Methods and systems for modeling a cardiac system

Abstract

This invention provides a system for determining the real-time valvular function of an object. The system includes a processing unit adapted to perform the following operations: obtaining a numerical model of a cardiac system, the numerical model being either a 0D or 1D numerical model, wherein the numerical model is adapted to receive physiological data as input and output, in real-time, a simulated function of the cardiac system, wherein the simulated function of the cardiac system includes a simulated function of the valves within the cardiac system. The processor is further adapted to: obtain a continuous stream of physiological data from the object; provide the continuous stream of physiological data as input to the numerical model of the cardiac system, thereby generating a simulated real-time function of the cardiac system of the object; and determine the real-time valvular function of the object based on the simulated real-time function of the cardiac system of the object.

Description

Technical Field

[0001] This invention relates to the field of cardiac system modeling, and more particularly, to the field of hemodynamic functional modeling. Background Technology

[0002] The human heart contains four valves: the aortic valve, the mitral valve (MV), the pulmonary valve, and the tricuspid valve. The MV, located between the left atrium and the left ventricle, has two main functions: maintaining a hemodynamic seal during ventricular ejection and ensuring rapid ventricular refill after ejection. Optimal MV function depends on several factors, such as hemodynamic load, the biomechanical properties of the MV connective tissue, and the functional anatomy of the left ventricle. Dysfunction in one or more of these factors can lead to suboptimal filling or ejection.

[0003] Mitral regurgitation (MVR) is the most common MV dysfunction, accounting for approximately 70% of all MV dysfunctions. Due to changes in MV function (such as MV prolapse or cardiomyopathy), the MV no longer maintains unidirectional flow in MVR. Retrograde blood flow enters the left atrium during ventricular ejection. This increases the hemodynamic load in the left atrium (also known as volume overload), which can lead to other heart-related conditions such as atrial fibrillation.

[0004] MVR can be corrected in either of the following ways: repairing the existing valve; or replacing it with a prosthesis. However, repair has significant benefits, such as reduced mortality (2.0% for repair, 6.1% for replacement) and minimizing other complications such as thrombosis. One such repair technique for MVR is edge-to-edge repair (ETER), which attempts to restore MV fusion by physically connecting the prolapsed areas together.

[0005] ETER was originally developed as an open-chest surgery (i.e., midline sternotomy). However, minimally invasive methods are now available, where repair is performed using a percutaneous delivery device. Such a device can take the form of a clamp that holds the prolapsed area together. However, there remains some uncertainty regarding the number of devices required to restore normal valve function during the deployment of such a device. Typically, during the procedure, the clinician must determine whether the current repair is sufficient or whether the subject requires further repair.

[0006] While ETER mitigates MVR, it can negatively impact ventricular filling. Therefore, ETER aims to strike a balance between reducing retrograde inflow to the atria during ventricular systole and avoiding reducing the orifice area, which can impair ventricular filling. For this reason, a common dilemma is whether to place an additional repair device (which could further reduce the orifice area and potentially impair ventricular filling) or to accept the current configuration while assuming no adequate reduction in MVR.

[0007] Imaging tools can be used to provide anatomical guidance, reducing uncertainty in deciding whether to provide additional repair equipment. However, these tools lack hemodynamic information related to blood flow in the repair area.

[0008] Document US2018 / 174068 discloses an object-specific simulation model of at least one component in the cardiovascular system for simulating blood flow and / or structural features. Summary of the Invention

[0009] This invention is defined by the claims.

[0010] According to an example of one aspect of the present invention, a system for determining the real-time valve function of an object is provided, the system comprising:

[0011] Processing unit, which is suitable for:

[0012] A numerical model of the cardiac system is obtained, wherein the numerical model is a 0D numerical model or a 1D numerical model, wherein the numerical model is adapted to receive physiological data as input and output the simulation function of the cardiac system in real time, wherein the simulation function of the cardiac system includes the simulation function of the valves within the cardiac system.

[0013] A continuous stream of physiological data obtained from an object;

[0014] The continuous stream of physiological data is provided as input to the numerical model of the cardiac system, thereby generating a real-time simulation of the cardiac system of the object; and

[0015] The real-time valve function of the object is determined based on the simulated real-time function of the object's cardiac system.

[0016] The system provides a means of determining the real-time hemodynamic function of an object.

[0017] For example, when performing percutaneous flap repair, clinicians may need data related to the patient's hemodynamic function to make a decision. Such data is typically determined based on qualitative anatomical examination and user-related measurements, both of which can vary in accuracy.

[0018] However, these decisions and their consequences often remain unclear. Therefore, by providing an accurate model of an object's real-time hemodynamic function based on object-specific measurements, a more accurate description of the object's hemodynamic function over time can be generated. This may then lead to a clearer understanding of the state of the cardiac system and subsequently enable clinicians to make more beneficial decisions.

[0019] In one embodiment, a continuous stream of physiological data is obtained from an object experiencing changes in valvular function, and wherein the real-time valvular function, determined based on a simulation of the real-time function of the cardiac system, represents the changes in valvular function.

[0020] In this way, changes in valvular function can be monitored and even predicted by the system through numerical models that take into account the entire cardiac system.

[0021] In another embodiment, the system is suitable for use when a subject is undergoing valve repair.

[0022] In this way, the system can provide users with guidance and support information during the valve repair process.

[0023] In one embodiment, the system further includes a physiological sensor adapted to obtain physiological data from an object, wherein the sensor includes one or more of the following:

[0024] An electrocardiogram (ECG) sensor, wherein the physiological data includes ECG data;

[0025] A blood pressure measuring device, wherein the physiological data includes numerical pressure data and / or pressure waveform data; and

[0026] A volume waveform sensor, wherein the physiological data includes volume waveform data.

[0027] In another embodiment, the volume waveform sensor includes one or more of the following:

[0028] An ultrasonic transducer, wherein the volumetric waveform data includes ultrasonic data;

[0029] Inflatable cuffs, suitable for wearing by the object; and

[0030] A conduit with a thermistor at one end, wherein the volume waveform data is derived using a thermal dilution technique.

[0031] In one embodiment, the numerical model is based on physical parameters, and the processor is further adapted to adjust the physical parameters of the numerical model based on at least a portion of the continuous stream of physiological data.

[0032] In this way, numerical models can be customized for objects based on changes in physiological data over time.

[0033] In one embodiment, the numerical model is based on physical parameters, and the processor is further adapted to:

[0034] Preliminary physiological data were obtained from the object; and

[0035] The physical parameters of the numerical model are adjusted based on preliminary physiological data from the object.

[0036] In this way, the numerical model can be customized for the object before the simulation begins, thereby improving the accuracy of the determined hemodynamic functions.

[0037] In one embodiment, the numerical model is based on physical parameters, and the method further includes predicting the future hemodynamic functions of the object, wherein the processor is also adapted to:

[0038] Adjust the physical parameters of the numerical model to generate a predictive numerical model;

[0039] The continuous stream of physiological data is provided as input to the predictive numerical model, thereby simulating the predictive function of the object's cardiac system; and

[0040] The future hemodynamic function of the object is predicted based on the predictive capabilities of the simulation of the object's cardiac system.

[0041] This allows for the simulation of various scenarios that affect hemodynamic function in different ways. For example, the effects of various stresses or drugs on the cardiac system can be studied within a simulated safety context.

[0042] In one embodiment, the physiological data includes one or more of the following:

[0043] Electrocardiogram data;

[0044] Pressure numerical data;

[0045] Pressure waveform data;

[0046] Physiological data based on echocardiography; and

[0047] Volume waveform data.

[0048] In another embodiment, the volume waveform data includes one or more of the following:

[0049] Ventricular volume waveform; and

[0050] Atrial volume waveform.

[0051] In one embodiment, the volumetric waveform data includes ultrasonic data.

[0052] In one embodiment, the pressure waveform data includes one or more of the following:

[0053] Atrial pressure waveform; and

[0054] Arterial pressure waveform.

[0055] In one embodiment, the physiological data includes estimated physiological data.

[0056] In this way, intermittent data collection can be considered by providing estimated data.

[0057] According to an example of one aspect of the present invention, a method for determining the real-time valve function of an object is provided, the method comprising:

[0058] A numerical model of the cardiac system is obtained, wherein the numerical model is a 0D numerical model or a 1D numerical model, wherein the numerical model is adapted to receive physiological data as input and output the simulation function of the cardiac system in real time, wherein the simulation function of the cardiac system includes the simulation function of the valves within the cardiac system.

[0059] A continuous stream of physiological data is obtained from the object;

[0060] The continuous stream of physiological data is provided as input to the numerical model of the cardiac system, thereby generating a real-time simulation of the cardiac system of the object; and

[0061] The real-time valve function of the object is determined based on the simulated real-time function of the object's cardiac system.

[0062] According to an example of one aspect of the present invention, a computer program including computer program code units is provided, wherein when the computer program is run on a computer, the computer program code units are adapted to implement the method as described above.

[0063] These and other aspects of the invention will become apparent and will be explained with reference to the embodiments described below. Attached Figure Description

[0064] To better understand the invention and to more clearly illustrate how it can be practiced, reference will now be made to the accompanying drawings by way of example only, wherein,

[0065] Figure 1 An ultrasound diagnostic imaging system for explaining general operation is shown;

[0066] Figure 2 The method of the present invention is shown;

[0067] Figure 3 A schematic diagram of the numerical model is shown;

[0068] Figure 4 An example of simulated hemodynamic function of the cardiac system is shown; and

[0069] Figure 5 A schematic diagram of a system for deriving the hemodynamic function of an object's cardiac system is shown. Detailed Implementation

[0070] The invention will be described with reference to the accompanying drawings.

[0071] It should be understood that while the detailed description and specific examples indicate exemplary embodiments of the devices, systems, and methods, they are intended for illustrative purposes only and are not intended to limit the scope of the invention. These and other features, aspects, and advantages of the devices, systems, and methods of the present invention will be better understood from the following description, the appended claims, and the accompanying drawings. It should be understood that the drawings are schematic only and are not drawn to scale. It should also be understood that the same reference numerals are used throughout the drawings to denote the same or similar parts.

[0072] This invention provides a system for determining the real-time valvular function of an object. The system includes a processing unit adapted to perform the following operations: obtaining a numerical model of a cardiac system, the numerical model being either a 0D or 1D numerical model, wherein the numerical model is adapted to receive physiological data as input and output, in real-time, a simulated function of the cardiac system, wherein the simulated function of the cardiac system includes a simulated function of the valves within the cardiac system. The processor is further adapted to obtain a continuous stream of physiological data from the object; provide the continuous stream of physiological data as input to the numerical model of the cardiac system, thereby generating a simulated function of the cardiac system of the object; and determine the real-time valvular function of the object based on the real-time function of the simulated cardiac system of the object.

[0073] First, refer to Figure 1 The present invention describes the general operation of an exemplary ultrasound system, with an emphasis on the system’s signal processing capabilities, as the present invention relates to the processing of signals measured by a transducer array.

[0074] The system includes an array transducer probe 4 having a transducer array 6 for transmitting ultrasound and receiving echo information. The transducer array 6 may include: a capacitive micromechanical ultrasonic transducer (CMUT); a piezoelectric transducer made of materials such as PZT (lead zirconate titanate) or PVDF (polyvinylidene fluoride); or any other suitable transducer technology. In this example, the transducer array 6 is a two-dimensional array of transducers 8 capable of scanning a 2D plane or a three-dimensional volume of a region of interest. In another example, the transducer array may be a 1D array.

[0075] The transducer array 6 is coupled to a microwave beamformer 12, which controls the signal reception of the transducer elements. As described in U.S. Patents US 5,997,479 (Savord et al.), US 6,013,032 (Savord), and US 6,623,432 (Powers et al.), the microwave beamformer is capable of performing at least partial beamforming on the signals received by the subarrays of the transducers (generally referred to as a “group” or “patch”).

[0076] It should be noted that the microwave beamformer is entirely optional. Furthermore, the system includes a transmit / receive (T / R) switch 16, to which the microwave beamformer 12 can be coupled and used to switch the array between transmit and receive modes, and to protect the main beamformer 20 from high-energy transmitted signals when the microwave beamformer is not used and the transducer array is directly operated by the main system beamformer. The transmission of the ultrasonic beam from the transducer array 6 is indicated via the T / R switch 16 to a transducer controller 18 of the microwave beamformer and the main transmitting beamformer (not shown), which can receive input from user-to-user interface or control panel 38. The controller 18 may include transmit circuitry arranged to drive the transducer elements of array 6 during transmit mode (directly or via the microwave beamformer).

[0077] In a typical line-by-line imaging sequence, the beamforming system within the probe can operate as follows. During transmission, a beamformer (which may be a microwave beamformer or a main system beamformer, depending on the implementation) activates the transducer array or sub-apertures of the transducer array. The sub-apertures can be one-dimensional lines of transducers within a larger array or two-dimensional sheets of transducers. In transmission mode, the focusing and steering of the ultrasonic beam generated by the array or its sub-apertures are controlled as described below.

[0078] Upon receiving the backscattered echo signal from the object, the received signal undergoes receive beamforming (as described below) to align the received signal, and, in the case of a sub-aperture, the sub-aperture is shifted, for example, by a transducer element. The shifted sub-aperture is then activated, and this process is repeated until all transducer elements of the transducer array are activated.

[0079] For each line (or sub-aperture), the total received signal associated with the line used to form the final ultrasound image will be the sum of the voltage signals measured by the transducer elements of a given sub-aperture during the reception period. Following the beamforming process below, the resulting line signals are typically referred to as radio frequency (RF) data. Each line signal (RF dataset) generated from the individual sub-apertures is then further processed to generate the line of the final ultrasound image. The variation in the amplitude of the line signal over time contributes to the variation in brightness of the ultrasound image with depth, where high-amplitude peaks will correspond to bright pixels (or sets of pixels) in the final image. Peaks appearing near the beginning of the line signal will represent echoes from shallow structures, while peaks appearing later in the line signal will represent echoes from structures of increasing depth within the object.

[0080] One of the functions controlled by the transducer controller 18 is the direction in which the beam is steered and focused. The beam can be steered vertically forward from the transducer array (perpendicular to the transducer array) or at different angles for a wider field of view. The steer and focus of the transmitted beam can be controlled based on the actuation time of the transducer elements.

[0081] In conventional ultrasound data acquisition, two methods can be distinguished: plane wave imaging and beam steering imaging. The difference between the two methods lies in the presence of beamforming in the transmit mode (beam steering imaging) and / or receive mode (plane wave imaging and beam steering imaging).

[0082] First, let's look at the focusing function. By simultaneously activating all transducer elements, the transducer array generates a plane wave that diverges as it passes through an object. In this case, the ultrasound beam remains unfocused. By introducing a location-dependent time delay into the transducer activation, the wavefront of the beam can be converged to a desired point, called the focal zone. The focal zone is defined as a point where the lateral beamwidth is less than half the width of the emitted beam. In this way, the lateral resolution of the final ultrasound image is improved.

[0083] For example, if a time delay causes the transducer elements to activate sequentially, starting from the outermost element and ending at one or more central elements of the transducer array, a focal region will be formed at a given distance from the probe, aligned with the central elements. The distance between the focal region and the probe will vary depending on the time delay between each subsequent round of transducer element activation. After the beam passes through the focal region, it will begin to diverge, forming a far-field imaging region. It should be noted that for the focal region located close to the transducer array, the ultrasound beam will diverge rapidly in the far field, resulting in beamwidth artifacts in the final image. Typically, due to large overlap in the ultrasound beam, little detail is displayed in the near field between the transducer array and the focal region. Therefore, changing the position of the focal region can lead to significant changes in the final image quality.

[0084] It should be noted that in emission mode, only one focus can be defined unless the ultrasound image is divided into multiple focal regions (each of which may have a different emission focus).

[0085] Furthermore, upon receiving an echo signal from within the object, the reverse process described above can be performed to achieve receiver focusing. In other words, the incoming signal can be received by the transducer elements and undergoes an electronic time delay before being transmitted to the system for signal processing. The simplest example is called delay-summation beamforming. The receiver focusing of the transducer array can be dynamically adjusted according to time.

[0086] Now consider the function of beam steering. By correctly applying a time delay to the transducer elements, a desired angle can be imparted to the ultrasonic beam as it leaves the transducer array. For example, by activating the transducers on the first side of the transducer array, and then activating the remaining transducers in a sequence ending on the opposite side of the array, the wavefront of the beam will tilt towards the second side. The magnitude of the steering angle relative to the normal of the transducer array depends on the magnitude of the time delay between the subsequent activation of the transducer elements.

[0087] Furthermore, the steering beam can be focused, where the total time delay applied to each transducer element is the sum of the focusing and steering time delays. In this case, the transducer array is called a phased array.

[0088] When the CMUT transducer requires a DC bias to be activated, the transducer controller 18 can be coupled to control the DC bias controller 45 of the transducer array. The DC bias controller 45 sets the bias applied to one or more of the CMUT transducer elements.

[0089] For each transducer element in the transducer array, an analog ultrasonic signal (typically referred to as channel data) enters the system through a receiving channel. In the receiving channel, a partially beamformed signal is generated from the channel data by a microwave beamformer 12 and then transmitted to a main receiving beamformer 20. In the main receiving beamformer 20, the partially beamformed signals from individual transducer elements are combined into a fully beamformed signal, referred to as radio frequency (RF) data. Beamforming at each stage can be performed as described above, or additional functionality can be included. For example, the main beamformer 20 may have 128 channels, each receiving tens or hundreds of partially beamformed signals from the transducer elements. In this way, signals received by thousands of transducers in the transducer array can be effectively contributed to a single beamformed signal.

[0090] The beamformed received signal is coupled to signal processor 22. Signal processor 22 can process the received echo signal in various ways, such as: bandpass filtering; decimation; I and Q component separation; and harmonic signal separation to separate linear and nonlinear signals in order to identify nonlinear (higher harmonics of the fundamental frequency) echo signals returning from tissue and microbubbles. The processor can also perform signal enhancement, such as ripple reduction, signal recombination, and noise cancellation. The bandpass filter in the signal processor can be a tracking filter, wherein its passband slides from a higher frequency band to a lower frequency band as the echo signal is received from increasing depth, thereby rejecting noise from higher frequencies at greater depths, which typically lacks anatomical information.

[0091] Beamformers for transmitting and receiving are implemented in different hardware and can have different functions. Of course, the receiver beamformer is designed to take into account the characteristics of the transmitting beamformer. For simplicity, in... Figure 1 Only receiver beamformers 12 and 20 are shown in the diagram. Throughout the system, there will also be a transmitter chain with a transmit microwave beamformer and a main transmit beamformer.

[0092] The function of microwave beamformer 12 is to provide an initial combination of signals in order to reduce the number of analog signal paths. This is typically performed in the analog domain.

[0093] The final beamforming is performed in the main beamformer 20, and typically after digitization.

[0094] The transmit and receive channels use the same transducer array 6 with a fixed frequency band. However, the bandwidth occupied by the transmit pulse can vary depending on the transmit beamforming used. The receive channel can capture the entire transducer bandwidth (this is the classic approach), or it can extract only the bandwidth containing the desired information (e.g., harmonics of the main harmonic) by using bandpass processing.

[0095] The RF signal can then be coupled to a B-mode (i.e., luminance mode or 2D imaging mode) processor 26 and a Doppler processor 28. The B-mode processor 26 performs amplitude detection on the received ultrasound signal to image structures in the body, such as organs, tissues, and blood vessels. In the case of line-by-line imaging, each line (beam) is represented by an associated RF signal whose amplitude is used to generate a luminance value to be assigned to a pixel in the B-mode image. The exact location of a pixel within the image is determined by its position along the associated amplitude measurement of the RF signal and the number of lines (beams) of the RF signal. B-mode images of this configuration can be formed in harmonic or fundamental image modes or a combination of both, as described in U.S. Patent 6283919 (Roundhill et al.) and U.S. Patent 6458083 (Jago et al.). The Doppler processor 28 can process temporally discrete signals originating from tissue motion and blood flow for detecting moving substances, such as the flow of blood cells in the image field. Doppler processor 28 typically includes a wall filter having parameters that are set to allow or reject echoes returning from a selected type of material in the body.

[0096] The structural and motion signals generated by the B-mode and Doppler processors are coupled to a scan converter 32 and a multiplane reformer 44. The scan converter 32 arranges the echo signals in the desired image format according to the spatial relationships in which the echo signals are received. In other words, the scan converter converts the RF data from a cylindrical coordinate system to a Cartesian coordinate system suitable for displaying an ultrasound image on an image display 40. In the case of B-mode imaging, the brightness of a pixel at a given coordinate is proportional to the amplitude of the RF signal received from that location. For example, the scan converter can arrange the echo signals in a two-dimensional (2D) sector format or a cone-shaped three-dimensional (3D) image. The scan converter can superimpose colors corresponding to the motion of individual points in the image field onto the B-mode structural image, where the Doppler-estimated velocity produces the given color. The combined B-mode structural image and color Doppler image describe the motion of tissue and blood flow within the structural image field. The multiplane reformer converts echoes received from points in a common plane within a volumetric region of the body into an ultrasound image of that plane, as described in U.S. Patent US 6443896 (Detmer). Volume plotter 42 converts the echo signal of the 3D dataset into a 3D image of the projection as seen from a given reference point, as described in U.S. Patent US 6530885 (Entrekin et al.).

[0097] 2D or 3D images are coupled from the scan converter 82, multiplane reformer 44, and volume plotter 42 to the image processor 30 for further enhancement, caching, and temporary storage for display on the image display 40. The image processor may be adapted to remove certain imaging artifacts from the final ultrasound image, such as: acoustic shadows, e.g., caused by strong attenuators or refraction; post-enhancement, e.g., caused by weak attenuators; reverberation artifacts, e.g., adjacent locations of highly reflective tissue interfaces; and so on. Additionally, the image processor may be adapted to perform specific ripple reduction functions to improve the contrast of the final ultrasound image.

[0098] In addition to being used for imaging, blood flow values ​​generated by the Doppler processor 28 and tissue structure information generated by the B-mode processor 26 are coupled to the quantization processor 34. The quantization processor generates measurements of different flow conditions (e.g., blood flow volume ratio) and structural measurements (e.g., organ size and gestational age). The quantization processor 46 can receive output from the user control panel 38, such as points in the anatomical structures of the image to be measured.

[0099] Output data PUHC from the quantization processor is coupled to the graphics processor 36 for reproducing measurement graphs and values ​​on the display 40 along with images, and for outputting audio from the display device 40. The graphics processor 36 can also generate graphic overlays for display alongside ultrasound images. These overlays may include standard identification information such as the patient's name, date and time of the image, imaging parameters, etc. For these purposes, the graphics processor receives input from the user interface 38, such as the patient's name. The user interface is also coupled to the transmit controller 18 to control the generation of ultrasound signals from the transducer array 6, and thus control the images generated by the transducer array and the ultrasound system. The transmit control function of the controller 18 is only one of the functions performed. The controller 18 also considers the operating mode (given by the user) and the corresponding required transmitter and bandpass configurations in the receiver analog-to-digital converter. The controller 18 may be a state machine with fixed states.

[0100] The user interface can also be coupled to the multiplane reformer 44 to select and control the planes of multiple multiplane reformulated (MPR) images, which can be used to perform quantization measurements in the image field of the MPR images.

[0101] The method described herein can be executed on a processing unit. Such a processing unit can be located within an ultrasound system, such as the one described above. Figure 1 The system described. For example, the image processor 30 described above can perform some or all of the method steps detailed below. Alternatively, the processing unit can be located in any suitable system adapted to receive object-related input, such as a monitoring system.

[0102] Figure 2 A method 100 for determining the real-time hemodynamic function of an object is shown. Real-time hemodynamic function can refer to any bodily function involving the movement or flow of blood. For example, real-time hemodynamic function can refer to the movement of blood through valves, such as the mitral or aortic valve. Furthermore, real-time hemodynamic function can refer to the volume changes of a given cardiac chamber (e.g., an atrium or ventricle).

[0103] The method begins at step 110, obtaining a numerical model of the cardiac system, wherein the numerical model is adapted to take physiological data as input and output a function of the cardiac system, the simulated function of the cardiac system including the simulated function of the valves within the cardiac system.

[0104] In other words, a numerical model simulates the function of a given cardiac system, such as several ventricles, atria, systemic arteries, the left side of the heart, the entire heart, etc. For example, the cardiac system can include the left ventricle and systemic arteries. See below for reference. Figure 3 An example of a numerical model describing the cardiac system.

[0105] Numerical models can be constructed based on multiple physical parameters. For example, a numerical model can be based on any one or more of the following: pressure-volume relationship; stiffness of the cardiac system; energy conservation; mass conservation; and momentum conservation. A numerical model can also include a system arterial model, representing the object's arterial system.

[0106] Incorporating physical parameters into numerical models provides a framework within which data from various sources (e.g., ultrasound data; peripheral, whole-body, or intracardiac blood pressure data; clinical guidelines; machine learning estimates; etc.) can be fused together according to physical principles (e.g., conservation of mass, momentum, and energy). This allows for more consistent estimations of results from numerical models (e.g., real-time hemodynamic functions), particularly when the input is noisy or received from different imaging modalities and / or at different time points.

[0107] When the numerical model is based on one or more physical parameters, the method may further include adjusting the physical parameters(s) of the numerical model based on at least a portion of a continuous stream of physiological data. Alternatively, preliminary physiological data can be obtained from the objects and used to adjust the physical parameters(s) of the numerical model. Furthermore, the physical parameters of the numerical model can be adjusted based on physiological data collected from multiple objects, i.e., using a set of physiological data.

[0108] In other words, patient-specific data can be used to tailor numerical models for individual users. This can be performed using a continuous stream of physiological data during the examination, or using preliminary physiological data prior to the examination, which can be collected from the same source as the continuous stream of physiological data. By using patient-specific inputs (e.g., ultrasound volume segmentation acquired from ultrasound data or peripheral pressure measurements), a personalized numerical model can be created for each patient, providing patient-specific estimates of cardiac function, such as real-time hemodynamics.

[0109] Adjusting the numerical model can include identifying physical parameters based on physiological data and providing those physical parameters to the numerical model.

[0110] For example, (one or more) physical parameters may include one or more of the following: systemic circulatory parameters; filling parameters; ejection parameters; heart rate parameters; stiffness parameters; valve-related parameters, such as valvular regurgitation or valve opening size; blood flow parameters; etc.

[0111] For example, arterial blood pressure measurements can be used to adjust parameters in a systemic arterial model. Arterial blood pressure measurements can include one or more of the maximum, minimum, and average blood pressure values. Arterial blood pressure measurements can be used to adjust the resistance and compliance of the systemic system in a numerical model, and vice versa.

[0112] In the example, the ventricular pressure measurement can be derived using an estimate of the pressure gradient across the aortic valve. Doppler ultrasound measurements can be used to estimate the pressure gradient across the aortic valve. In the simplest implementation, the pressure gradient across the aortic valve can be assumed to be zero.

[0113] Using the complete blood pressure waveform can further refine the tuning of the numerical model. In this way, the numerical model can be further personalized to the object, for example, by including a pressure decay constant in the simulation of the cardiac system, which can be used to model the stiffness and relaxation of the heart chambers.

[0114] Blood pressure information used to adjust the numerical model can be obtained from peripheral arteries (such as the brachial or radial arteries) or systemic arteries (such as the aorta or femoral artery). Due to variations in vessel diameter and stiffness, peripheral pressure measurements at these locations are amplified relative to central aortic pressure values.

[0115] In numerical models, multi-step methods can be used to identify physical parameters. For example, physical parameters representing systemic circulation (i.e., parameters related to the afterload of the cardiac system) can be identified first, followed by parameters representing cardiac ejection and filling. These patient-specific physical parameters can be estimated using a combination of techniques such as physiology-based rule-based methods, direct optimization methods, and sequential filtering methods.

[0116] In step 120, a continuous stream of physiological data is obtained from the object. The continuous stream of physiological data can be obtained from the object in any suitable manner depending on the application.

[0117] Physiological data may include one or more of the following: electrocardiogram data; pressure waveform data, which may include atrial pressure waveforms and / or arterial pressure waveforms; and volume waveform data, which may include ventricular volume waveforms and / or atrial volume waveforms. Volume waveform data may be based on ultrasound data collected from the subject. Furthermore, physiological data includes estimated physiological data, wherein the estimated physiological data is estimated based on available intermittent physiological data, thereby generating a continuous stream of physiological data based on the intermittent physiological data.

[0118] In step 130, a continuous stream of physiological data is provided as input to the numerical model of the cardiac system, thereby simulating the real-time function of the target cardiac system. (See below for reference.) Figure 4 Further discussion will focus on examples of simulating the real-time function of the cardiac system.

[0119] In step 140, the real-time hemodynamic function of the object is determined based on the real-time function of the simulation of the object's cardiac system.

[0120] In patients undergoing MVR repair via minimally invasive ETER, the goal is to reduce the level of MV regurgitation without significantly reducing impaired ventricular filling. In approximately 40% of ETER procedures, this requires the use of multiple devices, such as clamps, and the benefit of the second device is typically determined intraoperatively after successful deployment of the first device. Current decision-making processes rely primarily on echocardiographic assessment (i.e., qualitative anatomical examination) or on user-related measurements (e.g., pressure gradients across the MV).

[0121] However, the benefits of additional equipment remain unclear. In such cases, the hemodynamic state of the subject can be pharmacologically altered to simulate a more representative hemodynamic state, allowing for further testing of ETER's hemodynamic function (e.g., regurgitation level and filling volume at specific phases of the cardiac cycle) under normal conditions (i.e., post-intervention). Observing the hemodynamic response to these alterations allows cardiologists to determine the suitability of the current ETER configuration.

[0122] The methods described above can provide real-time assessment of hemodynamic function during the ETER procedure using numerical models. Using patient-specific inputs (e.g., ultrasound volume segmentation, pressure waveforms, etc.), this model can be personalized per beat for each individual, thus providing subject-specific real-time estimates of hemodynamic function.

[0123] For example, the method can be deployed as follows. During the ETER procedure, intermittent ultrasound is typically used, which would otherwise provide only a limited assessment of the hemodynamic function of the subject's cardiac system. However, pressure waveforms, such as left atrial and arterial pressures, can be continuously recorded.

[0124] Numerical models can take pressure waveforms and simultaneous volumetric waveforms (segmented from ultrasound data when available) as inputs and output continuous estimates of the object's hemodynamic function. Volumetric waveforms can also be obtained using alternative techniques, such as using inflatable finger cots, thermal dilution techniques, or by estimating the complete volumetric waveform based on available ultrasound data. The outputs of numerical models can provide decision support for the effectiveness of deploying additional reparative equipment.

[0125] In addition, numerical models can generate corresponding pressure-volume hysteresis loops for the left ventricle (atrium and ventricle), thereby providing further physiological information for clinical assessment, such as the heart's ability to adapt to changing conditions (e.g., exercise and / or stress).

[0126] In other words, the cardiac system can represent the heart of the object, and in particular the left heart, and the method can also include determining the pressure-volume hysteresis of the left ventricle and / or left atrium of the cardiac system based on the real-time function of the simulated cardiac system of the object.

[0127] In the above method, the real-time function of the object's valves is determined based on real-time simulations generated from a continuous stream of physiological data. Real-time simulation means there is virtually no noticeable delay between the generation of the numerical model receiving the continuous physiological data stream and the simulation of the cardiac system. In other words, the output of the real-time simulation of the cardiac system is, or nearly is, simultaneous with, the current state of the object's actual cardiac system. In this way, the system can provide accurate real-time simulations of cardiac function, which can be used during interventional procedures such as edge-to-edge repair to assess the progress of the procedure.

[0128] Since pharmacologically altered cardiac states are not always possible or desirable, numerical models can be used to predict a subject's future hemodynamic function. For example, physical parameters of the numerical model, such as valvular ejection or regurgitation, can be adjusted according to the desired predictive scenario. A continuous stream of physiological data can then be fed as input to the predictive numerical model, simulating the predicted function of the subject's cardiac system. Therefore, the subject's future hemodynamic function can be predicted based on the simulated predictive function of the subject's cardiac system.

[0129] For example, during the ETER procedure, anesthetic drugs are administered to the subject, which temporarily reduce vascular tone, thereby reducing cardiac afterload. Therefore, the hemodynamic function assessed during ETER may not represent normal conditions. Numerical models can therefore be used to virtually predict the effects of increased afterload, providing an estimate of post-intervention hemodynamic function. Consequently, numerical models can be used to provide additional decision support for adding further restorative devices.

[0130] In other words, a system for determining the real-time valve function of an object may include one or more edge-to-edge valve repair devices and a processing unit suitable for performing the steps described above.

[0131] More specifically, the processing unit can be adapted to obtain a numerical model of the cardiac system, as described herein, and to obtain a continuous stream of physiological data from the object. This continuous stream of physiological data can be obtained from objects undergoing changes in valvular function, for example, due to the deployment of edge-to-edge valve repair devices at the valve.

[0132] A continuous stream of physiological data can be fed as input to a numerical model of the cardiac system, thereby generating a simulated real-time function of the object's cardiac system. Based on this simulated real-time function, the object's real-time valvular function can be determined. The real-time valvular function determined from the simulated real-time function of the cardiac system can represent changes in valvular function.

[0133] Determining the real-time valvular function of an object can be performed by adjusting the simulated real-time function of the cardiac system based on changes in vascular tension in the cardiac system caused by the anesthetic administered to the object. Furthermore, the numerical model can also be adapted to predict future simulated valvular function based on the determined real-time valvular function of the object by providing additional edge-to-edge valve repair devices to the valves.

[0134] Figure 3 An example of a schematic representation of a numerical model 200 of a part of the cardiac system, namely the left ventricle 210 and the aorta 220, is shown.

[0135] This example illustrates a simplified 0D approach to simulate blood flow or hemodynamic function during the cardiac cycle. However, 1D / 3D modeling methods can also be combined within the described framework, and models of the complete circulatory system can also be included.

[0136] Zero-dimensional (0D) models, also known as lumped-parameter models, generate a set of simultaneous ordinary differential equations (ODEs) describing the behavior of the cardiac system, as illustrated in Shi, Y., Lawford, P. & Hose, R., “Review of Zero-D and 1-D Models of Blood Flow in the Cardiovascular System”, BioMed Eng OnLine 10, 33 (2011), https: / / doi.org / 10.1186 / 1475-925X-10-33. When representing the vascular system, there are typically two ODEs for each compartment, representing conservation of mass and momentum, which can be supplemented by algebraic balance equations relating compartment volume to pressure. Numerical models built from 0D components are typically characterized by the major components of the cardiac system, such as the heart, heart valves, and compartments of the vascular system, and are suitable for examining the global distribution of pressure, flow, and blood volume under certain physiological conditions.

[0137] One-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) models generate a series of partial differential equations (Navier-Stokes equations) describing the conservation of mass and momentum, which can be supplemented by algebraic equilibrium equations. In the context of cardiovascular numerical modeling, one-dimensional models are convenient for representing wave transmission effects within the vascular system and can be used to represent the aorta and larger arteries throughout the body. 3D models can be used to compute complex flow patterns, such as those in the ventricles, around heart valves, near bifurcation, or any region with eddy or separated flows. Except for the simplest geometries, no analytical solution is available for any 3D model, and numerical solutions are always resorted to.

[0138] For example, during the ETER procedure, numerical models may be needed to estimate the real-time hemodynamic function of the mitral valve in the target. Figure 3 An example of 0D numerical model 200 is shown, represented as an electronic circuit.

[0139] In 0D modeling, the concept of hydraulic-electrical simulation is frequently applied. Typically, there are numerous similarities between blood flow in a circulatory system and electrical conduction in a circuit. For example, the blood pressure gradient in a circulatory loop drives blood to flow against hydraulic resistance, while the voltage gradient in a circuit drives current to flow against electrical impedance. Hydraulic impedance represents the combined effects of frictional losses, vessel wall elasticity, and blood inertia in blood flow, while electrical impedance represents the combination of resistance, capacitance, and inductance in a circuit.

[0140] exist Figure 3 In the model shown, voltage represents blood pressure and current represents blood flow. In this method, different compartments of the arterial system (such as atria, ventricles, aorta, etc.) are combined into electrical components related to hemodynamic analogues, such as resistors and capacitors.

[0141] Starting from the left 210, the power supply (P) la The variable capacitor 230 will be charged, simulating the left atrium pumping blood into the left ventricle. The left atrium will fill the left ventricle (variable capacitor) to its passive limit. Physiological data obtained from the object may include the continuous flow of left atrial pressure, which can be used to inform the behavior of the model's left atrium.

[0142] The capacitance of variable capacitor 230 represents the stiffness of the ventricle, i.e., muscle contraction. Volume is a state variable derived from the user's physiological data.

[0143] E lv This refers to the elasticity of the left ventricle. It relates ventricular volume to the pressure within the left ventricle. Although it is a measure of stiffness (i.e., ventricular muscle contraction), it is not material stiffness in the strict sense. This relationship has been experimentally measured based on simultaneous ventricular pressure and volume waveforms.

[0144] The charge travels along the circuit, where diode 240 acts as a valve to define the direction of flow. The blood (charge) then enters the aorta 220 and enters the systemic circulatory system.

[0145] Resistance term (mitral valve resistance, R) mv Aortic valve resistance, R av Proximal systemic resistance, R sys＝p Distal systemic resistance, R sys＝d ) represents the resistance of blood vessels and valves to blood flow and is directly related to the pressure in a given area. C sys This indicates overall body compliance. The resistance term can represent various narrowings within the cardiac system.

[0146] In this example, the model parameters are represented using an electrical simulation. However, such a model does follow physical principles, such as the conservation of mass, for example, the conservation of blood flow (current) into each node of the model. Furthermore, the electrical simulation can be derived from a linearization of the mass and momentum conservation equations for blood flow in a deformable vessel.

[0147] By acquiring a continuous stream of physiological data and inputs (such as a combination of ultrasound data and pressure waveforms obtained from the object), numerical models can output a representation of the real-time hemodynamic function of the object's cardiac system.

[0148] It should be noted that, Figure 3 The example shown is just one of many possible models of the left ventricle. Different components of the model can be interchanged depending on the specific application. In the example from the ETER program, the numerical model can be adapted to include a regurgitated mitral valve. Furthermore, the model can be adapted to include a dynamic left atrium, a dynamic left ventricle, etc. As mentioned above, the numerical model can also include a systemic arterial model.

[0149] The model can be adapted to incorporate additional ultrasound data for specific applications, such as Doppler waveforms in cardiac diagnosis; however, this additional data must be collected periodically.

[0150] The numerical model described above can be integrated into an ultrasound analysis platform. This allows the model to utilize patient-specific segmentation of the left ventricle.

[0151] In other words, in Figure 3 In the example shown, an OD numerical model is used to simulate the physical properties of cardiac blood flow. Numerical models are suitable for providing real-time patient-specific cardiac output or mitral regurgitation calculations, such as the real-time hemodynamics of the subject's cardiac system. For example, the model's input may include quantitative echocardiographic data of the heart chambers (which may be based on ultrasound data obtained from the subject) and pressure waves from invasive or non-invasive measurements related to the subject's blood pressure.

[0152] The numerical model can be either a 0D numerical model or a 1D numerical model. Since 0D and 1D numerical models are computationally simple, they can process incoming physiological data from the object with almost no latency, thus providing the ability to simulate the cardiac system in real time.

[0153] Within this model-based framework, pre-computed information, such as that from complex 3D numerical models, can be provided. This pre-computed information can provide initial estimates of key physical parameters to be addressed, which can then be further personalized based on physiological data (e.g., nonlinear valve resistance in ETER). This mapping of nonlinear pressure-flow relationships can be pre-computed across a range of different valve sizes, and repair replacement can be achieved using coupled fluid and solid numerical simulations. The pre-computed values ​​can then be mapped to the patient based on collected physiological data using appropriate techniques (e.g., machine learning algorithms, suitable orthogonal decomposition, etc.).

[0154] In other words, computationally intensive calculations can be performed before applying numerical models to the physiological data of the object, thereby reducing the computational resources and time required to simulate the cardiac system.

[0155] Figure 4 A visual representation of the simulated hemodynamic function of the mitral valve 300 after repair following the ETER procedure is shown. Figure 4 In the example shown, band 310 represents the blood flow path through the mitral valve and can be used to assess the valve's hemodynamic function.

[0156] Figure 5 A schematic diagram of a system for determining the real-time hemodynamic function of object 400 is shown.

[0157] In the example of the ETER program, the physiological data that may be available are shown in Table 1 below.

[0158] Data types continuous Intermittent atrial pressure waveform yes Arterial pressure waveform yes electrocardiogram waveform yes Ventricular volume waveform Possibly, depending on the clinical situation. yes atrial volume waveform Possibly, depending on the clinical situation. yes

[0159] Table 1 - Data Available in ETER

[0160] refer to Figure 5 Ventricular and atrial volume waveforms can be obtained using ultrasound system 410. Arterial pressure waveforms can be obtained using anesthesia settings 420, and atrial pressure waveforms can be obtained using interventional pressure measurement device 430.

[0161] Using the input data described above, patient-specific physical parameters (e.g., resistance, compliance, etc.) of the numerical model 440 can be estimated using combinations of, for example, physiological rules, direct optimization, and sequential estimation. The numerical model can then output the real-time hemodynamic function 450 of the object's cardiac system, such as the mitral valve.

[0162] As detailed in Table 1, volumetric data obtained, for example, via an ultrasound system may be intermittent. Therefore, the numerical model may need to run during periods when no volumetric waveform input is available. In this case, physical parameters controlling cardiac contractility (e.g., maximal contractility) can be used to automatically estimate the missing physiological data. For example, the physiological data can be estimated using a combination of direct estimation techniques and nonlinear state estimation (e.g., unscented Kalman filtering). When the volumetric waveform data becomes available again, the numerical model can then be updated with the new volumetric data, thereby recalibrating the numerical model.

[0163] In addition to ultrasound systems, volumetric waveform data can be obtained through an inflatable cuff and / or a catheter with a thermistor suitable for wearing by the subject, wherein the volumetric waveform data is derived using a thermal dilution technique.

[0164] Those skilled in the art, through studying the accompanying drawings, disclosure, and claims, will understand and implement variations of the disclosed embodiments when practicing the claimed invention. In the claims, the word "comprising" does not exclude other elements or steps, and the words "a" or "an" do not exclude multiple. A single processor or other unit can perform the functions of several items recited in the claims. Although specific measures are recited in dissimilar dependent claims, this does not imply that combinations of these measures cannot be advantageously used. If a computer program has been described above, it may be stored / distributed on suitable media such as optical storage media or solid-state media provided with or as part of other hardware, but may also be distributed in other forms such as via the Internet or other wired or wireless telecommunications systems. If the term "suitable" is used in the claims or description, it should be noted that the term "suitable" is intended to be equivalent to the term "configured as." Any reference numerals in the claims should not be construed as limiting the scope.

Claims

1. A system for determining the real-time valve function of an object (400), the system comprising: Processing unit, which is suitable for: A numerical model (440) of the cardiac system is obtained, wherein the numerical model is an OD numerical model, wherein the numerical model is represented as an electronic circuit and is adapted to receive a continuous stream of physiological data as input and output simulated hemodynamic functions of the cardiac system in real time, wherein the simulated hemodynamic functions of the cardiac system include simulated functions of valves within the cardiac system, wherein in the numerical model, voltage represents blood pressure, current represents blood flow, and model parameters are represented by electrical simulation; A continuous stream of physiological data is obtained from the object; The continuous stream of physiological data is provided as input to the numerical model of the cardiac system, thereby generating a real-time simulation of the cardiac system of the object; and The real-time valve function of the object is determined based on the simulated real-time function of the object's cardiac system.

2. The system according to claim 1, wherein, The continuous stream of physiological data is obtained from an object experiencing changes in valvular function, and wherein the real-time valvular function, determined based on the simulated real-time function of the cardiac system, represents the changes in valvular function.

3. The system according to claim 2 is suitable for use when the subject undergoes valve repair.

4. The system according to any one of claims 1 to 3, wherein, The system further includes physiological sensors adapted to obtain physiological data from the object, wherein the physiological sensors include one or more of the following: An electrocardiogram (ECG) sensor, wherein the physiological data includes ECG data; A blood pressure measuring device, wherein the physiological data includes numerical pressure data and / or pressure waveform data; and A volume waveform sensor, wherein the physiological data includes volume waveform data.

5. The system according to claim 4, wherein, The volume waveform sensor includes one or more of the following: An ultrasonic transducer, wherein the volumetric waveform data includes ultrasonic data; Inflatable cuffs, suitable for wearing by the object; and A conduit with a thermistor at one end, wherein the volume waveform data is derived using a thermal dilution technique.

6. The system according to any one of claims 1 to 3, wherein, The numerical model is based on physical parameters, and the processing unit is further adapted to adjust the physical parameters of the numerical model based on at least a portion of the continuous stream of physiological data.

7. The system according to any one of claims 1 to 3, wherein, The numerical model is based on physical parameters, and the processing unit is further adapted to: Preliminary physiological data were obtained from the object; and The physical parameters of the numerical model are adjusted based on the preliminary physiological data from the subject.

8. The system according to any one of claims 1 to 3, wherein, The numerical model is based on physical parameters, wherein the processing unit is further adapted to: Adjust the physical parameters of the numerical model to generate a predictive numerical model; The continuous stream of physiological data is provided as input to the predictive numerical model, thereby simulating the predictive function of the object's cardiac system; and The future hemodynamic function of the object is predicted based on the predictive capabilities of the simulation of the object's cardiac system.

9. The system according to any one of claims 1 to 3, wherein, The physiological data includes one or more of the following: Electrocardiogram data; Pressure numerical data; Pressure waveform data; Physiological data based on echocardiography; and Volume waveform data.

10. The system according to claim 9, wherein, The volume waveform data includes one or more of the following: Ventricular volume waveform; and Atrial volume waveform.

11. The system according to claim 9, wherein, The volumetric waveform data includes ultrasonic data.

12. The system according to claim 9, wherein, The pressure waveform data includes one or more of the following: Atrial pressure waveform; and Arterial pressure waveform.

13. The system according to any one of claims 1 to 3, wherein, The physiological data includes estimated physiological data.

14. A method (100) for determining the real-time valve function of an object, the method comprising: Obtain (110) a numerical model of the cardiac system, the numerical model being an OD numerical model, wherein the numerical model is represented as an electronic circuit and is adapted to receive a continuous stream of physiological data as input and output simulated hemodynamic functions of the cardiac system in real time, wherein the simulated hemodynamic functions of the cardiac system include simulated functions of valves within the cardiac system, wherein in the numerical model, voltage represents blood pressure, current represents blood flow, and model parameters are represented by electrical simulation; A continuous stream of (120) physiological data is obtained from the object; The continuous stream of physiological data (130) is provided as input to the numerical model of the cardiac system, thereby generating a real-time simulation of the cardiac system of the object; and (140) The real-time valve function of the object is determined based on the simulated real-time function of the heart system of the object.

15. A computer program including computer program code modules, wherein when the computer program is run on a computer, the computer program code modules are adapted to implement the method according to claim 14.

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