KR20230114058A - Optimization method of temporal interpolation for the calculation of pulse wave velocity based on 4D flow magnetic resonance imaging apparatus - Google Patents

Abstract

A temporal interpolation optimization method for calculating pulse wave propagation velocity based on 4D magnetic resonance flow imaging is disclosed. A time interpolation optimization method for calculating pulse wave propagation velocity based on a 4-dimensional magnetic resonance flow imaging device includes the steps of setting an elasticity measurement section in the aorta, the number of faces of the set elasticity measurement section, and the coefficient of variation (CoV) The step of setting the allowable value of , the step of deriving the optimal time interpolation interval using the set number of faces and the allowable value of the coefficient of variation, and resetting the elasticity measurement section and the number of faces to use the derived optimal time interpolation interval. and calculating the pulse wave propagation velocity by doing so.

Description

Optimization method of temporal interpolation for the calculation of pulse wave velocity based on 4D flow magnetic resonance imaging apparatus}

The present invention relates to a time interpolation optimization method for calculating pulse wave propagation velocity based on a 4-dimensional magnetic resonance flow-velocity imaging device.

Arterial elasticity decreases due to various causes such as aging and high blood pressure. A decrease in arterial elasticity is known to closely affect cardiovascular disease or stroke. In order to measure the elasticity of these arteries, a 4D flow MRI technique has recently emerged as one of the non-invasive methods. That is, elasticity of the artery can be predicted by obtaining 4-dimensional (3-dimensional space + 1-dimensional time information) blood flow information of the aorta based on the 4-dimensional magnetic resonance flow imaging technique and calculating the pulse wave propagation velocity.

However, since the 4D magnetic resonance flow imaging technique has a low temporal resolution of 30 to 40 ms, blood flow information is generally temporally interpolated at 1 ms intervals and then the pulse wave propagation velocity is calculated. However, the conventional method of calculating the pulse wave propagation velocity through time interpolation has a large error depending on various conditions such as elasticity of the aorta and blood flow, and verification has not been conducted properly.

Republic of Korea Patent Registration No. 10-1334064 (2013.11.22)

The present invention is based on a 4D magnetic resonance flow rate imaging device that derives an optimized time interpolation interval by calculating the pulse wave propagation velocity while changing the time interpolation interval based on the number of planes per compartment, flow rate, elasticity, and heart rate of the aorta. It is to provide a time interpolation optimization method for calculating pulse wave propagation velocity.

According to an aspect of the present invention, a temporal interpolation optimization method for calculating pulse wave propagation velocity based on a 4D magnetic resonance flow-velocity imaging device is disclosed.

A time interpolation optimization method for calculating pulse wave propagation velocity based on a 4D magnetic resonance flow imaging device according to an embodiment of the present invention includes the steps of setting an elasticity measurement section in an aorta, and the number and variation of the elasticity measurement section of the set section. Setting an allowable value of coefficient of variation (CoV), deriving an optimal time interpolation interval using the set allowable value of the number of faces and coefficient of variation, and determining the elasticity measurement section and the number of faces and resetting and calculating the pulse wave propagation velocity using the derived optimal temporal interpolation interval.

Prior to the step of setting the elasticity measurement section, the step of setting disease group information of the patient to be measured is further included.

After the step of deriving the optimal time interpolation interval and before the step of calculating the pulse wave propagation velocity using the derived optimal temporal interpolation interval, a first pulse wave propagation velocity is calculated using the derived optimal temporal interpolation interval, Calculating a plurality of second pulse wave propagation velocities using a plurality of time interpolation intervals shorter than the optimal temporal interpolation interval by a preset length, and calculating a difference between the first pulse wave propagation velocity and the plurality of second pulse wave propagation velocities and recording an allowable value of the variation coefficient when an average of differences between the first pulse wave propagation velocity and the plurality of second pulse wave propagation velocity is within a preset allowable value range.

In the step of recording the allowable value of the coefficient of variation, the allowable value of the coefficient of variation is recorded by mapping to a patient group corresponding to the set disease group information of the patient to be measured.

The coefficient of variation is a coefficient of variation of pulse transit time (PTT) and is represented by the following equation.

The time interpolation optimization method for calculating the pulse wave propagation velocity based on the 4D magnetic resonance flow imaging device according to an embodiment of the present invention changes the time interpolation interval based on the number of planes per section of the aorta, flow rate, elasticity, and heart rate. By calculating the pulse wave propagation velocity and deriving the optimized time interpolation interval, the elasticity of the artery can be predicted accurately and quickly.

1 to 6 are diagrams showing the experimental results of the relationship between various parameters of the aorta.
7 is a flowchart schematically illustrating a temporal interpolation optimization method for calculating the pulse wave propagation velocity based on a 4D magnetic resonance flow imaging apparatus performed by the temporal interpolation optimization apparatus according to an embodiment of the present invention.
8 is a view showing an example of the appearance of the aorta.
9 is a diagram schematically illustrating the configuration of a time interpolation optimization apparatus for calculating pulse wave propagation velocity based on a 4D magnetic resonance flow imaging apparatus according to an embodiment of the present invention.

Singular expressions used herein include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as "consisting of" or "comprising" should not be construed as necessarily including all of the various components or steps described in the specification, and some of the components or some of the steps It should be construed that it may not be included, or may further include additional components or steps. In addition, terms such as "...unit" and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented as hardware or software or a combination of hardware and software. .

Hereinafter, various embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 to 6 are views showing experimental results on the relationship between various parameters of the aorta. Hereinafter, prior to explaining a time interpolation optimization method for calculating pulse wave propagation velocity based on a 4D magnetic resonance imaging device according to an embodiment of the present invention, for convenience of understanding and description of the present invention, FIGS. Reference will be made to examine the relationship between various parameters of the aorta for deriving the optimal time interpolation interval.

Referring to FIG. 1, the graph of FIG. 1 shows the correlation of flow waveforms according to time interpolation intervals. That is, FIG. 1 compares the induced waveforms inside the curve-type silicon phantom model based on the 4-dimensional magnetic resonance imaging device, and shows the flow waveform on a plane 250 mm (Plane 25) away from the reference plane. It is a comparative analysis of correlations using a cross-correlation algorithm. Here, the cross-correlation algorithm used for correlation analysis is only one example, and various algorithms capable of comparing and analyzing the correlation of flow waveforms may be applied.

In (a) of FIG. 1, by using the original time resolution (T ₀ ), the pulse transit time (PTT) at which the flow waveforms in the two planes best match is derived, and the pulse transit time is as much as the pulse wave transit time. 25 as the reference plane. For example, by moving the flow waveforms on Plane 25 in the direction of the reference plane (left) over time, the cross-correlation algorithm is used to find the time when the two flow waveforms match best.

In addition, (b) of FIG. 1 shows that flow waveforms in two planes are matched by performing time interpolation at T ₀ /416 intervals in order to overcome the existing low original time resolution.

Next, referring to FIG. 2, the graph of FIG. 2 shows a comparison of pulse wave transit times according to flow rates and time interpolation intervals.

1, it was confirmed that the pulse wave propagation times corresponding to each other of the two flow waveforms change little by little according to the time interpolation interval. 2 shows the pulse wave transit time (PTT) obtained according to the flow rate and time interpolation interval in more detail.

2 shows that the pulse wave transit time value at a low flow rate is higher than the pulse wave transit time value at a high flow rate. It can be seen that there is a slight tremor before reaching the equilibrium state in both types. In the case of a pulse wave propagation time where the location (red arrow) where the tremor occurs is low, it appears at a place where the time interpolation interval is smaller. You can check. This indicates that, in the case of a model having a low pulse wave transit time, a value similar to the value of the pulse wave transit time in an equilibrium state can be obtained only when the time interpolation interval is small.

Next, referring to FIG. 3 , FIG. 3 compares optimal time interpolation intervals according to the magnitude of CoV and flow rate.

In FIG. 2 above, it was possible to confirm the position of the small tremor before reaching the equilibrium state. In order to mathematically define this position, a coefficient of variation (CoV) represented by the following equation is used.

Using the coefficient of variation, starting with the pulse wave propagation time value obtained at the time interpolation interval of 0.1 ms, increasing the size of the time interpolation value to find the location where the small tremor occurs, and the time interpolation interval at the moment when the location is found is optimal It can be defined as a time interpolation interval.

3(a) to (c) show optimal time interpolation interval values when the coefficient of variation is 0.01, 0.005 and 0.001, respectively.

In the case of (a), since the allowable value for the standard deviation is large, it can be confirmed that the size of the optimal time interpolation value is larger than that of (b) and (c). That is, (a) has the advantage of reducing the calculation time because the time interpolation interval is large, but the difference may be large compared to the pulse wave transit time value in the equilibrium state.

On the other hand, in the case of (c), since the allowable value for the standard deviation is small, it will be very similar to the value of the pulse wave transit time in the equilibrium state, but the time required for calculation is very long.

Accordingly, as in the case of (b), when the coefficient of variation is 0.005, using values within the optimal time interpolation interval obtained, it is possible to derive an accurate pulse wave transit time while reducing the time required for calculation. Pulse wave velocity (PWV) may be calculated from the derived pulse wave transit time (PTT) using the following equation.

Next, referring to FIGS. 4 to 6, FIG. 4 compares pulse wave propagation speeds according to changes in flow conditions, elasticity, and time interpolation intervals, and FIG. 5 compares pulse wave propagation speeds according to changes in heart rate and interpolation intervals. 6 is a comparison of pulse wave propagation speeds according to flow conditions and the number of surfaces.

That is, FIGS. 4 to 6 are pulse waves obtained at a time interpolation interval of 0.1 ms (T ₀ /416) by changing various parameters in order to check whether the optimal time interpolation value obtained in FIG. 3 is well applied. It compares the bias that occurs based on the delivery speed.

For example, it can be confirmed that the larger the size of the time interpolation interval, the larger the bias. In addition, in the case of a model with low elasticity (stiff model), it can be seen that the larger the size of the time interpolation interval, the larger the bias. This indicates that an accurate pulse wave transit time value cannot be obtained with low temporal resolution.

It can be seen that a bias value within about 0.5% occurs even at a time interpolation interval of 1 ms (T ₀ /41.6), which is widely used in the prior art. It is known that a difference between 0 and 10% represents a significant value. Also, it can be seen that the bias value changes according to the number of faces, and it can be seen that the pulse wave propagation speed changes greatly as the number of faces decreases.

FIG. 7 is a flowchart schematically illustrating a temporal interpolation optimization method for calculating pulse wave propagation velocity based on a 4D magnetic resonance flow imaging apparatus performed by a temporal interpolation optimization apparatus according to an embodiment of the present invention. FIG. It is a drawing showing an example. Hereinafter, a temporal interpolation optimization method for calculating pulse wave propagation velocity based on a 4D magnetic resonance flow imaging apparatus according to an embodiment of the present invention will be described with reference to FIG. 7 , but reference will be made to FIG. 8 .

A time interpolation optimization method for calculating pulse wave propagation velocity based on a 4D magnetic resonance imaging device according to an embodiment of the present invention is derived based on the relationships of various parameters of the aorta described above with reference to FIGS. 1 to 6 . That is, based on the above-described experimental results, it was confirmed that the bias of the pulse wave propagation speed changes with respect to various parameters. When applied to a real patient, flow rate and heart rate are variables that cannot be controlled because they vary from patient to patient. Therefore, another time interpolation optimization method can be applied to the embodiment of the present invention by classifying patient disease groups so that the flow rate, elasticity, and heart rate are similar.

In step S710, the time interpolation optimization device sets information on the patient to be measured.

That is, the apparatus for optimizing time interpolation may receive and set patient information including disease group information, number of patients, and personal identification information of the patient to be measured.

In step S720, the time interpolation optimization device sets the elasticity measurement section in the aorta.

That is, the apparatus for optimizing time interpolation may receive information about a section to measure elasticity in the aorta of a patient to be measured and set a section for measuring elasticity.

For example, the aorta is largely divided into three sections as shown in FIG. 8, and elasticity measurement sections may be set among the three sections.

In step S730, the time interpolation optimization device sets the number of faces of the set elasticity measurement section and an allowable value of CoV (Coefficient of variation).

That is, the time interpolation optimizer may receive and set the number of faces and the allowable value of the coefficient of variation for the set elasticity measurement section.

For example, based on the experimental results described above with reference to FIGS. 1 to 6 , when the number of faces is set to 5, it can be confirmed that a pulse wave propagation speed bias of 1 to 2% occurs. Also, as in FIG. 3 described above, allowable values of the coefficient of variation may be set to 0.01, 0.005, and 0.001.

In step S740, the time interpolation optimizer derives an optimal time interpolation interval using the set number of faces and the allowable value of the coefficient of variation.

That is, as described above in FIGS. 2 and 3, starting from the pulse wave transit time value obtained at the time interpolation interval of 0.1 ms, while increasing the size of the time interpolation value of the pulse wave transit time, small fluctuations in the pulse wave transit time occur. A location is found, and the time interpolation interval of the found location can be derived as an optimal time interpolation interval. Here, the small tremor is defined as the above-described variation coefficient of the pulse wave transit time, and can be identified by a set allowable value of the variation coefficient.

In step S750, the time interpolation optimization apparatus calculates a first pulse wave propagation velocity using the derived optimal temporal interpolation interval, and uses a plurality of second temporal interpolation intervals shorter than the optimal temporal interpolation interval by a preset length. A pulse wave propagation speed is calculated, and a difference between a first pulse wave propagation speed and a plurality of second pulse wave propagation velocities is calculated.

In step S760, the time interpolation optimization apparatus determines whether the average of the difference between the first pulse wave propagation velocity and the plurality of second pulse wave propagation velocity is within a preset allowable value range.

If the average of the differences is out of the allowable value range, step S730 is entered.

In step S770, the time interpolation optimizer, when the average of the differences is within a preset allowable value range, records the allowable value of the coefficient of variation (CoV) by mapping it to a patient group corresponding to the set disease group information of the patient to be measured.

In step S780, the time interpolation optimizer resets the elasticity measurement section and the number of faces of the section in the aorta, and calculates the pulse wave propagation velocity using the derived optimal time interpolation interval.

For example, when five planes are used in the preliminary verification procedure of steps S720 to S760, a larger number of planes are used in subsequent calculations, thereby reducing a potential pulse wave propagation velocity bias.

Through this, a pulse wave propagation velocity with high accuracy can be derived for the patient to be measured, and furthermore, the elasticity of the aorta of the patient to be measured can be accurately and quickly predicted.

9 is a diagram schematically illustrating the configuration of a time interpolation optimization device for calculating pulse wave propagation velocity based on a 4D magnetic resonance flow imaging device according to an embodiment of the present invention.

Referring to FIG. 9 , an apparatus for optimizing time interpolation for calculating pulse wave propagation velocity based on a 4D magnetic resonance imaging device according to an embodiment of the present invention includes a processor 10, a memory 20, a communication unit 30, and an interface unit ( 40) included.

The processor 10 may be a CPU or a semiconductor device that executes processing instructions stored in the memory 20 .

Memory 20 may include various types of volatile or non-volatile storage media. For example, memory 20 may include ROM, RAM, and the like.

For example, the memory 20 may store instructions for performing a temporal interpolation optimization method for calculating pulse wave propagation velocity based on a 4D magnetic resonance flow imaging device according to an embodiment of the present invention.

The communication unit 30 is a means for transmitting and receiving data with other devices through a communication network.

The interface unit 40 may include a network interface and a user interface for accessing a network.

On the other hand, the components of the above-described embodiment can be easily grasped from a process point of view. That is, each component can be identified as each process. In addition, the process of the above-described embodiment can be easily grasped from the viewpoint of components of the device.

In addition, the technical contents described above may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. Program commands recorded on the medium may be specially designed and configured for the embodiments or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. A hardware device may be configured to act as one or more software modules to perform the operations of the embodiments and vice versa.

The embodiments of the present invention described above have been disclosed for illustrative purposes, and those skilled in the art having ordinary knowledge of the present invention will be able to make various modifications, changes, and additions within the spirit and scope of the present invention, and such modifications, changes, and additions will be considered to fall within the scope of the following claims.

10: Processor
20: memory
30: Ministry of Communications
40: interface unit

Claims (5)

In the time interpolation optimization method for calculating pulse wave propagation velocity based on 4-dimensional magnetic resonance flow imaging device,
Establishing an elasticity measurement section in the aorta;
Setting an allowable value of the number of surfaces of the set elasticity measurement section and a coefficient of variation (CoV);
deriving an optimal time interpolation interval using the set number of faces and an allowable value of a coefficient of variation; and
Time interpolation for calculation of pulse wave propagation velocity based on a 4D magnetic resonance flow imaging device comprising resetting the elasticity measurement section and the number of surfaces and calculating the pulse wave propagation velocity using the derived optimal time interpolation interval optimization method.
According to claim 1,
Prior to the step of setting the elasticity measurement section,
A time interpolation optimization method for calculating pulse wave propagation velocity based on a 4-dimensional magnetic resonance flow imaging device, further comprising the step of setting disease group information of the patient to be measured.
According to claim 2,
After the step of deriving the optimal temporal interpolation interval and before the step of calculating the pulse wave propagation velocity using the derived optimal temporal interpolation interval,
A first pulse wave propagation velocity is calculated using the derived optimal temporal interpolation interval, and a plurality of second pulse wave propagation velocities are calculated using a plurality of temporal interpolation intervals that are shorter by a predetermined length than the optimal temporal interpolation interval, calculating a difference between a first pulse wave propagation speed and the plurality of second pulse wave propagation velocities; and
and recording an allowable value of the coefficient of variation when an average of differences between the first pulse wave propagation velocity and the plurality of second pulse wave propagation velocity is within a preset allowable value range. Time Interpolation Optimization Method for Calculation of Pulse Wave Transit Velocity Based on Magnetic Resonance Fluid Imaging Device.
According to claim 3,
The step of recording the allowable value of the variation coefficient,
A method for optimizing time interpolation for calculation of pulse wave propagation velocity based on a 4D magnetic resonance imaging device, characterized in that mapping a patient group corresponding to the set disease group information of the target patient to be measured and recording an acceptable value of the coefficient of variation.
According to claim 1,
The coefficient of variation is a coefficient of variation of pulse transit time (PTT), and is represented by the following equation.

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