WO2019242160A1 - 基于特定的生理参数获取血管压力值的方法及装置 - Google Patents

基于特定的生理参数获取血管压力值的方法及装置 Download PDF

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WO2019242160A1
WO2019242160A1 PCT/CN2018/109079 CN2018109079W WO2019242160A1 WO 2019242160 A1 WO2019242160 A1 WO 2019242160A1 CN 2018109079 W CN2018109079 W CN 2018109079W WO 2019242160 A1 WO2019242160 A1 WO 2019242160A1
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model
blood flow
blood
vascular
interest
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PCT/CN2018/109079
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English (en)
French (fr)
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涂圣贤
李泽杭
林晓杰
张素
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博动医学影像科技（上海）有限公司
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Publication of WO2019242160A1 publication Critical patent/WO2019242160A1/zh

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

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  • the invention relates to a method and a device for obtaining a blood vessel pressure value based on a specific physiological parameter, and belongs to the field of medical technology.
  • lipids and carbohydrates in human blood on the vessel wall will form plaques on the vessel wall, which will lead to vascular stenosis; especially the vascular stenosis that occurs near the coronary artery of the heart will cause insufficient blood supply to the heart muscle and induce coronary heart disease And angina pectoris, which pose a serious threat to human health.
  • vascular stenosis especially the vascular stenosis that occurs near the coronary artery of the heart will cause insufficient blood supply to the heart muscle and induce coronary heart disease And angina pectoris, which pose a serious threat to human health.
  • the blood flow reserve fraction usually refers to the myocardial blood flow reserve fraction, which is defined as the ratio of the maximum blood flow that the diseased coronary artery can provide to the heart muscle to the maximum blood supply flow when the coronary artery is completely normal.
  • the blood flow ratio can be replaced by the pressure value. That is to say, the measurement of FFR value can be calculated by measuring the pressure of the distal stenosis of the coronary artery and the pressure of the proximal stenosis of the coronary artery with a pressure sensor under the condition of maximum congestion of the coronary artery.
  • the prior art provides methods to determine the blood flow reserve fraction (FFR) from different angles and different methods, its essence is through the blood pressure P a and
  • the difference ⁇ P in blood flow pressure at the proximal end and the distal end of the vascular segment of the region of interest was used to calculate the FFR.
  • factors such as the location, size, and type of the lesion will affect the calculation of the difference ⁇ P in blood flow pressure; in particular, the difference in individual physiological parameters will cause the proximal end of the vascular segment in the region of interest.
  • the acquisition of the blood pressure P a at the end point and the difference ⁇ P between the blood pressure at the proximal end and the distal end of the vascular segment in the region of interest produce an error.
  • the physiological parameters are different in the process of image acquisition. It will lead to the quality of image acquisition, which leads to errors in parameter acquisition during the calculation of the difference ⁇ P of blood pressure, and further leads to the FFR calculated by the calculation of blood pressure Pa and the difference ⁇ P of blood pressure in the prior art.
  • the blood flow characteristic values and the like deviate from the actual values, resulting in errors in the results of functional evaluation of the vascular system.
  • the purpose of the present invention is to provide a method and a device for obtaining a vascular pressure value based on a specific physiological parameter, so as to solve at least one of the technical problems existing in the prior art.
  • the device for obtaining vascular pressure values based on specific physiological parameters provided by the present invention introduces individual physiological parameters to correct various types of data in the process of calculating pressure values at both ends of a vascular segment in a region of interest, and clarifies different physiological parameters. The influence of vascular pressure value calculation improves the accuracy of vascular pressure value calculation.
  • the present invention provides a method for obtaining a vascular pressure value based on a specific physiological parameter.
  • the method for obtaining a vascular pressure value based on a specific physiological parameter includes:
  • S1 Collect anatomical data of at least a part of the vascular system, acquire geometric parameters of a region of interest according to the anatomical data, and establish a geometric model of the region of interest;
  • the calculation model of the vascular pressure value includes at least a part of a vascular segment and / or a vascular tree in the geometric model, and a horizontal position at each position between a proximal end and a distal end of the region of interest.
  • a cross-section morphology model which includes the presence or absence of plaques on each cross-section, the location of the plaques, the size of the plaques, the angle at which the plaques are formed, the composition of the plaques, and changes in the composition of the plaques, Changes in shape and plaque shape.
  • the establishment of the cross-sectional morphological model includes:
  • the cross section at the proximal end of the vascular segment of the region of interest is defined as the reference plane, and the central radial line of the geometric model is obtained through the method of centerline extraction and establishment;
  • the calculation model of the blood vessel pressure value further includes fitting the cross-sectional morphology model at different scales using the proximal end point of the region of interest as a reference point to obtain the blood vessel lumen.
  • Morphological difference function f (x) the scale is the distance between two adjacent cross sections when the morphological difference function f (x) is calculated.
  • the obtaining of the morphological difference function f (x) includes:
  • the rate of change of the lumen morphology with the distance x from the reference point is obtained according to the difference change function.
  • the morphological difference function f (x) includes an area function, a diameter function, and an edge position function.
  • the blood flow model includes a fixed blood flow model and a personalized blood flow model;
  • the personalized blood flow model includes a resting blood flow model and a load blood flow model, and the blood flow model It includes the blood flow velocity V of the region of interest, and when the blood flow model is a resting state blood flow model, the blood flow velocity V can be obtained by calculating the velocity of fluid filling in a blood vessel, or by calculating the shape of a blood vessel tree Obtained; wherein the morphology of the blood vessel tree includes at least one or more of the area, volume, and lumen diameter of a blood vessel segment in the blood vessel tree; the blood flow velocity V passing through the blood vessel tree When the morphological calculation is obtained, the geometric parameter further includes one or more of a length, a perfusion area, and a branch angle of a blood vessel segment in the blood vessel tree.
  • the specific physiological parameters include physiological information that can be directly obtained such as age, gender, blood pressure, and body mass index.
  • the specific physiological parameter when the vascular system is a coronary vascular system, the specific physiological parameter further includes a dominant type of a coronary artery.
  • the present invention also provides a device for obtaining a blood pressure value based on a specific physiological parameter, wherein the device for obtaining a blood pressure value based on a specific physiological parameter includes:
  • a data collector for acquiring and storing geometric parameters of a region of interest in an anatomical model of a vascular device
  • a pressure value processor which is used to establish a blood flow model of the region of interest and based on the geometric parameters, establish a geometric model corresponding to the region of interest;
  • the pressure value processor is further configured to obtain a vascular pressure value calculation model based on the geometric model and the blood flow model; meanwhile, according to the vascular pressure value calculation model and combined with hemodynamics, obtain a region of interest near The blood pressure Pa at the end point and the pressure difference value ⁇ P between the proximal end and the distal end of the vascular segment in the region of interest.
  • the device for obtaining a vascular pressure value based on a specific physiological parameter further includes a correction processor, the correction processor is configured to receive one or more physiological parameters of the individual, generate the correction parameters after processing, and The correction parameter is transmitted to a pressure value processor to correct the geometric model and / or the blood flow model.
  • the geometric model is calculated by the pressure value processor by measuring the geometric parameters of the anatomical model transmitted by the data collector, and combining the correction parameters transmitted by the correction processor to prepare Obtained by calibration;
  • the vascular pressure value calculation model includes a cross-sectional morphology model at various positions between the proximal end and the distal end of the region of interest and at least a part of a vessel segment and / or a vessel tree in the geometric model of the region of interest.
  • the vessel tree Including at least one section of the aorta or including at least one section of the aorta and a plurality of coronary arteries emanating from the aorta;
  • the cross-sectional morphological model is obtained directly / indirectly by the pressure value processor through the geometric model; the cross-sectional morphological model includes the presence or absence of plaques on each cross-section, the location of the plaques, the size of the plaques, The angle of plaque formation, the composition of plaques and changes in plaque composition, the shape of plaques, and changes in plaque shape.
  • the device for obtaining a vascular pressure value based on a specific physiological parameter further includes a speed acquisition module, the speed acquisition module is configured to acquire a blood flow velocity V of a region of interest, and the blood flow velocity V is in the interest between the second blood pressure estimate a first blood pressure P at the end of the proximal region P 1 and the first blood pressure at the region of interest proximal end and a distal end point P 1 of 2
  • the speed collector includes a speed calculation module and a speed extraction module; the speed extraction module directly obtains blood flow velocity information through a data acquisition module, or directly extracts blood flow velocity V through a blood flow model; and the speed calculation module includes speed conversion A module and a speed measurement module, the blood flow velocity V is obtained by converting the velocity of fluid filling in a blood vessel through a speed conversion module, or calculated by calculating the shape of a blood vessel tree in the geometric model through the speed calculation module.
  • the present invention further provides a device for obtaining a blood pressure difference of a patient, the device having a processor, wherein the processor is configured to cause the device to perform the following steps:
  • a blood vessel pressure difference of the blood vessel to be examined is determined based on the modified calculation model of the blood vessel model and the blood vessel pressure difference value.
  • the specific physiological parameters of the patient include one or more of human physiological information that can be directly obtained, such as age, gender, body temperature, body mass index, and the like.
  • the calculation model of the vascular pressure difference value is established based on a multi-scale calculation method.
  • the beneficial effect of the present invention is that the method for obtaining vascular pressure values based on specific physiological parameters of the present invention, by introducing individual specific physiological parameters in the calculation process of vascular pressure values, on the one hand, it can ensure various parameters at the initial stage of vascular pressure value calculations.
  • the extraction and establishment are accurate, on the other hand, the blood flow model during the calculation of the vascular pressure value can be modified to ensure the accuracy of the geometric model and the blood flow model, and further ensure that the geometric model and the blood flow model are passed.
  • the obtained related parameters are accurate, so that the blood vessel pressure value calculated by the method for obtaining a blood vessel pressure value based on a specific physiological parameter of the present invention can accurately reflect the blood flow pressure of the region of interest, and the result is accurate and reliable.
  • FIG. 1 is a schematic diagram of a geometric model of a vascular segment of a region of interest of the present invention in one form.
  • FIG. 2 is a schematic structural diagram of a cross-sectional morphological model at a position D 1 in FIG. 1.
  • FIG. 3 is a schematic structural diagram of a cross-sectional morphological model at a position D 2 in FIG. 1.
  • FIG. 4 is a schematic structural diagram of the cross-sectional morphological model at positions D 1 and D 2 in FIG. 2 and FIG. 3 after fitting.
  • FIG. 5 is a schematic diagram of a geometric model of a vascular segment in a region of interest of the present invention in another form.
  • FIG. 6 is a schematic structural diagram of a cross-sectional morphological model at a position D 1 in FIG. 5.
  • FIG. 7 is a schematic structural diagram of a cross-sectional morphological model at a position D 2 in FIG. 5.
  • FIG. 8 is a schematic structural diagram of the cross-sectional morphological model at positions D 1 and D 2 in FIG. 6 and FIG. 7 after fitting.
  • FIG. 9 is a structural block diagram of a device for obtaining a blood vessel pressure value based on a specific physiological parameter of the present invention.
  • the present invention provides a method for obtaining a vascular pressure value based on a specific physiological parameter.
  • the method for obtaining a vascular pressure value based on a specific physiological parameter includes the following steps:
  • S1 Collect anatomical data of at least a part of the vascular system, acquire geometric parameters of a region of interest according to the anatomical data, and establish a geometric model of the region of interest;
  • the vascular pressure value includes the blood pressure Pa at the proximal end of the vascular segment of the region of interest and the pressure difference value ⁇ P between the proximal end and the distal end of the region of interest in the corresponding state; of course, in other implementations
  • the vascular pressure value also includes other values used to characterize the pressure condition of the vascular segment in the region of interest, such as blood pressure at the distal end of the region of interest;
  • the specific physiological parameters in the present invention include age, Individual physiological information that can be directly obtained such as gender, blood pressure and body mass index (BMI).
  • the geometric model is a three-dimensional model reflecting the geometry of at least a part of the vascular system of the individual, and the geometric model is obtained by modeling the anatomical data of the individual vascular system;
  • the blood flow model is a reflection
  • a data model of blood flow in a blood vessel segment of an individual's region of interest includes data that reflects blood characteristics, such as blood flow in the blood vessel segment of the region of interest, and blood characteristics, and the blood flow model in the present invention is a sense of passage Establishment of anatomical data and / or individual specific data of vascular segments of the region of interest
  • anatomical data of the individual vascular system described in the present invention can be obtained through common image generation equipment such as CT equipment, OCT equipment, IVUS equipment, and contrast equipment.
  • CT equipment e.g., CT equipment
  • OCT equipment e.g., OCT equipment
  • IVUS equipment e.g., CT equipment
  • contrast equipment e.g., CT equipment, OCT equipment, IVUS equipment
  • X-rays can be used to develop body fluids containing the radiant after oral / injection of the radiation, further reflecting the image of the individual's vascular system / organs.
  • the degree of obesity of an individual can be reflected by a body mass index (BMI), which is the ratio of the individual's weight (kg) to the square of the height (m), when the individual's body mass index is different
  • BMI body mass index
  • the intensity of X-rays can be increased to ensure that the anatomical model formed when X-rays act on the individual is clear, and then the accuracy of the anatomical data is improved.
  • the tube voltage of the X-ray tube is 80 to 120 kV; when the body mass index of the individual is between 18.5 and 23.9, the The tube voltage is 120kV; when the body mass index of the individual is greater than 24, the tube voltage of the X-ray tube is 120-140kV; this setting can ensure the geometric parameters obtained when the individual's radioactive intake is constant. Accurate, further improve the accuracy of the geometric model.
  • the tube voltage of the X-ray tube is 120 to 130 kV; when the body mass index of the individual is 28 to 32 In between, the tube voltage of the X-ray tube is 130-135 kV; when the body mass index of the individual is> 32, the tube voltage of the X-ray tube is 135-140 kV.
  • the blood flow model includes a fixed blood flow model and a personalized blood flow model; and the blood flow model may be either a data calculation model or a three-dimensional fluid flow model; further, the fixed blood flow model is an empirical value
  • the blood flow model is directly established through the method of large data collection and simulation based on clinical practical experience; the personalized blood flow model includes a resting state blood flow model and a load state blood flow model.
  • both the blood flow velocity V and the blood flow pressure Pa are obtained directly / indirectly through the blood flow model.
  • the personalized blood flow model includes a resting-state blood flow model and a load-state blood flow model.
  • the blood flow velocity V can be obtained by calculating the velocity of fluid filling.
  • the resting blood flow model is a contrast agent blood flow model, and at this time, the blood flow velocity V is a target blood vessel obtained by using a gray-time fitting function during angiography. The average flow velocity of the agent; or the average flow velocity of the contrast agent during the angiography process obtained by using the TIMI frame method.
  • the blood flow velocity V may be obtained by calculating a morphology of a blood vessel tree, and the shape of the blood vessel tree includes at least an area, a volume, and a blood vessel tree.
  • the blood flow model is a load state blood flow model, and at this time, the blood flow velocity V is a blood flow velocity V after the adenosine injection vessel is sufficiently expanded, and at this time, the blood flow velocity V The blood flow velocity V is the maximum blood flow velocity Vmax.
  • the blood flow velocity V includes a blood flow velocity Vmax in a state where the target blood vessel is at a maximum congestion state and a blood flow velocity Vqc in a resting state.
  • the blood flow rate Velocity V is the blood flow velocity Vmax in the state of maximum congestion.
  • Further blood flow velocity Vmax can be obtained directly from the blood flow model, or can be obtained by converting the blood flow velocity V calculated from the blood flow model.
  • the blood flow velocity V is a blood flow velocity Vqc in a resting state.
  • the calculation model of the vascular pressure value is obtained by fitting the geometric model and the blood flow model, and the geometric model and / or the blood flow model are both a geometric model modified by an individual's physiological parameters and / Or blood flow model.
  • the vascular pressure value calculation model includes a cross-sectional morphology model at each position between the proximal end and the distal end of the region of interest and at least a part of the vascular segment and / or the vessel tree in the geometric model of the region of interest.
  • the vascular tree includes at least one aorta or includes at least one aorta and multiple coronary arteries emitted by the aorta, and each of the vascular segments and / or vascular trees includes the shape and diameter of the region of interest
  • anatomical data such as area, and further, the anatomical data also includes parameters such as the bending angle of the blood vessel segment that can reflect the actual shape of the blood vessel segment in the region of interest.
  • the cross-sectional morphological model is used to represent the geometric shape of the shape, area, and diameter of the cross-section of the blood vessel segment in the region of interest.
  • the cross-sectional morphological model is obtained directly / indirectly through the geometric model.
  • the establishment of the cross-sectional morphological model includes:
  • the cross section at the proximal end of the vascular segment of the region of interest is defined as the reference plane, and the central radial line of the geometric model is obtained through the method of centerline extraction and establishment;
  • the cross-sectional morphology model further includes plaque information at each cross-sectional position, where the plaque information is lesion information of a region of interest, and a large amount of data indicates that when the length of the plaque (that is, the lesion) is>
  • the pressure value ⁇ P of the vascular segment in the region of interest will increase, which deviates from the actual value.
  • the composition of the plaque at the same cross-section is complex or the size is too large, the stenosis rate of the vascular segment in the region of interest will be high.
  • the plaque information also needs to include the presence or absence of plaque, the location of the plaque, the size of the plaque, the angle at which the plaque forms, the composition of the plaque, and the composition of the plaque. Changes in the shape of the plaque and the shape of the plaque, and in the present invention, the planar geometric image of the lumen cross section at each position needs to be referenced to the coordinate system established in step S2 to clarify each cross section Plaque location to facilitate subsequent fitting of the cross-section morphological model.
  • the cross-sectional morphological model when the anatomical data is obtained by using CT, OCT, IVUS and other detection methods, the cross-sectional morphological model can be directly obtained through the geometric model. It is only necessary to ensure that the origin and coordinate direction of each of the cross-sectional morphological models are consistent; when the anatomical data is acquired using detection means such as X-rays, since the geometric model is a three-dimensional model extending in the direction of blood flow, Then, when the cross-sectional morphology model is established by using the geometric model, coordinate transformation of the geometric model is required to accurately reflect the cross-sectional morphology of each cross-section.
  • the method for obtaining a vascular pressure value based on a specific physiological parameter further includes modeling the cross-sectional morphology at different scales.
  • the fitting is performed to calculate the morphological difference function f (x) of the lumen of the target vessel.
  • the morphological difference function f (x) is a function that represents a change in the cross-sectional morphological change at different positions of the target blood vessel as a function of the distance x from the position to a reference point; and the acquisition of the morphological difference function f (x) include:
  • the change rate of the lumen morphology with the distance x from the reference point is obtained according to the difference change function, and the position parameters of the target vessel from the proximal end to the distal end are normalized. Processing to finally obtain the morphological difference function f (x).
  • the morphological function includes an area function, a diameter function, or an edge distance function, that is, in the present invention, the difference between two adjacent cross-sections at different scales can be obtained by fitting between the cross-sectional area, diameter, or edge distance functions.
  • the change function further, the change rate of the lumen morphology with the distance x to the reference point is obtained through the difference change function to obtain the morphological difference function f (x).
  • the morphological function is an area function
  • the two cross-sectional morphological models at D 1 and D 2 positions are fitted, and the cross-sectional morphological positions at D 1 and D 2 positions are fitted.
  • the area with increased vascular plaque was A 1 and the corresponding area S 1 ;
  • the area with reduced vascular lumen was A 2 and the corresponding area S 2 .
  • the difference change function It is the ratio of the area between the non-overlapping areas (S 1 , S 2 ) and the overlapping area (S 3 ) in the vascular lumen, or the area (S 1 , S 2 ) and the total area (S 1 , S 1 ) of the non-overlapping area. S 2 , S 3 ); and at this time, the morphological difference function f (x)> 0, that is, there is a pressure difference between the cross sections D 1 and D 2 .
  • the pressure difference value ⁇ P is obtained by calculating the morphological difference function f (x) at different scales and the blood flow velocity V of the vascular segment of the region of interest, and the calculation formula of the pressure difference value ⁇ P at different scales for:
  • ⁇ P (c 1 V + c 2 V 2 +... + c m V m )
  • c 1 , c 2 ,..., C m respectively represent parameter coefficients of the blood flow velocity V
  • the parameter coefficients include a plurality of parameter coefficients such as blood viscosity influence factors, blood turbulence influence factors, and viscosity coefficients;
  • m It is a natural number greater than or equal to 1, in order to represent the influence of different parameter coefficients on the blood flow velocity V, in order to modify the pressure difference value ⁇ P to ensure the accuracy of the pressure difference value ⁇ P calculation.
  • the value of m is 2, and when m is 2, c 1 is a parameter coefficient due to blood flow friction, and c 2 is a parameter coefficient due to blood turbulence.
  • ⁇ 1 , ⁇ 2 , ..., ⁇ n are the weighting coefficients of the morphological difference functions f 1 (x), f 2 (x), ..., f n (x) of the vascular lumen at different scales, where n is the scale It is a natural number greater than or equal to 1. Further, the increase of the weighting coefficient can further modify the morphological difference function f (x) to ensure the accuracy of the morphological difference fitting calculation between the two cross sections.
  • the different scales include a first scale, a second scale, ..., an n-th scale;
  • the first-scale morphological difference function f 1 (x) is used to detect a geometric morphological difference corresponding to two adjacent cross-sectional morphological models caused by a first lesion feature;
  • the second-scale morphological difference function f 2 (x) is used to detect a geometric morphological difference corresponding to two adjacent cross-sectional morphological models caused by a second lesion feature;
  • the n-th scale morphological difference function f n (x) is used to detect the geometric morphological differences corresponding to the morphological models of two adjacent cross-sections caused by the n-th lesion feature.
  • the calculation of the blood pressure difference may be independent of the blood flow velocity V of the region of interest, and the calculation formulas of the ⁇ P at different scales are:
  • ⁇ P k * [ ⁇ 1 * ⁇ f 1 (x) dx + ⁇ 2 * ⁇ f 2 (x) dx +... + ⁇ n * ⁇ f n (x) dx)
  • k is a correction parameter, and k is a constant that is a value obtained directly / indirectly based on individual information;
  • ⁇ 1 , ⁇ 2 , ..., ⁇ n are weighting coefficients of morphological difference functions f 1 (x), f 2 (x), ..., f n (x) of blood vessel lumen at different scales, respectively;
  • the different scales include a first scale, a second scale, ..., an n-th scale;
  • the first-scale morphological difference function f 1 (x) is used to detect a geometric morphological difference corresponding to two adjacent cross-sectional morphological models caused by a first lesion feature;
  • the second-scale morphological difference function f 2 (x) is used to detect a geometric morphological difference corresponding to two adjacent cross-sectional morphological models caused by a second lesion feature;
  • the n-th scale morphological difference function f n (x) is used to detect the geometric morphological difference between two adjacent cross-sectional morphological models caused by the n-th lesion feature; wherein n is a natural number greater than or equal to 1.
  • the physiological parameter is blood pressure.
  • the abnormal blood pressure change will cause a change in the blood pressure Pa at the proximal end in the blood vessel.
  • the blood flow pressure Pa of the region of interest should be corrected.
  • the blood flow pressure Pa includes the first blood flow pressure P 1 directly obtained based on the blood flow model and the corrected blood pressure. Then, a second blood flow pressure P 2 is obtained , and the relationship between the first blood flow pressure P 1 and the second blood flow pressure P 2 satisfies a relationship:
  • ⁇ is a correction parameter related to individual blood pressure information.
  • the physiological parameter is a coronary dominant type
  • the geometric model is a model at an individual coronary vascular system position.
  • the dominant coronary types include left superior, right superior, and balanced.
  • the left coronary artery has greater blood flow than the right because of the large area of myocardial perfusion in the left coronary artery.
  • Coronary blood flow; for the right superior type the area of myocardial perfusion of the right coronary artery is large, the maximum blood flow of the right coronary artery in the same cardiac cycle is greater than that of the left coronary artery; and when the plaque is located in different dominant types
  • the blood flow velocity V of the region of interest changes as the volume of the perfusion changes. Further, the change in the blood flow velocity V will affect the calculation of the pressure difference value ⁇ P in the blood vessel pressure value.
  • the blood flow velocity V of the region of interest should be modified.
  • the blood flow velocity V includes the blood flow velocity based on the blood flow.
  • the first blood flow velocity V 0 directly obtained by the model and the modified second blood flow velocity V 1 are obtained , and the relationship between the first blood flow velocity V 0 and the second blood flow velocity V 1 satisfies:
  • V 1 ⁇ * V 0 ;
  • ⁇ is a correction parameter related to an individual's coronary dominance type.
  • ⁇ P (c 1 V 1 + c 2 V 1 2 +... + c m V 1 m )
  • the physiological parameter is gender. Specifically, men have stronger ability to contract myocardium than women, and the blood flow velocity V that they can reach is also larger. Since the pressure difference value ⁇ P at both ends of the target blood vessel is calculated, the blood flow velocity V is mostly through the blood. The flow model is obtained directly / indirectly, and the establishment of the blood flow model often ignores the influence of gender on the calculation result. Therefore, there is an error in the calculation of the pressure difference value ⁇ P.
  • the blood flow velocity V of the region of interest should be modified.
  • the blood flow velocity V includes the first blood obtained directly based on the blood flow model.
  • the flow velocity V 0 and the corrected second blood flow velocity V 1 are obtained , and the relationship between the first blood flow velocity V 0 and the second blood flow velocity V 1 is:
  • V 1 ⁇ * V 0 ;
  • ⁇ is a correction parameter related to an individual's coronary dominance type.
  • ⁇ P (c 1 V 1 + c 2 V 1 2 +... + c m V 1 m )
  • the physiological parameter is age.
  • the myocardial microcirculation function gradually decreases, and the blood flow through a region of interest in a single cardiac cycle decreases, so that the blood flow velocity V of the region of interest will also change accordingly, and conventional
  • the blood flow velocity V is mostly obtained directly / indirectly through a blood flow model, and the influence of the age factor on the blood flow velocity is not considered. Therefore, there is an error in the calculation of the pressure difference value ⁇ P.
  • the blood flow velocity V of the region of interest should be modified.
  • the blood flow velocity V includes the first blood obtained directly based on the blood flow model.
  • the flow velocity V 0 and the corrected second blood flow velocity V 1 are obtained , and the relationship between the first blood flow velocity V 0 and the second blood flow velocity V 1 is:
  • V 1 ⁇ * V 0 ;
  • ⁇ is a correction parameter related to the age of the individual.
  • ⁇ P (c 1 V 1 + c 2 V 1 2 +... + c m V 1 m )
  • the correction parameter ⁇ is an empirical value obtained through a method of large data collection and simulation according to clinical practical experience.
  • the present invention further provides a device for obtaining a blood pressure value based on a specific physiological parameter.
  • the device for obtaining a blood pressure value based on a specific physiological parameter includes:
  • the device for obtaining a vascular pressure value based on a specific physiological parameter includes:
  • a data collector for acquiring and storing geometric parameters of a region of interest in an anatomical model of a vascular device
  • a pressure value processor which is used to establish a blood flow model of the region of interest and based on the geometric parameters, establish a geometric model corresponding to the region of interest;
  • the pressure value processor is further configured to obtain a vascular pressure value calculation model based on the geometric model and the blood flow model; meanwhile, according to the vascular pressure value calculation model and combined with hemodynamics, obtain a region of interest near The blood pressure Pa at the end point and the pressure difference value ⁇ P between the proximal end and the distal end of the vascular segment in the region of interest.
  • the geometric model is obtained by measuring and fitting the geometric parameters of the region of interest in the anatomical model, and fitting and calibrating; the calculation model of the vascular pressure value includes the proximal end and the distal end of the region of interest.
  • the cross-sectional morphological model is obtained directly / indirectly through the geometric model.
  • the cross-sectional morphological model includes the presence or absence of plaques on each cross-section, the position of the plaques, the angle of the plaques, the angle of the plaques, and the size of the plaques.
  • the device for obtaining a blood vessel pressure value further includes a speed collector, the speed collector is used to obtain a blood flow velocity in the region of interest, and the blood flow velocity is used to estimate the The first blood pressure Pa and the pressure difference value ⁇ P between the proximal end and the distal end of the region of interest.
  • the speed collector includes a speed calculation module and a speed extraction module; the speed extraction module can directly obtain the blood flow velocity through the data collector, and can also directly extract the blood flow velocity through the blood flow model.
  • the speed calculation module includes a speed conversion module and a speed measurement module.
  • the blood flow speed can be obtained by converting the speed of fluid filling in a blood vessel through the speed conversion module, and can also be obtained through the speed measurement module through the shape of a blood vessel tree in a geometric model. Calculated.
  • the pressure difference value ⁇ P in the present invention is calculated by the following formula:
  • ⁇ P (c 1 V + c 2 V 2 +... + c m V m )
  • c 1 , c 2 ,..., Cm respectively represent parameter coefficients of the blood flow velocity V
  • the parameter coefficients include a plurality of parameter coefficients such as blood viscosity influence factors, blood turbulence influence factors, and viscosity coefficients
  • m is Natural numbers greater than or equal to 1 are used to represent the influence of different parameter coefficients on the blood flow velocity V to correct the pressure difference value ⁇ P to ensure the accuracy of the pressure difference value ⁇ P calculation.
  • the value of m is 2, and when m is 2, c 1 is a parameter coefficient due to blood flow friction, and c 2 is a parameter coefficient due to blood turbulence.
  • the ⁇ 1 , ⁇ 2 , ..., ⁇ n are weighting coefficients of morphological difference functions f 1 (x), f 2 (x), ..., f n (x) of blood vessel lumen at different scales, respectively, where n Is a natural number with a scale of 1 or more; further, the increase of the weighting coefficient can further modify the morphological difference function f (x) to ensure the accuracy of the morphological difference fitting calculation between the two cross sections.
  • the device for obtaining a vascular pressure value based on a specific physiological parameter further includes a correction processor, which is configured to receive one or more physiological parameters of the individual, generate a correction parameter after processing, and convert the correction parameter It is passed to the pressure value processor to modify the geometric model and / or the blood flow model.
  • a correction processor configured to receive one or more physiological parameters of the individual, generate a correction parameter after processing, and convert the correction parameter It is passed to the pressure value processor to modify the geometric model and / or the blood flow model.
  • the correction parameter can both modify the blood flow velocity V, and then ensure the accuracy of the calculation of the blood pressure value; it can also directly adjust the blood pressure value (such as the proximal end of the region of interest)
  • the end point blood flow pressure Pa and pressure difference value ⁇ P) were corrected.
  • the present invention also provides a device for acquiring an individual blood vessel pressure difference, the device having a processor, wherein the processor is configured to cause the device to perform the following steps:
  • a blood vessel pressure difference of the blood vessel to be detected is determined based on the corrected calculation model of the blood vessel model and the blood vessel pressure difference.
  • the "processor” includes any device that receives and / or generates a signal, and the data processed by the processor may be a text message, an instruction of an object / fluid movement, an input of an application program, or some other information;
  • the blood vessel to be tested Alternative terms may be target blood vessels or blood vessels of interest; and the blood vessels to be tested include coronary blood vessels, branch blood vessels issued by coronary blood vessels, blood vessel trees, and single vessel segments, such as blood vessel tissue at any location;
  • the blood vessel model includes at least one of the second geometric model and the second blood flow model, and alternative terms of the blood vessel model may also be a lumen model, a fluid flow model, and the like, which may reflect an individual's blood vessel to be examined A model of morphology and fluid flow in a blood vessel.
  • the blood vessel model includes the length, diameter, and bending angle of the blood vessel to be tested, and the existence of branch blood vessels in the blood vessel to be tested, the angle of the branch blood vessels, and the number of branch blood vessels. The data about the geometry of the blood vessel to be examined are described.
  • the alternative term of the luminal morphology model may also be a cross-sectional morphological model, and the luminal morphological model includes the presence or absence of plaque, the location of the plaque, the size of the plaque, and the plaque.
  • the angle formed, the composition of the plaque and the change in the composition of the plaque, the shape of the plaque and the change in the shape of the plaque; further establishing the luminal morphology model includes the following steps:
  • the cross section at the proximal end of the object to be examined is defined as a reference plane, and a center line of the blood vessel model is established and obtained by a center line extraction method;
  • the planar geometric image of the lumen morphology at each position needs to use the coordinate system established in step S2 as a reference to determine the position of the plaque on each lumen cross section to facilitate subsequent fitting of the lumen morphology model. .
  • the luminal morphological model when the anatomical data is obtained by using CT, OCT, IVUS and other detection methods, the luminal morphological model can be directly obtained through the vascular model. It is only necessary to ensure that the origin and coordinate directions of each of the luminal morphological models are consistent; when the anatomical data is acquired using detection methods such as X-rays, since the blood vessel model is a three-dimensional model extending in the direction of blood flow, Then, when the luminal morphology model is established through the vascular model, coordinate conversion is required on the vascular model to accurately reflect the cross-sectional morphology of each cross-section.
  • the processor is further configured to determine, based on a preset morphological difference function, a vascular pressure difference between any two positions of a blood vessel to be detected through the luminal morphological model and the blood vessel model.
  • the morphological difference function is obtained by fitting and establishing the luminal morphological model, and is used to represent the function of the luminal morphological change at different positions of the blood vessel to be tested as a function of the distance x from the position to the reference point; and
  • the morphological difference function includes a difference function related to the area, volume, edge position and edge morphology of the blood vessel to be examined, which can reflect the morphological difference between any two positions of the blood vessel to be examined, and the difference function can be obtained directly / indirectly through the luminal morphology model .
  • the anatomical data may also be defined as parameters that can reflect the shape of the lumen directly and / or indirectly from the image acquisition device, such as anatomical data.
  • the processor, the blood vessel to be examined, the anatomical data, the luminal morphology model, and the blood vessel model may be different names having the same meaning.
  • the scale is a distance between two adjacent cross sections; the different scales include a first scale, a second scale, ..., an n-th scale;
  • the morphological difference function f 1 (x) at the first scale is used to detect the geometric morphological differences corresponding to the morphological models of two adjacent cross-sections caused by the first lesion feature;
  • the morphological difference function f 2 (x) at the second scale is used to detect a geometric morphological difference corresponding to two adjacent cross-sectional morphological models caused by a second lesion feature;
  • the morphological difference function f n (x) on the n-th scale is used to detect the geometric morphological differences corresponding to the morphological models of two adjacent cross-sections caused by the n-th lesion feature.
  • the blood vessel model is established in the same manner as the blood flow model and the geometric model, and the only difference is that the blood vessel model can include both the shape and Blood flow information, so in this embodiment, the specific establishment method of the blood vessel model is not described in detail here.
  • the specific physiological parameters described in this device include one or more of physiological information that can be directly obtained, such as age, gender, blood pressure, and body mass index.
  • the processor may be further configured to run the following formula to calculate and obtain the vascular pressure difference ⁇ P:
  • ⁇ P (c 1 V + c 2 V 2 +... + c m V m )
  • V is the blood flow velocity, which is obtained directly / indirectly through the second blood flow model;
  • c 1 , c 2 ,..., C m respectively represent the parameter coefficients of the blood flow velocity V, and the parameter coefficients include factors affecting blood viscosity, Multiple parameter coefficients such as blood turbulence influencing factors and viscosity coefficients;
  • m is a natural number greater than or equal to 1 to represent the effect of different parameter coefficients on blood flow velocity V, and to correct the pressure difference value ⁇ P to ensure blood vessels Accuracy of pressure difference ⁇ P calculation.
  • the value of m is 2, and when m is 2, c 1 is a parameter coefficient due to blood flow friction, and c 2 is a parameter coefficient due to blood turbulence.
  • the ⁇ 1 , ⁇ 2 , ..., ⁇ n are weighting coefficients of morphological difference functions f 1 (x), f 2 (x), ..., f n (x) of blood vessel lumen at different scales, respectively, where n Is a natural number with a scale of 1 or more; further, the increase of the weighting coefficient can further modify the morphological difference function f (x) to ensure the accuracy of the morphological difference fitting calculation between the two cross sections.
  • physiological parameters described in this device include one or more of physiological information that can be directly acquired, such as age, gender, blood pressure, and body mass index.
  • the calculation model of the vascular pressure difference value is basically consistent with the method for establishing the cross-sectional morphological model, and both are based on a multi-scale calculation method.
  • the method for obtaining vascular pressure values based on specific physiological parameters of the present invention by introducing individual specific physiological parameters in the calculation process of vascular pressure values, on the one hand, it can ensure the extraction of various parameters in the initial calculation of vascular pressure values. And establish accuracy, on the other hand, the blood flow model during the calculation of the vascular pressure value can be modified to ensure the accuracy of the geometric model and the blood flow model, and further ensure that the geometric model and the blood flow model obtain the The related parameters are accurate, so that the blood vessel pressure value calculated by the method for obtaining a blood vessel pressure value based on a specific physiological parameter of the present invention can accurately reflect the blood flow pressure in the region of interest, and the result is accurate and reliable.

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Abstract

一种基于特定的生理参数获取血管压力值的方法及装置。基于特定的生理参数获取血管压力值的方法包括：采集血管系统的解剖数据，并建立感兴趣区域的几何模型和血流模型；基于一个或多个特定的生理参数，获取感兴趣区域血管压力值的计算模型及感兴趣区域的血流速度；并根据血管压力值计算模型、血流速度，获取感兴趣区域的血管压力值。基于特定的生理参数获取血管压力值的装置通过引入个体的生理参数，对感兴趣区域血管段两端的压力值计算过程中的各类数据进行修正，明确不同的生理参数等对血管压力值计算的影响，提高血管压力值计算的准确性。

Description

基于特定的生理参数获取血管压力值的方法及装置 技术领域
本发明涉及一种基于特定的生理参数获取血管压力值的方法及装置，属于医疗技术领域。
背景技术
人体血液中的脂类及糖类物质在血管壁上的沉积将在血管壁上形成斑块，继而导致血管狭窄；特别是发生在心脏冠脉附近的血管狭窄将导致心肌供血不足，诱发冠心病、心绞痛等病症，对人类的健康造成严重威胁。据统计，我国现有冠心病患者约1100万人，心血管介入手术治疗患者数量每年增长大于10％。
冠脉造影、CT等常规医用检测手段虽然可以显示心脏冠脉血管狭窄的严重程度，但是并不能准确评价冠脉的缺血情况。为提高冠脉血管功能评价的准确性，1993年Pijls提出了通过压力测定推算冠脉血管功能的新指标——血流储备分数(Fractional Flow Reserve，FFR)，经过长期的基础与临床研究，FFR已成为冠脉狭窄功能性评价的金标准。
血流储备分数(FFR)通常是指心肌血流储备分数，定义为病变冠脉能为心肌提供的最大血流与该冠脉完全正常时最大供血流量之比，研究表明，在冠脉最大充血状态下，血流量的比值可以用压力值来代替。即FFR值的测量可在冠脉最大充血状态下，通过压力传感器对冠脉远端狭窄处的压力和冠脉狭窄近端压力进行测定继而计算得出。近年来，基于压力导丝测量FFR值的方法逐渐进入临床应用，成为冠心病患者获得精准诊断的有效方法；然而，由于压力导丝在介入过程中易对病人的血管造成损伤；同时，通过压力导丝对FFR值进行测定需要注射腺苷/ATP等药物保证冠脉达到最大充血状态， 部分病人会因药物的注射感到不适，使得基于压力导丝测量FFR值的方法存在较大的局限性。
随着CT与三维造影重建技术的发展及3D冠状动脉几何重建技术在血液力学研究领域的推广应用，同时，为减少FFR值测量过程中对人体带来的伤害及测量成本，基于医疗影像学的FFR计算技术已成为研究重点。
事实上，现有技术虽然从不同角度、不同方法中给出了确定血流储备分数(FFR)的方法，但其实质均是通过感兴趣区域血管段近端终点处的血流压力P a和感兴趣区域血管段近端终点处和远端终点处的血流压力的差值ΔP来计算FFR。而在血液流动的实际过程中，病变的位置、大小和类型等因素均会对血流压力的差值ΔP的计算产生影响；特别地，个体的生理参数不同将导致感兴趣区域血管段近端终点处的血流压力P a的获取和感兴趣区域血管段近端终点处和远端终点处的血流压力的差值ΔP计算产生误差，同时生理参数的不同在图像的获取过程中，也将导致图像获取的质量，从而导致血流压力的差值ΔP计算过程中的参数获取存在误差，进一步导致现有技术中，通过血流压力Pa、血流压力的差值ΔP计算获得的FFR、血流特征值等偏离实际值，致使对血管系统的功能评价的结果存在误差。
有鉴于此，确有必要提供一种新的获取血管压力值的方法，以解决上述问题。
发明内容
本发明的目的在于提供一种基于特定的生理参数获取血管压力值的方法及装置，以至少解决现有技术中存在的技术问题之一。本发明提供的基于特定的生理参数获取血管压力值的装置，通过引入个体的生理参数，对感兴趣区域血管段两端的压力值计算过程中的各类数据进行修正，明确不同的生理参数等对血管压力值计算的影响，提高血管压力值计算的准确性。
为实现上述发明目的，本发明提供了一种基于特定的生理参数获取血管压力值的方法，所述基于特定的生理参数获取血管压力值的方法包括：
S1、采集至少一部分的血管系统的解剖数据，根据所述解剖数据获取感兴趣区域的几何参数，并建立感兴趣区域的几何模型；
S2、根据感兴趣区域的解剖数据和/或个体特异性数据建立感兴趣区域的血流模型；
S3、基于一个或多个特定的生理参数，对所述几何模型和/或所述血流模型进行修正，获取感兴趣区域血管压力值的计算模型及感兴趣区域的血流速度V；
S4、根据所述血管压力值计算模型、血流速度V并结合血流动力学，获取感兴趣区域近端终点处的血流压力Pa，及相应状态下感兴趣区域近端终点处与远端终点处的压力差数值ΔP。
作为本发明的进一步改进，所述血管压力值的计算模型包括所述几何模型中至少一部分的血管段和/或血管树，以及感兴趣区域近端终点和远端终点之间各个位置处的横截面形态模型，所述横截面形态模型包括各横截面上斑块的有无、斑块的位置、斑块的大小、斑块形成的角度、斑块的组成及斑块组成的变化、斑块的形状及斑块形状的变化。
作为本发明的进一步改进，所述横截面形态模型的建立包括：
S1、定义感兴趣区域血管段近端终点处的横截面为参考面，通过中心线提取与建立方法获得所述几何模型的中心径线；
S2、以所述参考面的中心点为原点建立坐标系，沿垂直所述中心径线的方向对所述感兴趣区域血管段进行分割，将各横截面内外边缘投影在所述坐标系中，以获取感兴趣区域血管段在各个位置处管腔横截面的平面几何图像，横截面形态模型建立结束。
作为本发明的进一步改进，所述血管压力值的计算模型还包括以感兴趣区域的近端终点为参考点，对不同尺度下的所述横截面形态模型进行拟合，获取的血管管腔的形态差异函数f(x)，所述尺度为计算形态差异函数f(x)时相邻两横截面之间的距离。
作为本发明的进一步改进，所述形态差异函数f(x)的获取包括：
基于横截面形态模型，建立各横截面的形态函数；
对相邻两横截面的形态函数进行拟合，并获取相邻两横截面在不同尺度下的差异变化函数；
以感兴趣区域血管段的近端终点为参考点，根据差异变化函数获取管腔形态随着到参考点的距离x的变化率，对感兴趣区域血管段从近端终点到远端终点范围内的位置参数进行归一化处理，获取形态差异函数f(x)；所述形态函数包括面积函数、直径函数和边缘位置函数。
作为本发明的进一步改进，所述血流模型包括固定血流模型及个性化血流模型；所述个性化血流模型包括静息态血流模型和负荷态血流模型，所述血流模型包括感兴趣区域的血流速度V，且当所述血流模型为静息态血流模型时，所述血流速度V可通过血管中流体充盈的速度计算获得，或者通过血管树的形态计算获得；其中，所述血管树的形态至少包括所述血管树的面积、体积和血管树中血管段的管腔直径中的一种或几种；所述血流速度V通过所述血管树的形态计算获得时，所述几何参数还包括所述血管树中血管段的长度、灌注面积及分支角度中的一种或几种。
作为本发明的进一步改进，所述特定的生理参数包括年龄、性别、血压及身体质量指数等可直接获取的生理信息。
作为本发明的进一步改进，当所述血管系统为冠脉血管系统时，所述特定的生理参数还包括冠状动脉优势类型。
为实现上述发明目的，本发明还提供了一种基于特定的生理参数获取血管压力值的装置，其特征在于，所述基于特定的生理参数获取血管压力值的装置包括：
数据采集器，所述数据采集器用于获取及存储血管装置的解剖模型中感兴趣区域的几何参数；
压力值处理器，所述压力值处理器用于建立感兴趣区域的血流模型和基于所述几何参数，建立对应感兴趣区域的几何模型；
所述压力值处理器还用于，基于所述几何模型和所述血流模型获取血管 压力值计算模型；同时，根据所述血管压力值计算模型并结合血流动力学，获取感兴趣区域近端终点处的血流压力Pa，及感兴趣区域血管段近端终点与远端终点之间的压力差数值ΔP。
作为本发明的进一步改进，所述基于特定的生理参数获取血管压力值的装置还包括纠偏处理器，所述纠偏处理器用于接收个体的一个或多个生理参数，处理后生成纠偏参数，并将所述纠偏参数传递至压力值处理器中对所述几何模型和/或所述血流模型进行修正。
作为本发明的进一步改进，所述几何模型为所述压力值处理器通过对所述数据采集器传递的所述解剖模型的几何参数进行测算，并结合所述纠偏处理器传递的纠偏参数经拟合校准获得；
所述血管压力值计算模型包括感兴趣区域近端终点和远端终点之间各个位置处的横截面形态模型及感兴趣区域几何模型中至少一部分的血管段和/或血管树，所述血管树包括至少一段主动脉或者包括至少一段主动脉和由所述主动脉发出的多个冠状动脉；
所述横截面形态模型为所述压力值处理器通过所述几何模型直接/间接获得；所述横截面形态模型包括各横截面上斑块的有无、斑块的位置、斑块的大小、斑块形成的角度、斑块的组成及斑块组成的变化、斑块的形状及斑块形状的变化。
作为本发明的进一步改进，所述基于特定的生理参数获取血管压力值的装置还包括速度采集模块，所述速度采集模块用于获取感兴趣区域的血流速度V，所述血流速度V用以推算所述感兴趣区域近端终点处的第一血流压力P 1及感兴趣区域近端终点处的第一血流压力P 1与远端终点处的第二血流压力P 2之间的压力差数值ΔP；
所述速度采集器包括速度计算模块及速度提取模块；所述速度提取模块通过数据采集模块直接获取血流速度信息，或通过血流模型直接提取血流速度V；所述速度计算模块包括速度转换模块及速度测算模块，所述血流速度V通过血管中流体充盈的速度经速度转换模块转换获得，或通过几何模型中 血管树的形态经速度测算模块计算获得。
为实现上述发明目的，本发明还提供了一种用于获取患者血管压力差的设备，所述设备具有处理器，其中，所述处理器被设置为使得所述设备执行以下步骤：
收集患者特定生理参数和待检血管的几何参数；
根据所述待检血管的几何参数建立患者的血管模型；
根据患者特定生理参数修正所述血管模型；
提供至少一种血管压力差数值的计算模型；
基于修正后的所述血管模型与所述血管压力差数值的计算模型确定待检血管的血管压力差。
作为本发明的进一步改进，所述患者的特定生理参数包括年龄、性别、体温、身体质量指数等可直接获取的人体生理信息中的一个或多个。
作为本发明的进一步改进，所述血管压力差数值的计算模型是基于多尺度计算方法而建立的。
本发明的有益效果是：本发明的基于特定的生理参数获取血管压力值的方法，通过在血管压力值的计算过程中引入个体特定的生理参数，一方面可保证血管压力值计算初期各类参数的提取和建立准确，另一方面，可对血管压力值计算过程中的血流模型进行修正，保证几何模型和血流模型建立的准确性，进一步保证通过所述几何模型和所述血流模型获取的相关参数准确，使得通过本发明的基于特定的生理参数获取血管压力值的方法计算得到的血管压力值可准确反映感兴趣区域的血流压力，且结果准确可靠。
附图说明
图1是本发明感兴趣区域血管段在一种形态下的几何模型的示意图。
图2是图1中D 1位置处横截面形态模型的结构示意图。
图3是图1中D 2位置处横截面形态模型的结构示意图。
图4是图2和图3中D 1和D 2位置处横截面形态模型拟合后的结构示意图。
图5是本发明感兴趣区域血管段在另一种形态下的几何模型的示意图。
图6是图5中D 1位置处横截面形态模型的结构示意图。
图7是图5中D 2位置处横截面形态模型的结构示意图。
图8是图6和图7中D 1和D 2位置处横截面形态模型拟合后的结构示意图。
图9是本发明基于特定的生理参数获取血管压力值的装置的结构框图。
具体实施方式
为了使本发明的目的、技术方案和优点更加清楚，下面结合附图和具体实施例对本发明进行详细描述。
本发明提供了一种基于特定的生理参数获取血管压力值的方法，所述基于特定的生理参数获取血管压力值的方法包括一下步骤：
S1、采集至少一部分的血管系统的解剖数据，根据所述解剖数据获取感兴趣区域的几何参数，并建立感兴趣区域的几何模型；
S2、根据感兴趣区域的解剖数据和/或个体特异性数据建立感兴趣区域的血流模型；
S3、基于一个或多个特定的生理参数，对所述几何模型和/或所述血流模型进行修正，获取感兴趣区域血管压力值的计算模型及感兴趣区域的血流速度V；
S4、根据所述血管压力值计算模型、血流速度V并结合血流动力学，获取感兴趣区域近端终点处的血流压力Pa，及相应状态下感兴趣区域近端终点处与远端终点处的压力差数值ΔP。
在本发明中，所述血管压力值包括感兴趣区域血管段近端终点的血流压力Pa及相应状态下感兴趣区域近端终点处与远端终点处的压力差数值ΔP；当然在其他实施例中，所述血管压力值还包括感兴趣区域远端终点血流压力等其它用于表征感兴趣区域血管段压力情况的数值；进一步的，在本发明中所述特定的生理参数包括年龄、性别、血压及身体质量指数(BMI)等可直接获取的个体生理信息。
进一步的，所述几何模型为反映个体至少一部分血管系统的几何形状的三维模型，且所述几何模型为对个体血管系统的解剖数据进行建模后获得；进一步的，所述血流模型为反映个体感兴趣区域血管段中血液流动情况的数据模型，包括感兴趣区域血管段中血液的流动情况、血液的性质等可反映血液特性的数据，且在本发明中所述血流模型为通过感兴趣区域血管段的解剖数据和/或个体的特异性数据建立
需要说明的是，在本发明中所述个体血管系统的解剖数据，可通过CT设备、OCT设备、IVUS设备和造影设备等常用图像生成设备生成获取，具体来讲，当采用基于X射线的装置获取个体血管系统的解剖数据时，个体通过口服/注射放射剂后，X射线可对含有放射剂的体液进行显影，进一步反映出个体血管系统/脏器的图像。
然而，在使用X射线装置获取个体的解剖数据时，相同的放射剂量作用在肥胖个体上时，X射线装置发出的X射线无法全部穿过个体准确的形成个体的影响，致使肥胖个体经X射线装置获取的解剖模型边缘位置影像噪声大、质量差，进一步致使获取的解剖数据存在误差；因此，在使用X射线装置获取解剖数据时，需根据个体的肥胖程度对解剖数据进行修正，以保证几何模型和/或血流模型建立准确。
具体来讲，个体的肥胖程度可通过身体质量指数(BMI)体现，所述身体质量指数(BMI)为个体体重(kg)与身高(m)的平方的比值，当个体的身体质量指数不同时，调整X射线装置中X射线管的工作参数，可提高X射线的强度，以保证X射线作用在个体上时形成的解剖模型清晰，继而提高解剖数据的准确性。
进一步的，当所述个体的身体质量指数＜18.5时，所述X射线管的管电压为80～120kV；当所述个体的身体质量指数在18.5～23.9之间时，所述X射线管的管电压为120kV；当所述个体的身体质量指数＞24时，所述X射线管的管电压为120～140kV；如此设置，可在保证个体放射剂摄入量不变时，获得的几何参数准确，进一步提高几何模型建立的准确性。
为进一步提高X射线装置获取解剖数据的准确性，当个体的身体质量指数在24～27之间时，所述X射线管的管电压为120～130kV；当个体的身体质量指数在28～32之间时，所述X射线管的管电压为130～135kV；当个体的身体质量指数＞32时，所述X射线管的管电压为135～140kV。
所述血流模型包括固定血流模型及个性化血流模型；且所述血流模型既可为数据计算模型也可为三维流体流动模型；进一步的，所述固定血流模型即为经验值血流模型，为根据临床实际经验，通过大数据采集及模拟的方法直接建立；所述个性化血流模型包括静息态血流模型和负荷态血流模型。
在本发明中，所述血流速度V和所述血流压力Pa均通过所述血流模型直接/间接获取。具体来讲，当所述血流模型为固定血流模型或静息态血流模型时，所述血流压力Pa可通过获取的个体的收缩压混合舒张压计算获得，且此时所述血流压力Pa＝1/3收缩压+2/3舒张压；当所述血流模型为负荷态血流模型，此时所述血流压力Pa可通过所述负荷态血流模型直接测量获得。
所述个性化血流模型包括静息态血流模型和负荷态血流模型；当所述血流模型为静息态血流模型时，所述血流速度V可通过流体充盈的速度计算获得；在本发明的一个实施例中，所述静息态血流模型为造影剂血流模型，此时所述血流速度V为利用灰度时间拟合函数获得的目标血管在造影过程中造影剂的平均流动速度；或者利用TIMI数帧法计算获得的所述目标血管在造影过程中造影剂的平均流动速度。
当所述静息态血流模型为CT血流模型时，所述血流速度V可通过血管树的形态计算获得，所述血管树的形态至少包括所述血管树的面积、体积和血管树中血管段的管腔直径中的一种或几种；且当所述血流速度通过所述血管树的形态计算获得时，所述几何参数还包括所述血管树中血管段的长度、灌注面积及分支角度中的一种或几种。
在本发明的另一实施例中，所述血流模型为负荷态血流模型，此时所述血流速度V为注射腺苷血管充分扩张后的血流速度V，且此时，所述血流速度V为最大血流速度Vmax。
特别地，在本发明中所述血流速度V包括目标血管处于最大充血状态下的血流速度Vmax和静息状态下的血流速度Vqc，当目标血管位于冠脉区域时，所述血流速度V为最大充血状态下的血流速度Vmax，进一步的血流速度Vmax可直接通过血流模型获取，或通过血流模型计算的血流速度V转换获得；当目标血管位于外周血管系统时，所述血流速度V为静息态下的血流速度Vqc。
所述血管压力值的计算模型为经所述几何模型和所述血流模型拟合处理获得，且所述几何模型和/或所述血流模型均为经个体的生理参数修正后几何模型和/或血流模型。
进一步的，所述血管压力值计算模型包括感兴趣区域近端终点和远端终点之间各个位置处的横截面形态模型及感兴趣区域几何模型中至少一部分的血管段和/或血管树，所述血管树包括至少一段主动脉或者包括至少一段主动脉和由所述主动脉发出的多个冠状动脉，且每个所述血管段和/或血管树均包括所述感兴趣区域的形状、直径和面积等解剖数据，进一步的，所述解剖数据还包括血管段的弯曲角度等可以反映感兴趣区域血管段实际形态的参数。
所述横截面形态模型用于表示感兴趣区域血管段横截面的形状、面积和直径的几何形态，且在本发明中所述横截面形态模型为通过所述几何模型直接/间接获得，具体来讲，所述横截面形态模型的建立包括：
S1、定义感兴趣区域血管段近端终点处的横截面为参考面，通过中心线提取与建立方法获得所述几何模型的中心径线；
S2、以所述参考面的中心点为原点建立坐标系，沿垂直所述中心径线的方向对所述感兴趣区域血管段进行分割，将各横截面内外边缘投影在所述坐标系中，以获取目标血管在各个位置处管腔横截面的平面几何图像，横截面形态模型建立结束。
进一步的，所述横截面形态模型还包括各横截面位置处的斑块信息，所述斑块信息即为感兴趣区域的病变信息，大量数据表明：当斑块(即为病变)的长度＞20mm时，将导致感兴趣区域血管段压力值数值ΔP的升高，偏离 实际值；而当同一横截面处斑块的组成复杂或尺寸过大致使感兴趣区域血管段的狭窄率高，则会进一步导致感兴趣区域血管段压力差数值ΔP的计算；同时当所述斑块处于不同的位置处时，目标血管所供应的心肌体积区域不同，将导致病变位置与非病变位置处的比例发生变化，进一步影响血流速度V，从而导致感兴趣区域血管段压力差数值ΔP的计算发生偏差。
因此，在建立所述横截面形态模型时，所述斑块信息还需包括斑块的有无、斑块的位置、斑块的大小、斑块形成的角度、斑块的组成及斑块组成的变化、斑块的形状及斑块形状的变化，且在本发明中，各个位置处的管腔横截面的平面几何图像均需以步骤S2中建立的坐标系为参考，明确各横截面上斑块的位置，以方便横截面形态模型的后续拟合。
需要说明的是，在所述横截面形态模型的建立过程中，当所述解剖数据为采用CT、OCT、IVUS等检测手段获取时，所述横截面形态模型可通过所述几何模型直接获取，只需保证每个所述横截面形态模型的原点及坐标方向一致即可；当所述解剖数据为采用X射线等检测手段获取时，由于所述几何模型为沿血流方向延伸的立体模型，则在通过所述几何模型建立所述横截面形态模型时，需对所述几何模型进行坐标转换，以准确反应各个横截面的截面形态。
为进一步保证所述基于特定的生理参数获取血管压力值的方法获取的压力差数值ΔP准确，所述基于特定的生理参数获取血管压力值的方法还包括对不同尺度下的所述横截面形态模型进行拟合，计算目标血管管腔的形态差异函数f(x)。其中，所述形态差异函数f(x)用于表示目标血管不同位置处的横截面形态变化随着该位置到参考点的距离x变化的函数；且所述形态差异函数f(x)的获取包括：
基于横截面形态模型，建立各横截面的形态函数；
对相邻两横截面的形态函数进行拟合，并获取相邻两横截面在不同尺度下的差异变化函数；
以目标血管的近端终点为参考点，根据差异变化函数获取管腔形态随着 到参考点的距离x的变化率，对目标血管从近端终点到远端终点范围内的位置参数进行归一化处理，以最终获取形态差异函数f(x)。
所述形态函数包括面积函数、直径函数或边缘距离函数，即在本发明中可通过各横截面面积、直径或边缘距离函数之间的拟合，获取相邻两横截面在不同尺度下的差异变化函数；进一步的，通过差异变化函数获取管腔形态随着到参考点的距离x的变化率，获得形态差异函数f(x)。
具体来讲，当所述形态函数为面积函数时，如图1至图4，对D 1和D 2位置处的两横截面形态模型进行拟合，D 1、D 2位置处的横截面形态模型拟合后，有血管管腔斑块增加的区域为A 1，对应的面积S 1；血管管腔减少的区域为A 2，对应的面积S 2。由于所述D 1和D 2位置处的血管管腔(斑块)不重叠，因此当血流经D 1处流向D 2处时，血流压力将随之发生变化；此时，差异变化函数即为血管管腔中非重叠区域(S 1、S 2)与重叠区域之间面积(S 3)的比值，或者为非重叠区域的面积(S 1、S 2)与总面积(S 1、S 2、S 3)的比值；且此时，所述形态差异函数f(x)＞0，即横截面D 1和D 2之间存在压力差。
进一步的，当所述D 1和D 2位置处的血管管腔(斑块)完全重叠时，如图5至图8，所述区域A 1与A 2完全重叠，即非重叠区域A 1与A 2的面积S 1＝S 2＝0，此时，差异变化函数为0，即所述形态差异函数f(x)＝0，此时，横截面D 1和D 2之间不存在压力差。
进一步的，所述压力差数值ΔP为通过不同尺度下的形态差异函数f(x)和感兴趣区域血管段的血流速度V计算获得，且所述压力差数值ΔP在不同尺度下的计算公式为：
ΔP＝(c 1V+c 2V 2+…+c mV m)
        *[α 1*∫f 1(x)dx+α 2*∫f 2(x)dx+…+α n*∫f n(x)dx]
其中，c 1、c 2、…、c m分别代表血流速度V的参数系数，所述参数系数包括血液粘度影响因素、血液湍流影响因素及粘滞系数等多个参数系数；进一步的，m为大于等于1的自然数，以分别代表不同参数系数对血流速度V的 影响，以对压力差数值ΔP进行修正，保证压力差数值ΔP计算的准确性。优选的，在本发明中m的取值为2，且当m为2时，c 1为因血液流动摩擦产生的参数系数，c 2为血液湍流产生的参数系数。
α 1、α 2、…、α n分别为不同尺度下血管管腔的形态差异函数f 1(x)、f 2(x)、…、f n(x)的加权系数，其中，n为尺度为大于等于1的自然数；进一步的，所述加权系数的增加可进一步对形态差异函数f(x)进行修正，保证两横截面之间形态差异拟合计算的准确性。
具体来讲，所述不同尺度包括第一尺度、第二尺度、……、第n尺度；
所述第一尺度形态差异函数f 1(x)用于检测第一种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异；
所述第二尺度形态差异函数f 2(x)用于检测第二种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异；
……
所述第n尺度形态差异函数f n(x)用于检测第n种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异。
进一步的，在本发明的另一实施例中，所述血管压力差的计算还可与所述感兴趣区域的血流速度V无关，此时所述ΔP在不同尺度下的计算公式为：
ΔP＝k*[α 1*∫f 1(x)dx+α 2*∫f 2(x)dx+…+α n*∫f n(x)dx]
其中，k为修正参数，且k为常数为基于个体信息直接/间接获取的数值；
α 1、α 2、…、α n分别为不同尺度下血管管腔的形态差异函数f 1(x)、f 2(x)、…、f n(x)的加权系数；
优选的，所述不同尺度包括第一尺度、第二尺度、……、第n尺度；
所述第一尺度形态差异函数f 1(x)用于检测第一种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异；
所述第二尺度形态差异函数f 2(x)用于检测第二种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异；
……
所述第n尺度形态差异函数f n(x)用于检测第n种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异；其中，所述n为大于等于1的自然数。
以下说明书部分将以具体的影响血管压力值的生理参数为例，对本发明的基于特定的生理参数获取血管压力值的方法进行详细阐述。
实施例1：
在本实施例中，所述生理参数为血压，当个体存在血压异常时，异常的血压变化将导致血管中近端终点处的血流压力Pa发生变化。
因此，当个体存在血压异常时，应对感兴趣区域的血流压力Pa进行修正，此时，所述血流压力Pa包括基于所述血流模型直接获取的第一血流压力P 1及经修正后获得第二血流压力P 2，且所述第一血流压力P 1和所述第二血流压力P 2之间满足关系式：
P 2＝ω×P 1；
其中，ω为与个体的血压信息有关的纠偏参数。
实施例2：
在本实施例中，所述生理参数为冠脉优势类型，且所述几何模型为个体冠脉血管系统位置处的模型。具体来讲，冠脉优势类型一般包括左优型、右优型以及均衡型；对左优型而言，由于左冠状动脉灌注的心肌区域大，因此同一心动周期左冠脉的血流量大于右冠脉的血流量；而对于右优型而言，右冠状动脉灌注的心肌区域大，则同一心动周期右冠脉的最大血流量大于左冠脉；而当斑块位于不同的优势型的不同血管内时，由于灌注的体积发生变化因此感兴趣区域的血流速度V也随之发生变化，进一步的，血流速度V的变化将影响血管压力值中压力差数值ΔP的计算。
因此，当个体感兴趣区域的冠脉优势类型发生变化时，应对感兴趣区域的血流速度V进行修正，具体来讲，在本实施例中，所述血流速度V包括基于所述血流模型直接获取的第一血流速度V 0及经修正后获得第二血流速度 V 1，且所述第一血流速度V 0和所述第二血流速度V 1之间满足关系式：
V 1＝ω*V 0；
其中，ω为与个体的冠脉优势类型有关的纠偏参数。
且此时所述压力差数值ΔP在不同尺度下的计算公式为：
ΔP＝(c 1V 1+c 2V 1 2+…+c mV 1 m)
        *[α 1*∫f 1(x)dx+α 2*∫f 2(x)dx+…+α n*∫f n(x)dx]
实施例3：
在本实施例中，所述生理参数为性别。具体来讲，男性比女性心肌收缩能力更强，其所能达到的血流速度V也较大，而由于在对目标血管两端的压力差数值ΔP进行计算时，血流速度V多是通过血流模型直接/间接的获取，而血流模型的建立常常会忽略性别对计算结果造成的影响，因此，在所述压力差数值ΔP的计算过程中存在误差。
因此，当个体的性别不同时，应对感兴趣区域的血流速度V进行修正，具体来讲，在本实施例中，所述血流速度V包括基于所述血流模型直接获取的第一血流速度V 0及经修正后获得第二血流速度V 1，且所述第一血流速度V 0和所述第二血流速度V 1之间满足关系式：
V 1＝ω*V 0；
其中，ω为与个体的冠脉优势类型有关的纠偏参数。
且此时所述压力差数值ΔP在不同尺度下的计算公式为：
ΔP＝(c 1V 1+c 2V 1 2+…+c mV 1 m)
        *[α 1*∫f 1(x)dx+α 2*∫f 2(x)dx+…+α n*∫f n(x)dx]
实施例4：
在本实施例中，所述生理参数为年龄。具体来讲，成年个体随着年龄的增大，心肌微循环功能逐渐降低，单一心动周期流经感兴趣区域的血流量减少，从而感兴趣区域的血流速度V也将随之改变，而常规计算中，血流速度V多是通过血流模型直接/间接的获取，并未考虑年龄因素对血流速度的影响， 因此，在所述压力差数值ΔP的计算过程中存在误差。
因此，当个体的年龄不同时，应对感兴趣区域的血流速度V进行修正，具体来讲，在本实施例中，所述血流速度V包括基于所述血流模型直接获取的第一血流速度V 0及经修正后获得第二血流速度V 1，且所述第一血流速度V 0和所述第二血流速度V 1之间满足关系式：
V 1＝ω*V 0；
其中，ω为与个体的年龄有关的纠偏参数。
且此时所述压力差数值ΔP在不同尺度下的计算公式为：
ΔP＝(c 1V 1+c 2V 1 2+…+c mV 1 m)
        *[α 1*∫f 1(x)dx+α 2*∫f 2(x)dx+…+α n*∫f n(x)dx]
需要说明的是，在本发明的实施例中，所述纠偏参数ω是根据临床实际经验，通过大数据采集及模拟的方法获取的经验值。
请参参阅图9所示，本发明还提供了一种基于特定的生理参数获取血管压力值的装置，所述基于特定的生理参数获取血管压力值的装置包括：
所述基于特定的生理参数获取血管压力值的装置包括：
数据采集器，所述数据采集器用于获取及存储血管装置的解剖模型中感兴趣区域的几何参数；
压力值处理器，所述压力值处理器用于建立感兴趣区域的血流模型和基于所述几何参数，建立对应感兴趣区域的几何模型；
所述压力值处理器还用于，基于所述几何模型和所述血流模型获取血管压力值计算模型；同时，根据所述血管压力值计算模型并结合血流动力学，获取感兴趣区域近端终点处的血流压力Pa，及感兴趣区域血管段近端终点与远端终点之间的压力差数值ΔP。
进一步的，所述几何模型为通过对所述解剖模型中感兴趣区域的几何参数进行测算，并拟合校准获得；所述血管压力值的计算模型包括感兴趣区域近端终点和远端终点之间各个位置处的横截面形态模型及感兴趣区域几何模型中至少一 部分的血管段和/或血管树，所述血管树包括至少一段主动脉或者包括至少一段主动脉和由所述主动脉发出的多个冠状动脉，且每个所述血管段和/或血管树均包括所述感兴趣区域的形状、直径和面积等解剖数据，进一步的，所述解剖数据还包括血管段的弯曲角度等可以反映感兴趣区域血管段实际形态的参数。
所述横截面形态模型为通过所述几何模型直接/间接获得，所述横截面形态模型包括各横截面上斑块的有无、斑块的位置、斑块的大小斑块形成的角度、斑块的组成及斑块组成的变化、斑块的形状及斑块形状的变化。
进一步的，所述获取血管压力值的装置还包括速度采集器，所述速度采集器用于获取感兴趣区域的血流速度，所述血流速度用以推算所述感兴趣区域近端终点处的第一血流压力Pa及感兴趣区域近端终点与远端终点之间的压力差数值ΔP。
所述速度采集器包括速度计算模块及速度提取模块；所述速度提取模块可通过所述数据采集器直接采集获得血流速度，也可通过所述血流模型直接提取血流速度。
所述速度计算模块包括速度转换模块及速度测算模块，所述血流速度可通过血管中流体充盈的速度经所述速度转换模块转换获得，还可通过几何模型中血管树的形态经速度测算模块计算获得。
优选的，在本发明中所述压力差数值ΔP通过如下公式计算获得：
ΔP＝(c 1V+c 2V 2+…+c mV m)
        *[α 1*∫f 1(x)dx+α 2*∫f 2(x)dx+…+α n*∫f n(x)dx]
其中，c 1、c 2、…、cm分别代表血流速度V的参数系数，所述参数系数包括血液粘度影响因素、血液湍流影响因素及粘滞系数等多个参数系数；进一步的，m为大于等于1的自然数，以分别代表不同参数系数对血流速度V的影响，以对压力差数值ΔP进行修正，保证压力差数值ΔP计算的准确性。优选的，在本发明中m的取值为2，且当m为2时，c 1为因血液流动摩擦产生的参数系数，c 2为血液湍流产生的参数系数。
所述α 1、α 2、…、α n分别为不同尺度下血管管腔的形态差异函数f 1(x)、f 2(x)、…、f n(x)的加权系数，其中，n为尺度为大于等于1的自然数；进一步的，所述加权系数的增加可进一步对形态差异函数f(x)进行修正，保证两横截面之间形态差异拟合计算的准确性。
进一步的，所述基于特定的生理参数获取血管压力值的装置还包括纠偏处理器，所述纠偏处理器用于接收个体的一个或多个生理参数，处理后生成纠偏参数，并将所述纠偏参数传递至压力值处理器中对所述几何模型和/或所述血流模型进行修正。
需要说明的是，所述纠偏参数既可为对所述血流速度V进行修正，继而保证所述血管压力值计算的准确性；还可直接对所述血管压力值(如感兴趣区域近端终点的血流压力Pa、压力差数值ΔP)进行修正。
进一步的，本发明还提供一种用于获取个体血管压力差的设备，所述设备具有处理器，其中，所述处理器被设置为使得所述设备执行以下步骤：
收集个体特定生理参数和待检血管的几何参数；
根据所述待检血管的几何参数建立个体的血管模型；
根据个体特定生理参数修正所述血管模型；
提供至少一种血管压力差的计算模型；
基于修正后的所述血管模型与所述血管压力差的计算模型确定待检血管的血管压力差。
所述“处理器”包括接收和/或生成信号的任意装置，所述处理器处理的数据可以是文本消息、物体/流体运动的指令、应用程序的输入或一些其它信息；所述待检血管的备选术语可以为目标血管或感兴趣血管；且所述待检血管包括冠脉血管、由冠脉血管发出的分支血管、血管树和单支血管段等个体任意位置处的血管组织；所述血管模型至少包括所述第二几何模型和所述第二血流模型中的一种，且所述血管模型的备选术语还可为管腔模型、流体流动模型等可反映个体待检血管形态和血管内流体流动情况的模型，进一步的， 所述血管模型包括待检血管的长度、直径、弯曲角度及待检血管中分支血管的存在、分支血管的角度、分支血管的数量等与所述待检血管的几何形貌有关的数据。
在本实施例中，所述管腔形态模型的备选术语还可为横截面形态模型，且所述管腔形态模型包括斑块的有无、斑块的位置、斑块的大小、斑块形成的角度、斑块的组成及斑块组成的变化、斑块的形状及斑块形状的变化；进一步的所述管腔形态模型的建立包括以下步骤：
S1、定义待检近端终点处的横截面为参考面，通过中心线提取方法，建立获取所述血管模型的中心径线；
S2、以所述参考面的中心点为原点建立坐标系，沿垂直所述中心径线的方向对所述待检血管进行分割，将各横截面内外边缘投影在所述坐标系中，以获取待检血管在各个位置处管腔形态的平面几何图像，管腔形态模型建立结束。
在本发明中，各个位置处的管腔形态的平面几何图像均需以步骤S2中建立的坐标系为参考，明确各管腔截面上斑块的位置，以方便管腔形态模型的后续拟合。
需要说明的是，在所述管腔形态模型的建立过程中，当所述解剖数据为采用CT、OCT、IVUS等检测手段获取时，所述管腔形态模型可通过所述血管模型直接获取，只需保证每个所述管腔形态模型的原点及坐标方向一致即可；当所述解剖数据为采用X射线等检测手段获取时，由于所述血管模型为沿血流方向延伸的立体模型，则在通过所述血管模型建立所述管腔形态模型时，需对所述血管模型进行坐标转换，以准确反映各个截面的截面形态。
所述处理器还用于基于预设的形态差异函数，通过所述管腔形态模型以及所述血管模型确定待检血管任意两位置间的血管压力差。其中，所述形态差异函数通过所述管腔形态模型拟合建立获取，用于表示待检血管不同位置处的管腔形态变化随着该位置到参考点的距离x变化的函数；且所述形态差异函数包括与待检血管的面积、体积、边缘位置和边缘形态有关的可以体现 待检血管任意两位置间形态差异的差异函数，且所述差异函数可通过管腔形态模型直接/间接获取。
所述解剖数据在其他实施例中还可定义为解剖数据等可从图像获取装置直接和/或间接获取的可反映管腔形态的参数。
即在另一上下文中，所述处理器、待检血管、解剖数据、管腔形态模型和血管模型可以为具有相同含义的不同名称。
所述尺度为所述尺度为相邻两横截面之间的距离；所述不同尺度包括第一尺度、第二尺度、……、第n尺度；
所述第一尺度下的形态差异函数f 1(x)用于检测第一种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异；
所述第二尺度下的形态差异函数f 2(x)用于检测第二种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异；
……
所述第n尺度下的形态差异函数f n(x)用于检测第n种病变特征所引起的相邻两横截面形态模型所对应的几何形态差异。
进一步的，在本发明中所述血管模型的建立方式与所述血流模型和所述几何模型的建立方式基本相同，其差别点仅在于所述血管模型可同时包括待检血管段的形态和血流信息，故在本实施方式中，所述血管模型的具体建立方式与此不在赘述。
当然，在本设备中所述特定的生理参数包括年龄、性别、血压及身体质量指数等可直接获取的生理信息中的一个或多个。
进一步的，在本发明中所述处理器还可用于运行如下公式以计算获得所述血管压力差ΔP：
ΔP＝(c 1V+c 2V 2+…+c mV m)
        *[α 1*∫f 1(x)dx+α 2*∫f 2(x)dx+…+α n*∫f n(x)dx]
其中，c 1V+c 2V 2+…+c mv m可为常数；
V为血流速度，为通过所述第二血流模型直接/间接获取；c 1、c 2、…、c m分别代表血流速度V的参数系数，所述参数系数包括血液粘度影响因素、血液湍流影响因素及粘滞系数等多个参数系数；进一步的，m为大于等于1的自然数，以分别代表不同参数系数对血流速度V的影响，以对压力差数值ΔP进行修正，保证血管压力差ΔP计算的准确性。优选的，在本发明中m的取值为2，且当m为2时，c 1为因血液流动摩擦产生的参数系数，c 2为血液湍流产生的参数系数。
所述α 1、α 2、…、α n分别为不同尺度下血管管腔的形态差异函数f 1(x)、f 2(x)、…、f n(x)的加权系数，其中，n为尺度为大于等于1的自然数；进一步的，所述加权系数的增加可进一步对形态差异函数f(x)进行修正，保证两横截面之间形态差异拟合计算的准确性。
当然，在本装置中所述特定的生理参数包括年龄、性别、血压及身体质量指数等可直接获取的生理信息中的一个或多个。
进一步的，在本发明中所述血管压力差数值的计算模型与所述横截面形态模型的建立方法基本一致，均是是基于多尺度计算方法而建立的。
需要指出的是，上述装置及功能模块仅仅为示例性的给出实现该技术方案的基本结构，而非唯一结构。
综上所述，本发明的基于特定的生理参数获取血管压力值的方法，通过在血管压力值的计算过程中引入个体特定的生理参数，一方面可保证血管压力值计算初期各类参数的提取和建立准确，另一方面，可对血管压力值计算过程中的血流模型进行修正，保证几何模型和血流模型建立的准确性，进一步保证通过所述几何模型和所述血流模型获取的相关参数准确，使得通过本发明的基于特定的生理参数获取血管压力值的方法计算得到的血管压力值可准确反映感兴趣区域的血流压力，且结果准确可靠。
以上实施例仅用以说明本发明的技术方案而非限制，尽管参照较佳实施例对本发明进行了详细说明，本领域的普通技术人员应当理解，可以对本发明的技术 方案进行修改或者等同替换，而不脱离本发明技术方案的精神和范围。

Claims (15)

  1. 一种基于特定的生理参数获取血管压力值的方法，其特征在于，包括：
    S1、采集至少一部分的血管系统的解剖数据，根据所述解剖数据获取感兴趣区域的几何参数，并建立感兴趣区域的几何模型；
    S2、根据感兴趣区域的解剖数据和/或个体特异性数据建立感兴趣区域的血流模型；
    S3、基于一个或多个特定的生理参数，对所述几何模型和/或所述血流模型进行修正，获取感兴趣区域血管压力值的计算模型及感兴趣区域的血流速度V；
    S4、根据所述血管压力值计算模型、血流模型并结合血流动力学，获取感兴趣区域近端终点处的血流压力Pa，及相应状态下感兴趣区域近端终点处与远端终点处的压力差数值ΔP。
  2. 根据权利要求1所述的基于特定的生理参数获取血管压力值的方法，其特征在于：所述血管压力值的计算模型包括所述几何模型中至少一部分的血管段和/或血管树，以及感兴趣区域近端终点和远端终点之间各个位置处的横截面形态模型，所述横截面形态模型包括各横截面上斑块的有无、斑块的位置、斑块的大小、斑块形成的角度、斑块的组成及斑块组成的变化、斑块的形状及斑块形状的变化。
  3. 根据权利要求2所述的基于特定的生理参数获取血管压力值的方法，其特征在于：所述横截面形态模型的建立包括：
    S1、定义感兴趣区域血管段近端终点处的横截面为参考面，通过中心线提取与建立方法获得所述几何模型的中心径线；
    S2、以所述参考面的中心点为原点建立坐标系，沿垂直所述中心径线的方向对所述感兴趣区域血管段进行分割，将各横截面内外边缘投影在所述坐标系中，以获取感兴趣区域血管段在各个位置处管腔横截面的平面几何图像，横截面形态模型建立结束。
  4. 根据权利要求2所述的基于特定的生理参数获取血管压力值的方法，其特征在于：所述血管压力值的计算模型还包括以感兴趣区域的近端终点为参考 点，对不同尺度下的所述横截面形态模型进行拟合，获取的血管管腔的形态差异函数f(x)，所述尺度为计算形态差异函数f(x)时相邻两横截面之间的距离。
  5. 根据权利要求4所述的基于特定的生理参数获取血管压力值的方法，其特征在于，所述形态差异函数f(x)的获取包括：
    基于横截面形态模型，建立各横截面的形态函数；
    对相邻两横截面的形态函数进行拟合，并获取相邻两横截面在不同尺度下的差异变化函数；
    以感兴趣区域血管段的近端终点为参考点，根据差异变化函数获取管腔形态随着到参考点的距离x的变化率，对感兴趣区域血管段从近端终点到远端终点范围内的位置参数进行归一化处理，获取形态差异函数f(x)；所述形态函数包括面积函数、直径函数和边缘位置函数。
  6. 根据权利要求1所述的基于特定的生理参数获取血管压力值的方法，其特征在于：所述血流模型包括固定血流模型及个性化血流模型；所述个性化血流模型包括静息态血流模型和负荷态血流模型，所述血流模型包括感兴趣区域的血流速度V，且当所述血流模型为静息态血流模型时，所述血流速度V可通过血管中流体充盈的速度计算获得，或者通过血管树的形态计算获得；其中，所述血管树的形态至少包括所述血管树的面积、体积和血管树中血管段的管腔直径中的一种或几种；所述血流速度V通过所述血管树的形态计算获得时，所述几何参数还包括所述血管树中血管段的长度、灌注面积及分支角度中的一种或几种。
  7. 根据权利要求1～6任一项所述的基于特定的生理参数获取血管压力值的方法，其特征在于：所述特定的生理参数包括年龄、性别、血压及身体质量指数等可直接获取的生理信息。
  8. 根据权利要求7所述的基于特定的生理参数获取血管压力值的方法，其特征在于：当所述血管系统为冠脉血管系统时，所述特定的生理参数还包括冠状动脉优势类型。
  9. 一种基于特定的生理参数获取血管压力值的装置，其特征在于，所述基 于特定的生理参数获取血管压力值的装置包括：
    数据采集器，所述数据采集器用于获取及存储血管装置的解剖模型中感兴趣区域的几何参数；
    压力值处理器，所述压力值处理器用于建立感兴趣区域的血流模型和基于所述几何参数，建立对应感兴趣区域的几何模型；
    所述压力值处理器还用于，基于所述几何模型和所述血流模型获取血管压力值计算模型；同时，根据所述血管压力值计算模型并结合血流动力学，获取感兴趣区域近端终点处的血流压力Pa，及感兴趣区域血管段近端终点与远端终点之间的压力差数值ΔP。
  10. 根据权利要求9所述的基于特定的生理参数获取血管压力值的装置，其特征在于：所述基于特定的生理参数获取血管压力值的装置还包括纠偏处理器，所述纠偏处理器用于接收个体的一个或多个生理参数，处理后生成纠偏参数，并将所述纠偏参数传递至压力值处理器中对所述几何模型和/或所述血流模型进行修正。
  11. 根据权利要求10所述的基于特定的生理参数获取血管压力值的装置，其特征在于：所述几何模型为所述压力值处理器通过对所述数据采集器传递的所述解剖模型的几何参数进行测算，并结合所述纠偏处理器传递的纠偏参数经拟合校准获得；
    所述血管压力值计算模型包括感兴趣区域近端终点和远端终点之间各个位置处的横截面形态模型及感兴趣区域几何模型中至少一部分的血管段和/或血管树，所述血管树包括至少一段主动脉或者包括至少一段主动脉和由所述主动脉发出的多个冠状动脉；
    所述横截面形态模型为所述压力值处理器通过所述几何模型直接/间接获得；所述横截面形态模型包括各横截面上斑块的有无、斑块的位置、斑块的大小、斑块形成的角度、斑块的组成及斑块组成的变化、斑块的形状及斑块形状的变化。
  12. 根据权利要求10所述的基于特定的生理参数获取血管压力值的装置，其特征在于：所述基于特定的生理参数获取血管压力值的装置还包括速度采集 模块，所述速度采集模块用于获取感兴趣区域的血流速度V，所述血流速度V用以推算所述感兴趣区域近端终点处的第一血流压力P 1及感兴趣区域近端终点处的第一血流压力P 1与远端终点处的第二血流压力P 2之间的压力差数值ΔP；
    所述速度采集器包括速度计算模块及速度提取模块；所述速度提取模块通过数据采集模块直接获取血流速度信息，或通过血流模型直接提取血流速度V；所述速度计算模块包括速度转换模块及速度测算模块，所述血流速度V通过血管中流体充盈的速度经速度转换模块转换获得，或通过几何模型中血管树的形态经速度测算模块计算获得。
  13. 一种用于获取患者血管压力差的设备，所述设备具有处理器，其特征在于：所述处理器被设置为使得所述设备执行以下步骤：
    收集患者特定生理参数和待检血管的几何参数；
    根据所述待检血管的几何参数建立患者的血管模型；
    根据患者特定生理参数修正所述血管模型；
    提供至少一种血管压力差数值的计算模型；
    基于修正后的所述血管模型与所述血管压力差数值的计算模型确定待检血管的血管压力差。
  14. 根据权利要求13所述的用于获取患者血管压力差的设备，其特征在于：所述患者的特定生理参数包括年龄、性别、体温、身体质量指数等可直接获取的人体生理信息中的一个或多个。
  15. 根据权利要求13所述的用于获取患者血管压力差的设备，其特征在于：所述血管压力差数值的计算模型是基于多尺度计算方法而建立的。
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