Determining a flow profile in an artery based on ultrasound imaging data

Abstract

The present invention relates to determining a flow profile in an artery based on ultrasound imaging data. To this end, a computer-implemented method (300) is provided for determining (330) a flow profile based on an artery dimension, a velocity in the artery, and a measure of asymmetry, wherein the artery dimension, the velocity in the artery, and the measure of asymmetry are determined (320) based on ultrasound imaging data, the ultrasound imaging data including B-mode ultrasound imaging data, pulsed wave Doppler ultrasound imaging data, 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 ultrasound imaging data. Background Art

[0002] When using ultrasound to determine blood flow in an artery, an ultrasound physician typically positions the ultrasound probe so that the imaging plane is in the middle of the artery and along the main axis of the blood flow. During the examination, the ultrasound physician typically utilizes two types of measurements: color or power Doppler measurements for evaluating the flow distribution within the artery lumen, and pulsed-wave Doppler measurements for obtaining the blood flow velocity waveform. A exemplary method for continuously and non-invasively monitoring multiple arterial parameters of a patient is provided in US2012 / 0078106. However, this process assumes that the velocity distribution is axisymmetric and that the maximum velocity is close to the center of the artery or lumen. However, most arteries are not straight, and the tortuosity of arteries also increases with the age of the patient. Summary of the Invention

[0003] Among other things, an object of the present invention is to determine a flow profile in an artery with increased accuracy, especially when the tortuosity of the artery increases.

[0004] The present 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:

[0006] - receiving triple-mode ultrasound imaging data of the artery, wherein the triple mode comprises:

[0007] - B-mode ultrasound data,

[0008] - pulsed-wave Doppler ultrasound data, and

[0009] - color or power Doppler ultrasound data;

[0010] - determining (320) based on the ultrasound imaging data

[0011] - the artery dimensions;

[0012] - the velocity in the artery cross-section, and

[0013] - a measure of the asymmetry of the flow profile; and

[0014] - determining the flow profile according to

[0015] - the artery dimensions,

[0016] - the velocity in the artery cross-section, and

[0017] - A measure of the asymmetry of the flow profile.

[0018] In this way, by obtaining a number of measurement points from the ultrasound imaging data (i.e., arterial dimensions, velocity in the arterial cross-section, and a measure of the asymmetry of the flow), an accurate flow profile can be determined according to the analytical expression. In other words, the flow profile is reconstructed using the knowledge of parabolic flow and the parameters determined from the ultrasound imaging data. The method can also be performed during or after the ultrasound imaging process.

[0019] The method may further include:

[0020] - Determining a local arterial curvature based on

[0021] - The arterial dimensions,

[0022] - The flow profile, and

[0023] - A measure of the asymmetry of the flow profile.

[0024] By determining the local arterial curvature, it is possible to improve methods for, for example, plaque removal and / or stent placement.

[0025] In an example, the arterial dimensions are determined based on the B-mode ultrasound data. In an example, the velocity in the arterial cross-section is determined based on the pulsed wave Doppler ultrasound data. In an example, the velocity in the arterial cross-section is determined at the center of the arterial cross-section. In an example, a measure of the asymmetry of the flow profile is determined based on the color or power Doppler ultrasound data.

[0026] In an example, the measure of the asymmetry includes determining the position of the maximum flow velocity in the arterial cross-section; and, based on the position, determining a parameter representing the deviation of the position relative to the center of the arterial cross-section.

[0027] In an example, the parameter representing the deviation of the position of the maximum flow velocity in the arterial cross-section is the Dean number.

[0028] According to one aspect of the present invention, there is provided a computer program product including instructions for enabling a processor to execute the above method. The computer program product may be software that can be downloaded from a server via, for example, the Internet. Alternatively, the computer program product may be a suitable (non-transitory) computer-readable medium on which the instructions are stored, such as an optical storage medium or a solid-state medium provided together with or as part of other hardware.

[0029] According to one aspect of the present invention, there is provided a system for determining a flow profile based on ultrasonic imaging data, the system including a processor configured to perform the above method.

[0030] In an example, the system may further include

[0031] - an array of acoustic elements, which communicates with the processor, and

[0032] - wherein the processor is configured to control the array of acoustic elements to transmit and receive acoustic signals to generate ultrasonic imaging data.

[0033] In an example, the system is a hemodynamic monitoring patch.

[0034] These and other aspects of the present invention will be apparent from, and will be elucidated with reference to, the embodiments described hereinafter.

[0035] Definition

[0036] "Cross-section" refers to the intersection of an artery in three-dimensional space with an imaging plane. Thus, a "cross-section" of an artery is any plane that intersects the artery itself (not necessarily at a 90-degree angle).

[0037] "Transverse cross-section" is used to refer to a plane that intersects an artery, where the plane 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.

[0038] "Maximum velocity" is used to refer to the maximum velocity generated in the velocity profile across the transverse cross-section of an artery.

[0039] "Peak velocity" is used to refer to the peak velocity in an instantaneous (i.e., time-varying) velocity profile at a location. For example, the peak in the instantaneous velocity profile from pulsed-wave Doppler data.

[0040] "Centerline" refers to the axis of symmetry along the length of an artery. In other words, the axis of the cylinder representing the artery.

[0041] "Offset of the maximum velocity" or "maximum velocity offset" or "velocity maximum offset" or any other combination of these terms refers to the offset of the maximum velocity in the velocity profile relative to the centroid of the artery cross-section. In other words, the distance between the position of the velocity maximum and the central axis of the artery. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of an ultrasonic system is shown, in which the present invention can be used.

[0043] Figure 2 A schematic diagram of a processing circuit that can be used in an embodiment is shown.

[0044] Figure 3 A diagram showing a method according to an embodiment.

[0045] Figure 4 Shows a exemplary B-mode ultrasound image.

[0046] Figure 5 Shows a exemplary pulsed wave Doppler ultrasound image.

[0047] Figure 6A Shows a exemplary flow profile in an artery.

[0048] Figure 6B Shows a exemplary flow overview in an artery.

[0049] Figure 7 Shows a exemplary arterial branch.

[0050] Figure 8 Shows a exemplary color Doppler ultrasound image.

[0051] Figure 9 Shows a exemplary relationship between the maximum velocity shift and the Dean number.

[0052] Figure 10 Shows a exemplary flow overview. Detailed Description

[0053] The present invention will be described with reference to the accompanying drawings.

[0054] It should be understood that the following description is intended for illustrative purposes only when indicating exemplary embodiments, and is not intended to limit the scope of the present invention. It should also be understood that the drawings are only schematic and not drawn to scale. It should further be understood that the same reference numerals are used throughout the drawings to indicate the same or similar parts.

[0055] The present invention provides a computer-implemented method and a system for performing the computer-implemented method to determine a flow profile within an artery based on ultrasound imaging data. The flow profile can be a 2D flow profile and / or a 3D flow profile. According to an exemplary embodiment, the computer-implemented method can also be used to determine the curvature of an artery. As disclosed herein, the method can be performed by the system (i.e., in real time) during image acquisition, or can be performed a posteriori in a subsequent step (at any time after image acquisition).

[0056] Figure 1A schematic diagram showing an exemplary ultrasound imaging system 100 is presented. System 100 includes an ultrasound imaging probe 110 that communicates with a host 130 via a communication interface or link 120. Probe 110 may include a transducer array 112, a beamformer 114, a processor 116, and a communication interface 118. Host 130 may include a display 131, a processor 136, a communication interface 138, and a memory 133. Instead of or in addition to the systems mentioned herein, host 130 and / or processor 136 of host 130 may also communicate with other types of systems or devices, such as external memory, external display, object tracking system, inertial measurement unit, etc. It is to be understood that the beamformer may also be a microbeamformer. It is also to be understood that the components shown herein may also be configured in alternative arrangements. For example, processor 116 and / or beamformer 114 may be located outside probe 110, and / or display 131 and / or memory 133 may be located outside host 130.

[0057] In some embodiments, probe 110 is an external ultrasound imaging device that includes a housing configured for handheld operation by a user. Transducer array 112 may be configured to obtain ultrasound data when the user holds the housing of probe 110 such that transducer array 112 is positioned adjacent to or in contact with the patient's skin. Probe 110 is configured to obtain ultrasound data of the anatomical structures within the patient when probe 110 is positioned outside the patient's body. In some embodiments, probe 110 may be a patch-based external ultrasound probe. For example, the probe may be a hemodynamic patch.

[0058] In other embodiments, probe 110 may be an internal ultrasound imaging device and may include a housing configured to be positioned within the patient (including the patient's coronary vessels, peripheral vessels, esophagus, ventricles, or other body or body cavities). In some embodiments, probe 110 may be an intravascular ultrasound (IVUS) imaging catheter or an intracardiac echocardiogram (ICE) catheter. In other embodiments, probe 110 may be a transesophageal echocardiogram (TEE) probe. Probe 110 may be in any suitable form for any suitable ultrasound imaging application (including both extracorporeal and intracorporeal ultrasound imaging).

[0059] The transducer array 112 transmits an ultrasonic signal to the anatomical target 105 of the patient and receives the echo signal reflected from the target 105 back to the transducer array 112. The transducer array 112 may include any suitable number of acoustic elements, including one or more acoustic elements and / or multiple acoustic elements. In some cases, the transducer array 112 includes a single acoustic element. In some cases, the transducer array 112 may include an array of acoustic elements having any number of acoustic elements in any suitable configuration. For example, the transducer array 112 may include from 1 to 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 larger and smaller 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 curved line 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., 1.5D array), or a two-dimensional (2D) array. The arrays 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 obtain one-dimensional, two-dimensional, and / or three-dimensional images of the anatomical structure of the patient. In some embodiments, the transducer array 112 may include piezoelectric micromachined ultrasonic transducers (PMUTs), capacitive micromachined ultrasonic sensors (CMUTs), single-crystal lead zirconate titanate (PZT), PZT composites, other suitable transducer types, and / or combinations thereof.

[0060] The beamformer 114 is coupled to the transducer array 112. The beamformer 114 controls the transducer array 112, e.g., for the transmission of ultrasonic signals and the reception of ultrasonic echo signals. In some embodiments, the beamformer 114 may apply time delays to the signals sent to the individual acoustic transducers within the array in the transducer array 112 such that the acoustic signals are steered in any suitable direction away from the probe 110. The beamformer 114 may also provide an image signal to the processor 116 based on the response to the received ultrasonic echo signals. The beamformer 114 may include multiple stages of beamforming. Beamforming may 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 ultrasonic imaging component. The beamformer 114 may also be a microbeamformer.

[0061] The processor 116 is coupled to the beamformer 114. The processor 116 may also be described as a processor circuit, which may include other components communicating with the processor 116, such as a memory, the beamformer 114, the communication interface 118, and / or other suitable 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 adjust the image signal. The processor 116 and / or 134 may be configured to control the array 112 to obtain ultrasonic data associated with the target 105.

[0062] 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 components and / or software components that implement a specific communication protocol suitable for transmitting 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.

[0063] The communication link 120 may be any suitable communication link. For example, the communication link 120 may be a wired link, such as a Universal Serial Bus (USB) link or an Ethernet link. Alternatively, the communication 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.

[0064] At the host 130, the communication interface 138 may receive the image signal. The communication interface 138 may be substantially similar to the communication interface 118. The host 130 may be any suitable computing and display device, such as a workstation, a personal computer (PC), a laptop, a tablet, or a mobile phone.

[0065] The processor 136 is coupled to the communication interface 138. The processor 136 may also be described as a processor circuit, which may include other components communicating with the processor 136, such as the memory 133, the communication interface 138, and / or other suitable components. The processor 136 may be configured to generate image data based on 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. Examples of image processing include performing pixel-level analysis to evaluate whether the color of a pixel has changed, which may correspond to the edge of a target (i.e., the edge of an anatomical feature). In some embodiments, the processor 136 may form a three-dimensional (3D) volume image based on 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 ultrasonic image of the target 105.

[0066] Memory 133 is coupled to processor 136. Memory 133 may be configured to store patient information related to a patient's medical history, measurement results, data or files, surgical history, anatomy or biometrics, characteristics or medical conditions associated with the patient, computer-readable instructions (such as code, software or other applications), and any other suitable information or data. Memory 133 may be located within host 130. There may also be additional external memory, or external memory in place of memory 133. The external memory may be a cloud-based server or an external storage device that is located outside host 130 and communicates with host 130 and / or the processor 136 of the host via a suitable communication link (such as the communication link 120 disclosed by reference). Patient information may include measurement results, data, files, other forms of medical history, such as but not limited to ultrasound images, ultrasound videos, and / or any imaging information related to the patient's anatomy. Patient information may include parameters related to the imaging procedure, such as probe position and / or orientation.

[0067] Display 131 is coupled to processor 136. Display 131 may be a monitor or any suitable display or display device. Display 131 is configured to display ultrasound images, image videos, and / or any imaging information of target 105.

[0068] System 100 can be used to assist an ultrasound physician or operator in performing an ultrasound scan. The scan can be performed in a point-of-care setting. In some cases, host 130 is a console or a mobile cart. In some cases, host 130 may be a mobile device, such as a tablet computer, a mobile phone, or a laptop computer. In other examples, the host is a server on the cloud, and an external display is connected to the host on the cloud. During the imaging procedure, ultrasound system 100 can acquire ultrasound images of the region of interest of an object.

[0069] 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 can be obtained from a single instruction in the so-called triple sound mode, where the three ultrasound modes are used simultaneously to acquire ultrasound data in each of the three modes. In a preferred practice, the ultrasound probe is placed approximately vertically and at an angle of approximately 50 to 70 degrees relative to the artery to acquire ultrasound data. Note that other angles between 1 and 89 degrees are also contemplated by the present disclosure.

[0070] Figure 2 is a schematic diagram of a processor circuit. Processor circuit 200 can be in Figure 1implemented in the probe 110 and / or the host system 130 or any other suitable location (e.g., 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 an 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 directly or indirectly with each other, for example, via one or more buses. The processor circuit may also communicate with an external storage and / or an external display. The external storage may be used to retrieve or store data, including images, ultrasound data, and / or patient information. The external display may be used to display outputs and / or control the processing circuit (e.g., by giving instructions).

[0071] The processors 116, 136, 206 contemplated by the present disclosure may include a central processing unit (CPU), a graphics 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 additionally include or be a preprocessor in hardware or software implementation.

[0072] The memories 118, 138, 208 contemplated by the present disclosure can be any suitable storage devices, such as caches (e.g., caches of processors 116, 136, 206), random access memories (RAM), magnetoresistive RAM (MRAM), read-only memories (ROM), programmable read-only memories (PROM), erasable programmable read-only memories (EPROM), electrically erasable programmable read-only memories (EEPROM), flash memories, solid-state memory devices, hard disk drives, other forms of volatile and non-volatile memories, or combinations of different types of memories. The memories can be distributed across multiple memory devices and / or be remote relative to the processing circuitry. In an embodiment, the memory 203 can store instructions 205. The instructions 205 can include instructions that, when run by processors 116, 136, 206, cause processors 116, 136, 206 to perform the operations described herein with reference to probe 110 and / or host 130( Figure 1 )).

[0073] The instructions 205 can also be referred to as code. The terms “instructions” and “code” should be broadly interpreted to include any type of (one or more) computer-readable statements. For example, the terms “instructions” and “code” can refer to one or more programs, routines, subroutines, functions, procedures, etc. “Instructions” and “code” can include a single computer-readable statement or many computer-readable statements. The instructions 205 can be in the form of an executable computer program or script. For example, routines, subroutines, and / or functions can be defined in a programming language, 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, according to the present disclosure, the instructions contemplated with reference to method 300 are disclosed herein.

[0074] The communication module 208 can include any electronic circuitry and / or logic circuitry to facilitate direct or indirect communication of data between processor circuitry 200, probe 110, host 130, and / or 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 the respective elements of processor circuitry 200, probe 110( Figure 1 ) and / or host 130( Figure 1 ).

[0075] According to an exemplary embodiment, the computer-implemented method includes Figure 3 the steps disclosed in

[0076] In step 310, ultrasonic imaging data of an artery is received. The ultrasonic data can be received in real time (i.e., during image acquisition), or can be queried from a storage facility (such as a memory or storage within the image acquisition device, cloud, or a physical hard drive external to the image acquisition device) in response to a request from a user or a machine. According to the present invention, the ultrasonic data includes any combination containing the following:

[0077] - B-mode ultrasonic data,

[0078] - pulsed wave Doppler ultrasonic data, and

[0079] - color or power Doppler ultrasonic data.

[0080] Those skilled in the art will understand that other forms of ultrasonic data additional to and / or in place of the above ultrasonic data can also be received.

[0081] According to an embodiment of the present invention, the ultrasonic data can be received from an ultrasonic device or system as provided in Figure 1 which includes an array 112 of acoustic elements configured to acquire

[0082] - B-mode ultrasonic data,

[0083] - pulsed wave Doppler ultrasonic data, and

[0084] - color or power Doppler ultrasonic data.

[0085] The acquisition mode can be pre-programmed as, for example, a triple ultrasonic imaging mode to obtain the following ultrasonic data according to consecutive or alternating ultrasound shots in this way:

[0086] - B-mode ultrasonic data,

[0087] - pulsed wave Doppler ultrasonic data, and

[0088] - color or power Doppler ultrasonic data.

[0089] The pre-programmed control can be run in the triple mode at the request of the user, or can be run under a machine command in the case of selecting to determine a velocity profile.

[0090] According to an embodiment, an ultrasound device including an acoustic array configured for triple mode can be a hemodynamic 1D ultrasound patch, such as an ultrasound patch that can be attached to the skin of an object for continuously monitoring characteristics (such as the heart, lungs, etc.) within the object. In this case, the array of acoustic elements can continuously acquire data in triple mode (e.g., by simultaneously acquiring ultrasound data in each mode or by alternating different modes within the triple mode). In other words, for example, data is acquired for a sufficient duration first in B mode, then in pulsed wave Doppler mode, and finally in color or power Doppler mode, and then the acquisition is repeated. It should be understood that the present invention contemplates any order of these modes.

[0091] 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, based on the ultrasound data,

[0092] - the dimensions of the artery,

[0093] - the velocity in the artery, and

[0094] - a measure of the flow profile asymmetry.

[0095] The artery dimension (or lumen dimension) refers to any dimension related to the cross-section of the artery. Thus, the artery dimension (or lumen dimension) can be, for example, the artery diameter or radius. However, the artery dimension can also be, for example, the surface area or perimeter of the cross-section of the artery. The artery or lumen dimension can be obtained based on, for example, B-mode ultrasound data.

[0096] Figure 4 An ultrasound image 410 generated from B-mode ultrasound data of a cross-section of an artery according to an embodiment of the present invention is shown. In particular, Figure 4 a cross-section of the artery is shown that is approximately 20 to 40 degrees relative to the length of the artery and approximately 50 to 70 degrees relative to the cross-section, such that the diameter or radius can be obtained based on the short axis 412 of the illustrative oval 414 drawn for illustrative purposes only. It should be clear to those skilled in the art that other ultrasound data can also be suitable for determining the dimension of the artery, such as Figure 8 the color or power Doppler ultrasound data shown in. It should also be clear to those skilled in the art that the artery dimension and the lumen dimension can be used interchangeably in the context of the present invention.

[0097] According to an embodiment of the present invention, the velocity in an artery refers to the local velocity measured over an area smaller than the cross-sectional area of the artery. Thus, the velocity in an artery is the local velocity at any given location or area within the lumen of the artery. For example, the velocity in an artery can be the velocity at the center of the artery. According to another example, the velocity can be the velocity at a predefined location within the artery, such as the location of the maximum velocity within the artery, or a location near the edge of the artery. The velocity in an artery can be determined according to any ultrasound mode, such as color Doppler, power Doppler, or pulsed-wave Doppler ultrasound. In an embodiment, the velocity is determined according to pulsed-wave Doppler ultrasound data. For example, the pulsed-wave Doppler ultrasound mode allows for measuring the local velocity with higher accuracy than the color or power Doppler ultrasound modes. Due to the high frame rate, the pulsed-wave Doppler ultrasound mode can also be beneficial for resolving important features of the velocity waveform in an artery, such as the systolic peak velocity.

[0098] Figure 5 Visualized ultrasound data 500 obtained according to the pulsed-wave Doppler ultrasound mode is shown. The ultrasound data includes an ultrasound image 510 and a timeline 520 of velocity, where the velocity is determined within a relatively small sampling region 530. The timeline shows the evolution of the velocity within the sampling region 530 over time, resolving the systolic peak 522 due to the high frame rate of pulsed-wave Doppler. Thus, the velocity at a given location within the artery or lumen can be determined as an instantaneous velocity (e.g., a single point from the timeline 520), or as an average velocity (averaging the velocities on the timeline 520). Additionally, the sampling region 530 can be at the center of the artery as shown in Figure 5 or at any point within the cross-section, such as the location of the maximum velocity determined according to color Doppler mode ultrasound data.

[0099] According to an embodiment of the present invention, a measure of the asymmetry of the flow refers to any parameter that indicates the level of asymmetry or skewness of the flow profile relative to a symmetric flow profile. For example, a measure of the asymmetry can be the deviation of the flow profile from a symmetric parabolic flow profile. In another example, a measure of the asymmetry can be the deviation of the maximum velocity from the central axis of the artery or the centroid of the artery cross-section. For example, in a curved artery, so-called Dean vortices can occur and skew the typically symmetric parabolic flow profile observed in a straight artery, such that the maximum velocity within the artery is no longer located at the central axis of the artery, but at a certain distance from the central axis of the artery. This deviation of the flow is shown in Figure 6A and 6B below.

[0100] Figure 6A The 2D velocity distribution in a curved blood vessel is shown as a contour plot. Each line in the contour plot represents a specific velocity. For example, starting from zero velocity at the outermost line, each next line towards the center of the figure represents an increasing velocity.

[0101] In a generally straight artery, the velocity profile can be overall symmetric on the two shown axes 680 and 690 (these axes can be in any orientation as long as the two axes are orthogonal to each other). However, in a curved artery, due to Dean vortices, the velocity distribution may be shifted to be asymmetric on at least one axis 690. Thus, the maximum velocity (at the center of the region depicted by the innermost contour line 640) is shifted a distance 632 from the centroid 670 to a new position 630. The distance by which the velocity maximum is shifted is determined by the radius of curvature R of the artery 700 c 734, as shown in Figure 7 the figure.

[0102] Figure 6B The velocity profiles along the axis of asymmetry 680 for various radii of curvature 734 are shown. For example, an artery with a radius of curvature of zero will show a completely symmetric flow profile 631. As the radius of curvature increases, the distance 632 by which the velocity maximum is shifted increases, where the distance 632 increases with increasing radius of curvature.

[0103] Figure 8 An ultrasound image 810 from color or power Doppler ultrasound data is shown, which has a heat map 850 of the velocity in a cross-section of the artery. Although the heat map may be qualitative, for example without any indication of absolute velocity values, it can 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 centroid 670 of the artery cross-section can then be determined, for example, by calculating the distance 632 between the velocity maximum position 630 and the centroid 670 of the artery cross-section.

[0104] According to an embodiment of the present invention, the velocity maximum shift 632 can be related to a dimensionless parameter, such as the local Dean number De. In particular, for example in et al. (2012), "Can the Dean number alone characterize flow similarity in differently bent tubes?", Verkaik et al. (2009), "Estimation of volume flow in curved tubes based on analytical and computational analysis of axial velocity profiles", and Petrakis et al. (2009), "Steady Flow in a Curved Pipe with Circular Cross-Section. Comparison of Numerical and Experimental Results" have shown that, at least for self-similar flows, the offset dx 632 of the position of the maximum velocity depends on the Dean number De according to Figure 9 That is to say, the local Dean number can be extracted, for example, according to Figure 9 , by determining only the offset 632 of the maximum velocity, without the value of the velocity. For example, it can be determined that the maximum velocity offset is 40% of the artery diameter, such that the local Dean number corresponds to approximately 200.

[0105] It should be noted that the present invention also contemplates such a method in which the Dean number is obtained based on the velocity offset and Figure 9 The obtained Dean number can be only a first estimate and can be recalculated at a later stage. The Dean number can be determined iteratively, for example, to converge to a value by combining the blocks of method 300 in a different order, and / or adding and / or removing the blocks of method 300.

[0106] Referring again to Figure 3 , in step 330, the flow profile within the artery is determined. For example, the color or power Doppler ultrasound data can be integrated pixel by pixel on the heat map 850 of Figure 8 . In another example, the flow profile is determined based on the first set of properties determined in step 320 in combination with an analytical expression. For example, the artery dimensions, the velocity in the artery, and a measure of asymmetry can be combined to determine the flow profile. Various suitable methods for determining the flow profile will be presented below. However, it should be clear that the present invention also contemplates methods that deviate from those below but are within the same spirit.

[0107] According to an embodiment, based on "Viscous flow in curved tubes - I. Velocity Profiles" by Soedberg (1987), the dimensionless or normalized flow profile u(r) through the maximum velocity can be determined according to the following formula based on arterial dimensions and a measure of asymmetry

[0108] u(r) = w0(r) - w1(r) + … (1)

[0109] The first two terms are given by

[0110]

[0111] and

[0112]

[0113] Here, w0 and w1 represent the zero - th and first - th tangential harmonic contributions to the flow. Higher - order harmonic contributions, such as second - order, third - order, etc., can also be considered. Additionally or alternatively, different expressions for the harmonic contributions can be used, such as

[0114]

[0115] In addition, r represents the radial coordinate normalized by the total arterial radius R (i.e., r = r′ / R), which can be derived as described above. It should be noted that the velocity profile can be obtained in any radial direction along the cross - section. For example, one velocity profile u(r) can be along Figure 6A the axis 680 in Figure 6A and another velocity profile u(r) can be along

[0116] the axis 690 shown in

[0117] F = 0.5·q 0.6 + 1.5,

[0118] F = 0.5(1 + q 0.5 ) + 1.5,

[0119] F = 0.5(1 + q) 0.6 + 1.5,

[0120] where

[0121] q = De / 16,

[0122] where De is the local Dean number, representing a measure of asymmetry, and it can be derived according to step 320 of method 300 based on the offset of the maximum velocity as discussed above.

[0123] According to an embodiment, based on "Axial dispersion in helically coiled open columns for chromatography" by Tijssen (1979), the flow profile can be estimated according to the following formula

[0124] u(r) = q 2 (1 - r) 2 exp{(1 - r)(ln(8 / 9) - 0.5ln[(q / 1.6) 3.4 + 1])} (2)

[0125] or

[0126]

[0127] where, in addition to the above variable definitions, 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 thus can deviate from the values mentioned, can be removed or replaced by different fitting constants.

[0128] Following the above expression for u(r), the obtained velocity profile may be accurate in shape but not in absolute value as it relates to a normalized velocity profile. Thus, the normalized velocity profile can be shifted or scaled by the velocity in the artery, such as the velocity derived from pulsed wave Doppler measurements. In this case, the normalized velocity profile u(r) (which can be Figure 6B any of the velocity profiles shown in) can be offset from the dimensionless normalized unit to have units of distance per time (i.e., m / s, cm / s, feet / s, etc.).

[0129] The present inventors have further recognized that when 16 < De < 240, the accuracy of the velocity distribution obtained according to Equation (1) may be within 10% of the true velocity distribution, and when De > 100, the accuracy of the velocity distribution obtained according to Equation (2) or (3) below may be within 10% of the true velocity distribution.

[0130] According to an embodiment, Equation (1) can thus be combined with either Equation (2) or (3) such that Equation (1) is used for lower De numbers and either Equation (2) or (3) is used for higher De numbers to obtain an accuracy of the velocity profile within 10% for a larger range of De numbers. For example, the relevant De range within an artery can be 1 < De < 2000.

[0131] According to an embodiment, a flow profile (which may be a dimensionless normalized flow profile or a scaled and dimensional flow profile) can also be used to determine a 3D flow profile, as proposed in Verkaik et al. (2009). A cross-section (e.g., Figure 6A as shown) is divided into two semi-circles along a diameter (perpendicular to the known flow profile thereon). Then, the flow velocity Q(r,θ) is estimated by assuming that the axial flow is axisymmetric in each semi-circle as shown in Figure 10 , giving the following expression

[0132]

[0133] This expression can be solved according to the method of partial integration.

[0134] In an optional step 340, the radius of curvature R can be determined based on the flow profile u(r) c 734.

[0135] i) Based on the flow profile determined in step 130, the Reynolds number Re can be determined according to the following formula

[0136]

[0137] Here ρ is the blood density, U is the average velocity in the artery at the imaged cross-section, D and μ are the dynamic viscosities. The average velocity can be obtained as:

[0138] - half of the maximum velocity of laminar flow,

[0139] - the central velocity of turbulent flow, or

[0140] - the average velocity over the entire cross-section, which can be obtained by mathematical averaging.

[0141] ii) The radius of curvature can be obtained by correlating the Reynolds number with the Dean number according to the following formula

[0142]

[0143] Those skilled in the art will understand that although method 300 is presented in a specific order, the order of the steps can be changed, additional steps can be added between the steps, and / or steps can be removed.

[0144] Furthermore, it should also be understood that the individual steps in method 300 can be performed in real time (i.e., during the examination procedure), or afterwards. For example, ultrasonic data can be obtained in real time and analyzed according to method 300 during the image acquisition procedure, or the imaging data can be obtained first during the acquisition step and analyzed only at the request of the operator and / or expert. Thus, method 100 can be implemented in an image acquisition system ( Figure 1) implemented within, or outside the hemodynamic patch or in a separate computing unit ( Figure 1 ). In another embodiment, method 100 may also be executed on the cloud.

[0145] It should be noted that the embodiments mentioned above are illustrative and not restrictive of the present invention, and those skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed in parentheses shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of other elements or steps than those listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements, and / or by means of a suitably programmed processor. In a device claim enumerating several means, several of these means may be embodied by one and the same piece of hardware. The measures recited in mutually different dependent claims may be used in combination.

Claims

1. A computer-implemented method (300) for determining a flow profile in an artery based on ultrasound imaging data, the method comprising: - receiving (310) ultrasound imaging data of the artery in a triple mode, wherein the triple mode comprises: - B-mode ultrasound data, - pulsed wave Doppler ultrasound data, and - color or power Doppler ultrasound data; - determining (320) based on the ultrasound imaging data, - artery dimensions; - velocity in the artery cross-section, and - a measure of the asymmetry of the flow profile in the artery; and - determining (330) the flow profile based on - the artery dimensions, - the velocity in the artery cross-section, and - the measure of the asymmetry of the flow profile.

2. The method according to claim 1, further comprising: - determining (340) local arterial curvature based on - the artery dimensions, - the flow profile, and - the measure of the asymmetry of the flow profile.

3. The method according to any one of claims 1-2, wherein, The artery dimensions are determined based on the B-mode ultrasound data.

4. The method according to any one of claims 1-2, wherein, The velocity in the artery cross-section is determined based on the pulsed wave Doppler ultrasound data.

5. The method according to any one of claims 1-2, wherein The velocity in the artery cross-section is determined at the center of the artery cross-section.

6. The method according to any one of claims 1-2, wherein, The measure of the asymmetry of the flow profile is determined based on the color or power Doppler ultrasound data.

7. The method according to any one of claims 1-2, wherein The measure of asymmetry comprises: - determining the position of the maximum flow velocity in the artery cross-section; and, based on the position, determining a parameter representing the deviation of the position relative to the center of the artery cross-section.

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

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

10. A system (100) for determining a flow profile based on ultrasound imaging data, the system comprising a processor configured to execute the method according to any one of claims 1-8.

11. The system according to claim 10, further comprising: - an array (112) of acoustic elements in communication with the processor (116, 136), and - wherein the processor is configured to control the array of acoustic elements to transmit and receive acoustic signals to generate ultrasound imaging data.

12. The system according to claim 10 or 11, wherein The system is a hemodynamic monitoring patch.

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