Determination of intraarterial flow profiles based on ultrasound imaging data.

Abstract

The present invention relates to determining a flow profile in an artery from ultrasound imaging data. To this end, a computer-implemented method is provided for determining a flow profile based on arterial measurements, intra-arterial velocities, and asymmetry measures, the arterial measurements, intra-arterial velocities, and asymmetry measures determined from ultrasound imaging data, including B-mode, pulsed wave Doppler, and color or power Doppler ultrasound imaging data.

Description

Technical Field

[0001] The present invention relates to determining a flow profile in an artery based on ultrasonic imaging data.

Background Art

[0002] When determining blood flow in an artery using ultrasound, an ultrasound examiner typically positions an ultrasound probe having an imaging plane at the center of the artery and along the main axis of the flow. During the examination, the ultrasound examiner typically utilizes two types of measurements, namely, color or power Doppler measurements for evaluating the flow distribution across the lumen of the artery and pulse wave Doppler measurements for obtaining a blood flow velocity waveform. An exemplary method for continuous non-invasive monitoring of multiple arterial parameters of a patient is provided in U.S. Patent Application Publication No. 2012 / 0078106. However, this procedure assumes that the velocity distribution is axisymmetric and that the maximum velocity is close to the artery or lumen center. However, most arteries are not straight, and the tortuosity of arteries increases with the age of the patient.

Summary of the Invention

Problems to be Solved by the Invention

[0003] In particular, an object of the present invention is to determine a flow profile in an artery with enhanced accuracy and enhanced tortuosity.

Means for Solving the Problems

[0004] The present invention is defined by independent claims. Advantageous embodiments are defined in the dependent claims.

[0005] According to one aspect of the present invention, there is provided a computer-implemented method for determining a flow profile in an artery based on ultrasonic imaging data, the method comprising: receiving ultrasonic imaging data of an artery in a triple mode, the triple mode comprising: B-mode ultrasonic data, Pulsed wave Doppler ultrasound data, and Color or powered Doppler ultrasound data It has, From the aforementioned ultrasound imaging data, Arterial dimensions, Velocity in the arterial cross-section, and Measure of the asymmetry of the flow profile The steps to determine, The dimensions of the aforementioned artery, The velocity in the arterial cross-section, and Measure of the asymmetry of the flow profile The steps to determine the flow profile and A computer implementation method having the above characteristics is provided.

[0006] Thus, by obtaining a small number of measurement points (i.e., arterial dimensions, velocity within the arterial cross-section, and a measure of flow asymmetry) from ultrasound imaging data, an accurate flow profile can be determined according to an analytical formula. In other words, the flow profile is reconstructed using knowledge of parabolic flow and parameters determined from ultrasound imaging data. This method may also be performed during or after the ultrasound imaging procedure.

[0007] The method is further, The arterial dimensions, The aforementioned flow profile, and Measure of the asymmetry of the flow profile Steps to determine local arterial curvature based on It also possesses.

[0008] By determining the curvature of the local arteries, it is possible to improve methods for plaque removal and / or stent placement, for example.

[0009] In one example, arterial dimensions are determined based on B-mode ultrasound data. In another example, velocity in an arterial cross-section is determined based on pulsed Doppler ultrasound data. In yet another example, velocity in an arterial cross-section is determined at the center of the arterial cross-section. In yet another example, the measure of flow profile asymmetry is determined based on color or power Doppler ultrasound data.

[0010] In one example, the measure of asymmetry includes the steps of determining the location of the maximum flow velocity in the arterial cross-section, and determining a parameter that represents the deviation of the location from the center of the arterial cross-section based on the location. It holds.

[0011] For example, the parameter that represents the deviation of the position of maximum flow velocity in an arterial cross-section is the Dean number.

[0012] According to one aspect of the present invention, a computer program product is provided which includes instructions for enabling a processor to perform the above method. The computer program product may be software available for download from a server, for example, via the Internet. Alternatively, the computer program product may be a suitable (non-temporary) computer-readable medium on which the instructions are stored, such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware.

[0013] According to one aspect of the present invention, a system is provided for determining a flow profile from ultrasound imaging data, the system comprising a processor configured to perform the above method.

[0014] In one example, the system may further include an array of acoustic elements that communicate with a processor, which is configured to control the array of acoustic elements to send and receive acoustic signals to generate ultrasonic imaging data.

[0015] One example is a hemodynamic monitoring patch.

[0016] These and other aspects of the invention will be apparent from, and will be described with reference to, the embodiments described below. Definitions "Cross-section" refers to the intersection of an artery and an imaging plane in three-dimensional space. Thus, a "cross-section" of an artery is any plane that intersects the artery itself, not necessarily at a 90-degree angle. "Transverse cross-section" is used to refer to a plane that intersects an artery and forms a 90-degree angle with the length of the artery. Thus, the cross-section of an artery includes the possibility of a transverse cross-section. "Maximum velocity" is used to refer to the maximum velocity encountered in the velocity profile in the transverse cross-section of an artery. "Peak velocity" is used to refer to the peak velocity in a transient (i.e., time-evolving) velocity profile at a location. For example, the peak in a transient velocity profile from pulsed wave Doppler data. "Centerline" refers to the axis of symmetry along the length of an artery. In other words, it is the axis of the cylinder representing the artery. "Shift at maximum velocity" or "maximum velocity shift" or "velocity maximum shift" or any other combination of these terms refers to the shift of the maximum velocity in the velocity profile with respect to the centroid of the artery cross-section. In other words, it is the distance between the location of maximum velocity and the central axis of the artery. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] [Figure 1] A schematic diagram of an ultrasonic system in which the present invention can be used is shown. [Figure 2] A schematic diagram of a processing circuit that can be used in one embodiment is shown. [Figure 3] A diagram of a method according to one embodiment is shown. [Figure 4] An exemplary B-mode ultrasonic image is shown. [Figure 5] An exemplary pulsed wave Doppler ultrasonic image is shown. [Figure 6A] An exemplary contour of flow in an artery is shown. [Figure 6B]An exemplary flow profile in an artery is shown. [Figure 7] Exemplary arterial branches are shown. [Figure 8] An exemplary color Doppler ultrasound image is shown. [Figure 9] This illustrates an exemplary relationship between maximum velocity shift and Dean number. [Figure 10] An exemplary flow profile is shown. [Modes for carrying out the invention]

[0018] The present invention is described herein with reference to the drawings.

[0019] The following description illustrates exemplary embodiments, but please understand that these are for illustrative purposes only and are not intended to limit the scope of the invention. Also, please understand that the drawings are schematic diagrams and are not drawn to scale. Furthermore, please understand that the same reference numerals are used throughout the drawings to indicate the same or similar parts.

[0020] The present invention provides a computer implementation method and system for performing the computer implementation method to determine an intraarterial flow profile from ultrasound imaging data. The flow profile may be a 2D flow profile and / or a 3D flow profile. According to exemplary embodiments, the computer implementation method can also be used to determine the curvature of an artery. As disclosed herein, the method may be performed by the system during image acquisition, i.e., in real time, or it may be performed retrospectively in a subsequent step at any point after image acquisition.

[0021] Figure 1 shows a schematic diagram of an exemplary ultrasound imaging system 100. System 100 includes an ultrasound imaging probe 110 that communicates with a host 130 via a communication interface or link 120. The probe 110 may include a transducer array 112, a beamformer 114, a processor 116, and a communication interface 118. The host 130 may include a display 131, a processor 136, a communication interface 138, and a memory 133. The host 130 and / or the processor 136 may also communicate with other types of systems or devices, or in addition to, systems referred to herein, such as external memory, an external display, a subject tracking system, or an inertial measurement device. It is understood that the beamformer may also be a microbeamformer. Furthermore, it is understood that the components shown herein may be configured in alternative configurations. For example, the processor 116 and / or the beamformer 114 may be located outside the probe 110, and / or the display 131 and / or the memory 133 may be located outside the host 130.

[0022] In some embodiments, the probe 110 is an external ultrasound imaging device including a housing configured for user-held operation. The transducer array 112 may be configured to acquire ultrasound data while the user grasps the housing of the probe 110 so that the transducer array 112 is positioned adjacent to or in contact with the patient's skin. The probe 110 is configured to acquire ultrasound data of anatomical structures within the patient's body while the probe 110 is positioned on the patient's body. In some embodiments, the probe 110 may be a patch-based external ultrasound probe. For example, the probe may be a hemodynamic patch.

[0023] In other embodiments, the probe 110 may be an internal ultrasound imaging device and may include a housing configured to be positioned inside the patient's body, including the patient's coronary vascular system, peripheral vascular system, esophagus, cardiac chambers, or other body parts. In some embodiments, the probe 110 may be an intravascular ultrasound (IVUS) imaging catheter or an intracardiac echocardiography (ICE) catheter. In other embodiments, the probe 110 may be a transesophageal echocardiography (TEE) probe. The probe 110 may be any suitable form for any suitable ultrasound imaging application, including both external and internal ultrasound imaging.

[0024] The transducer array 112 emits an ultrasound signal toward the patient's anatomical object 105 and receives an echo signal reflected from the object 105 and returning to the transducer array 112. The transducer array 112 may contain any appropriate number of acoustic elements, including one or more acoustic elements and / or more acoustic elements. In some examples, the transducer array 112 contains a single acoustic element. In some examples, the transducer array 112 may contain an array of acoustic elements having any number of acoustic elements in any appropriate configuration. For example, the transducer array 112 may contain acoustic elements between one and 10,000, including values ​​such as two acoustic elements, four acoustic elements, 36 acoustic elements, 64 acoustic elements, 128 acoustic elements, 500 acoustic elements, 812 acoustic elements, 1,000 acoustic elements, 3,000 acoustic elements, 8,000 acoustic elements, and / or other values ​​greater than and less than. In some embodiments, the transducer array 112 may include an array of acoustic elements having any number of acoustic elements in any suitable configuration, such as a linear array, planar array, curved array, curved array, circumferential array, annular array, phased array, matrix array, one-dimensional (1D) array, 1.x-dimensional array (e.g., a 1.5D array), or two-dimensional (2D) array. The array of acoustic elements (e.g., one or more rows, one or more columns, and / or one or more orientations) can be controlled and activated uniformly or independently. The transducer array 112 may be configured to acquire one-dimensional, two-dimensional, and / or three-dimensional images of the patient's anatomical structure. In some embodiments, the transducer array 112 may include piezoelectric micro-machined ultrasonic transducers (PMUTs), capacitive micro-machined ultrasonic transducers (CMUTs), single crystals, lead zirconate titanate (PZT), PZT composites, other suitable transducer types, and / or combinations thereof.

[0025] The beamformer 114 is coupled to the transducer array 112. The beamformer 114 controls the transducer array 112, for example, for transmitting ultrasonic signals and receiving ultrasonic echo signals. In some embodiments, the beamformer 114 can apply a time delay to the signals transmitted to individual acoustic transducers in the array within the transducer array 112 so that the acoustic signals are steered in any suitable direction away from the probe 110. Based on the response of the received ultrasonic echo signals, the beamformer 114 may further provide the image signal to the processor 116. The beamformer 114 may include multiple stages of beamforming. Beamforming can reduce the number of signal lines to be coupled to the processor 116. In some embodiments, the transducer array 112, combined with the beamformer 114, may be referred to as the ultrasonic imaging component. The beamformer 114 may be a microbeamformer.

[0026] The processor 116 is coupled to the beamformer 114. The processor 116 can also be described as a processor circuit that may include other components that communicate with the processor 116, such as memory, the beamformer 114, a communication interface 118, and / or other appropriate components. The processor 116 is configured to process the beamformed image signal. For example, the processor 116 may perform filtering and / or quadrature demodulation to refine the image signal. The processors 116 and / or 134 may be configured to control the array 112 to acquire ultrasonic data related to the object 105.

[0027] The communication interface 118 is coupled to the processor 116. The communication interface 118 may include one or more transmitters, one or more receivers, one or more transceivers, and / or circuits for transmitting and / or receiving communication signals. The communication interface 118 may include hardware and / or software components that implement a specific communication protocol suitable for transferring signals to the host 130 via the communication link 120. The communication interface 118 may be referred to as a communication device or a communication interface module.

[0028] Communication link 120 can be any suitable communication link. For example, communication link 120 could be a wired link such as a Universal Serial Bus (USB) link or an Ethernet® link. Alternatively, communication link 120 could be a wireless link such as an ultra-wideband (UWB) link, an IEEE 802.11 Wi-Fi link, or a Bluetooth link.

[0029] In host 130, the communication interface 138 can receive image signals. The communication interface 138 may be substantially the same as the communication interface 118. Host 130 may be any suitable computing and display device, such as a workstation, personal computer (PC), laptop, tablet, or mobile phone.

[0030] The processor 136 is coupled to the communication interface 138. The processor 136 may also be described as a processor circuit that may include other components communicating with the processor 136, such as memory 133, the communication interface 138, and / or other appropriate component elements. The processor 136 may be configured to generate image data from the image signal received from the probe 110. The processor 136 may apply advanced signal processing and / or image processing techniques to the image signal. An example of image processing includes performing pixel-level analysis to evaluate whether there are color changes in pixels that may correspond to the edges of an object (e.g., edges of anatomical features). In some embodiments, the processor 136 may form a three-dimensional (3D) volumetric image from the image data. In some embodiments, the processor 136 may perform real-time processing on the image data to provide a streaming video of the ultrasound image of object 105.

[0031] Memory 133 is coupled to processor 136. Memory 133 may be configured to store patient information relating to the patient's medical history, history of procedures performed, anatomical or biological characteristics, traits, or medical conditions related to the patient, measurements, data, or computer-readable instructions such as files, code, software, or other applications, as well as any other appropriate information or data. Memory 133 may be located within host 130. Alternatively, there may be additional external memory or external storage instead of memory 133. External memory may be located outside host 130 and communicate with host 130 and / or processor 136 via an appropriate communication link, as disclosed with respect to communication link 120, and may be a cloud-based server or external storage device. Patient information may include, but is not limited to, measurements, data, files, ultrasound images, ultrasound videos, and / or any imaging information relating to the patient's anatomical structure, and may include other forms of medical history. Patient information may include parameters related to imaging procedures, such as probe position and / or orientation.

[0032] The display 131 is coupled to the processor 136. The display 131 may be a monitor or any suitable display or display device. The display 131 is configured to display ultrasound images, image videos, and / or any imaging information of object 105.

[0033] System 100 can be used to assist an ultrasound examiner or operator in performing an ultrasound scan. The scan may be performed in a point-of-care setting. In some examples, the host 130 is a console or a mobile cart. In some examples, the host 130 may be a mobile device such as a tablet, mobile phone, or portable computer. In yet another example, the host is a server in the cloud, and an external display connects to the host in the cloud. During the imaging procedure, the ultrasound system 100 can acquire ultrasound images of the region of interest.

[0034] In particular, the ultrasound system 100 can acquire ultrasound images of arteries. More specifically, the ultrasound system 100 may be configured to acquire ultrasound imaging data according to method 300, which is discussed below, including ultrasound data from B-mode ultrasound, pulsed Doppler-mode ultrasound, and color or powered Doppler-mode ultrasound. These three ultrasound modes may be acquired from a single command in a “so-called” triple ultrasound mode, and the three ultrasound modes are used simultaneously to acquire ultrasound data in each of the three modes. In a preferred form of operand, the ultrasound probe is positioned approximately perpendicular to the artery at an angle of about 50 to 70 degrees to acquire ultrasound data. Other angles between 1 and 89 degrees should be noted, as also assumed by this disclosure.

[0035] Figure 2 is a schematic diagram of a processor circuit. The processor circuit 200 may be implemented in any other suitable location, such as an external computing system separate from the probe 110 and / or host system 130 in Figure 1, or the image acquisition device or system. One or more processor circuits may be configured to perform the operations described herein. The processor circuit 200 may be part of the processor 116 and / or processor 136, or it may be a separate circuit. In one example, the processor circuit 200 may communicate with the transducer array 112, the beamformer 114, the communication interface 118, the communication interface 138, the memory 133, and / or the display 131, and any other suitable components or circuits in the ultrasonic system 100. As shown, the processor circuit 200 may include a processor 206, a memory 203, and a communication module 208. These elements may communicate with each other directly or indirectly, for example, via one or more buses. The processor circuit may further communicate with an external storage device and / or an external display. External storage devices may be used to retrieve or store data including images, ultrasound data, and / or patient information. External displays may be used, for example, to display outputs and / or control processing circuits by issuing commands.

[0036] The processors 116, 136, and 206 envisioned by this disclosure may include a central processing unit (CPU), a graphical processing unit (GPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a controller, a field-programmable gate array (FPGA) device, another hardware device, a firmware device, or any combination thereof configured to perform the operations described herein. The processors 116, 136, and 206 may also be implemented as a combination of computing devices, for example, a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors working with a DSP core, or any other such configuration. The processor 260 may also implement various deep learning networks, which may include hardware or software implementations. The processor 206 may further include a preprocessor in either a hardware or software implementation.

[0037] The memories 118, 138, and 208 envisioned in this disclosure may be any suitable storage device, such as cache memory (e.g., the cache memory of processors 116, 136, and 206), random access memory (RAM), magnetoresistive RAM (MRAM), read-only memory (ROM), field-programmable gate array read-only memory (PROM), erasable field-programmable gate array read-only memory (EPROM), electrically erasable field-programmable gate array read-only memory (EEPROM), flash memory, solid-state memory devices, hard disk drives, other forms of volatile and non-volatile memory, or combinations of different types of memory. The memory may be distributed across multiple memory devices and / or located remotely from the processing circuitry. In one embodiment, memory 203 may store instructions 205. When executed by processors 116, 136, and 206, the instructions 205 may include instructions that cause processors 116, 136, and 206 to perform the operations described herein with reference to probe 110 and / or host 130 (Figure 1).

[0038] Instruction 205 is sometimes referred to as code. The terms “instruction” and “code” should be interpreted broadly to include any type of computer-readable statement. For example, the terms “instruction” and “code” may refer to one or more programs, routines, subroutines, functions, procedures, etc., and “instruction” and “code” may include a single computer-readable statement or many computer-readable statements. Instruction 205 may form an executable computer program or script. For example, routines, subroutines, and / or functions can be defined in programming languages ​​including, but not limited to, C, C++, C#, Pascal, BASIC, API calls, HTML, XHTML, XML, ASP scripts, JavaScript, FORTRAN, COBOL, Perl, Java, ADA, NET, etc. In particular, instructions disclosed with reference to Method 300 are assumed herein.

[0039] The communication module 208 may include any electronic and / or logic circuits to facilitate direct or indirect data communication between the processor circuit 200, the probe 110, the host 130, and / or the display 131. In this regard, the communication module 208 can be an input / output (I / O) device. In some cases, the communication module 208 facilitates direct or indirect communication between various elements of the processor circuit 200, the probe 110 (Figure 1), and / or the host 130 (Figure 1).

[0040] According to an exemplary embodiment, the computer implementation method includes the steps disclosed in Figure 3.

[0041] In step 310, arterial ultrasound imaging data is received. The ultrasound data may be received in real time, i.e., during image acquisition, or it may be queried in response to a request from the user or machine from a storage device, e.g., a storage device or memory within the image acquisition device, the cloud, or a physical hard drive outside the image acquisition device. According to the present invention, the ultrasound data is B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or powered Doppler ultrasound data It has any combination including It will be understood by those skilled in the art that, in addition to and / or instead of the above-mentioned ultrasonic data, other forms of ultrasonic data may also be received.

[0042] According to one embodiment of the present invention, ultrasound data is B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or powered Doppler ultrasound data It can be received from an ultrasonic device or system, such as the one provided in Figure 1, which includes an array of acoustic elements 112 configured to acquire the signal.

[0043] The acquisition mode is, B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or powered Doppler ultrasound data The system may be pre-programmed, for example, as a triple ultrasound imaging mode, so that the images are acquired from consecutive or alternating ultrasound shots. This pre-programmed control may be performed in response to a user request to use the triple mode, or in response to a machine command, if selected so as to determine the velocity profile.

[0044] According to one embodiment, an ultrasound device comprising an acoustic array configured for the triple modes described above may be a hemodynamic 1D ultrasound patch, for example, an ultrasound patch that can be attached to the skin of a subject for continuous monitoring of features within the subject (e.g., heart, lungs, etc.). In such a case, the array of acoustic elements can continuously acquire data in triple modes (for example, by acquiring ultrasound data simultaneously in each mode, or by alternately acquiring different modes within the triple modes). In other words, for example, data of sufficient duration can be acquired first in mode B, then in pulsed Doppler mode, and finally in color or powered Doppler mode, and then the acquisition can be repeated. It should be understood that any order of these modes is assumed by the present invention.

[0045] In step 320, ultrasound data is processed to determine a first set of characteristics or measurements from the artery. In particular, in step 320, Arterial dimensions, Velocity within the arteries, and Measure of flow profile asymmetry However, this is determined from ultrasound data.

[0046] Arterial dimensions (or lumen dimensions) refer to any dimension related to the cross-section of an artery. Therefore, arterial dimensions (or lumen dimensions) may, for example, be the diameter or radius of the artery. However, arterial dimensions may also refer to, for example, the surface area or perimeter of the arterial cross-section. Arterial or lumen dimensions can be obtained, for example, from B-mode ultrasound data.

[0047] Figure 4 shows an ultrasound image 410 generated from B-mode ultrasound data of an arterial cross-section according to one embodiment of the present invention. Specifically, Figure 4 shows an arterial cross-section at an angle of about 20 to 40 degrees relative to the arterial length and about 50 to 70 degrees relative to the cross-section, and as a result, the diameter or radius can be obtained from the minor axis 412 of an exemplary ellipse 414 drawn for illustrative purposes only. As will be apparent to those skilled in the art, other ultrasound data, such as the color or power Doppler ultrasound data shown in Figure 8, may also be suitable for determining the dimensions of the artery. Furthermore, as will be apparent to those skilled in the art, arterial dimensions and lumen dimensions in the context of the present invention may be used interchangeably.

[0048] According to one embodiment of the present invention, intraarterial velocity refers to local velocity measured in an area smaller than the area of ​​a transverse arterial cross-section. Thus, intraarterial velocity is local velocity at any given position or region within the lumen of the artery. For example, intraarterial velocity may be the velocity at the center of the artery. In another example, velocity may be the velocity at a predetermined position within the artery, such as the location of maximum velocity within the artery, or a location near the edge of the artery. Intraarterial velocity can be determined from any ultrasound mode, such as color Doppler, power Doppler, or pulsed Doppler ultrasound. In one embodiment, velocity is determined from pulsed Doppler ultrasound data. Pulsed Doppler ultrasound mode allows for the measurement of local velocity with higher accuracy than, for example, color or power Doppler ultrasound mode. Therefore, due to its high frame rate, pulsed Doppler ultrasound mode may also be advantageous in resolving important features of the intraarterial velocity waveform, such as systolic peak velocity.

[0049] Figure 5 shows visualized ultrasound data 500 obtained from pulsed-wave Doppler ultrasound mode. The ultrasound data includes an ultrasound image 510 and a velocity timeline 520, where the velocity is determined within a relatively small sample area 530. The timeline displays the evolution of velocity within the sampling area 530 over time, and due to the high frame rate of pulsed-wave Doppler, it resolves the systolic peak 522. Thus, the velocity at a given location in an artery or lumen can be determined as an instantaneous velocity, e.g., as a single point from the timeline 520, or as an average velocity averaged over the velocity within the timeline 520. In addition, the sample area 530 can be at the center of the artery or at any point in the cross-section, e.g., the location of maximum velocity determined from the color Doppler example ultrasound data, as shown in Figure 5.

[0050] According to one embodiment of the present invention, the measure of flow asymmetry refers to any parameter indicating the level of asymmetry or distortion of the flow profile relative to a symmetric flow profile. For example, the measure of asymmetry may be the deviation of the flow profile from a symmetric parabolic flow profile. In another example, the measure of asymmetry may be the deviation of the maximum velocity from the central axis of the artery or the centroid of the arterial cross-section. For example, in a curved artery, so-called Dean vortices may occur, distorting the typically symmetric parabolic flow profile observed in a straight artery such that the maximum velocity in the artery is no longer at the central axis of the artery, but shifts away from the central axis of the artery by a certain distance. Such flow deviations are shown in Figures 6A and 6B.

[0051] Figure 6A shows the 2D velocity distribution in a curved vessel as a contour plot. Each line in the contour plot represents a specific velocity. For example, starting with zero velocity for the outermost line, each subsequent line moving towards the center of the figure represents an increasing velocity.

[0052] In a typical straight artery, the velocity profile may be perfectly symmetrical across both axes 680 and 690 shown in the figure (these axes may be in any orientation as long as the two axes are perpendicular to each other). However, in a curved artery, due to Dean vortices, the velocity distribution may be asymmetrically shifted across at least one axis 690. The maximum velocity is at the center of the region defined by the innermost contour line 640, and is therefore shifted by a distance 632 from the centroid 670 to a new position 630. The distance at which the velocity is shifted to its maximum is the radius of curvature R of the artery 700, as shown in Figure 7. c Determined by 734.

[0053] Figure 6B shows velocity profiles along the asymmetric axis 680 for various radii of curvature 734. For example, an artery with zero radius of curvature exhibits a perfectly symmetric flow profile 631. As the radius of curvature increases, the maximum velocity shifts by a distance 632, and the distance 632 increases as the radius of curvature increases.

[0054] Figure 8 shows an ultrasound image 810 from color or power Doppler ultrasound data having a heatmap 850 of velocities in a cross-section of an artery. The heatmap may be qualitative, for example, without an index of absolute velocity values, but it may provide information about the maximum velocity 630 due to changes in color, color intensity, and / or brightness at the maximum value. The shift 632 of the maximum velocity 630 relative to the centroid 670 of the artery cross-section can then be determined, for example, by calculating the distance 632 between the maximum velocity position 630 and the centroid 670 in the artery cross-section.

[0055] According to one embodiment of the present invention, the maximum velocity shift 632 can be associated with non-dimensional parameters such as the local Dean number De. In particular, it has been shown, for example, in Cieslicki et al. (2012) "Can the Dean number alone characterize the similarity of flow in different bends?", Verkaik et al. (2009) "Analysis of axial velocity profiles and estimation of volumetric flow rates in bends based on computational analysis", and Petrakis et al. (2009) "Comparison of steady flow values ​​and experimental results in bends with circular cross-sections", that the shift dx632 of the maximum velocity position depends on the Dean number De according to Figure 9, at least for self-similar flows. In other words, the local Dean number may be extracted, for example, from Figure 9 by simply determining the maximum velocity shift 632 without requiring a velocity value. For example, the maximum velocity shift may be determined to be 40% of the arterial diameter, such that the local Dean number corresponds to approximately 200.

[0056] It should be noted that the present invention also envisions an approach in which the Dean number obtained according to the velocity shift and Figure 9 may be only a first estimate and may be recalculated at a later stage. The Dean number may be determined iteratively to converge to a value, for example, by combining the blocks of method 300 in different orders and / or by adding and / or removing blocks of method 300.

[0057] Referring again to Figure 3, in step 330, the flow profile within the artery is determined. For example, color or power Doppler ultrasound data may be integrated pixel by pixel on the heatmap 850 in Figure 8. In another example, the flow profile is determined in combination with an analytical formula based on the first set of characteristics determined in step 320. For example, the flow profile can be determined by combining measures of arterial dimensions, intraarterial velocity, and asymmetry. Various suitable methods for determining the flow profile are presented below. However, it is clear that methods that deviate from the following but are within the same spirit are also assumed by the present invention.

[0058] According to embodiments based on Soedberg (1987) "Viscous flow in curved tubes—I. velocity profiles", the dimensionless or normalized flow profile u(r) passing through the maximum velocity may be determined from arterial dimensions and a measure of symmetry. u(r) = w0(r) - w1(r) + ... (1) The two first terms are, TIFF0007848938000001.tif1443 and Given by TIFF0007848938000002.tif1057, where w0 and w1 represent the 0th and 1st tangential harmonic contributions to the flow. Higher harmonic contributions, such as the 2nd, 3rd, etc., may also be considered. In addition, or by substitution, different representations for harmonic contributions are also possible. It can be used like TIFF0007848938000003.tif1348.

[0059] Furthermore, r represents a radial coordinate normalized by the total arterial radius (i.e., r = r' / R), which can be derived as described above. Note that velocity profiles can be obtained along any radial direction of the cross-section. For example, one velocity profile u(r) may be along axis 680 in Figure 6A, and another velocity profile u(r) may be along axis 690 shown in Figure 6A.

[0060] Also, F is, F = 0.5·q 0.6 +1.5 F=0.5(1+q 0.5 ) + 1.5 F = 0.5(1 + q) 0.6 +1.5 This represents a form factor that may be any of the following: q = De / 16 De is a local Dean number representing a measure of asymmetry, which can be derived from the shift of the maximum velocity, as described above under step 320 of Method 300.

[0061] According to an embodiment based on Tijssen (1979), "Axial Dispersion in Spirally Wound Open Columns for Chromatography", the flow profile is estimated by TIFF0007848938000004.tif8134 or TIFF0007848938000005.tif12130. In addition to the definitions of the above variables, a is typically between 0.2 and 0.3, preferably 0.25, and b is between 3.5 and 4, preferably 3.75. It should be understood that a and b are fitting constants and may therefore deviate from the values mentioned and can be removed or replaced by different fitting constants.

[0062] According to the above equation for u(r), if the resulting velocity profile is related to the normalized velocity profile, the shape is accurate, but the absolute value may not be accurate. Therefore, the normalized velocity profile can be shifted or scaled by the velocity derived from, for example, pulse wave Doppler measurements, or by the velocity in the artery. In such a case, the normalized velocity profile u(r), which can be any velocity profile as shown in Figure 6B, can be shifted from dimensionless normalized units to units of distance over time (i.e., m / s, cm / s, feet / s, etc.).

[0063] The inventors have evaluated that when 16 < De < 240, the accuracy of the flow velocity distribution obtained according to equation (1) is within 10% of the actual flow velocity distribution, and when De > 110, the accuracy of the flow velocity distribution obtained according to equation (2) or (3) may be within 10% of the actual flow velocity distribution.

[0064] According to one embodiment, Equation (1) is used for smaller De numbers, and for larger De numbers, Equation (1) can be combined with either Equation (2) or (3) such that either Equation (2) or (3) can be used to obtain an accuracy of the velocity profile within 10% for a larger De number range. The relevant De range in the artery can be, for example, 1 < De < 2000.

[0065] According to one embodiment, a flow profile (which can be a dimensionless normalized flow profile or a scaled and dimensional flow profile) can be further used to determine a 3D flow profile, as proposed by Verkaik et al. (2009). The cross-section (e.g., shown in FIG. 6A) is divided into two semi-circles along a diameter perpendicular to the diameter for which the flow profile is known. Next, the flow rate Q(r,θ) is estimated by assuming axial symmetry of the axial flow in each semi-circle shown in FIG. 10, and the expression TIFF0007848938000006.tif1372 is obtained. This expression can be solved according to partial integration.

[0066] In optional step 340, the radius of curvature R c 734 may be determined from the flow profile u(r). i) From the flow profile determined in step 130, the Reynolds number Re may be determined by TIFF0007848938000007.tif1637. Here, ρ is the blood density, U is the average velocity in the artery at the imaged cross-section, and D and μ are the dynamic viscosities. The average velocity is half of the maximum velocity of laminar flow, the central velocity of turbulent flow, or the average velocity of the entire cross-section obtained by mathematical averaging and is obtained as. ii) The radius of curvature is The Reynolds number can be obtained in relation to the Dean number according to TIFF0007848938000008.tif1527.

[0067] Although Method 300 is presented in a specific order, it will be understood by those skilled in the art that the order of the steps may be changed, additional steps may be added in between, and / or steps may be removed.

[0068] Furthermore, it is understood that the individual steps in Method 300 may be performed in real time, i.e., during or after the examination procedure. For example, ultrasound data may be acquired in real time and analyzed according to Method 300 during the image acquisition procedure, or imaging data may be acquired first during the acquisition step and analyzed only at the request of the operator and / or specialist. Thus, Method 100 may be performed within the image acquisition system (Figure 1), or within the hemodynamic patch, or outside of it, in a separate computing unit (Figure 2). In another embodiment, Method 100 may also be performed in the cloud.

[0069] The embodiments described above are illustrative rather than limiting, and it should be noted that those skilled in the art can design many alternative embodiments without departing from the scope of the appended claims. Reference numerals in parentheses within the claims should not be construed as limiting the claims. The term “including” does not exclude the existence of elements or steps other than those enumerated in the claims. The words “a” or “an” preceding an element do not exclude the existence of multiple such elements. The invention can be implemented by hardware comprising several distinct elements and / or by a appropriately programmed processor. In an apparatus claim enumerating several means, some of these means may be embodied by the same hardware item. Means described in different dependent claims may be used advantageously in combination.

Claims

1. A method for operating a system for determining an arterial flow profile based on ultrasound imaging data, wherein the system has a processor, and the method is The processor receives arterial ultrasound imaging data in triple mode, wherein the data received in triple mode is B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or powered Doppler ultrasound data Includes, The processor then processes the ultrasonic imaging data, Arterial dimensions, Velocity in the arterial cross-section, and Measure of the asymmetry of the flow profile The steps to determine, The aforementioned processor, The dimensions of the aforementioned artery, The velocity in the arterial cross-section, and Measure of the asymmetry of the flow profile The steps to determine the flow profile and A method having.

2. The aforementioned processor, The arterial dimensions, The aforementioned flow profile, and Measure of the asymmetry of the flow profile Steps to determine local arterial curvature based on The method according to claim 1, further comprising:

3. The method according to claim 1, wherein the arterial dimensions are determined based on the B-mode ultrasound data.

4. The method according to claim 1, wherein the velocity in the arterial cross-section is determined based on the pulsed wave Doppler ultrasound data.

5. The method according to claim 1, wherein the velocity in the arterial cross-section is determined at the center of the arterial cross-section.

6. The method according to claim 1, wherein the measure of the asymmetry of the flow profile is determined based on the color or powered Doppler ultrasound data.

7. The method according to claim 1, wherein the parameter representing the deviation of the position of the maximum flow velocity in the arterial cross-section is the Dean number.

8. A computer program having instructions for causing a processor to perform the method according to any one of claims 1 to 7.

9. A system for determining a flow profile from ultrasound imaging data, comprising a processor configured to perform the method according to any one of claims 1 to 7.

10. An array of acoustic elements that communicate with the processor. It has, The processor is configured to generate ultrasonic imaging data by controlling the array of acoustic elements to send and receive acoustic signals. The system according to claim 9.

11. The system according to claim 9, wherein the system is a hemodynamic monitoring patch.

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