothing processing on the connected blood vessels, such as repairing defects such as eyelets, so that the surface triangular mesh can be uniformly operated (because the triangular mesh in the extracted blood vessel contour is of different sizes), and then a volume network with tetrahedron as a segmentation unit is established according to the surface mesh, to facilitate subsequent pressure calculation.

[0097] In step 102, the blood flow of the hepatic vein under normal conditions and the blood flow of the hepatic vein under occlusion conditions are simulated in the blood vessel model based on the same preset boundary conditions by means of fluid mechanics, so as to calculate the hepatic vein free pressure and the hepatic vein wedge pressure at the first preset position of the hepatic vein, respectively.

[0098] In the embodiment, the preset boundary conditions specifically include a velocity boundary condition and a pressure boundary condition. Specifically, in the embodiment, the blood vessel model reconstructed by the surface network and the volume network is taken as a calculation domain, the Navier-Stokes equation is used, it is assumed that the blood is an incompressible Newtonian fluid, the boundary is set to be non-slip, the velocity boundary condition of the blood flow velocity is set at the entrance of the hepatic portal vein, and the pressure boundary condition is set at the outlet of the hepatic vein.

[0099] Under the foregoing preset conditions, the blood flow process of the blood in the blood vessels of the liver under normal conditions is simulated based on the blood model, and the hepatic vein free pressure is calculated at the first preset position of the hepatic vein.

[0100] Similarly, under the foregoing preset conditions, a small section of the simulated blood vessel is cut off above the first preset position, and then the two ends are completely closed respectively, so that the branch blood vessel is completely occluded to simulate the blood flow process of the hepatic vein under occlusion conditions, and the hepatic vein wedge pressure is calculated at the first preset position of the hepatic vein.

[0101] In the embodiment, the velocity boundary condition can be calculated by the following method:

[0102] The blood flow velocity at the entrance of the hepatic vein is measured, and the blood flow velocity is taken as a velocity boundary condition.

[0103] Specifically, the blood flow velocity at the entrance of the hepatic vein can be measured based on the blood vessel image of the liver obtained in step 1011 using a phase-contrast gradient echo sequence (PC GRE), and after a skilled radiology technician manually labels a blood vessel cross-sectional region, all cardiac cycles within a sampling time are counted to obtain an average velocity at several equally spaced times within a cycle, and the average velocity is taken as a velocity boundary condition.

[0104] In this embodiment, the pressure boundary condition is a preset value, and the specific preset value can be selected according to the actual pressure boundary condition.

[0105] In a specific implementation, during simulation of blood flow, the zero point and the first measured blood flow velocity of the simulated hepatic vein under normal conditions can be connected by a smoothing function, and specifically, the zero point and the first measured blood flow velocity of the simulated hepatic vein under normal conditions can be connected by a smoothing function, and blood flow in the hepatic vein under normal conditions is simulated; the zero point and the first measured blood flow velocity of the simulated hepatic vein under occlusion conditions are connected by a smoothing function, and blood flow in the hepatic vein under occlusion conditions is simulated. By means of the smoothing function, fast convergence of calculation can be ensured, thereby improving the accuracy of the calculation results while improving the calculation efficiency.

[0106] Step 103, obtaining the hepatic vein pressure gradient according to the hepatic vein free pressure and the hepatic vein wedge pressure.

[0107] Specifically, the hepatic vein pressure gradient is the difference between the hepatic vein wedge pressure and the hepatic vein free pressure.

[0108] In this embodiment, using one-stop MRI measurement combined with CFD calculation, accurate virtual hepatic vein pressure gradient can be obtained conveniently and quickly without trauma, which can replace the invasive measurement of the hepatic vein pressure gradient, provide auxiliary diagnostic basis for clinical portal hypertension, and is beneficial to timely detection of diseases in the early stage of various liver diseases and early treatment.

[0109] In order to better understand this embodiment, the following will describe this embodiment through a specific example:

[0110] Figure 3 Fig. 1 shows a schematic diagram of the overall processing process of this embodiment, Figures 4-21 Fig. 2 is a schematic diagram of the decomposition of each process.

[0111] First, based on the conventional liver nuclear magnetic resonance scanning, 3T magnetic field is used, and the imaging parameters are as follows: time of repetition (TR) = 3.4 ms, time of echo (TE) = 0.95 ms, field of view (FOV) = 350*350*120 mm 3 , flip angle (FA) = 10°, spatial resolution = 0.87*0.87*2.0 mm 3 , parallel imaging acceleration factor = 2, and scanning time = 12.5 ms. Clear images of main blood vessels of the liver are obtained in the dicom format. Figures 4 to 7 The blood vessel images of the liver taken by different shooting parameters are shown, wherein the brighter area is the blood vessel.

[0112] The measurement of blood flow velocity at the entrance of the hepatic vein uses a phase-contrast gradient echo sequence (PC GRE), and the start and end of the measurement are automatically controlled by the heart and breathing gates under the free breathing of the subject. The measurement parameters are as follows: time of repetition (TR) = 2.9 ms, time of echo (TE) = 1.45 ms, field of view (FOV) = 300*300 3 , flip angle (FA) = 6°, spatial resolution = 0.87*0.87*2.0 mm 3 , parallel imaging acceleration factor = 2, and encoding velocity = 40 cm / s. The sampling time depends on the heart rate of the subject, and is generally about 2.5 min. The blood flow velocity is measured on the cross section of the hepatic vein using a flow velocity encoding gradient echo sequence, and the measured velocity data are shown in Figure 12 , wherein the abscissa represents time, and the ordinate represents velocity.

[0113] The blood vessel contour is extracted from the original dicom format image using a pre-trained deep neural network. The blood flow velocity information is manually labeled by an experienced radiology technician on the cross section area of the blood vessel (as shown in Figure 5 , Figure 7 , the area marked by a black circle on the brighter area), and the average value of several cardiac cycles is taken to obtain the velocity value of 30 equally spaced sampling times in a cycle.

[0114] After the geometric morphology of the main branches of the hepatic vein and the portal vein is extracted, the two parts of the blood vessels are connected by a fully automatic method, Figure 8 The extracted schematic diagram of the hepatic vein is shown, which includes the main trunk of the hepatic vein and several branches connected thereto, Figure 9The extracted hepatic portal vein diagram is shown, and similarly, the hepatic portal vein also includes the hepatic portal vein trunk and several branches connected thereto.

[0115] Specifically, Figure 10 The connection process of the hepatic vein and the hepatic portal vein is shown, wherein a, b, and c show a one-to-one connection diagram, and d, e, and f show a one-to-many connection diagram.

[0116] In this embodiment, the size of the included angle θ between the normal vectors of the hepatic portal vein branch to be connected and the hepatic vein branch is used as a selection criterion for one-to-one connection or one-to-many connection. Specifically, if the angle is greater than 90°, a one-to-one connection is used, and the end points on both sides are translated along the respective normal vectors v1, v2 by half the distance |P1P3| / 2 to obtain points P'1, P3', and then the midpoint P of the two translated points is obtained. c Then, interpolation is performed between the end points of the two end vessels and the midpoint, so that the two vessels are extended and grown with the midpoint as the central axis and the original radius maintained, and the two ends are finally converged and then the interface is smoothed. If the included angle is less than 90°, a one-to-many connection is used, that is, after the same connection operation according to the above rules, the connection is used as a new port to participate in the connection of other vessels. Finally, a file format stl (Stereolithography) is obtained.

[0117] The liver blood vessel network obtained by automatic connection is further smoothed to repair defects such as holes, and the surface triangular mesh is uniformly operated, and then a volume network with tetrahedron as the segmentation unit is established according to the surface mesh. For the outline of the blood vessel after connection and meshing, please refer to Figure 11 .

[0118] The blood vessel model reconstructed by the surface network and the volume network is used as the calculation domain, the Navier-Stokes equation is used, the blood is assumed to be an incompressible Newtonian fluid, the boundary is set to be non-slip, and the blood flow velocity obtained above is used as the boundary condition at the entrance of the hepatic portal vein. Details are shown in Figure 13 In the initial 100 ms, the zero point and the first real blood flow velocity at 100 ms are smoothed to ensure faster convergence of the calculation; the blood flow velocity function is interpolated using a cubic spline function to ensure smooth changes in velocity; and to ensure that the fluid in the calculation result is already flowing stably and fully developed, the original blood flow period is extended to obtain four blood flow period functions connected in a loop. Figure 14A line graph showing the blood flow velocity as a function of time is shown, wherein the abscissa represents time and the ordinate represents velocity. The pressure boundary condition is set at the outlet of the hepatic vein, and the simulation proves that the specific value of the pressure does not affect the final hepatic vein pressure gradient. In order to make the absolute pressure in the simulation close to the actual measured value, the value of the preset pressure boundary condition is 7.5 mmHg (millimeters of mercury).

[0119] The three-dimensional Navier-Stokes equation used in the present application can be expressed as:

[0120]

[0121] Wherein ρ is the density of blood flow, u is the velocity of blood flow, p is the pressure of blood flow, μ is the dynamic viscosity, and F is the volume force of blood flow, which is set to 0 here.

[0122] The physical parameters of blood are set as follows: density = 1050 kg / m 3 , dynamic viscosity μ = 0.005 Pa·s (pascal per second), wherein, in order to facilitate calculation, the gravity of blood flow is ignored in the present model.

[0123] Figure 16 An enlarged schematic view of the circled area of the blood vessel profile in Figure 15 is shown, and the pressure of the blood in each grid can be obtained.

[0124] A measurement point is set 1 cm outside the rightmost branch point of the hepatic vein, and the pressure value of the point is obtained as a function of time by calculation. Taking the pressure value as 0 as the baseline, the positive value above and the negative value below, the pressure-time curve is integrated, and the integral result is divided by the total calculation time to obtain the average pressure, i.e. vFHVP.

[0125] A small section of blood vessel above the measurement point 1 cm outside the rightmost branch point of the hepatic vein is artificially truncated, so that the branch blood vessel is completely blocked, and then the same boundary condition setting and simulation calculation are performed. After averaging the pressure of the same observation point, vWHVP is obtained.

[0126] The difference between the above two pressure values is calculated, and is denoted as the hepatic vein pressure gradient: HVPG = WHVP - FHVP.

[0127] After the above operation, the complete liver blood vessel pressure distribution of the healthy volunteer obtained by processing is shown in Figure 17 , vFHVP = 9.8 mmHg, and the blood flow pressure distribution after blocking the rightmost branch of the hepatic vein is shown in Figure 18, vWHVP = 14.5 mmHg was calculated, so the virtual hepatic venous pressure gradient of the healthy volunteer was vHVPG = 4.7 mmHg, which is within the normal range. Correspondingly, the complete hepatic vascular pressure distribution of patients with cirrhosis is shown in Figure 19 , vFHVP=9.6mmHg, blood flow pressure distribution after blocking the rightmost branch of the hepatic vein is shown Figure 20 , vWHVP was calculated to be 19.8 mmHg, so the virtual hepatic venous pressure gradient of this patient with cirrhosis was vHVPG = 10.2 mmHg, which is greater than the standard of 10 mmHg and is clinically significant portal hypertension.

[0128] Figure 21 A schematic diagram shows the time-dependent periodic function of four vHVPGs connected end-to-end in a specific scenario. The specific grid area is the area represented by parameter 130941.9983, and the FWHM is 3589.81336.

[0129] Example 2

[0130] This embodiment provides a system for measuring the hepatic venous pressure gradient. Figure 22 As shown, the measurement system includes: a model building module 201, a pressure calculation module 202 and a pressure gradient acquisition module 203.

[0131] The model construction module 201 is used to construct a vascular model of the liver, and the vascular model includes the interconnected hepatic vein and portal vein. The way in which the model construction module 201 constructs the liver vascular model can refer to the specific way of constructing the vascular model in Example 1, and will not be repeated in this embodiment.

[0132] The pressure calculation module 202 is configured to simulate the blood flow of the hepatic vein under normal conditions and under blocked conditions in the vascular model using fluid dynamics, based on the same preset boundary conditions, to calculate the hepatic vein free pressure and the hepatic vein wedge pressure at the first preset location of the hepatic vein. The methods for calculating the hepatic vein free pressure and the hepatic vein wedge pressure by the pressure calculation module 202 can be found in the specific methods described in Example 1 and are not further described in this example.

[0133] The pressure gradient acquisition module 203 is configured to acquire the hepatic venous pressure gradient based on the hepatic venous free pressure and the hepatic venous wedging pressure. The method for acquiring the hepatic venous pressure gradient by the pressure gradient acquisition module 203 can be referred to as that described in Example 1, and will not be further described in this embodiment.

[0134] In this embodiment, the one-stop MRI measurement is used in combination with the CFD calculation to obtain the accurate virtual hepatic vein pressure gradient in a non-invasive manner, which can replace the invasive measurement of the hepatic vein pressure gradient, provide an auxiliary diagnosis basis for clinical portal hypertension, and is beneficial to timely detection of diseases in the early stage of various liver diseases and early treatment.

[0135] Embodiment 3

[0136] The embodiment provides an electronic device which can be in the form of a computing device (for example, can be a server device) and includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor can implement the measurement method of the hepatic vein pressure gradient in embodiment 1 when executing the computer program.

[0137] Figure 23 A hardware structure schematic diagram of the embodiment is shown, as shown in the figure, the electronic device 9 specifically includes: Figure 23

[0138] The at least one processor 91, the at least one memory 92, and the bus 93 for connecting different system components (including the processor 91 and the memory 92), wherein:

[0139] The bus 93 includes a data bus, an address bus, and a control bus.

[0140] The memory 92 includes a volatile memory, for example, a random access memory (RAM) 921 and / or a cache memory 922, and can further include a read-only memory (ROM) 923.

[0141] The memory 92 further includes a program / utility 925 having a set of program modules 924, such as an operating system, one or more application programs, other program modules, and program data, and each of these examples, or some combination thereof, can include implementation of a network environment.

[0142] The processor 91 performs various functional applications and data processing by running the computer program stored in the memory 92, for example, the measurement method of the hepatic vein pressure gradient in embodiment 1 of the present application.

[0143] ​The electronic device 9 can further communicate with one or more external devices 94 such as a keyboard, a pointing device, etc. through an input / output (I / O) interface 95. Further, the electronic device 9 can communicate with one or more networks, such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet, through a network adapter 96. The network adapter 96 communicates with the other modules of the electronic device 9 through the bus 93. It should be appreciated that although not shown, other hardware and / or software modules could be used in connection with the electronic device 9 including, but not limited to, microcode, device drivers, redundant processors, external disk drive arrays, RAID (Redundant Array of Independent Disks) systems, tape drives, and data archival storage systems, etc.

[0144] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the foregoing detailed description, such a division is merely exemplary and not mandatory. Indeed, according to an embodiment of the application, the features and functionalities of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functionalities of one unit / module described above can be further divided into embodied by a plurality of units / modules.

[0145] Embodiment 4

[0146] The embodiment provides a computer readable storage medium, and a computer program is stored on the computer readable storage medium. The program is executed by a processor to implement the measurement method of the hepatic venous pressure gradient in the embodiment 1.

[0147] More specifically, the readable storage medium can include, but is not limited to, a portable disc, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0148] In a possible implementation, the application can also be implemented in the form of a program product, which includes program codes for causing a terminal device to execute the measurement method of the hepatic venous pressure gradient in the embodiment 1 when the program product is run on the terminal device.

[0149] The program codes for executing the application can be written in any combination of one or more programming languages, and can be executed completely on the user device, partially on the user device, as a stand-alone software package, partially on the user device and partially on a remote device, or completely on a remote device.

[0150] Although the specific embodiments of the present application have been described above, it is understood by those skilled in the art that the present application is only illustrated by way of example, and the scope of protection of the present application is defined by the appended claims. Those skilled in the art can make various changes or modifications to the embodiments without departing from the principles and essence of the present application, and such changes and modifications fall within the scope of protection of the present application.

Claims

1. A method for measuring hepatic venous pressure gradient, characterized in that: The measuring method comprises: constructing a vascular model of the liver, wherein the vascular model includes a hepatic vein and a portal vein connected to each other; By means of fluid mechanics, blood flow in the hepatic vein under normal conditions and blood flow in the hepatic vein under blocked conditions are simulated in the blood vessel model based on the same preset boundary conditions, so as to respectively calculate a hepatic vein free pressure and a hepatic vein wedging pressure at a first preset position of the hepatic vein; obtaining a hepatic vein pressure gradient according to the hepatic vein free pressure and the hepatic vein wedge pressure; The steps of constructing the liver vascular model specifically include: Acquiring a vascular image of the liver, wherein the vascular image includes the hepatic vein and the portal vein; extracting a blood vessel contour from the blood vessel image; connecting the hepatic vein and the portal vein in the vascular contour to construct a vascular model; The preset boundary conditions include velocity boundary conditions and pressure boundary conditions. The measurement method further includes the following steps: measuring the blood flow velocity at the inlet of the hepatic vein and using the blood flow velocity as the velocity boundary condition; The pressure boundary condition at the hepatic vein outlet is preset.

2. The method for measuring hepatic venous pressure gradient according to claim 1, wherein: The measuring method comprises at least one of the following steps: The step of obtaining a vascular image of the liver specifically includes: scanning the liver under a 3T magnetic field using a three-dimensional multiple gradient echo magnetic resonance sequence to obtain the vascular image of the liver; The step of extracting the blood vessel contour from the blood vessel image specifically includes: extracting the blood vessel contour in the blood vessel image by using a pre-trained deep neural network; The step of measuring the blood flow velocity at the entrance of the hepatic vein specifically includes: measuring the blood flow velocity at the entrance of the hepatic vein using a phase contrast gradient echo sequence.

3. The method for measuring hepatic venous pressure gradient according to claim 1, wherein: The hepatic vein includes a main hepatic vein trunk and a plurality of hepatic vein branches connected to the main hepatic vein trunk, and the portal vein includes a main hepatic portal vein trunk and a plurality of portal vein branches connected to the main hepatic portal vein trunk; The step of connecting the hepatic vein and the portal vein in the vascular contour to construct a vascular model specifically includes: Connect the hepatic vein branches to the corresponding portal vein branches.

4. The method for measuring hepatic venous pressure gradient according to claim 3, wherein: The step of connecting the hepatic vein branch with the corresponding portal vein branch specifically includes the following steps: When the angle between the hepatic vein branch to be connected and the corresponding portal vein branch is greater than a first preset angle, extending the hepatic vein branch along the blood vessel direction toward the corresponding portal vein branch, and extending the corresponding portal vein branch along the blood vessel direction toward the hepatic vein branch to connect the hepatic vein branch with the corresponding portal vein branch; When the angle between the hepatic vein branch to be connected and the corresponding portal vein branch is less than a first preset angle, the hepatic vein branch is extended along the blood vessel direction toward the corresponding portal vein branch, and the corresponding portal vein branch is extended along the blood vessel direction toward the hepatic vein branch to connect the hepatic vein branch with the corresponding portal vein branch, and the connection point is used as a new blood vessel port to connect to the corresponding hepatic vein branch or the corresponding portal vein branch.

5. The method for measuring hepatic venous pressure gradient according to claim 3, wherein: The step of connecting the hepatic vein branch with the corresponding portal vein branch also includes the following steps: Smooth the connected blood vessels.

6. The method for measuring hepatic venous pressure gradient according to claim 1, wherein: The steps of respectively simulating the blood flow of the hepatic vein under normal conditions and the blood flow of the hepatic vein under blocked conditions specifically include: connecting a zero point and a first measured blood flow velocity of the simulated hepatic vein under normal conditions through a smoothing function, and simulating the blood flow in the hepatic vein under normal conditions; A zero point and a first measured blood flow velocity of the simulated hepatic vein under occlusion are connected by a smoothing function, and the blood flow in the hepatic vein under the occlusion condition is simulated.

7. A system for measuring hepatic venous pressure gradient, characterized in that: The measurement system includes: a model building module, a pressure calculation module and a pressure gradient acquisition module; The model building module is used to build a vascular model of the liver, wherein the vascular model includes a hepatic vein and a portal vein connected to each other; The pressure calculation module is configured to simulate, in the blood vessel model, the blood flow of the hepatic vein under normal conditions and the blood flow of the hepatic vein under blocked conditions by means of fluid mechanics based on the same preset boundary conditions, so as to respectively calculate the hepatic vein free pressure and the hepatic vein wedging pressure at a first preset position of the hepatic vein; The pressure gradient acquisition module is used to acquire the hepatic vein pressure gradient according to the hepatic vein free pressure and the hepatic vein wedging pressure; The model building module is specifically used to obtain a vascular image of the liver, the vascular image including the hepatic vein and the portal vein; extract a vascular contour from the vascular image; and connect the hepatic vein and the portal vein in the vascular contour to build a vascular model; The preset boundary conditions include velocity boundary conditions and pressure boundary conditions. The measurement system also includes a boundary setting module for measuring the blood flow velocity of the blood at the inlet of the hepatic vein and using the blood flow velocity as the velocity boundary condition; and presetting the pressure boundary condition at the outlet of the hepatic vein.

8. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for measuring the hepatic venous pressure gradient according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for measuring the hepatic venous pressure gradient according to any one of claims 1 to 6 is implemented.

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