WO2025132115A1 - Systems and methods for automated computation of heart parameters from ultrasound m-mode data - Google Patents

Abstract

Provided herein are systems and methods for automatically computing fetal heart parameters, such as fetal heart rate, from M-mode ultrasound data and/or B-mode ultrasound data. In particular, the systems and methods involve: (i) obtaining ultrasound input data comprising M- mode ultrasound data along a cardiac plane of a fetus; (ii) automatically localizing one or more regions of motion present based on the ultrasound input data; (iii) labeling the one or more regions of motion based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus; (iv) analyzing the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion; and (v) determining one or more fetal heart parameters based on the periodicity determined for the one or more regions of motions.

Description

SYSTEMS AND METHODS FOR AUTOMATED COMPUTATION OF HEART PARAMETERS FROM ULTRASOUND M-MODE DATA

Field of the Disclosure

[0001] The present disclosure relates generally to measuring heart parameters in fetuses, and more specifically to systems and methods of measuring fetal heart parameters based on ultrasound imaging data.

Background

[0002] Acute congenital heart diseases (CHDs) affects nearly 1 % of pregnancies and roughly 40,000 births per year in the United States. Of these, nearly 25% are critical CHDs, sometimes leading to death, but generally requiring surgery or other procedures during the first year of life of the infant. According to the Centers for Disease Control, a study revealed that 4.2% of all neonatal deaths were due to a CHD, and approximately 10% of all pregnancies are complicated by fetal arrhythmias, which may be life-threatening. Prenatal diagnosis of congenital heart diseases helps planning for their management during pregnancy and reduce the mortality rate due to such problems after birth. Thus, prenatal care is essential for maternal and fetal health through the progression of pregnancy.

[0003] However, the availability, quality, and affordability of prenatal care varies greatly depending on many geographical and socioeconomic factors. Ultrasound imaging is generally viewed as cost-effective, and due to its relatively safe and non-invasive nature, ultrasound imaging has been recommended for evaluating cardiac health of patients in general. Nevertheless, it may be undesirable to utilize certain types of ultrasound imaging, such as spectral Doppler ultrasound, for fetuses due to relatively high time-averaged acoustic intensity delivered to the fetus. Additionally, even if appropriately configured ultrasound machines are available, there may not be enough sonographers trained to perform cardiac examinations of prenatal patients, or not enough radiologists trained to make the necessary diagnoses.

Summary of the Disclosure

[0004] Accordingly, it is an object of the present disclosure to provide systems and methods for automatically computing fetal heart parameters, including fetal heart rate, from ultrasound modes other than spectral Doppler ultrasound. As described in more detail below, the systems and methods provided herein enable the computation of a variety of fetal heart parameters using acquired M-mode ultrasound data and/or B-mode ultrasound data without the use of spectral Doppler ultrasound and without requiring input from a sonographer.

[0005] According to an embodiment of the present disclosure, a system for measuring and validating fetal heart parameters of a fetus is provided. The system can include: an ultrasound imaging device comprising one or more ultrasound transducers configured to generate ultrasound data of the fetus; and an electronic device in communication with the ultrasound imaging device. The electronic device can include a display device configured to display a graphical user interface comprising a visual validation of fetal heart parameters, a computer-readable storage medium having stored thereon computer-readable instructions to be executed by one or more processors, and one or more processors configured by the computer-readable instructions stored on the computer-readable storage medium to perform the following operations: (i) obtain ultrasound input data comprising M-mode ultrasound data along a cardiac plane of the fetus; (ii) automatically localize one or more regions of motion present based on the ultrasound input data; (iii) label the one or more regions of motion based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus; (iv) analyze the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion; (v) determine one or more fetal heart parameters based on the periodicity determined for the one or more regions of motions. [0006] In an aspect, the one or more processors can be further configured to: analyze the M- mode ultrasound data to determine changes in the periodicity of one or more regions of motion present in the M-mode ultrasound data; and determine one or more fetal heart parameters based on the changes in the periodicity of the one or more regions of motion present in the M-mode ultrasound data.

[0007] In an aspect, the one or more fetal heart parameters can include a fetal heart rate, a heart chamber wall thickness, a left ventricular systolic function, a left ventricular mass, and/or a heart chamber diameter.

[0008] In an aspect, the one or more fetal heart parameters can be a ratio of two or more fetal heart parameters.

[0009] In an aspect, the one or more processors can be configured to analyze the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion by: detecting an edge contour of at least a first region of motion present in the M-mode ultrasound data; determining a plurality of local peaks based on the edge contour detected for the first region of motion; determining locations for a plurality of markers to be associated with the first region of motion, wherein each marker corresponds to one of the plurality of local peaks determined; and determining a periodicity for at least the first region of motion based on the locations determined for the plurality of markers.

[0010] In an aspect, the one or more processors can be further configured to visually validate the fetal heart parameters by: generating a visual validation of fetal heart parameters for the fetus; and displaying the visual validation of fetal heart parameters via the display device as part of a graphical user interface. The visual validation can include: (a) a visualization of the first region of motion of the M-mode ultrasound data; (b) a visualization of the detected edge contour that is superimposed over the visualization of the first region of motion of the M-mode ultrasound data; and (c) a visualization of the plurality of markers that is superimposed over the first region of motion of the M-mode ultrasound data at the determined locations

[0011] In an aspect, the ultrasound imaging device can be configured to generate B-mode ultrasound data of the fetus, and the one or more processors can be further configured to perform the following operations: obtain ultrasound input data comprising B-mode ultrasound data, wherein the B-mode ultrasound data includes a cineloop of the fetal cardiac structure and covers a plurality of cardiac cycles for the fetus; and reconstruct M-mode ultrasound data along a cardiac plane of the fetus based on the B-mode ultrasound data obtained from the ultrasound imaging device.

[0012] According to another embodiment of the present disclosure, a computer program product is provided. The computer program product can include a non-transitory computer- readable storage medium having stored thereon computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the following operations: (i) obtain ultrasound input data comprising M-mode ultrasound data along a cardiac plane of the fetus; (ii) automatically localize one or more regions of motion present based on the ultrasound input data; (iii) label the one or more regions of motion based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus; (iv) analyze the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion; and (v) determine one or more fetal heart parameters based on the periodicity determined for the one or more regions of motions.

[0013] According to still another embodiment of the present disclosure, a method of measuring fetal heart parameters of a fetus is provided. The method can include: obtaining ultrasound input data comprising M-mode ultrasound data along a cardiac plane of the fetus; automatically localizing one or more regions of motion present based on the M-mode ultrasound data; labelling the one or more regions of motion present in the M-mode ultrasound data based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus; analyzing the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion; and determining one or more fetal heart parameters for the fetus based on the periodicity of the one or more regions of motions.

[0014] In an aspect, the ultrasound input data comprising M-mode ultrasound data can be obtained via an ultrasound imaging device.

[0015] In an aspect, the ultrasound input data comprising M-mode ultrasound data can be obtained by: obtaining, via an ultrasound imaging device, ultrasound input data comprising B- mode ultrasound data, wherein the B-mode ultrasound data includes a cineloop of the fetal cardiac structure and covers a plurality of cardiac cycles for the fetus; and reconstructing M-mode ultrasound data long a cardiac plane of the fetus based on the B-mode ultrasound data obtained from the ultrasound imaging device.

[0016] In an aspect, the M-mode ultrasound data can be analyzed to determine a periodicity for one or more of the regions of motion by: performing one or more image processing techniques to automatically detect an edge contour of at least a first region of motion present in the M-mode ultrasound data; determining a plurality of local peaks based on the edge contour detected for the first region of motion; determining locations for a plurality of markers to be associated with the first region of motion, wherein each marker corresponds to one of the plurality of local peaks determined; and determining a periodicity for at least the first region of motion based on the locations determined for the plurality of markers.

[0017] In an aspect, the method can further include visually validating the fetal heart parameters by: generating a visual validation of fetal heart parameters for the fetus; and displaying the visual validation of fetal heart parameters via the display device as part of a graphical user interface. The visual validation can include: (a) a visualization of the first region of motion of the M-mode ultrasound data; (b) a visualization of the detected edge contour that is superimposed over the visualization of the first region of motion of the M-mode ultrasound data; and (c) a visualization of the plurality of markers that is superimposed over the first region of motion of the M-mode ultrasound data at the determined locations

[0018] In an aspect, the method can further include: analyzing the M-mode ultrasound data to determine changes in the periodicity of one or more regions of motion present in the M-mode ultrasound data; and determining one or more fetal heart parameters based on the changes in the periodicity of the one or more regions of motion present in the M-mode ultrasound data.

[0019] In an aspect, the one or more fetal heart parameters can include a fetal heart rate, a heart chamber wall thickness, a left ventricular systolic function, a left ventricular mass, and/or a heart chamber diameter.

[0020] These and other aspects of the various embodiments will be apparent from and elucidated with reference to the embodiments described hereinafter.

Brief Description of the Drawings

[0021] In the drawings, like reference characters generally refer to the same parts throughout the different views. Also, the drawings are not necessarily to scale, emphasis instead generally being placed upon illustrating the principles of the various embodiments.

[0022] FIG. 1 is a diagram illustrating a system for automatically computing diagnostic parameters pertaining to fetal heart conditions in accordance with aspects of the present disclosure. [0023] FIG. 2 is a block diagram illustrating an electronic device configured to measure fetal heart parameters of a fetus in accordance with aspects of the present disclosure.

[0024] FIG. 3 is a flowchart illustrating a method of measuring fetal heart parameters of a fetus in accordance with aspects of the present disclosure.

[0025] FIG. 4 is an illustration of M-mode ultrasound scan output shown in accordance with aspects of the present disclosure.

[0026] FIG. 5 is a flow diagram illustrating a method of reconstructing M-mode data from B- mode images in accordance with aspects of the present disclosure.

[0027] FIG. 6 is an illustration of M-mode ultrasound data annotated in accordance with aspects of the present disclosure. [0028] FIG. 7 is an enlarged illustration of certain regions of motion within an M-mode ultrasound image shown in accordance with aspects of the present disclosure.

[0029] FIG. 8A is an isolated region of motion extracted from an M-mode ultrasound image in accordance with aspects of the present disclosure.

[0030] FIG. 8B is a processed region of motion extracted from an M-mode ultrasound image in accordance with further aspects of the present disclosure.

[0031] FIG. 8C is a masked region of motion extracted from an M-mode ultrasound image in accordance with aspects of the present disclosure.

[0032] FIG. 8D is an output of an edge detection and enhancement algorithm applied to the masked region of motion in accordance with aspects of the present disclosure.

[0033] FIG. 8E is a masked region of motion extracted from an M-mode ultrasound image in accordance with further aspects of the present disclosure.

[0034] FIG. 9 is an exemplary visual validation display for validating the fetal heart parameters determined in accordance with aspects of the present disclosure.

Detailed Description of Embodiments

[0035] As described herein, various systems and methods for automatically computing diagnostic parameters pertaining to fetal heart conditions based on M-mode or B-mode ultrasound data (i.e., without the use of spectral Doppler ultrasound data) are provided. In particular embodiments, where only B-mode ultrasound data is available, the systems and methods also provide a solution for reconstructing pseudo M-mode ultrasound data, which can then be used to automatically compute the diagnostic fetal heart parameters.

[0036] For example, with reference to FIG. 1, a system 100 for measuring and validating fetal heart parameters of a fetus 102 is provided. In embodiments, the system 100 includes an ultrasound imaging device 104 comprising one or more ultrasound transducers (not shown) configured to generate ultrasound data 106 of the fetus 102, and an electronic device 108 in communication with the ultrasound imaging device 104. The electronic device 108 can include a display device 110 configured to display a graphical user interface comprising a visual validation of fetal heart parameters for the fetus 102. As described in more detail below, the electronic device 108 can also comprise a computer-readable storage medium having stored thereon computer-readable instructions to be executed by one or more processors, and one or more processors configured by the computer-readable instructions stored on the computer-readable storage medium to perform the following operations: (i) obtain ultrasound input data 106 comprising M-mode ultrasound data along a cardiac plane of the fetus 102; (ii) automatically localize one or more regions of motion present based on the ultrasound input data 106; (iii) label the one or more regions of motion based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus 102; (iv) analyze the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion; (v) determine one or more fetal heart parameters based on the periodicity determined for the one or more regions of motions.

[0037] More specifically, as shown in the example of FIG. 2, the electronic device 108 can include one or more processors 202 and a computer-readable memory 204 interconnected and/or in communication via a system bus 206 containing conductive circuit pathways through which instructions (e.g., machine-readable signals) may travel to effectuate communication, tasks, storage, and the like. The electronic device 108 can be connected to a power source (not shown), which can include an internal power supply and/or an external power supply. In embodiments, the electronic device 108 can also include one or more additional components, such as a user interface 112, a display 110, an input/output (I/O) interface 212, a networking unit 214, and the like, including combinations thereof. As shown, each of these components may be interconnected and/or in communication via the system bus 206, for example.

[0038] In embodiments, the one or more processors 202 can include one or more high-speed data processors adequate to execute the program components described herein and/or perform one or more operations of the methods described herein. The one or more processors 202 may include a microprocessor, a multi-core processor, a multithreaded processor, an ultra-low voltage processor, an embedded processor, and/or the like, including combinations thereof. The one or more processors 202 can include multiple processor cores on a single die and/or may be a part of a system on a chip (SoC) in which the processor 202 and other components are formed into a single integrated circuit, or a single package. That is, the one or more processors 202 may be a single processor, multiple independent processors, or multiple processor cores on a single die.

[0039] In embodiments, the user interface 112 may be configured to receive various forms of input from a user 114 associated with the electronic device 108. The user interface 112 can include, but is not limited to, one or more of a keyboard, keypad, trackpad, trackball(s), capacitive keyboard, controller (e.g., a gaming controller), computer mouse, computer stylus / pen, a voice input device, and/or the like, including combinations thereof.

[0040] In embodiments, the display device 110 may be configured to display information, including text, graphs, and/or the like. In particular embodiments, the display device 110 may be configured to a graphical user interface comprising a visual validation of fetal heart parameters, including but not limited to, one or more visualizations of the regions of motion present in the M- mode ultrasound data and a visualization of a plurality of markers superimposed over the regions of motion. The display device 110 can include, but is not limited to, a liquid crystal display (LCD), a light-emitting diode (LED) display, a touch screen or other touch-enabled display, a foldable display, a projection display, and so on, or combinations thereof.

[0041] In embodiments, the input/output (I/O) interface 212 may be configured to connect and/or enable communication with one or more peripheral devices (not shown), including but not limited to additional machine-readable memory devices, diagnostic equipment, and other attachable devices. The I/O interface 212 may include one or more I/O ports that provide a physical connection to the one or more peripheral devices. In some embodiments, the I/O interface 212 may include one or more serial ports.

[0042] In embodiments, the networking unit 214 may include one or more types of networking interfaces (such as various types of transceivers and/or modems) that facilitate wired and/or wireless communication between the electronic device 108 and one or more external devices. That is, the networking unit 214 may operatively connect the electronic device 108 to one or more types of communications networks 216, which can include a direction interconnection, the Internet, a local area network (“LAN”), a metropolitan area network (“MAN”), a wide area network (“WAN”), a wired or Ethernet connection, a wireless connection, a cellular network, and similar types of communications networks, including combinations thereof. In some embodiments, the electronic device 108 may communicate with one or more remote / cloud-based servers and/or cloud-based services, such as remote server 218, via the communications network 216.

[0043] In embodiments, the memory 204 can be variously embodied in one or more forms of machine accessible and machine-readable memory. In some embodiments, the memory 204 includes a storage device (not shown), which can include, but is not limited to, a non-transitory storage medium, a magnetic disk storage, an optical disk storage, an array of storage devices, a solid-state memory device, and/or the like, as well as combinations thereof. The memory 204 may also include one or more other types of memory, such as dynamic random-access memory (DRAM), static random-access memory (SRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), Flash memory, and/or the like, as well as combinations thereof. In embodiments, the memory 204 may include one or more types of transitory and/or non-transitory memory.

[0044] The electronic device 108 can be configured by software components stored in the memory 204 to perform one or more operations of the methods described herein. More specifically, the memory 204 can be configured to store data / information 220 and computer- readable instructions 222 that, when executed by the one or more processors 202, causes the electronic device 108 to measure and validate a variety of fetal heart parameters for a fetus 102. Such data 220 and the computer-readable instructions 222 stored in the memory 204 may form a fetal cardiac module 224 that may be incorporated into, loaded from, loaded onto, or otherwise operatively available to and from the electronic device 108. Thus, in some embodiments, the fetal cardiac module 224 and/or one or more individual software packages may be stored in a local storage device of the memory 204. However, in other embodiments, the fetal cardiac module 224 and/or one or more individual software packages may be loaded onto and/or updated from a remote server or service, such as server 218, via the communications network 216.

[0045] The electronic device 108 may also include an operating system component 226, which may be stored in the memory 204. The operating system component 224 may be an executable program facilitating the operation of the electronic device 108. Typically, the operating system component 226 can facilitate access of the I/O interface 212, network interface 214, the user interface 112, and the display 110, and can communicate or control other components of the electronic device 108.

[0046] Thus, in accordance with certain aspects of the present disclosure, provided herein is a computer program product 224 comprising a non-transitory computer-readable storage medium 204 having stored thereon computer-readable instructions 222 that, when executed by one or more processors (such as processors 202), cause the one or more processors to perform one or more operations of the methods described below. For example, in specific embodiments, the computer- readable storage medium 204 may include computer-readable instructions 222 that, when executed by one or more processors (such as processors 202), cause the one or more processors to perform the following operations: (i) obtain ultrasound input data 106 comprising M-mode ultrasound data along a cardiac plane of a fetus 102; (ii) automatically localize one or more regions of motion present based on the ultrasound input data 106; (iii) label the one or more regions of motion based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus 102; (iv) analyze the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion; and (v) determine one or more fetal heart parameters based on the periodicity determined for the one or more regions of motions.

[0047] More specifically, with reference to FIG. 3, a method 300 for measuring fetal heart parameters of a fetus 102 is illustrated in accordance with certain aspects of the present disclosure. As shown, the method 300 can include: in a step 305, obtaining ultrasound input data 106; in a step 310, localizing one or more regions of motion present in the ultrasound input data 106; in a step 315, identifying and labeling the one or more regions of motion based on domain knowledge and/or the ultrasound input data 106; in a step 320, analyzing the ultrasound input data 106 to determine a periodicity for one or more of the regions of motion; and in a step 325, determining one or more fetal heart parameters for the fetus 102 based on the periodicity of the one or more regions of motion.

[0048] According to the step 305, the method 300 can include obtaining ultrasound input data 106 comprising M-mode ultrasound data along a cardiac plane of the fetus 102. As described herein, M-mode ultrasound data generally refers the information collected when a single scan line from an ultrasound transducer is emitted and received, and represents the acoustic impedance or density of the tissues encountered. Put another way, M-Mode scans are cross sectional plots along a specified scan line, where these lines can be chosen across cardiac structure in order to measure cardiac parameters. In embodiments, the M-mode ultrasound data may be displayed with an x-axis representing time, a y-axis representing distance from the transducer, and varying brightness that is proportional to the amplitude of the reflected ultrasound waves.

[0049] In some embodiments, the ultrasound input data 106 may include M-mode ultrasound data that is obtained via the ultrasound imaging device 104 (i.e., the ultrasound imaging device 104 is configured to generate M-mode ultrasound data). For example, with reference to FIG. 4, an exemplary display of the output 400 of an M-mode scan is illustrated in accordance with aspects of the present disclosure. As shown, the output 400 of the M-mode scan includes a B-mode image 410 that shows the anatomical structure being imaged (e.g., the heart of a fetus 102) with a line across the anatomical structure. The line crossing the anatomical represents the single scan line for which the M-mode image 420 is obtained. In embodiments, the ultrasound input data 106 can include both the B-mode image 410 showing the scan line and the M-mode image data 420 corresponding to that scan line. In such embodiments, the M-mode image data 420 may be isolated for analysis as discussed in more detail below.

[0050] In other embodiments, the ultrasound input data 106 can include a plurality of B-mode ultrasound images that are used to reconstruct the M-mode ultrasound data. For example, with reference to FIG. 5, M-mode ultrasound data can be reconstructed from B-mode ultrasound data in a three-step process that includes: in a step 510, selecting a line for the M-mode image reconstruction; in a step 520, detecting and extracting consistent fetal heart view planes from a B- mode cineloop covering multiple cardiac cycles; and in a step 530, reconstructing an M-mode image along the selected line from the acquired cineloop. Put another way, the M-mode ultrasound data can be obtained by obtaining B-mode ultrasound data (e.g., a cineloop covering a plurality of cardiac cycles for the fetus 102), and reconstructing M-mode data along a consistent cardiac plane based on the acquired B-mode cineloop.

[0051] In embodiments, detection, classification and extraction of fetal heart views from B- mode cineloops may be performed in accordance with various algorithms known in the art. However, as described herein, the B-mode data can include, at a minimum, a series of contiguous frames from a static heart plane chosen covering about five heart cycles or more. In embodiments, this series of frames may need to be registered for accuracy in accordance with other algorithms known in the art. In further embodiments, selection of a line for M-Mode image reconstruction can be done through identifying specific landmarks such as mitral or aortic valves, and short or long axis through supervised learning. In still further embodiments, reconstruction of M-mode data from the B-mode cineloop can be performed by extracting the pixel values along the selected line across all frames that were collected, and stacking these pixel values to reconstruct a pseudo M- Mode image. In some embodiments, a group-wise registration of the frames may be performed when needed.

[0052] Returning to FIG. 3, the method 300 can then include, in a step 310, localizing one or more regions of motion within the M-mode ultrasound data. In particular embodiments, the one or more regions of motion may be automatically localized without user input or intervention. In embodiments, various algorithms may be used to identify each region of motion because cardiac structures in a viable heart generally move periodically. For example, in some embodiments, a zero crossings approach produced by a Laplacian-of-Gaussian operator may be utilized. In particular embodiments, a relative measure of dispersion approach that uses a partial differential equation (PDE)-based speckle-reducing filter may be utilized. In some embodiments, the computation cost for localizing the different regions of motions may be reduced by computing the coefficient of variation along each horizontal line in the M-mode image, while a band of such lines can be evaluated to accommodate for small / subtle movements in the cardiac sub-structures.

[0053] With reference to FIG. 6, for example, a M-mode ultrasound image 420 is shown where three regions of motion 610, 620, 630 are localized. For illustrative purposes, each region of motion 610, 620, 630 is highlighted with a semi-transparent, shaded box covering the region of motion. However, it should be appreciated that this emphasis can take other graphical forms, such as different coloring, transparencies, and/or the like.

[0054] The method 300 can then include, in a step 315, identifying and labelling each of the one or more regions of motion 610, 620, 630 present in the M-mode ultrasound image 420. In embodiments, each of the regions of motion 610, 620, 630 can correspond to different anatomical features of the fetus 102. Thus, in embodiments, cardiac plane data can be utilized to identify the heart region and label the regions of motion and edges based on domain knowledge.

[0055] With reference to FIG. 7, for example, the regions of motion 610, 620, 630 each identified based on the cardiac plane 410 (i.e., shown in FIG. 4). Specifically, region 610 is labeled as corresponding to the right ventricle anterior wall, region 620 is labeled as corresponding to the interventricular septum, and region 630 is labeled as corresponding to the left ventricle posterior wall. As also shown in FIG. 7, the regions 710, 720 between the regions of motion 610, 620, 630 may be labeled in the same manner. In particular, the region 710 between the right ventricle anterior wall and the interventricular septum corresponds to the right ventricle interior diameter, and the region 720 between the interventricular septum and the left ventricle posterior wall corresponds to the left ventricle internal diameter.

[0056] As described herein, this identification and labeling of organs and their relative positions can be done based on the collected B-mode images 410 and relevant domain knowledge in conjunction with a pre-trained machine learning algorithm. For example, in some embodiments, a pre-trained YOFO-based model can be used for organ identification, and in conjunction with domain knowledge of anatomy, the regions of motion identified in the M-mode image can be correlated with organ structures. [0057] Next, the method 300 can include, in a step 320, analyzing the M-mode ultrasound data (e.g., M-mode ultrasound images 420, 530, etc.) to determine a periodicity for one or more of the regions of motion 610, 620, 630. In particular embodiments, the periodicity of a region of motion 610, 620, 630 may be determined by: (i) performing one or more image processing techniques to automatically detect an edge contour of the region of motion 610, 620, 630 present in the M-mode ultrasound data 420, 530; (ii) determining the location of one or multiple local peaks based on the edge contour detected for the region of motion 610, 620, 630; and (iii) determining a periodicity for the region of motion 610, 620, 630 based on the locations of the local peaks. In some embodiments, this process can also involve generating one or multiple markers corresponding to each of the one or multiple local peaks.

[0058] As described herein, the motion pattern and periodicity can be performed through autocorrelation computation to capture all possible variations in the motion patterns and periodicity. For computational efficiency, this process may utilize an FFT-based auto-correlation computation, but other approaches are contemplated. In particular embodiments, the subtle motion in heart location during the ultrasound scan can be compensated for by taking a column-wise maximum of the correlation computation matrix, which provides an indication of periodicity in motion with setting a measure of prominence of the maxima compared to the central maxima. The gaps between the maxima provide the measure of periodicity, and from the position of these maxima, it can be determined (1) whether there is periodicity in motion, (2) if so, the period of motion, consistency in periodicity, or accelerations or decelerations, and (3) if different regions of motion 610, 620, 630 are in sync or go out of sync.

[0059] More specifically, with reference to FIGS. 8A-8E, illustrated are certain steps used to analyze one of the regions of motion 610, 620, 630 of the M-mode ultrasound data 420, 530 and determine a periodicity for the region of motion 610, 620, 630 in accordance with aspects of the present disclosure. As shown in FIG. 8 A, the region of motion 610A is isolated from the M-mode ultrasound data 420. One or more image processing techniques may then be applied to the region of motion 610A in order to generate a processed region 610B. For example, in some embodiments, the region 610A may be normalized and/or smoothed using a Gaussian kernel, or another smoothing filter. As shown in FIG. 8C, a static or adaptive threshold value may be calculated for and applied to the region 610B, which produces the masked region 610C. Next, as shown in FIG. 8D, an edge detection and enhancement algorithm using an appropriate structural element may be applied to the masked region 6 IOC to extract the edge contour 800. Based on the extracted edge contour 800, the local minima / maxima can be calculated and the locations of those minima / maxima can be marked using one or multiple markers 805, 810 as shown in FIG. 8E. In embodiments, the locations of the minima / maxima may only be marked among peaks having similar or consistent gaps between them, such as the markers 805, 810.

[0060] Although the analysis of only one region of motion 610 is illustrated, it should be appreciated that the same methods can be applied to each of the regions of motion 610, 620, 630 identified and labelled in accordance with aspects of the present disclosure. As such, a periodicity of one or multiple regions of motion 610, 620, 630 can be determined.

[0061] The method 300 can then include, in a step 325, determining one or more fetal heart parameters for the fetus 102 based on the periodicity of the one or more regions of motion 610, 620, 630. For example, fetal heart rate can be determined based on the periodicity of one or multiple regions of motion 610, 620, 630. In embodiments, the region between successive extremas can represent a cardiac cycle, where the duration of each cardiac cycle (T, in milliseconds) thus measures the instantaneous fetal heart rate (FHR) values. The FHR values can be expressed in beats per minute (bpm) and calculated according to the following equation:

• • • = 6000/ • where the measurement of value “T” is determined based on the acquisition frequency of the scan. [0062] As described herein, computation of the FHR values over available cardiac cycles may be noted, and the mean and standard deviation of these values may be calculated. In some embodiments, if the standard deviation is within acceptable limits for the patient, then the computed mean is prescribed as the FHR. Otherwise, if the standard deviation is beyond this predetermined range, this could indicate arrhythmia and require further investigation.

[0063] Apart from the fetal heart rate, there are other important structural parameters can be determined, including but not limited to, chamber wall thickness, LVSF, LVM, chamber sizes, and/or the like. For example, hypertrophy may be evaluated by measuring ratios of thicknesses of parameters right ventricular (RV) anterior wall, interventricular septum(IVS), and LV posterior wall (LVPW) in systole and diastole. In further embodiments, other important measurements of interest, such as left ventricular systolic function, can be estimated by computing fractional shortening (FS) and ejection fraction (EF), LV mass and chamber sizes. [0064] In further embodiments, step 325 of the method 300 can include analyzing the M-mode ultrasound data 106 to determine one or more changes in the periodicity of one or more regions of motion 610, 620, 630, and determining one or more fetal heart parameters based on those changes. For example, any asynchronous motion of atria and ventricles or between two atria or two ventricles can also be identified, which could suggest a cardiac arrhythmia, such as tachycardia or bradycardia. For example, in tachycardia, the atria move at a higher rate than the ventricles or vice versa (atrial and ventricular tachycardia, respectively). In bradycardia the fetal heart rate is less than a threshold set for each gestational age. Prenatal diagnosis of these parameter can help preventing the congenital heart defects which may reduce the survival chance of the newborns.

[0065] Also provided herein are steps for validating the fetal heart parameters determined in accordance with aspects of the present disclosure. For example, as shown in FIG. 9, the method 300 can further include: (i) generating a visual validation 910 of the fetal heart parameters for the fetus 102; and (ii) displaying the visual validation 910 on a display device (e.g., display 110) as part of a graphical user interface. In embodiments, the visual validation can include one or more of the following: (a) a visualization 920 of one or more regions of motion 610, 620, 630 of the M- mode ultrasound data; (b) a visualization 930 of the detected edge contour that is superimposed over the visualization of the one or more regions of motion 610, 620, 630 of the M-mode ultrasound data; and/or (c) a visualization 940 of the plurality of markers that is superimposed over the one or more regions of motion 610, 620, 630 of the M-mode ultrasound data at the determined locations.

[0066] It should be appreciated that all combinations of the foregoing concepts and additional concepts discussed in greater detail below (provided such concepts are not mutually inconsistent) are contemplated as being part of the inventive subject matter disclosed herein. In particular, all combinations of claimed subject matter appearing at the end of this disclosure are contemplated as being part of the inventive subject matter disclosed herein. It should also be appreciated that terminology explicitly employed herein that also may appear in any disclosure incorporated by reference should be accorded a meaning most consistent with the particular concepts disclosed herein.

[0067] All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms. [0068] The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”

[0069] The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified.

[0070] As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of’ or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.”

[0071] As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified.

[0072] As used herein, although the terms first, second, third, etc. may be used herein to describe various elements or components, these elements or components should not be limited by these terms. These terms are only used to distinguish one element or component from another element or component. Thus, a first element or component discussed below could be termed a second element or component without departing from the teachings of the inventive concept. [0073] Unless otherwise noted, when an element or component is said to be “connected to,” “coupled to,” or “adjacent to” another element or component, it will be understood that the element or component can be directly connected or coupled to the other element or component, or intervening elements or components may be present. That is, these and similar terms encompass cases where one or more intermediate elements or components may be employed to connect two elements or components. However, when an element or component is said to be “directly connected” to another element or component, this encompasses only cases where the two elements or components are connected to each other without any intermediate or intervening elements or components.

[0074] In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of’ and “consisting essentially of’ shall be closed or semi-closed transitional phrases, respectively.

[0075] It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.

[0076] The above-described examples of the described subject matter can be implemented in any of numerous ways. For example, some aspects can be implemented using hardware, software or a combination thereof. When any aspect is implemented at least in part in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single device or computer or distributed among multiple devices/computers.

[0077] The present disclosure can be implemented as a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure. [0078] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium comprises the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0079] Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.

[0080] Computer readable program instructions for carrying out operations of the present disclosure can be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, comprising an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions can execute entirely on the user’s computer, partly on the user’s computer, as a standalone software package, partly on the user’s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, comprising a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some examples, electronic circuitry comprising, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0081] Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to examples of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

[0082] The computer readable program instructions can be provided to a processor of a, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture comprising instructions which implement aspects of the function/act specified in the flowchart and/or block diagram or blocks.

[0083] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0084] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various examples of the present disclosure. In this regard, each block in the flowchart or block diagrams can represent a module, segment, or portion of ins tractions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks can occur out of the order noted in the Figures. For example, two blocks shown in succession can, in fact, be executed substantially concurrently, or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

[0085] Other implementations are within the scope of the following claims and other claims to which the applicant can be entitled.

[0086] While several inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the inventive teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure.

Claims

Claims What is claimed is:

1. A system (100) for measuring and validating fetal heart parameters of a fetus (102), the system comprising: an ultrasound imaging device (104) comprising one or more ultrasound transducers configured to generate ultrasound data (106) of the fetus (102); and an electronic device (108) in communication with the ultrasound imaging device (104), wherein the electronic device (108) comprises: a display device (110) configured to display a graphical user interface comprising a visual validation of fetal heart parameters; a computer-readable storage medium (204) having stored thereon computer-readable instructions (222) to be executed by one or more processors (202); and one or more processors (202) configured by the computer-readable instructions (222) stored on the computer-readable storage medium (204) to perform the following operations: (i) obtain ultrasound input data (106) comprising M-mode ultrasound data along a cardiac plane of the fetus (102); (ii) automatically localize one or more regions of motion present based on the ultrasound input data (106); (iii) label the one or more regions of motion based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus (102); (iv) analyze the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion; (v) determine one or more fetal heart parameters based on the periodicity determined for the one or more regions of motions.

2. The system (100) of claim 1, wherein the one or more processors (202) are further configured to: analyze the M-mode ultrasound data to determine changes in the periodicity of one or more regions of motion present in the M-mode ultrasound data; and determine one or more fetal heart parameters based on the changes in the periodicity of the one or more regions of motion present in the M-mode ultrasound data.

3. The system (100) of claim 1, wherein the one or more fetal heart parameters includes a fetal heart rate, a heart chamber wall thickness, a left ventricular systolic function, a left ventricular mass, and/or a heart chamber diameter.

4. The system (100) of claim 3, wherein the one or more fetal heart parameters is a ratio of two or more fetal heart parameters.

5. The system (100) of claim 1, wherein the one or more processors (202) are configured to analyze the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion by: detecting an edge contour of at least a first region of motion present in the M-mode ultrasound data; determining a plurality of local peaks based on the edge contour detected for the first region of motion; determining locations for a plurality of markers to be associated with the first region of motion, wherein each marker corresponds to one of the plurality of local peaks determined; and determining a periodicity for at least the first region of motion based on the locations determined for the plurality of markers.

6. The system (100) of claim 5, wherein the one or more processors (202) are further configured to visually validate the fetal heart parameters by: generating a visual validation (910) of fetal heart parameters for the fetus, wherein the visual validation (910) comprises: (a) a visualization (920) of the first region of motion of the M-mode ultrasound data; (b) a visualization (930) of the detected edge contour that is superimposed over the visualization (920) of the first region of motion of the M-mode ultrasound data; and (c) a visualization (940) of the plurality of markers that is superimposed over the first region of motion of the M-mode ultrasound data at the determined locations; and displaying the visual validation (910) of fetal heart parameters via the display device (110) as part of a graphical user interface.

7. The system (100) of claim 1, wherein the ultrasound imaging device (104) is configured to generate B-mode ultrasound data of the fetus (102), and the one or more processors (202) are further configured to perform the following operations: obtain ultrasound input data (106) comprising B-mode ultrasound data, wherein the B-mode ultrasound data includes a cineloop of the fetal cardiac structure and covers a plurality of cardiac cycles for the fetus; and reconstruct M-mode ultrasound data along a cardiac plane of the fetus (102) based on the B-mode ultrasound data obtained from the ultrasound imaging device (104).

8. A computer program product (224) comprising: a non-transitory computer-readable storage medium (204) having stored thereon computer-readable instructions (222) that, when executed by one or more processors (202), cause the one or more processors (202) to perform the following operations: (i) obtain ultrasound input data comprising M-mode ultrasound data along a cardiac plane of the fetus; (ii) automatically localize one or more regions of motion present based on the ultrasound input data; (iii) label the one or more regions of motion based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus; (iv) analyze; (v) determine one or more fetal heart parameters based on the periodicity determined for the one or more regions of motions.

9. A method (300) of measuring fetal heart parameters of a fetus, the method comprising: obtaining (305) ultrasound input data comprising M-mode ultrasound data along a cardiac plane of the fetus; automatically localizing (310) one or more regions of motion present based on the M-mode ultrasound data; labelling (315) the one or more regions of motion present in the M-mode ultrasound data based on domain knowledge, wherein each labelled region of motion corresponds to a different anatomy of the fetus; analyzing (320) the M-mode ultrasound data to determine a periodicity for one or more of the regions of motion; and determining (325) one or more fetal heart parameters for the fetus based on the periodicity of the one or more regions of motions.

10. The method (300) of claim 9, wherein the ultrasound input data comprising M- mode ultrasound data is obtained via an ultrasound imaging device.

11. The method (300) of claim 9, wherein the ultrasound input data comprising M- mode ultrasound data is obtained by: obtaining, via an ultrasound imaging device, ultrasound input data comprising B- mode ultrasound data, wherein the B-mode ultrasound data includes a cineloop of the fetal cardiac structure and covers a plurality of cardiac cycles for the fetus; and reconstructing M-mode ultrasound data long a cardiac plane of the fetus based on the B-mode ultrasound data obtained from the ultrasound imaging device.

12. The method (300) of claim 9, wherein the M-mode ultrasound data is analyzed to determine a periodicity for one or more of the regions of motion by: performing one or more image processing techniques to automatically detect an edge contour of at least a first region of motion present in the M-mode ultrasound data; determining a plurality of local peaks based on the edge contour detected for the first region of motion; determining locations for a plurality of markers to be associated with the first region of motion, wherein each marker corresponds to one of the plurality of local peaks determined; and determining a periodicity for at least the first region of motion based on the locations determined for the plurality of markers.

13. The method (300) of claim 12, further comprising visually validating the fetal heart parameters by: generating a visual validation of fetal heart parameters for the fetus, wherein the visual validation comprises: (a) a visualization of the first region of motion of the M-mode ultrasound data; (b) a visualization of the detected edge contour that is superimposed over the visualization of the first region of motion of the M-mode ultrasound data; and (c) a visualization of the plurality of markers that is superimposed over the first region of motion of the M-mode ultrasound data at the determined locations; and displaying the visual validation of fetal heart parameters via the display device as part of a graphical user interface.

14. The method (300) of claim 9, further comprising: analyzing the M-mode ultrasound data to determine changes in the periodicity of one or more regions of motion present in the M-mode ultrasound data; and determining one or more fetal heart parameters based on the changes in the periodicity of the one or more regions of motion present in the M-mode ultrasound data.

15. The method (300) of claim 9, wherein the one or more fetal heart parameters includes a fetal heart rate, a heart chamber wall thickness, a left ventricular systolic function, a left ventricular mass, and/or a heart chamber diameter.