KR20230091291A - Method for quantifying cerebral blood flow in the whole brain in a diffusion model - Google Patents

Abstract

The present specification relates to a method for measuring cerebral blood flow by a cerebral blood flow quantification device. The method includes the steps of: generating an area having a three-dimensional grid shape; creating a brain model in the area based on an image of the brain; creating a blood vessel model in an empty area based on the brain model; and calculating cerebral blood flow based on the blood vessel model. The step of generating the blood vessel model may be based on diffusion from a CBF (cerebral blood flow) source.

Description

Method for quantifying cerebral blood flow in the whole brain in a diffusion model {METHOD FOR QUANTIFYING CEREBRAL BLOOD FLOW IN THE WHOLE BRAIN IN A DIFFUSION MODEL}

The present specification proposes a method of quantifying cerebral blood flow throughout the brain using a diffusion model.

Various imaging techniques such as positron emission tomography (PET), functional magnetic resonance imaging, magnetic resonance angiography, and computed tomography have been developed to visualize the three-dimensional structure of the brain and cerebral blood vessels. Advances in these imaging technologies have made it possible to measure cerebral blood flow throughout the brain.

However, despite the rapid development of imaging technology, it is still difficult to numerically predict cerebral blood flow because cerebrovascular structure modeling at the clinical level is complicated.

An object of the present specification is to propose a method for quantifying cerebral blood flow throughout the brain.

The technical problems to be achieved by this specification are not limited to the above-mentioned technical problems, and other technical problems not mentioned are clear to those skilled in the art from the detailed description of the specification below. will be understandable.

One aspect of the present specification is a method for measuring cerebral blood flow by a cerebral blood flow quantification device, comprising: generating a region having a three-dimensional lattice shape; generating a brain model on the region based on a photographed image of the brain; generating a blood vessel model in an empty area based on the brain model; and calculating cerebral blood flow based on the blood vessel model. Including, the generating of the blood vessel model may be based on diffusion from a cerebral blood flow (CBF) source.

In addition, the CBF source is the following equation:

는 CSF(cerebrospianl fluid) 영역의 소스값이고, 상기 x는 상기 영역 상의 노드이며, 상기

는 CSF 네트워크이고, 상기

는 상기 뇌혈관 네트워크의 노드이며, 상기

는 상기 뇌혈관 네트워크에서의 소스값이고, 상기 r은 확산영역에서의 상기

의 영향범위이며, 상기

는 뇌혈관의 최소 지름과 최대 지름 사이의 상대적인 직경일 수 있다.It is set based on, and

Is a source value of a Cerebrospian Fluid (CSF) area, where x is a node on the area,

is the CSF network, and

Is a node of the cerebrovascular network, wherein

is a source value in the cerebrovascular network, and r is the

is the range of influence of

May be a relative diameter between the minimum and maximum diameters of cerebral blood vessels.

는 다음의 수학식 :

Also, the above

is the following equation:

는 0.0000135/s/100g로 설정되고, 상기

는 상기

에서의 혈류량일 수 있다.Based on, the above

is set to 0.0000135/s/100g, and

said

may be the blood flow in

는 다음의 수학식 :Also, the above

is the following equation:

은 3으로 설정되며, 상기

는 0 이상 1 이하의 값으로 설정될 수 있다.Based on, h is the height of the lattice form,

is set to 3, and

may be set to a value greater than or equal to 0 and less than or equal to 1.

는 다음의 수학식 :Also, the above

is the following equation:

는 뇌혈관의 최대 지름이고, 상기

는 뇌혈관의 최소 지름일 수 있다.Based on, the above

is the maximum diameter of the cerebral blood vessel,

may be the minimum diameter of a cerebral blood vessel.

In addition, the step of calculating the cerebral blood flow

The following equation:

, where C is cerebral blood flow (CBF), t is time, and D is a diffusion coefficient.

Another aspect of the present specification is a cerebral blood flow quantification device for measuring cerebral blood flow, comprising: a memory; and a processor that functionally controls the memory, wherein the processor creates a region having a three-dimensional lattice shape, generates a brain model on the region based on a brain image, and Based on the model, a blood vessel model is created in an empty area, cerebral blood flow is calculated based on the blood vessel model, and the blood vessel model can be generated based on diffusion from a cerebral blood flow (CBF) source. there is.

According to an embodiment of the present specification, after defining a CBF source, cerebral blood flow can be quantified through a diffusion model using the CBF source.

Effects obtainable in the present specification are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below. .

1 is a block diagram for explaining an electronic device related to the present specification.
2 is an example of a method for predicting a cerebral blood flow diffusion process related to the present specification.
3 is an example of a vascular network diffusion model related to the present specification.
4 illustrates a method of transmitting a source value from a node of a cerebrovascular network to a node of a diffusion layer to which the present specification can be applied.
5 is an embodiment of the present specification.
The accompanying drawings, which are included as part of the detailed description to aid understanding of the present specification, provide examples of the present specification and describe technical features of the present specification together with the detailed description.

Hereinafter, the embodiments disclosed in this specification will be described in detail with reference to the accompanying drawings, but the same or similar components are given the same reference numerals regardless of reference numerals, and redundant description thereof will be omitted. The suffixes "module" and "unit" for components used in the following description are given or used together in consideration of ease of writing the specification, and do not have meanings or roles that are distinct from each other by themselves. In addition, in describing the embodiments disclosed in this specification, if it is determined that a detailed description of a related known technology may obscure the gist of the embodiment disclosed in this specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in this specification, the technical idea disclosed in this specification is not limited by the accompanying drawings, and all changes included in the spirit and technical scope of this specification , it should be understood to include equivalents or substitutes.

Terms including ordinal numbers, such as first and second, may be used to describe various components, but the components are not limited by the terms. These terms are only used for the purpose of distinguishing one component from another.

It is understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, but other elements may exist in the middle. It should be. On the other hand, when an element is referred to as “directly connected” or “directly connected” to another element, it should be understood that no other element exists in the middle.

Singular expressions include plural expressions unless the context clearly dictates otherwise.

In this application, terms such as "comprise" or "have" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

1 is a block diagram for explaining an electronic device related to the present specification.

The electronic device 100 includes a wireless communication unit 110, an input unit 120, a sensing unit 140, an output unit 150, an interface unit 160, a memory 170, a control unit 180, and a power supply unit 190. ) and the like. The components shown in FIG. 1 are not essential to implement an electronic device, so an electronic device described in this specification may have more or fewer components than those listed above.

More specifically, among the components, the wireless communication unit 110 is between the electronic device 100 and the wireless communication system, between the electronic device 100 and other electronic devices 100, or between the electronic device 100 and an external server. It may include one or more modules enabling wireless communication between Also, the wireless communication unit 110 may include one or more modules that connect the electronic device 100 to one or more networks.

The wireless communication unit 110 may include at least one of a broadcast reception module 111, a mobile communication module 112, a wireless Internet module 113, a short-distance communication module 114, and a location information module 115. .

The input unit 120 includes a camera 121 or video input unit for inputting a video signal, a microphone 122 for inputting an audio signal, or a user input unit 123 for receiving information from a user, for example , a touch key, a push key (mechanical key, etc.). Voice data or image data collected by the input unit 120 may be analyzed and processed as a user's control command.

The sensing unit 140 may include one or more sensors for sensing at least one of information within the electronic device, environmental information surrounding the electronic device, and user information. For example, the sensing unit 140 may include a proximity sensor 141, an illumination sensor 142, a touch sensor, an acceleration sensor, a magnetic sensor, and gravity. Sensor (G-sensor), gyroscope sensor (gyroscope sensor), motion sensor (motion sensor), RGB sensor, infrared sensor (IR sensor), finger scan sensor, ultrasonic sensor , optical sensor (e.g. camera (see 121)), microphone (see 122), battery gauge, environmental sensor (e.g. barometer, soil hygrometer, thermometer, radiation detection sensor) , a heat sensor, a gas sensor, etc.), and a chemical sensor (eg, an electronic nose, a health care sensor, a biometric sensor, etc.). Meanwhile, the electronic device disclosed in this specification may combine and utilize information sensed by at least two or more of these sensors.

The output unit 150 is for generating an output related to sight, hearing, or touch, and includes at least one of a display unit 151, a sound output unit 152, a haptic module 153, and an optical output unit 154. can do. The display unit 151 may implement a touch screen by forming a mutual layer structure or integrally with the touch sensor. Such a touch screen may function as a user input unit 123 providing an input interface between the electronic device 100 and the user and provide an output interface between the electronic device 100 and the user.

The interface unit 160 serves as a passage for various types of external devices connected to the electronic device 100 . The interface unit 160 connects a device equipped with a wired/wireless headset port, an external charger port, a wired/wireless data port, a memory card port, and an identification module. It may include at least one of a port, an audio input/output (I/O) port, a video input/output (I/O) port, and an earphone port. In response to the external device being connected to the interface unit 160, the electronic device 100 may perform appropriate control related to the connected external device.

In addition, the memory 170 stores data supporting various functions of the electronic device 100 . The memory 170 may store a plurality of application programs (application programs or applications) running in the electronic device 100 , data for operating the electronic device 100 , and commands. At least some of these application programs may be downloaded from an external server through wireless communication. In addition, at least some of these application programs may exist on the electronic device 100 from the time of shipment for basic functions of the electronic device 100 (eg, incoming and outgoing calls, outgoing functions, message receiving, and outgoing functions). Meanwhile, the application program may be stored in the memory 170, installed on the electronic device 100, and driven by the control unit 180 to perform an operation (or function) of the electronic device.

The controller 180 controls general operations of the electronic device 100 in addition to operations related to the application program. The control unit 180 may provide or process appropriate information or functions to the user by processing signals, data, information, etc. input or output through the components described above or by running an application program stored in the memory 170.

In addition, the controller 180 may control at least some of the components discussed in conjunction with FIG. 1 in order to drive an application program stored in the memory 170 . Furthermore, the controller 180 may combine and operate at least two or more of the components included in the electronic device 100 to drive the application program.

The power supply unit 190 receives external power and internal power under the control of the controller 180 and supplies power to each component included in the electronic device 100 . The power supply unit 190 includes a battery, and the battery may be a built-in battery or a replaceable battery.

At least some of the components may operate in cooperation with each other in order to implement an operation, control, or control method of an electronic device according to various embodiments described below. Also, the operation, control, or control method of the electronic device may be implemented on the electronic device by driving at least one application program stored in the memory 170 .

An apparatus for quantifying cerebral blood flow, which will be described later, may include the aforementioned electronic device.

2 is an example of a method for predicting a cerebral blood flow diffusion process related to the present specification.

The distribution of cerebral blood flow (CBF) throughout the brain is regulated by the transport of blood cells through blood vessels (arteries to veins). Therefore, in order to develop a computational model for predicting CBF distribution throughout the brain, it is essential to computationally construct the entire brain vessel geometry from major vessels to capillary ends. However, it is not easy to predict the CBF value computationally even after obtaining a complex cerebrovascular shape using MRI and positron emission tomography (PET).

Referring to FIG. 2, an efficient approach to predict CBF is to define a CBF source term in major blood vessels and then assume transport of blood cells through the microvascular network as a diffusion model. Here, the colored area means the diffusion area.

3 is an example of a vascular network diffusion model related to the present specification.

는 혈관의 직경이고,

는 뇌혈관 네트워크(

)의 노드이며, x는 확산 영역의 노드이다. h는 mesh size를 의미한다.Referring to FIG. 3, a cerebrovascular network model of a CBF diffusion area is illustrated. The shaded area represents the cerebrovascular network, and the CBF diffusion area is a separate background area.

is the diameter of the blood vessel,

is the cerebrovascular network (

), and x is the node of the diffusion region. h means mesh size.

Equation 1 below illustrates a blood flow calculation method assuming cerebrovascular diffusion.

는 뇌혈관 네트워크와 뇌 조직을 포함한 전체 영역을 의미한다.Referring to Equation 1, C is CBF, t is time, and D is the diffusion coefficient. S is a CBF source in the cerebrovascular structure,

means the entire area including the cerebrovascular network and brain tissue.

More specifically, D can be determined as a specific value by the permeability of blood cells through the microvascular network of brain tissue.

값으로 설정될 수 있다. 만일, 격자점(grid point)이 뇌척수액(cerebrospianl fluid, CSF)의 바깥 또는 뇌실의 안쪽에 있는 경우에는 D는 0으로 설정될 수 있다.For example, in the gray matter of the brain, D

value can be set. If the grid point is outside the cerebrospian fluid (CSF) or inside the ventricle, D may be set to 0.

Here, S can be measured as the amount of blood flow in cerebrovascular geometry.

Equation 2 below illustrates three types for setting S.

로 설정될 수 있다.Referring to Equation 2, first, the CSF region is surrounded by major blood vessels that supply oxygen and nutrients to tissues, and since it is difficult to model these blood vessels, S is a specific constant value in the CSF region.

can be set to

는 혈류량(

)에 비례할 수 있다. 따라서,

는 다음의 수학식 3과 같이 정의될 수 있다.Second,

is the blood volume (

) can be proportional to thus,

Can be defined as in Equation 3 below.

는 실험적 파라미터로서, 특정 상수값으로 정의되거나, 혈관에서는 혈류역학을 고려한 변수의 함수로 정의될 수 있다.Referring to Equation 3,

is an experimental parameter, and may be defined as a specific constant value, or may be defined as a function of a variable considering hemodynamics in blood vessels.

Finally, in other parts of the entire area, S may be set to 0.

4 illustrates a method of transmitting a source value from a node of a cerebrovascular network to a node of a diffusion layer to which the present specification can be applied.

In more detail, Fig. 4(a) illustrates source nodes in the diffusion region and the cerebrovascular region.

는 뇌혈관 네트워크의 소스값을 의미한다.Referring to FIG. 4(a), S(x) is the source value of the diffusion region,

denotes the source value of the cerebrovascular network.

4(b) illustrates the influence radius from the source node of the cerebrovascular network.

는 확산 영역에서

의 영향범위를 의미하고,

는 0에서 1까지의 뇌혈관의 최소 지름과 최대 지름 사이의 상대적인 직경을 의미한다. Referring to Figure 4 (b),

is in the diffusion region

means the range of influence of

Means the relative diameter between the minimum and maximum diameters of cerebral blood vessels from 0 to 1.

More specifically, since the lattice points between the brain tissue and the cerebrovascular network do not coincide, the source values of the cerebrovascular nodes may be distributed to adjacent brain tissue lattice points in the r range.

Therefore, the influence range can be defined as Equation 4 below through r.

은 실험적 파라미터이다.In Equation 4, r is the influence radius from the source node of the cerebrovascular network, h is the grid size,

is an experimental parameter.

을 정의할 수 있다.Equation 5 below is

can define

와

는 주어진 뇌혈관의 최대/최소 지름이다. 따라서,

는 0 이상 1 이하의 값을 가질 수 있다.Referring to Equation 5,

and

is the maximum/minimum diameter of a given brain vessel. thus,

may have a value greater than or equal to 0 and less than or equal to 1.

5 is an embodiment of the present specification.

Referring to FIG. 5 , the apparatus for quantifying cerebral blood flow may measure cerebral blood flow in the entire brain assuming a diffusion model using the above-described cerebral blood flow diffusion process prediction method.

The cerebral blood flow quantification device generates a region having a three-dimensional lattice shape (S5010). For example, the grid size (h) may be set to a specific value (eg, 3), and in this case, the size of the grid corresponding to the x-axis (dx), y-axis (dy), and z-axis (dz) It can be set to the same value (3).

The cerebral blood flow quantification apparatus creates a brain model on a region based on the brain image (S5020). For example, the brain model may be generated using computed tomography (CT), magnetic resonance image (MRI), or the like for imaging the brain structure.

The apparatus for quantifying cerebral blood flow generates a blood vessel model based on the brain model (S5030). For example, the apparatus for quantifying cerebral blood flow may generate a blood vessel model in an empty region of the brain model by setting a CBF source of a cerebrovascular structure by assuming diffusion in the CBF source.

는 0.0338 mm^3/s^2/10g로 설정될 수 있다. 또한,

를 계산하기 위한 수학식 3에서

는 0.0000135 /s/100g로 설정될 수 있으며,

를 계산하기 위한 수학식 4에서

은 3으로 설정될 수 있다.The CBF source (S) may be set based on Equation 2 above. For example, referring to Equation 2,

may be set to 0.0338 mm^3/s^2/10g. also,

In Equation 3 for calculating

can be set to 0.0000135 /s/100g,

In Equation 4 for calculating

may be set to 3.

로 설정될 수 있고, dt는 3600 sec (time interval)로 설정되며, total time은 3600 * 20 sec의 값을 갖을 수 있다.The apparatus for quantifying cerebral blood flow calculates cerebral blood flow based on the blood vessel model (S5040). Cerebral blood flow can be calculated based on Equation 1 above. For example, referring to Equation 1, D is

, dt is set to 3600 sec (time interval), and the total time may have a value of 3600 * 20 sec.

The above specification can be implemented as computer readable code on a medium on which a program is recorded. The computer-readable medium includes all types of recording devices in which data that can be read by a computer system is stored. Examples of computer-readable media include Hard Disk Drive (HDD), Solid State Disk (SSD), Silicon Disk Drive (SDD), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. , and also includes those implemented in the form of a carrier wave (eg, transmission over the Internet). Accordingly, the above detailed description should not be construed as limiting in all respects and should be considered illustrative. The scope of this specification should be determined by reasonable interpretation of the appended claims, and all changes within the equivalent scope of this specification are included in the scope of this specification.

In addition, although services and embodiments have been described above, this is only an example and does not limit the present specification, and those skilled in the art to which this specification belongs will not deviate from the essential characteristics of the present service and embodiments. It will be appreciated that various modifications and applications not exemplified above are possible. For example, each component specifically shown in the embodiments can be modified and implemented. And differences related to these modifications and applications should be construed as being included in the scope of the present specification as defined in the appended claims.

Claims (7)

In the method for measuring cerebral blood flow by a cerebral blood flow quantification device,
generating a region having a three-dimensional grid shape;
generating a brain model on the region based on a photographed image of the brain;
generating a blood vessel model in an empty area based on the brain model; and
calculating cerebral blood flow based on the blood vessel model;
Including,
The step of generating the blood vessel model
A measurement method based on diffusion in a cerebral blood flow (CBF) source.
According to claim 1,
The CBF source is
The following equation:

is set based on
remind

Is a source value of a Cerebrospian Fluid (CSF) area, where x is a node on the area,

is the CSF network,
remind

Is a node of the cerebrovascular network, wherein

is a source value in the cerebrovascular network, and r is the

is the range of influence of

Is the relative diameter between the minimum and maximum diameters of cerebral blood vessels, measurement method.
According to claim 2,
remind

Is
The following equation:

based on
remind

is set to 0.0000135/s/100g,
remind

said

Blood flow in, measurement method.
According to claim 2,
remind

Is
The following equation:

based on
The h is the height of the lattice form,
remind

is set to 3,
remind

Is set to a value of 0 or more and less than 1, a measurement method.
According to claim 4,
remind

Is
The following equation:

based on
remind

is the maximum diameter of the cerebral blood vessel,
remind

Is the minimum diameter of cerebral blood vessels, measurement method.
According to claim 2,
The step of calculating the cerebral blood flow is
The following equation:

based on
The C is CBF (cerebral blood flow),
Wherein t is time,
The D is a diffusion coefficient, a measurement method.
In the cerebral blood flow quantification device for measuring cerebral blood flow,
Memory; and
A processor functionally controlling the memory; includes,
The processor
A region having a three-dimensional lattice shape is created, a brain model is created on the region based on a brain image, a blood vessel model is created in an empty region based on the brain model, and the blood vessel model Based on, cerebral blood flow is calculated,
The blood vessel model
An apparatus for quantifying cerebral blood flow, which is generated based on diffusion in a CBF (cerebral blood flow) source.

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