WO2020173826A1

WO2020173826A1 - Pressure half-time (pht) correction for valvular disease assessment

Info

Publication number: WO2020173826A1
Application number: PCT/EP2020/054612
Authority: WO
Inventors: Christian Haase; Frank Michael WEBER; Michael Grass
Original assignee: Koninklijke Philips N.V.
Priority date: 2019-02-28
Filing date: 2020-02-21
Publication date: 2020-09-03

Abstract

A controller (130) for correcting pressure half-time for valvular disease assessment includes a memory (420, 430, 482) that stores instructions, and a processor (410) that executes the instructions. When executed by the processor (410), the instructions cause the controller (130) to execute a process. The process includes obtaining (S310) a dynamic image sequence of images of cardiac anatomy captured sequentially in time and performing (S320) image analysis of the dynamic image sequence of images of the cardiac anatomy captured sequentially in time. The process also includes identifying (S330), based on the image analysis of the dynamic image sequence of images, a characteristic of the cardiac anatomy, and determining (S340), based on the characteristic of the cardiac anatomy identified based on the image analysis of the dynamic image sequence of images, a variable correction level to modify pressure half-time for valvular disease assessment. Valvular disease of the cardiac anatomy is assessed (S350) using pressure half-time modified with the variable correction level.

Description

PRESSURE HALF-TIME (PHT) CORRECTION FOR VALVULAR DISEASE

ASSESSMENT

BACKGROUND

[001] Diastole is the phase of a heartbeat when heart muscles relax and allow ventricle chambers to fill with blood after the ventricle chambers are emptied during systole. The blood is provided to the ventricle chambers from atriums through heart valves (mitral valve and tricuspid valve) based on a pressure differential between the atriums and the ventricle chambers. The blood from the left atrium is provided to the left ventricle through the mitral valve, and then drained from the left ventricle to the aorta through another heart valve (the aortic valve).

[002] Pressure half-time is a simple and reliable tool used as a mechanism for quantizing the condition of heart anatomy, and specifically in diastole for assessing disease of the mitral valve and the aortic valve. Pressure half-time (PHT) uses Doppler ultrasound (high-frequency sound waves) to measure blood flow through one of the heart valves (mitral valve or aortic valve) in order to establish an approximate relationship between the blood flow and time required for the pressure gradient across the heart valve to decrease to half of its maximum value.

[003] Pressure half-time is inverse-proportionally related to the valve area (mitral valve or aortic valve) and can be used to quantify valvular stenosis severity or size of a regurgitant valvular area. As an example, high trans-mitral pressure half-time indicates a narrowed valve area, while low trans-aortic pressure half-time indicates a wide regurgitant valve area.

[004] However, application of pressure half-time measurements may be inaccurate when an additional cardiac disease such as left ventricular dysfunction is present. Although it is simple to measure, the pressure half-time approximation is neglecting other influence factors such as left ventricle diastolic function (relaxation/compliance), left atrial compliance (for the mitral valve) or aortic geometry/compliance (for the aortic valve). Thus, mechanisms for incorporating additional influence factors into the pressure half-time approximation are needed. 2018PF00983

SUMMARY

[005] In accordance with an aspect of the present disclosure, a controller for correcting pressure half-time for valvular disease assessment includes a memory that stores instructions, and a processor that executes the instructions. When executed by the processor, the instructions cause the controller to execute a process. The process includes obtaining a dynamic image sequence of images of cardiac anatomy captured sequentially in time and performing image analysis of the dynamic image sequence of images of the cardiac anatomy captured sequentially in time. The process also includes identifying, based on the image analysis of the dynamic image sequence of images, a characteristic of the cardiac anatomy and determining, based on the characteristic of the cardiac anatomy identified based on the image analysis of the dynamic image sequence of images, a variable correction level to modify pressure half-time for valvular disease assessment. Valvular disease of the cardiac anatomy may be assessed using pressure half-time modified with the variable correction level.

[006] In accordance with another aspect of the present disclosure, a method for correcting pressure half-time for valvular disease assessment includes obtaining a dynamic image sequence of images of cardiac anatomy captured sequentially in time and performing image analysis of the dynamic image sequence of images of the cardiac anatomy captured sequentially in time. The method also includes identifying, by a processor and based on the image analysis of the dynamic image sequence of images, a characteristic of the cardiac anatomy, and determining, based on the characteristic of the cardiac anatomy identified based on the image analysis of the dynamic image sequence of images, a variable correction level to modify pressure half-time for valvular disease assessment of the cardiac anatomy. Valvular disease of the cardiac anatomy may be assessed using pressure half-time modified with the variable correction level.

[007] In accordance with another aspect of the present disclosure, a system for correcting pressure half-time for valvular disease assessment includes a first ultrasound apparatus and a second ultrasound apparatus. The first ultrasound apparatus performs pressure half-time and includes a controller with a memory that stores instructions and a processor that executes the instructions. The second ultrasound apparatus obtains a dynamic image sequence of images of cardiac anatomy captured sequentially in time. When executed by the processor, the instructions cause the controller of the first ultrasound apparatus to execute a process. The process includes 2018PF00983 obtaining, by the first ultrasound apparatus, the dynamic image sequence of images of the cardiac anatomy captured sequentially in time and performing image analysis of the dynamic image sequence of images of the cardiac anatomy captured sequentially in time. The process also includes identifying, based on the image analysis of the dynamic image sequence of images, a characteristic of the cardiac anatomy, and determining, based on the characteristic of the cardiac anatomy identified based on the image analysis of the dynamic image sequence of images, a variable correction level to modify pressure half-time for valvular disease assessment of the cardiac anatomy. Valvular disease of the cardiac anatomy is assessed using pressure half time modified with the variable correction level.

BRIEF DESCRIPTION OF THE DRAWINGS

[008] The example embodiments are best understood from the following detailed description when read with the accompanying drawing figures. It is emphasized that the various features are not necessarily drawn to scale. In fact, the dimensions may be arbitrarily increased or decreased for clarity of discussion. Wherever applicable and practical, like reference numerals refer to like elements.

[009] FIG. 1 illustrates a system for pressure half-time correction for valvular disease assessment, in accordance with a representative embodiment.

[010] FIG. 2A illustrates heart segmentation in an end-systolic phase, in accordance with an embodiment.

[011] FIG. 2B illustrates heart segmentation in an end-diastolic phase, in accordance with an embodiment.

[012] FIG. 2C illustrates a volume curve during relaxation for a normal heart versus a volume curve during relaxation for a heart in an end-diastolic phase with diastolic dysfunction, in accordance with an embodiment.

[013] FIG. 3 illustrates a process for pressure half-time correction for valvular disease assessment, in accordance with another representative embodiment.

[014] FIG. 4 illustrates a general computer system, on which a method of pressure half-time correction for valvular disease assessment can be implemented, in accordance with another representative embodiment. 2018PF00983

[015] FIG. 5 illustrates a process for pressure half-time correction for valvular disease assessment, in accordance with another representative embodiment.

[016] FIG. 6 illustrates a process for pressure half-time correction for valvular disease assessment, in accordance with another representative embodiment.

[017] FIG. 7 illustrates a process for pressure half-time correction for valvular disease assessment, in accordance with another representative embodiment.

[018] FIG. 8A illustrates a lumped fluid dynamics representation of the aorta, the aortic valve, the left ventricle, the mitral valve and the left atrium for simulating a segment of the cardiac cycle, in accordance with another representative embodiment.

[019] FIG. 8B shows a simplified system representation of aspects of heart functionality to provide context for the descriptions herein.

DETAILED DESCRIPTION

[020] In the following detailed description, for purposes of explanation and not limitation, representative embodiments disclosing specific details are set forth in order to provide a thorough understanding of an embodiment according to the present teachings. Descriptions of known systems, devices, materials, methods of operation and methods of manufacture may be omitted so as to avoid obscuring the description of the representative embodiments. Nonetheless, systems, devices, materials and methods that are within the purview of one of ordinary skill in the art are within the scope of the present teachings and may be used in accordance with the representative embodiments. It is to be understood that the terminology used herein is for purposes of describing particular embodiments only, and is not intended to be limiting. The defined terms are in addition to the technical and scientific meanings of the defined terms as commonly understood and accepted in the technical field of the present teachings.

[021] It will be understood that, 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.

[022] The terminology used herein is for purposes of describing particular embodiments only, 2018PF00983 and is not intended to be limiting. As used in the specification and appended claims, the singular forms of terms‘a’,‘an’ and‘the’ are intended to include both singular and plural forms, unless the context clearly dictates otherwise. Additionally, the terms "comprises", and/or "comprising," and/or similar terms when used in this specification, specify the presence of stated features, elements, and/or components, but do not preclude the presence or addition of one or more other features, elements, components, and/or groups thereof As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

[023] 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.

[024] In view of the foregoing, the present disclosure, through one or more of its various aspects, embodiments and/or specific features or sub-components, is thus intended to bring out one or more of the advantages as specifically noted below. For purposes of explanation and not limitation, example embodiments disclosing specific details are set forth in order to provide a thorough understanding of an embodiment according to the present teachings. However, other embodiments consistent with the present disclosure that depart from specific details disclosed herein remain within the scope of the appended claims. Moreover, descriptions of well-known apparatuses and methods may be omitted so as to not obscure the description of the example embodiments. Such methods and apparatuses are within the scope of the present disclosure.

[025] As described herein, one or more characteristics of anatomical information can be identified based on image analysis of one or more image of cardiac anatomy. The characteristic(s) can be used to determine variable parameters for modifying pressure half-time approximations. The image analysis may be or include use of model-based segmentation. Accordingly, the pressure half-time method is improved using additional analysis from image analysis such as model-based 2018PF00983 segmentation.

[026] FIG. 8B shows a simplified system representation of aspects of heart functionality to provide context for the descriptions herein. In FIG. 8B, blood flows through valves from a right atrium to a right ventricle and then on to a pulmonary artery. Blood also flows through valves from a left atrium to a left ventricle and then on to the aorta. The pressure half-time described herein is measured based on the mitral valve that regulates blood flow from the left atrium to the left ventricle or based on the aortic valve that regulates blood flow from the left ventricle to the aorta. It goes without saying that the simplified system representation in FIG. 8B does not reflect many aspects of an actual heart, such as that the elements therein are part of a living being and may expand, contract and move relative to one another on an ongoing basis during operation.

[027] FIG. 1 illustrates a system for pressure half-time correction for valvular disease assessment, in accordance with a representative embodiment.

[028] In FIG. 1, the system includes a first ultrasound apparatus 110, an image analysis computer 120, a base station 130, and a second ultrasound apparatus 140. The first ultrasound apparatus 110 may be used to obtain ultrasound imagery. The first ultrasound apparatus 110 may be used to obtain a dynamic image sequence of ultrasound imagery, and thus may be termed a dynamic image sequencer. The image analysis computer 120 executes an image analysis software program with a processor to analyze the dynamic image sequence from the first ultrasound apparatus 110. The second ultrasound apparatus 140 may be used to obtain ultrasound imagery. The base station 130 integrates image analysis results from the image analysis computer 120 with results from the second ultrasound apparatus 140. For example, the base station 130 may determine a variable correction level based on the image analysis results from the image analysis computer 120. The base station may then apply the variable correction level to the results from the second ultrasound apparatus 140 to obtain a modified pressure half-time reflective of valvular disease of the cardiac anatomy reflected in the results from the second ultrasound apparatus 140.

[029] An example of the second ultrasound apparatus 140 is a TEE Doppler ultrasound apparatus used to obtain transesophageal echocardiography (TEE) Doppler ultrasound imagery. Thus, the second ultrasound apparatus 140 may be termed a TEE Doppler ultrasound apparatus. TEE produces detailed pictures of a heart and the arteries that lead to and from the heart. In TEE Doppler ultrasound, the ultrasound transducer that produces the sound waves may be attached to a thin 2018PF00983 endoscope tube that passes into the esophagus through the mouth and throat in order to perform the ultrasound. Pressure half-time can be determined from TEE Doppler ultrasound, or from transthoracic echocardiogram (TTE) Doppler ultrasound, so the second ultrasound apparatus 140 may also conceivably be a TTE Doppler ultrasound apparatus. In another embodiment, the second ultrasound apparatus 140 is an intra-cardiac echo (ICE) ultrasound apparatus.

[030] As explained later with respect to FIG. 4, any of the elements in FIG. 1 may include a controller with a combination of a memory that stores instructions and a processor that executes the instructions in order to implement processes described herein. In an embodiment, such a controller may be implemented by the base station 130. Additionally, although FIG. 1 shows four components networked together, two components may be integrated into a single system. For example, the image analysis computer 120 may be integrated with the first ultrasound apparatus 110 or with the base station 130. That is, in embodiments functionality attributed to the image analysis computer 120 may be implemented by (e.g., performed by) a system that includes the first ultrasound apparatus 110 or a system that includes the base station 130. On the other hand, the four networked components shown in FIG. 1 may also be spatially distributed such as by being distributed in different rooms or different buildings, in which case the four networked components may be connected via data connections. In still another embodiment, one or more of the four components in FIG. 1 is not connected to the other components via a data connection, and instead is provided with input or output manually such as by a memory stick or other form of memory. In yet another embodiment, functionality described herein such as an assessment (diagnosis) of valvular disease may be performed based on functionality of the elements in FIG. 1 but outside of the system shown in FIG. 1.

[031] As explained herein, the degree of valvular stenosis/regurgitation of a heart can be measured from images, and particularly from images generated by the first ultrasound apparatus 110 in FIG. 1. The image analysis by the image analysis computer 120 may be or include model- based segmentation, so that the image analysis results from the image analysis computer 120 can be used by the base station 130 to improve the pressure half-time method based on images from the second ultrasound apparatus 140 using additional analysis from model-based segmentation. Segmentation is a representation of the surface of an organ, and consists for example of a set of points in three-dimensional (3-D) coordinates on the surface of the organ, and triangular plane 2018PF00983 segments defined by connecting neighboring groups of 3 points, such that the entire organ surface is covered by a mesh of non-intersecting triangular planes. Segmentation is further explained below in relation to FIGs. 2A and 2B,

[032] As explained previously, pressure half-time method uses ultrasound Doppler to measure the blood flow through a heart valve (e.g. mitral or aortic valve). By establishing an approximate relation between the flow and the transvalvular pressure gradient, pressure half-time calculates how fast the pressure gradient across a valve drops. This, in its turn, is related to the valve area and thus a marker for the degree of, e.g., mitral valve stenosis. In the context of FIG. 1 , the pressure half-time may be measured by the second ultrasound apparatus 140, which may be a TEE Doppler ultrasound apparatus, a TTE Doppler ultrasound apparatus or an intra-cardiac echo (ICE) ultrasound apparatus. Accordingly, in an embodiment the pressure half-time is measured using one of TEE Doppler ultrasound, TTE ultrasound and ICE ultrasound.

[033] Anatomical information from model-based segmentation of an anatomical image can be used to determine relevant parameters from the image analysis of the ultrasound images from the first ultrasound apparatus 110. From a static image, for example, the aortic anatomy can be segmented. From a dynamic image sequence, dynamic parameters such as left ventricle relaxation or left atrial compliance can be computed. With these parameters, the degree of the stenosis/regurgitation can be calculated more accurately by the base station 130, and used to modify the pressure half-time from the results from the second ultrasound apparatus 140.

[034] FIGs. 2A and 2B illustrate multiple cardiac phases as segmented using model-based segmentation. One aspect of the cardiac phases shown in FIGs. 2A and 2B is wall motion. That is, wall motion occurs during cardiac phases, and the wall motion can be visualized in the cardiac phases shown in FIGs. 2A and 2B though the wall motion itself is not directly shown in FIG. 2A alone or FIG. 2B alone. The sequence of images of the multiple cardiac phases is used to indicate if the relation of pressure half-time to valvular performance or area is influenced by left ventricular function. As explained herein, a correction factor can be calculated and applied based on analysis of the degree of left ventricular function or dysfunction. The model-based segmentation used to obtain the segmented multiple cardiac phases in FIGs. 2A and 2B is performed based on an acquired three-dimensional (3D) volume. The specific 3D volume(s) segmented in the model- based segmenting to result in each of FIG. 2A and 2B were acquired using trans -thoracic echo 2018PF00983

(TTE) ultrasound. In alternative embodiments, trans-esophageal echo (TEE) ultrasound may be used to acquire a 3D volume subjected to model-based segmentation to obtain similar images. In yet another embodiment, intra-cardiac echo (ICE) ultrasound may be used to acquire a 3D volume subjected to model-based segmentation to obtain similar images.

[035] FIG. 2A illustrates heart segmentation in an end-systolic phase, in accordance with an embodiment. In FIG. 2A, the right ventricle 201 , the left ventricle 202, the right atrium 203 and the left atrium 204 are shown in an end-systolic (ES) phase, wherein the volume of blood in the ventricles is at a minimum. The 3-D volume represented in the heart segmentation in FIG. 2 A may be obtained prior to an interventional medical procedure, including at a different place and on a different date. In FIG. 2A and in FIG. 2B (explained below), the heart segmentation is obtained as a dynamic image sequence of images of cardiac anatomy captured sequentially in time. The dynamic image sequence in FIGs. 2A and 2B may be captured by the first ultrasound apparatus 110. The dynamic image sequence in FIGs. 2A and 2B reflects wall motion of the cardiac walls. For example, the outer contour in FIG. 2 A and FIG. 2B marks the outer border of the heart muscle.

[036] By way of explanation, diastolic dysfunction may result in a left ventricle (as a whole) filling too slowly as shown in the lower curve marked "Diastolic Dysfunction" in FIG. 2C. One of a variety of possible causes for the slow filling may be a regional abnormality that is detectable and detected from the wall motion occurring in the cardiac phases represented in the dynamic image sequence in FIGs. 2 A and 2B. The regional abnormality may be detected from the wall motion.

[037] FIG. 2B illustrates heart segmentation in an end-diastolic phase, in accordance with an embodiment. In FIG. 2B, the right ventricle 201, the left ventricle 202, the right atrium 203 and the left atrium 204 are shown in an end-diastolic (ED) phase, wherein the volume of blood in the ventricles is at a maximum. As shown in FIG. 2B, first segment 205 is inside of second segment 206 in FIG. 2B. The second segment 206 is part of the contour marking the outer border of the heart muscle. The first segment 205 marks a regional abnormality that is detectable and detected from the wall motion and that may affect the diastolic dysfunction in FIG. 2B. In other words, the first segment 205 marks a physical segment that affects relative slow filling of the left ventricle in the end-diastolic phase in FIG. 2B.

[038] In FIG. 2B, the difference between the first segment 205 and the second segment may 2018PF00983 indirectly affect a measurement of the degree of valvular stenosis/regurgitation reflected in pressure half-time. Valvular stenosis is a valvular heart disease condition in which tissues forming the valve leaflets become stiffer, in turn narrowing the valve opening and reducing the amount of blood that can flow through the valve. Identification and quantification of ventricular dysfunction (e.g., left ventricular dysfunction) or local wall motion abnormalities as identified using, e.g., using model-based segmentation techniques, can be used to correct pressure half-time measurements. As an example, a stiff left ventricle with decreased compliance and impaired relaxation may lead to a shorter pressure half-time and thus overestimation of the mitral valve area. As a result, valvular stenosis/regurgitation which are indicated by pressure half-time may be more accurately measured by identifying and accounting for abnormalities identified through wall motion analysis or other forms of image analysis of individual ultrasound images.

[039] FIG. 2C illustrates a volume curve 207 for a normal heart during relaxation versus a volume curve 208 during relaxation for a heart in an end-diastolic phase with diastolic dysfunction, in accordance with an embodiment. In FIG. 2C, the lower curve represents the diastolic dysfunction. As noted previously, the diastolic dysfunction may be affected by the regional abnormality detected from the wall motion analysis of the dynamic image sequence in FIGs. 2A and 2B. The volume curve 208 in FIG. 2C resulting from the diastolic dysfunction shown in FIG. 2B is derived from the dynamic segmentation shown in the dynamic image sequence of the cardiac anatomy captured sequentially in time as shown in FIGs. 2A and 2B. While FIGs. 2A and 2B show two images corresponding to segmentation of a heart in a sequence, the present disclosure is not limited to two images and an image sequence of cardiac anatomy used to assess valvular disease may include more than two images of cardiac anatomy illustrated as heart segmentations. The volume curve 207 in FIG. 2C may be generated as a result of performing image analysis of the dynamic image sequence of images of the cardiac anatomy captured sequentially in time in FIGs. 2A and 2B.

[040] FIG. 3 illustrates a process for pressure half-time correction for valvular disease assessment, in accordance with another representative embodiment.

[041] In FIG. 3, the process begins at S310 by capturing a dynamic image sequence of images of cardiac anatomy sequentially in time. For example, the dynamic image sequence may be captured by the first ultrasound apparatus 110 in the embodiment of FIG. 1. 2018PF00983

[042] At S320, image analysis of the dynamic image sequence of images of cardiac anatomy captured sequentially in time is performed. For example, the image analysis may be performed by the image analysis computer 120 in the embodiment of FIG. 1.

[043] At S330, a characteristic of the cardiac anatomy is identified based on image analysis of the dynamic image sequence of images. For example, the characteristic of the cardiac anatomy identified at S330 may be or include the regional abnormality identified from the wall motion analysis from FIGs. 2A and 2B. The image analysis may be used to determine disorders including at least one of diastolic dysfunction, left ventricle diastolic function relaxation, left ventricle diastolic function compliance, left atrial compliance, aortic geometry compliance for an aortic valve, calcified valves or regurgitant valves. Each of these disorders is briefly explained below, as the characteristic identified at S330 may be a characteristic of any of these disorders.

• Diastolic dysfunction refers to abnormal filling of the heart in the diastole phase. The diastolic function is particularly concerns with filling of the left ventricle from the left atrium through the mitral valve. Using TEE Doppler ultrasound or TTE ultrasound, a variety of characteristic of functionality in the diastole phase can be measured. For instance, diastolic dysfunction can be detected based on measurements such as an average rate or peak rate of filling in the left ventricle, an average rate or peak rate of evacuation from the left atrium, an amount or rate of expansion of the left ventricle or contraction of the left atrium, and other observable characteristics.

• Left ventricle diastolic function relaxation may refer to a measure of relaxation of the left ventricle that reflects stiffness. Insofar as the diastolic function reflects a pressure gradient between the left atrium (source) and the left ventricle (receptacle), elevated filling pressures may be characteristic of an impaired level of relaxation of the left ventricle due to increased stiffness.

• Left ventricle diastolic function compliance refers to a measure of how well the left ventricle responds to pressure in terms of increasing volume or reverting to original dimensions.

• Left atrial compliance refers to a measure of how well the left atrium responds to pressure in terms of increasing volume or reverting to original dimensions.

• Aortic geometry compliance refers to a measure of how well the aortic valve between the 2018PF00983 left ventricle and the aorta responds to changes in pressure.

• Calcified valves are aortic valves with calcium deposited thereon, which can cause stiffness and narrowing at an opening.

• Regurgitant valves refers to valves (e.g., mitral valves) that don't close tightly, which allows backflow such as from the left ventricle to the left atrium.

[044] At S340, a variable correction level is determined based on the characteristics of the cardiac anatomy identified at S330 based on the image analysis of the dynamic image sequence of images performed at S320. The variable correction level is determined in order to modify pressure half time for valvular disease assessment of the cardiac anatomy.

[045] At S350, valvular disease of the cardiac anatomy is assessed using pressure half-time modified with the variable correction level. For example, the valvular disease of the cardiac anatomy can be automatically assessed by the base station 130 in FIG. 1 or by another apparatus or system executing software with a processor. Alternatively, the valvular disease may be assessed manually, or by a combination of a human and a computer such as a by a human using a computer.

[046] At S360, a diagnosis is performed based on the assessment of the valvular disease of the cardiac anatomy. As with the valvular disease assessment at S350, diagnosis may be performed automatically by the base station 130 in FIG. 1, manually, or by a combination of a human and a computer such as by a human using a computer.

[047] At S370, the valvular disease of the cardiac anatomy is treated. For example, a patient may be subject to surgery and/or a prescription of medications in order to remedy the valvular disease diagnosed at S360 based on the assessment at S350.

[048] FIG. 4 illustrates a general computer system, on which a method of pressure half-time correction for valvular disease assessment can be implemented, in accordance with another representative embodiment.

[049] The computer system 400 can include a set of instructions that can be executed to cause the computer system 400 to perform any one or more of the methods or computer-based functions disclosed herein. The computer system 400 may operate as a standalone device or may be connected, for example, using a network 401, to other computer systems or peripheral devices.

[050] In a networked deployment, the computer system 400 may operate in the capacity of a server or as a client user computer in a server-client user network environment, or as a peer 2018PF00983 computer system in a peer-to-peer (or distributed) network environment. The computer system 400 can also be implemented as or incorporated into various devices, such as the first ultrasound apparatus 110, the image analysis computer 120, the base station 130, the second ultrasound apparatus 140, a stationary computer, a mobile computer, a personal computer (PC), a laptop computer, a tablet computer, or any other machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. The computer system 400 can be incorporated as or in a device that in turn is in an integrated system that includes additional devices. In an embodiment, the computer system 400 can be implemented using electronic devices that provide voice, video or data communication. Further, while the computer system 400 is illustrated in the singular, the term "system" shall also be taken to include any collection of systems or sub-systems that individually or jointly execute a set, or multiple sets, of instructions to perform one or more computer functions.

[051] As illustrated in FIG. 4, the computer system 400 includes a processor 410. A processor for a computer system 400 is tangible and non-transitory. As used herein, the term “non-transitory” is to be interpreted not as an eternal characteristic of a state, but as a characteristic of a state that will last for a period. The term“non-transitory” specifically disavows fleeting characteristics such as characteristics of a carrier wave or signal or other forms that exist only transitorily in any place at any time. A processor is an article of manufacture and/or a machine component. A processor for a computer system 400 is configured to execute software instructions to perform functions as described in the various embodiments herein. A processor for a computer system 400 may be a general-purpose processor or may be part of an application specific integrated circuit (ASIC). A processor for a computer system 400 may also be a microprocessor, a microcomputer, a processor chip, a controller, a microcontroller, a digital signal processor (DSP), a state machine, or a programmable logic device. A processor for a computer system 400 may also be a logical circuit, including a programmable gate array (PGA) such as a field programmable gate array (FPGA), or another type of circuit that includes discrete gate and/or transistor logic. A processor for a computer system 400 may be a central processing unit (CPU), a graphics processing unit (GPU), or both. Additionally, any processor described herein may include multiple processors, parallel processors, or both. Multiple processors may be included in, or coupled to, a single device or multiple devices. 2018PF00983

[052] Moreover, the computer system 400 may include a main memory 420 and a static memory 430, where memories may can communicate with each other via a bus 408. Memories described herein are tangible storage mediums that can store data and executable instructions and are non-transitory during the time instructions are stored therein. As used herein, the term“non- transitory” is to be interpreted not as an eternal characteristic of a state, but as a characteristic of a state that will last for a period. The term“non-transitory” specifically disavows fleeting characteristics such as characteristics of a carrier wave or signal or other forms that exist only transitorily in any place at any time. A memory described herein is an article of manufacture and/or machine component. Memories described herein are computer-readable mediums from which data and executable instructions can be read by a computer. Memories as described herein may be random access memory (RAM), read only memory (ROM), flash memory, electrically programmable read only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, a hard disk, a removable disk, tape, compact disk read only memory (CD-ROM), digital versatile disk (DVD), floppy disk, blu-ray disk, or any other form of storage medium known in the art. Memories may be volatile or non-volatile, secure and/or encrypted, unsecure and/or unencrypted.

[053] As shown, the computer system 400 may further include a video display unit 450, such as a liquid crystal display (LCD), an organic light emitting diode (OLED), a flat panel display, a solid-state display, or a cathode ray tube (CRT). Additionally, the computer system 400 may include an input device 460, such as a keyboard/virtual keyboard or touch-sensitive input screen or speech input with speech recognition, and a cursor control device 470, such as a mouse or touch-sensitive input screen or pad. The computer system 400 can also include a disk drive unit 480, a signal generation device 490, such as a speaker or remote control, and a network interface device 440.

[054] In an embodiment, as depicted in FIG. 4, the disk drive unit 480 may include a computer-readable medium 482 in which one or more sets of instructions 484, e.g. software, can be embedded. Sets of instructions 484 can be read from the computer-readable medium 482. Further, the instructions 484, when executed by a processor, can be used to perform one or more of the methods and processes as described herein. In an embodiment, the instructions 484 may 2018PF00983 reside completely, or at least partially, within the main memory 420, the static memory 430, and/or within the processor 410 during execution by the computer system 400.

[055] In an alternative embodiment, dedicated hardware implementations, such as application-specific integrated circuits (ASICs), programmable logic arrays and other hardware components, can be constructed to implement one or more of the methods described herein. One or more embodiments described herein may implement functions using two or more specific interconnected hardware modules or devices with related control and data signals that can be communicated between and through the modules. Accordingly, the present disclosure encompasses software, firmware, and hardware implementations. Nothing in the present application should be interpreted as being implemented or implementable solely with software and not hardware such as a tangible non -transitory processor and/or memory.

[056] In accordance with various embodiments of the present disclosure, the methods described herein may be implemented using a hardware computer system that executes software programs. Further, in an exemplary, non-limited embodiment, implementations can include distributed processing, component/object distributed processing, and parallel processing. Virtual computer system processing can be constructed to implement one or more of the methods or functionality as described herein, and a processor described herein may be used to support a virtual processing environment.

[057] The present disclosure contemplates a computer-readable medium 482 that includes instructions 484 or receives and executes instructions 484 responsive to a propagated signal; so that a device connected to a network 401 can communicate voice, video or data over the network 401. Further, the instructions 484 may be transmitted or received over the network 401 via the network interface device 440.

[058] The computer system 400 can be used by or in conjunction with the second ultrasound apparatus 140 in order to monitoring physiology of a patient as described herein. The computer system 400 can receive, download, collect or otherwise obtain raw sensor data from an initial set of sensors used to initially monitor physiology of the patient. The computer system 400 can then implement processes described herein to identify the optimal (e.g., minimal) arrangement of sensors to monitor the patient. The optimal arrangement of sensors is defined by the physiology of the patient as determined based on the raw sensor data from the initial set of 2018PF00983 sensors. The computer system 400 may be used to perform the process live as the initial set of sensors collects the raw sensor data, such as in a clinical setting. As an example, the computer system 400 may be implemented on a laptop or desktop used by a technician or medical professional.

[059] In an embodiment, a controller described herein may include a combination of more or less than all of the elements of the computer system 400 shown in FIG. 4. For example, a controller may include the processor 410 and a main memory 420 and/or a static memory 430. The controller may fully or partially execute a process described herein. For example, a controller may be a implemented in a system that includes the base station 130 and the image analysis computer 120, or at least that implements the functionality attributed herein to the base station 130 and the image analysis computer 120. As such, the controller may execute a process that includes, for example, any or all of obtaining the dynamic image sequence from the first ultrasound apparatus 110, performing image analysis, identifying a characteristic of the cardiac anatomy, and determining a variable correction level to modify pressure half-time for valvular disease assessment.

[060] FIG. 5 illustrates a process for pressure half-time correction for valvular disease assessment, in accordance with another representative embodiment.

[061] In FIG. 5, the process starts at S510 by performing wall motion analysis of a left ventricle based on cardiac segmentation. A characteristic of the cardiac anatomy may be identified based on the wall motion analysis. For example, a number or abnormalities, location of abnormalities and/or motion relative to neighboring segments may be identified.

[062] At S520, the characteristic of the cardiac anatomy is quantified. For example, the characteristic may be quantified on a scale of 0 to 10, or 0 to 100. The characteristic may be quantified based on an absolute metric such as an absolute distance, an absolute area, an absolute volume. The characteristic may also be quantified based on a relative metric, such as based on comparison to a model which in turn is based on an averaged or normalized set of quantifications based on the same or similar characteristic of other cardiac anatomy.

[063] At S530, a value of the characteristic of the cardiac anatomy may be generated from the quantifying. For example, the characteristic may be assigned a value of 6 on a scale of 01 to 10.

[064] At S540, a determination is made whether the value is above a predetermined threshold. If the value is not above the predetermined threshold (S540 = No), no warning is generated at S550 2018PF00983 and the process ends. If the value is above the predetermined threshold (S540 = Yes), a warning is generated and displayed. For example, an operator operating the second ultrasound apparatus 140 may be warned via a display that the pressure half-time being used for the current ultrasound procedure is being modified with a variable correction level based on image analysis of an earlier dynamic image sequence of images of the cardiac anatomy. The warning may also vary a visual characteristic of the warning such as size, color, brightness based on the value of the characteristic determined at S530. The warning may also inform the physician that the found characteristic suggests that a standard pressure half-time assessment may not be reliable for diagnosis and/or a treatment decision in this patient. Accordingly, it may be suggested that a modified pressure half time or a different method is used to make a diagnosis and/or a treatment decision.

[065] FIG. 6 illustrates a process for pressure half-time correction for valvular disease assessment, in accordance with another representative embodiment.

[066] In FIG. 6, the process begins at S610 by performing wall motion analysis of a left ventricle based on a dynamic image sequence. Wall motion analysis is based on a series of images showing how blood travels through the heart. The amount of blood pumped by the heart during each beat may be calculated, along with characteristics of the portions of the heart involved in the pumping.

[067] At S620, a characteristic of the cardiac anatomy is identified based on the wall motion analysis. As explained previously, the characteristic may be a characteristic reflective of functionality of dysfunctionality and may include multiple characteristics including related or unrelated characteristics.

[068] At S630, the characteristics of the cardiac anatomy is quantified.

[069] At S640, a variable correction level is determined as a value corresponding to the characteristic of the cardiac anatomy generated from the quantifying.

[070] FIG. 7 illustrates a process for pressure half-time correction for valvular disease assessment, in accordance with another representative embodiment.

[071] In FIG. 7, the process starts at S710 by creating a connected fluid dynamic model of elements of the cardiac anatomy. At S720, a normal function of the fluid dynamic model is assumed. At S730, the characteristic of the cardiac anatomy is identified from an abnormal function in any elements of the cardiac anatomy in the connected fluid dynamic model. At S740, the variable correction level is determined. The variable correction level is to modify pressure 2018PF00983 half-time for valvular disease assessment of the cardiac anatomy.

[072] FIG. 8A illustrates a lumped fluid dynamics representation of the aorta, the aortic valve, the left ventricle, the mitral valve and the left atrium for simulating a segment of the cardiac cycle, in accordance with another representative embodiment.

[073] In FIG. 8A, a connected fluid dynamic model 890 reflects representations of the left atrium 891, mitral valve 892, left ventricle 893, aortic valve 894 and aorta 895 in two configurations labelled A and B. The first configuration A and the second configuration B may be used at different times in a cycle. The first configuration A may model regurgitant valves in which flow passes both ways instead of in only one direction in that the mitral valve 892 and the aortic valve 894 are resistors that pass current both ways. The resistors may be time dependent in this case. In the second configuration B, the mitral valve 892 and the aortic valve 894 are diodes that primarily permit flow in one direction. The second configuration B may also model regurgitant valves insofar as a diode may have a small current against the primary permitted direction, but configuration A would be preferable for two-way currents. The aorta 895 is represented by a Windkessel model. The aortic valve 894 is represented as a resistor or diode. The left ventricle 893 is represented as a capacitor with variable capacitance. The mitral valve 892 is represented as a resistor or a diode. The left atrium 891 is represented as a capacitor with variable capacitance. The connected fluid dynamic model 890 is designed to simulate a segment of the cardiac cycle such as in the filling of the left ventricle 893.

[074] The connected fluid dynamic model 890 may be used in at least two ways. On one hand, the connected fluid dynamic model 890 can be created geometrically based on the dynamic images from the first ultrasound apparatus 110. This allows large scale fluid dynamic simulations such as finite element simulations which allow identification of characteristics like left ventricle function, stroke volume etc. On the other hand, the connected fluid dynamic model 890 can be a simple resistor/Windkessel model that uses previously extracted characteristics like wall motion stiffness or regurgitant valves as input to design a patient specific model. For example, a regurgitation identified from image analysis may lead to modeling of a valve as an imperfect diode that allows backflow. Using this specially designed resistor model provides for simulation of the effect of the regurgitation on the pressure half-time to allow an accurate correction.

[075] Accordingly, pressure half-time correction for mitral valve disease assessment enables 2018PF00983 improved assessment of valvular disease using pressure half-time. As an example, input data used conventionally to determine the pressure half-time is modified based on time dependent model- based segmentation from the dynamic image sequence. Both the input data for the pressure half time and the time dependent model-based segmentation may be measured using ultrasound, such as in FIG. 1 where the time dependent model-based segmentation is obtained based on ultrasound from the first ultrasound apparatus 110 and th input data for the pressure half-time is obtained from the second ultrasound apparatus 140. As noted previously, the pressure half-time may be determined from a transesophageal echocardiogram (TEE) Doppler ultrasound or transthoracic echocardiogram (TTE) Doppler ultrasound of the valve in question. The model-based segmentation may be applied to a time sequence of three-dimensional (3D) ultrasound images from the first ultrasound apparatus 110

[076] In one illustrative example, pressure half-time may be measured, and cardiac segmentation may be performed in 3D over time (i.e., in 4D). As a result, a wall motion analysis of the left ventricle may be performed. Wall motion abnormalities or left ventricular dysfunction can be determined from segmented cardiac data. Abnormalities can be identified and quantified such as based on the number and severity of wall motion abnormalities or motion relative to neighboring areas. An additional warning can be displayed when the pressure half-time is calculated due to identification and quantification of the wall motion abnormalities. Similarly, warnings can be generated and displayed when left ventricular dysfunction is determined based on the segmentation. In another example, warnings may be generated and displayed when dysfunction of the aortic valve is detected during a pressure half-time measurement at the mitral valve, or when dysfunction of the mitral valve is detected during pressure half-time measurement at the aortic valve.

[077] In another illustrative example, pressure half-time may be measured and 4D cardiac segmentation may be performed in 3D over time (i.e., in 4D). As a result, a wall motion analysis of the left ventricle may be performed. In this example, wall motion abnormalities may be identified and quantified. For example, a number or abnormalities, location of abnormalities and/or motion relative to neighboring segments may be identified and quantified. In another example, left ventricular dysfunction such as an ejection fraction relative to ventricle size and/or wall displacement speed can be identified and quantified. A corresponding correction factor can 2018PF00983 be calculated for the pressure half-time based on the quantified abnormalities. The correction factor can be achieved empirically or using a training-based method.

[078] In another example, compliance of the left ventricle and the left atrium can be measured together with the pressure half-time of the aortic and the mitral valve. As a result, a connected fluid dynamic model such as the model shown in FIG. 8A may be generated. The model may include the aorta, the aortic valve (AV), the left ventricle (LV), the mitral valve (MV), and the left atrium (LA). The target pressure half-time measurement, such as for the aortic valve is then corrected if any of the other involved elements shows abnormal function, by assuming a normal function in the fluid dynamic model.

[079] Modifications can be made to the embodiments described already without departing from the scope of the present disclosure. For example, the input data for pressure half-time may be from a source other than ultrasound. Pressure half-time can, for example, be determined using invasive pressure or flow measurements. In another example, cardiac segmentation may be based on image data that is 2D contrast enhanced angiography sequences and 4D CT or magnetic resonance (MR) images.

[080] In another modification, a machine learning approach such as a neural network can be used to derive corrected pressure half-time measurements from measured pressure half-time measurements and compliance measurements such as local wall motion measurements. Patient background information can be included in the training using machine learning, so as to enhance results using any commonalities or correlations that can be identified based on patient background characteristics. The machine learning training can be performed on a data set where valve area, valve resistance, or degree of regurgitation is known together with the input parameters. The valve area, valve resistance, or degree of regurgitation can then be used as a ground truth with a fixed relation to the corrected pressure half-time. For example, a ground truth may be that the mitral valve area for a heart or category of hearts in square centimeters is (220/pressure half-time).

[081] In another example, the pressure half-time value can be derived from a simulation based on noninvasive medical images of the valve geometry and cardiac compliance measurements.

[082] Although pressure half-time correction for mitral valve disease assessment has been described with reference to several exemplary embodiments, it is understood that the words that have been used are words of description and illustration, rather than words of limitation. Changes 2018PF00983 may be made within the purview of the appended claims, as presently stated and as amended, without departing from the scope and spirit of pressure half-time correction for mitral valve disease assessment in its aspects. Although pressure half-time correction for mitral valve disease assessment has been described with reference to particular means, materials and embodiments, pressure half-time correction for mitral valve disease assessment is not intended to be limited to the particulars disclosed; rather pressure half-time correction for mitral valve disease assessment extends to all functionally equivalent structures, methods, and uses such as are within the scope of the appended claims.

[083] Although the present specification describes components and functions that may be implemented in particular embodiments with reference to particular standards and protocols, the disclosure is not limited to such standards and protocols. For example, standards and protocols such as TTE, TEE and pressure half-time represent examples of the state of the art. Such standards are periodically superseded by more efficient equivalents having essentially the same functions. Accordingly, replacement standards and protocols having the same or similar functions are considered equivalents thereof.

[084] The illustrations of the embodiments described herein are intended to provide a general understanding of the structure of the various embodiments. The illustrations are not intended to serve as a complete description of all of the elements and features of the disclosure described herein. Many other embodiments may be apparent to those of skill in the art upon reviewing the disclosure. Other embodiments may be utilized and derived from the disclosure, such that structural and logical substitutions and changes may be made without departing from the scope of the disclosure. Additionally, the illustrations are merely representational and may not be drawn to scale. Certain proportions within the illustrations may be exaggerated, while other proportions may be minimized. Accordingly, the disclosure and the figures are to be regarded as illustrative rather than restrictive.

[085] One or more embodiments of the disclosure may be referred to herein, individually and/or collectively, by the term“invention” merely for convenience and without intending to voluntarily limit the scope of this application to any particular invention or inventive concept. Moreover, although specific embodiments have been illustrated and described herein, it should be appreciated that any subsequent arrangement designed to achieve the same or similar purpose may be 2018PF00983 substituted for the specific embodiments shown. This disclosure is intended to cover any and all subsequent adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the description.

[086] The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b) and is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, various features may be grouped together or described in a single embodiment for the purpose of streamlining the disclosure. This disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter may be directed to less than all of the features of any of the disclosed embodiments. Thus, the following claims are incorporated into the Detailed Description, with each claim standing on its own as defining separately claimed subject matter.

[087] The preceding description of the disclosed embodiments is provided to enable any person skilled in the art to practice the concepts described in the present disclosure. As such, the above disclosed subject matter is to be considered illustrative, and not restrictive, and the appended claims are intended to cover all such modifications, enhancements, and other embodiments which fall within the true spirit and scope of the present disclosure. Thus, to the maximum extent allowed by law, the scope of the present disclosure is to be determined by the broadest permissible interpretation of the following claims and their equivalents, and shall not be restricted or limited by the foregoing detailed description.

Claims

2018PF00983 CLAIMS:

1. A controller (130) for correcting pressure half-time for valvular disease assessment, comprising:

a memory (420, 430, 482) that stores instructions, and

a processor (410) that executes the instructions,

wherein, when executed by the processor (410), the instructions cause the controller (130) to execute a process (FIG. 3) comprising:

obtaining (S310) a dynamic image sequence of images of cardiac anatomy captured sequentially in time;

performing (S320) image analysis of the dynamic image sequence of images of the cardiac anatomy captured sequentially in time;

identifying (S330), based on the image analysis of the dynamic image sequence of images, a characteristic of the cardiac anatomy; and

determining (S340), based on the characteristic of the cardiac anatomy identified based on the image analysis of the dynamic image sequence of images, a variable correction level to modify pressure half-time for valvular disease assessment, wherein valvular disease of the cardiac anatomy is assessed (S350) using pressure half-time modified with the variable correction level.

2. The controller (130) of claim 1,

wherein the pressure half-time is measured using one of TEE ultrasound, TTE ultrasound and intra-cardiac echo (ICE) ultrasound.

3. The controller (130) of claim 1,

wherein the image analysis comprises identifying a degree (S520, S630) of valvular stenosis from the dynamic image sequence of images.

4. The controller (130) of claim 1,

wherein the image analysis is used to determine at least one of diastolic dysfunction, left ventricle diastolic function relaxation, left ventricle diastolic function compliance, left atrial 2018PF00983 compliance, aortic geometry compliance for an aortic valve, calcified valves or regurgitant valves.

5. The controller (130) of claim 1, wherein the process executed by the controller (130) further comprises:

performing (S510), based on the dynamic image sequence of images, wall motion analysis of a left ventricle and identifying the characteristic of the cardiac anatomy based on the wall motion analysis.

6. The controller (130) of claim 5, wherein the process executed by the controller (130) further comprises:

quantifying (S520, S630) the characteristic of the cardiac anatomy, and

when a value of the characteristic of the cardiac anatomy generated from the quantifying exceeds a predetermined threshold, generating and displaying (S560) a warning.

7. The controller (130) of claim 5, wherein the process executed by the controller (130) further comprises:

quantifying (S520, S630) the characteristic of the cardiac anatomy, and

determining (S640) the variable correction level as a value corresponding to the characteristic of the cardiac anatomy generated from the quantifying.

8. The controller (130) of claim 1, wherein the process executed by the controller (130) further comprises:

creating (S710) a connected fluid dynamic model of elements of the cardiac anatomy; and

identifying (S730) the characteristic of the cardiac anatomy from an abnormal function in any element of the cardiac anatomy in the connected fluid dynamic model. 2018PF00983

9. The controller (130) of claim 8, wherein the variable correction level is determined based on the connected fluid dynamic model.

10. The controller (130) of claim 8, wherein the process executed by the controller (130) further comprises:

assuming (S720) a normal function in the connected fluid dynamic model; and determining (S740) the variable correction level to modify pressure half-time for valvular disease assessment.

11. A method (FIG. 3) for correcting pressure half-time for valvular disease assessment, comprising:

identifying (S330), by a processor (410) and based on the image analysis of the dynamic image sequence of images, a characteristic of the cardiac anatomy; and

determining (S340), based on the characteristic of the cardiac anatomy identified based on the image analysis of the dynamic image sequence of images, a variable correction level to modify pressure half-time for valvular disease assessment of the cardiac anatomy, wherein valvular disease of the cardiac anatomy is assessed using pressure half-time modified with the variable correction level.

12. The method of claim 11, further comprising:

identifying, in the image analysis, a degree of valvular stenosis from the dynamic image sequence of images,

wherein the pressure half-time is measured using one of TEE ultrasound, TTE ultrasound and intra-cardiac echo (ICE) ultrasound. 2018PF00983

13. The method of claim 11 ,

wherein the image analysis is used to determine at least one of diastolic dysfunction, left ventricle diastolic function relaxation, left ventricle diastolic function compliance, left atrial compliance, aortic geometry compliance for an aortic valve, calcified valves or regurgitant valves.

14. The method of claim 11, further comprising:

performing (S650), based on the dynamic image sequence of images, wall motion analysis of a left ventricle and identifying the characteristic of the cardiac anatomy based on the wall motion analysis;

quantifying (S520) the characteristic of the cardiac anatomy, and

15. The method of claim 11, further comprising:

performing (S610), based on the dynamic image sequence of images, wall motion analysis of a left ventricle and identifying the characteristic of the cardiac anatomy based on the wall motion analysis;

quantifying (S630) the characteristic of the cardiac anatomy, and

16. The method of claim 11, further comprising:

creating (S710) a connected fluid dynamic model of elements of the cardiac anatomy; assuming (S720) a normal function in the connected fluid dynamic model;

identifying (S730) the characteristic of the cardiac anatomy from an abnormal function in any element of the cardiac anatomy in the connected fluid dynamic model; and

determining (S740) the variable correction level to modify pressure half-time for valvular disease assessment of the cardiac anatomy. 2018PF00983

17. A system (FIG. 1) for correcting pressure half-time for valvular disease assessment, comprising:

a first ultrasound apparatus (110, 130) that performs pressure half-time, and that includes a controller (130) with a memory (420, 430, 482) that stores instructions and a processor (410) that executes the instructions; and

a second ultrasound apparatus (140) that obtains a dynamic image sequence of images of cardiac anatomy captured sequentially in time;

wherein, when executed by the processor (410), the instructions cause the controller (130) of the first ultrasound apparatus to execute a process comprising:

obtaining (S310), by the first ultrasound apparatus, the dynamic image sequence of images of the cardiac anatomy captured sequentially in time;