Determination of flow profiles in arteries 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 flow profiles within arteries based on ultrasound imaging data. [Background technology]

[0002] When using ultrasound to determine blood flow in an artery, the sonographer typically positions an ultrasound probe with an imaging plane at the center of the artery and along the major axis of flow. During the examination, the sonographer typically utilizes two types of measures: color or power Doppler measurements to assess flow distribution across the arterial lumen, and pulsed-wave Doppler measurements to obtain blood flow velocity waveforms. An exemplary method for continuous noninvasive monitoring of multiple arterial parameters in a patient is provided in U.S. Patent Application Publication No. 2012 / 0078106. However, this procedure assumes that the velocity distribution is axisymmetric, with the maximum velocity near the center of the artery or lumen. However, most arteries are not straight, and arterial tortuosity also increases with patient age. Summary of the Invention [Problem to be solved by the invention]

[0003] Among other things, it is an object of the present invention to determine flow profiles in arteries with increased accuracy, particularly in arteries with increased tortuosity. [Means for solving the problem]

[0004] The invention is defined by the 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 ultrasound imaging data, the method comprising: receiving ultrasound imaging data of the artery in a triple mode, the triple mode comprising: B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or power Doppler ultrasound data and From the ultrasound imaging data, arterial dimensions, velocity at the cross section of the artery, and a measure of the asymmetry of the flow profile determining a the size of the artery; the velocity at the cross section of the artery, and a measure of the asymmetry of the flow profile determining a flow profile from A computer-implemented method is provided, comprising:

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

[0007] The method further comprises: the arterial dimensions, the flow profile, and a measure of the asymmetry of the flow profile determining the local arterial curvature based on It further has:

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

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

[0010] In one example, the measure of asymmetry is calculated by determining a position of maximum flow velocity in the arterial cross-section, and determining a parameter representing the deviation of the position from the center of the arterial cross-section based on the position. It has.

[0011] In one example, the parameter representing the deviation of the position of maximum flow velocity in the cross section of the artery is the Dean number.

[0012] According to one aspect of the present invention, there is provided a computer program product comprising instructions for enabling a processor to carry out the above-described 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-transitory) computer-readable medium on which 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, there is provided a system 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 in communication with the processor, the processor configured to control the array of acoustic elements to transmit and receive acoustic signals to generate ultrasound imaging data.

[0015] In one example, the system is a hemodynamic monitoring patch.

[0016] These and other aspects of the invention will be apparent from and elucidated with reference to the embodiments described hereinafter. definition A "cross section" refers to the intersection of the artery with the 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 plane" is used to refer to a plane that intersects the artery, and this plane forms a 90-degree angle with the length of the artery. Thus, a cross-section of an artery includes the possibility of a transverse plane. "Maximum velocity" is used to refer to the maximum velocity encountered in the velocity profile in the cross section of the artery. "Peak velocity" is used to refer to the peak velocity in a transient (i.e., time-evolving) velocity profile at a location, e.g., the peak in a transient velocity profile from pulsed wave Doppler data. "Centerline" refers to the axis of symmetry along the length of the artery, in other words, the axis of the cylinder representing the artery. "Shift in maximum velocity" or "maximum velocity shift" or "velocity maximum shift" or any other combination of these terms refers to the shift of maximum velocity in the velocity profile relative to the center of gravity of the artery cross section, in other words, the distance between the location of the velocity maximum and the central axis of the artery. [Brief explanation of the drawings]

[0017] [Figure 1] 1 shows a schematic diagram of an ultrasound system in which the present invention may be used; [Figure 2] FIG. 1 shows a schematic diagram of a processing circuit that may be used in one embodiment. [Figure 3] 1 shows a diagram of a method according to one embodiment. [Figure 4] 1 shows an exemplary B-mode ultrasound image. [Figure 5] 1 shows an exemplary pulsed wave Doppler ultrasound image. [Figure 6A] 1 shows an exemplary flow contour in an artery. [Figure 6B]1 shows an exemplary flow profile in an artery. [Figure 7] 1 illustrates an exemplary arterial branch. [Figure 8] 1 shows an exemplary color Doppler ultrasound image. [Figure 9] 1 illustrates an exemplary relationship between maximum velocity shift and Dean number. [Figure 10] 1 shows an exemplary flow profile. DETAILED DESCRIPTION OF THE INVENTION

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

[0019] While the following description sets forth exemplary embodiments, it should be understood that this is for purposes of illustration only and is not intended to limit the scope of the invention. It should also be understood that the drawings are merely schematic and are not drawn to scale. It should also be understood that the same reference numerals are used throughout the figures to indicate the same or similar parts.

[0020] The present invention provides a computer-implemented method and system for performing the computer-implemented method to determine a flow profile in an artery 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-implemented method may 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 may be performed retrospectively at any time after image acquisition in a subsequent step.

[0021] FIG. 1 shows a schematic diagram of an exemplary ultrasound imaging system 100. The 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 of the host 130 may also communicate with other types of systems or devices in place of or in addition to the systems mentioned herein, such as, for example, an external memory, an external display, a subject tracking system, an inertial measurement unit, etc. 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 that includes a housing configured for handheld operation by a user. The transducer array 112 can be configured to acquire ultrasound data while a user grasps the housing of the probe 110 such 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 a patient's internal anatomical structures while the probe 110 is positioned on the patient's body. In some embodiments, the probe 110 can be a patch-based external ultrasound probe. For example, the probe can be a hemodynamic patch.

[0023] In other embodiments, probe 110 may be an internal ultrasound imaging device and may include a housing configured to be placed within a patient's body, including the patient's coronary vasculature, peripheral vasculature, esophagus, heart chambers, or other body or tissue. In some embodiments, probe 110 may be an intravascular ultrasound (IVUS) imaging catheter or an intracardiac echocardiography (ICE) catheter. In other embodiments, probe 110 may be a transesophageal echocardiography (TEE) probe. 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 ultrasound signals toward an anatomical object 105 in a patient and receives echo signals that are reflected from the object 105 and return to the transducer array 112. The transducer array 112 can include any suitable number of acoustic elements, including one or more acoustic elements and / or multiple acoustic elements. In some examples, the transducer array 112 includes a single acoustic element. In some examples, the transducer array 112 can include an array of acoustic elements having any number of acoustic elements in any suitable configuration. For example, the transducer array 112 can include between 1 and 10,000 acoustic elements, including values ​​such as 2 acoustic elements, 4 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 greater and lesser values. In some cases, 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, a planar array, a curved array, a curvilinear array, a circumferential array, an annular array, a phased array, a matrix array, a one-dimensional (1D) array, a 1.x-dimensional array (e.g., a 1.5D array), or a 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) may 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 anatomy. In some embodiments, the transducer array 112 may include piezoelectric micromachined ultrasound transducers (PMUTs), capacitive micromachined ultrasound transducers (CMUTs), single crystal, 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, to transmit ultrasound signals and receive ultrasound echo signals. In some embodiments, the beamformer 114 can apply time delays to signals transmitted to individual acoustic transducers in the transducer array 112 so that the acoustic signals are steered in any suitable direction propagating away from the probe 110. The beamformer 114 can further provide image signals to the processor 116 based on the response of the received ultrasound echo signals. The beamformer 114 can include multiple stages of beamforming. Beamforming can reduce the number of signal lines for coupling to the processor 116. In some embodiments, the transducer array 112 in combination with the beamformer 114 may be referred to as an ultrasound imaging component. The beamformer 114 may be a microbeamformer.

[0026] The processor 116 is coupled to the beamformer 114. The processor 116 may also be described as a processor circuit that may include other components in communication with the processor 116, such as a memory, the beamformer 114, a communication interface 118, and / or other suitable components. The processor 116 is configured to process the beamformed image signals. For example, the processor 116 may perform filtering and / or quadrature demodulation to condition the image signals. The processors 116 and / or 134 may be configured to control the array 112 to acquire ultrasound 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 circuitry for transmitting and / or receiving communication signals. The communication interface 118 may include hardware and / or software components that implement a particular communication protocol suitable for transferring signals to the host 130 over the communication link 120. The communication interface 118 may be referred to as a communication device or a communication interface module.

[0028] Communications link 120 may be any suitable communications link. For example, communications link 120 may be a wired link such as a Universal Serial Bus (USB) link or an Ethernet link. Alternatively, communications link 120 may be a wireless link such as an Ultra Wideband (UWB) link, an Institute of Electrical and Electronics Engineers (IEEE) 802.11 Wi-Fi link, or a Bluetooth link.

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

[0030] The processor 136 is coupled to the communications interface 138. The processor 136 may also be described as a processor circuit, which may include other components in communication with the processor 136, such as the memory 133, the communications interface 138, and / or other suitable components. The processor 136 may be configured to generate image data from image signals received from the probe 110. The processor 136 may apply advanced signal processing and / or image processing techniques to the image signals. Examples of image processing include performing pixel-level analysis to evaluate whether there is a change in pixel color that may correspond to an edge of an object (e.g., the edge of an anatomical feature). 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 an ultrasound image of the object 105.

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

[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 video, and / or any imaging information of the object 105.

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

[0034] In particular, ultrasound system 100 can acquire ultrasound images of an artery. More specifically, ultrasound system 100 can be configured to acquire ultrasound imaging data according to method 300, discussed below, including ultrasound data from B-mode ultrasound, pulsed wave Doppler mode ultrasound, and color or power Doppler mode ultrasound. These three ultrasound modes may be acquired from a single command in a "so-called" triple ultrasound mode, in which the three ultrasound modes are used simultaneously to acquire ultrasound data in each of the three modes. In a preferred mode of operation, the ultrasound probe is positioned approximately perpendicular to the artery at an angle of approximately 50 to 70 degrees to acquire the ultrasound data. Note that other angles between 1 and 89 degrees are also contemplated by this disclosure.

[0035] FIG. 2 is a schematic diagram of a processor circuit. The processor circuit 200 may be implemented in the probe 110 and / or the host system 130 of FIG. 1 , or in any other suitable location, such as an external computing system separate from 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 the processor 136, or 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, as well as any other suitable components or circuits within the ultrasound 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. The external storage device may be used to retrieve or store data including images, ultrasound data, and / or patient information. The external display may be used to display output and / or control the processing circuitry, for example, by providing commands.

[0036] The processors 116, 136, 206 contemplated 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, 206 may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction 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 memory 118, 138, 208 contemplated by the present disclosure may be any suitable storage device, such as cache memory (e.g., cache memory of the processor 116, 136, 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 a combination of different types of memory. The memory may be distributed across multiple memory devices and / or located remotely relative to the processing circuitry. In one embodiment, the memory 203 may store instructions 205. The instructions 205 may include instructions that, when executed by the processor 116, 136, 206, cause the processor 116, 136, 206 to perform operations described herein with reference to the probe 110 and / or the host 130 (FIG. 1).

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

[0039] The communications module 208 may include any electronic and / or logical circuitry for facilitating direct or indirect communication of data between the processor circuit 200, the probe 110, the host 130, and / or the display 131. In this regard, the communications module 208 may be an input / output (I / O) device. In some instances, the communications module 208 facilitates direct or indirect communication between various elements of the processor circuit 200, the probe 110 (FIG. 1), and / or the host 130 (FIG. 1).

[0040] According to an exemplary embodiment, the computer-implemented method includes the steps disclosed in FIG.

[0041] In step 310, ultrasound imaging data of an artery is received. The ultrasound data may be received in real time, i.e., during image acquisition, or may be queried upon request from a user or machine from a storage facility, such as a storage device or memory within the image acquisition device, the cloud, or a physical hard drive external to the image acquisition device. In accordance with the present invention, the ultrasound data is: B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or power Doppler ultrasound data and any combination thereof. It will be understood by those skilled in the art that other forms of ultrasound data may be received in addition to and / or instead of the ultrasound data described above.

[0042] According to one embodiment of the present invention, the ultrasound data is B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or power Doppler ultrasound data The received signal may be received from an ultrasound device or system such as that provided in FIG. 1, comprising an array of acoustic elements 112 configured to acquire

[0043] The acquisition mode is B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or power Doppler ultrasound data may be preprogrammed, for example, in a triple ultrasound imaging mode, so that the velocity profiles are acquired from successive or alternating ultrasound shots. This preprogrammed control may be performed in response to a user request to use the triple mode, or in response to a machine command if a velocity profile is selected to be determined.

[0044] According to one embodiment, an ultrasound device with an acoustic array configured for such triple mode may be a hemodynamic 1D ultrasound patch, e.g., an ultrasound patch that can be attached to a subject's skin for continuous monitoring of features within the subject (e.g., heart, lungs, etc.). In such a case, the array of acoustic elements may acquire data sequentially in triple mode (e.g., by acquiring ultrasound data in each mode simultaneously, or by alternating between different modes within triple mode). In other words, for example, data may be acquired first in B-mode, then in pulsed wave Doppler mode, and finally in color or power Doppler mode for a sufficient length of time, and then the acquisition may be repeated. It should be understood that any sequence of these modes is contemplated by the present invention.

[0045] In step 320, the ultrasound data is processed to determine a first set of properties or measurements from the artery. In particular, in step 320: Arterial dimensions, velocity in the artery, and A measure of asymmetry in the flow profile is determined from the ultrasound data.

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

[0047] FIG. 4 illustrates an ultrasound image 410 generated from B-mode ultrasound data of a cross-section of an artery in accordance with one embodiment of the present invention. Specifically, FIG. 4 illustrates a cross-section of an artery at approximately 20-40 degrees to the artery's length and approximately 50-70 degrees to the transverse plane, such that the diameter or radius can be obtained from the minor axis 412 of an exemplary ellipse 414, drawn for illustrative purposes only. Those skilled in the art will appreciate that other ultrasound data, such as color or power Doppler ultrasound data shown in FIG. 8, may also be suitable for determining arterial dimensions. Those skilled in the art will also appreciate that arterial dimension and lumen dimension in the context of the present invention may be used interchangeably.

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

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

[0050] According to one embodiment of the present invention, a measure of flow asymmetry refers to any parameter that indicates the level of asymmetry or distortion of a flow profile relative to a symmetric flow profile. For example, the measure of asymmetry may be the deviation of a flow profile from a symmetric parabolic flow profile. In another example, the measure of asymmetry may be the deviation of the velocity maximum from the central axis of the artery or the center of gravity of the artery cross-section. For example, in curved arteries, so-called Dean vortices may arise, distorting the typically symmetric parabolic flow profile observed in straight arteries such that the maximum velocity within the artery is no longer at the central axis of the artery but shifts away from the central axis at a certain distance. Such flow deviations are illustrated 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 particular velocity. For example, starting at zero velocity for the outermost line, each subsequent line toward the center of the figure represents an increasing velocity.

[0052] In a typical straight artery, the velocity profile may be perfectly symmetric across both of the illustrated axes 680 and 690 (these axes may be in any orientation as long as they are perpendicular to one another). However, in a curved artery, due to Dean vortices, the velocity distribution may shift asymmetrically across at least one axis 690. The maximum velocity is at the center of the region defined by the innermost contour line 640, and therefore shifts from the center of gravity 670 to the new location 630 by a distance 632. The distance at which the velocity shifts to a maximum is proportional to the radius of curvature R of the artery 700, as shown in FIG. c 734.

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

[0054] 8 shows an ultrasound image 810 from color or power Doppler ultrasound data with a heat map 850 of velocities in a cross section of an artery. The heat map may be qualitative, e.g., without indication of absolute velocity values, but it may provide information about the velocity maximum 630 due to changes in color, color intensity, and / or brightness at the maximum. The shift 632 of the velocity maximum 630 relative to the center of gravity 670 of the artery cross section may then be determined, for example, by calculating the distance 632 between the velocity maximum location 630 and the center of gravity 670 in the artery cross section.

[0055] According to one embodiment of the present invention, the velocity maximum shift 632 can be related to a non-dimensional parameter, 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 flows in different curved pipes?", Verkaik et al. (2009) "Estimation of volumetric flow rate in curved pipes based on analysis of axial velocity profiles and computational analysis," and Petrakis et al. (2009) "Comparison of numerical and experimental results for steady flow in curved pipes with circular cross-sections," that the velocity maximum location shift dx 632 depends on the Dean number De according to FIG. 9, at least for self-similar flows. In other words, the local Dean number may be extracted, for example, from FIG. 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 artery diameter, corresponding to a local Dean number of approximately 200.

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

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

[0058] According to an embodiment based on Soedberg (1987) "Viscous flow in curved tubes—I. velocity profiles," a non-dimensional or normalized flow profile u(r) passing through a maximum velocity may be determined from the arterial dimensions and a measure of symmetry. u(r)=w0(r)―w1(r)+ (1) is that the two first terms are TIFF2025536413000002.tif1443 and TIFF2025536413000003.tif1057, where w0 and w1 represent the zeroth and first tangential harmonic contributions to the flow. Higher harmonic contributions may also be considered, e.g., second, third, etc. harmonic contributions. Additionally or alternatively, different expressions for harmonic contributions may also be used: It can be used as follows: TIFF2025536413000004.tif1348.

[0059] Furthermore, r represents the radial coordinate normalized by the total arterial radius (i.e., r = r' / R), which may be derived as described above. Note that velocity profiles along any radial direction of the cross section can be obtained. For example, one velocity profile u(r) may be along axis 680 in FIG. 6A, and another velocity profile u(r) may be along axis 690 shown in FIG. 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 where: q=De / 16 and De is the local Dean number, which represents a measure of asymmetry, which may be derived from the maximum velocity shift, as described above under step 320 of method 300.

[0061] According to an embodiment based on Tijssen (1979), "Axial Dispersion in a Spirally Wound Open Column for Chromatography", the flow profile is estimated by TIFF2025536413000005.tif8134 or TIFF2025536413000006.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 can 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, pulsed wave Doppler measurements, 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 at 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 TIFF2025536413000007.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 TIFF2025536413000008.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 center velocity of turbulent flow, or the average velocity of the entire cross-section obtained by mathematical averaging and is obtained as such. ii) The radius of curvature is The Reynolds number can be related to the Dean number according to TIFF2025536413000009.tif1527.

[0067] Although the method 300 has been presented in a particular 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 between, and / or steps may be removed.

[0068] It is further 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 initially during the acquisition step and analyzed only at the request of an operator and / or specialist. Thus, method 100 may be performed within the image acquisition system (FIG. 1), within the hemodynamic patch, or externally within a separate computing unit (FIG. 2). In another embodiment, method 100 may be performed in the cloud.

[0069] It should be noted that the above-described embodiments illustrate rather than limit the present invention, and that those skilled in the art can design many alternative embodiments without departing from the scope of the appended claims. In the claims, reference signs placed in parentheses shall not be construed as limiting the scope of the claims. The word "comprising" does not exclude the presence of elements or steps other than those listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Implementation can be by means of hardware comprising several distinct elements and / or by a suitably programmed processor. In a device claim enumerating several means, several of these means may be embodied by one and the same item of hardware. Measures recited in mutually different dependent claims may be advantageously used in combination.

Claims

1. 1. A computer-implemented method for determining a flow profile in an artery based on ultrasound imaging data, the method comprising: receiving ultrasound imaging data of the artery in a triple mode, the triple mode comprising: B-mode ultrasound data, Pulsed wave Doppler ultrasound data, and Color or power Doppler ultrasound data and From the ultrasound imaging data, arterial dimensions, velocity at the cross section of the artery, and a measure of the asymmetry of the flow profile determining a the size of the artery; the velocity at the cross section of the artery, and a measure of the asymmetry of the flow profile determining a flow profile from 10. A computer-implemented method comprising:

2. the arterial dimensions, the flow profile, and a measure of the asymmetry of the flow profile determining the local arterial curvature based on The method of claim 1 further comprising:

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

4. The method of claim 1 , wherein the velocity in the artery 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. 6. The method of claim 1, wherein the measure of asymmetry of the flow profile is determined based on the color or power Doppler ultrasound data.

7. The measure of asymmetry is determining a position of maximum flow velocity in the arterial cross-section; and determining, based on the position, a parameter representing a deviation of the position from a center of the arterial cross-section.

7. The method according to claim 1, comprising:

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

9. A computer program product comprising instructions for enabling a processor to carry out the method of any one of claims 1 to 8.

10. 9. A system for determining a flow profile from ultrasound imaging data, the system comprising a processor configured to perform the method of any one of claims 1 to 8.

11. an array of acoustic elements in communication with said processor and the processor is configured to control the array of acoustic elements to transmit and receive acoustic signals to generate ultrasound imaging data. The system of claim 10.

12. 12. The system of claim 10 or 11, wherein the system is a hemodynamic monitoring patch.

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