Method and appratus for the integrated assessment of cardiac function and vascular physiology

Abstract

Methods, devices, and systems for assessing the cardiovascular health of a patient are disclosed herein. In one instance, a method for evaluating a condition of a patient comprises collecting left ventricular global strain data from an echocardiogram of the patient, collecting blood pressure data from a blood pressure waveform generated by the patient's heart, matching the left ventricular global strain data and the blood pressure data with respect to time, and analyzing the time-matched strain data and blood pressure data to assess the condition of the patient.

Description

TITLE METHOD AND APPRATUS FOR THE INTEGRATED ASSESSMENT OF CARDIAC FUNCTION AND VASCULAR PHYSIOLOGY CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of U.S. Provisional Application No.63 / 660,054, entitled METHOD AND APPARATUS FOR THE INTEGRATED ASSESSMENT OF CARDIAC FUNCTION AND VASCULAR PHYSIOLOGY, filed on June 14, 2024, the entire disclosure of which is incorporated by reference herein. BACKGROUND

[0002] Cardiovascular disease (CVD) is the leading cause of death, accounting for 928,741 deaths in the United States in 2020. Cardiovascular disease pertains to diseases of the heart and vasculature, including coronary artery disease, stroke, high blood pressure, and heart failure. Evaluating cardiac function may provide significant improvements in the standard of care by monitoring the progression of these diseases and informing interventional methods. SUMMARY

[0003] In at least one form, the invention is a method of using echocardiography and blood pressure data to construct a pressure-strain loop (PSL) to quantify myocardial work (MWQ), aiming to better determine the presence and progression of disease. In at least one form, the invention is a device and / or system implementing this method. In at least one form, the device is a non-invasive testing device to evaluate cardiovascular health and function by coupling arterial blood pressure measurement and two-dimensional echocardiography imaging.

[0004] In at least one form, the invention is a method for evaluating a condition of a patient, comprising, collecting left ventricular global strain data from an echocardiogram of the patient, collecting blood pressure data from a blood pressure waveform generated by the patient’s heart, matching the left ventricular global strain data and the blood pressure data with respect to time,and analyzing the time-matched strain data and blood pressure data to assess the condition of the patient. In at least one form, the invention is a device and / or system that can implement the above.

[0005] In at least one form, the invention is a method for evaluating a condition of a patient comprising, collecting strain data from an echocardiogram of the patient’s heart, collecting blood pressure data from the patient at the same time that the strain data is collected, synchronizing the strain data and the blood pressure data with respect to time, and analyzing the synchronized strain data and blood pressure data to assess the condition of the patient. In at least one form, the invention is a device and / or system that can implement the above.

[0006] In at least one form, the invention is a method for evaluating a condition of a patient comprising obtaining distance data from an echocardiogram of the patient’s heart, obtaining blood pressure data from the patient at the same time that the distance data is obtained, calculating strain data from the distance data, synchronizing the strain data and the blood pressure data with respect to time, and analyzing the synchronized strain data and blood pressure data.

[0007] In at least one form, the invention is a system for evaluating a condition of a patient comprising a first device configured to obtain distance-related data of the patient’s heart, a blood pressure measurement device configured to obtain blood pressure-related data from the patient, and a controller configured to correlate the distance-related data and the blood pressure-related data with respect to time. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The features of the exemplary embodiments of the present invention will be described with reference to the following drawings, where like elements are labeled similarly, and in which:

[0009] FIG.1 illustrates a method of generating a clinical diagnosis from strain data taken from an echocardiogram of a patient and data related to the blood pressure of the patient that is time- synced with the strain data;

[0010] FIG.2 illustrates a method of generating a clinical diagnosis from a waveform taken from an echocardiogram of a patient and a waveform related to the blood pressure of the patient that is time-synced with the waveform from the echocardiogram;

[0011] FIG.3 illustrates a method of generating a clinical diagnosis from a pressure-strain loop comprised of time-synced data;

[0012] FIG.4 illustrates a method of generating a clinical diagnosis from a time-synced pressure-strain relationship;

[0013] FIG.5 illustrates a method of generating a pressure-strain loop comprised of time-synced data;

[0014] FIG.6 illustrates steps of the method of FIG.5 comprising obtaining, processing, and exporting strain data from an echocardiogram;

[0015] FIGS.6A-6E are detail views of FIG.6;

[0016] FIG.7 illustrates a central blood pressure waveform;

[0017] FIG.7A illustrates a central blood pressure waveform generated from measured waveform data;

[0018] FIG.8 is a graph comprising strain data taken from an echocardiogram of a patient time- synced with blood pressure data from the patient;

[0019] FIG.9 is a pressure-strain loop derived from the time-synced strain data and blood pressure data used to make the graph of FIG.8;

[0020] FIG.9A depicts measurable images usable to obtain strain data;

[0021] FIG.9B depicts the synchronization of pressure-strain data to create the loop of FIG.9;

[0022] FIG.10 is a schematic of a device configured to perform any of the methods disclosed herein;

[0023] FIG.11 depicts a laptop computer configured to perform any of the methods disclosed herein and a blood pressure measurement system in communication with the laptop computer;

[0024] FIG.12 depicts a blood pressure waveform produced by the blood measurement system of FIG.11;

[0025] FIG.13 depicts a strain measurement system in communication with the laptop computer of FIG.11; and

[0026] FIG.14 illustrates an echocardiogram produced by the strain measurement system of FIG.13.

[0027] Parts given a reference numerical designation in one figure may be considered to be the same parts where they appear in other figures without a numerical designation unless specifically labeled with a different part number and described herein.DETAILED DESCRIPTION

[0028] The features and benefits of the present invention are illustrated and described herein by reference to exemplary embodiments. This description of exemplary embodiments is intended to be read in connection with the accompanying drawings, which are to be considered part of the entire written description. Such exemplary embodiments are not limiting of the present invention.

[0029] In the description of embodiments provided herein, any reference to direction or orientation is merely intended for convenience of description and is not intended in any way to limit the scope of the present invention. Relative terms such as "lower," "upper," “horizontal,” “vertical,”, “above,” “below,” “up,” “down,” “top” and “bottom” as well as derivative thereof (e.g., “horizontally,” “downwardly,” “upwardly,” etc.) should be construed to refer to the orientation as then described or as shown in the drawing under discussion. These relative terms are for convenience of description only and do not require that the apparatus be constructed or operated in a particular orientation. Terms such as “attached,” “affixed,” “connected,” “coupled,” “interconnected,” and similar terms refer to a relationship wherein structures are secured or attached to one another either directly or indirectly through intervening structures, as well as both movable or rigid attachments or relationships, unless expressly described otherwise.

[0030] Until recently, the measure of left ventricle (LV) performance by echocardiography was qualitative, providing visual estimation of regional and global myocardial function and LV ejection fraction (LVEF). Ejection fraction refers to how well a heart pumps blood. In at least one sense, LVEF can quantify the amount of blood pumped out of a heart’s left ventricle each time it contracts. Myocardial strain including global longitudinal strain (GLS) imaging is a direct, quantitative measure that allows for the increased detection of sub-clinical dysfunction than the LVEF alone. The application of GLS provides surveillance of myocardial function in subjects undergoing cardiac surgeries, therapeutics, and treatment. However, like LVEF, strain is influenced by loading conditions and changes significantly with manipulation of preload, afterload, and heart rate. The application of myocardial work (MW) integrates arterial pressure and can “correct” for changes in the loading conditions on the heart. Table 1, provided further below, provides a summary of the potential application of MW in clinical practice. The clinical application of MW has extended from the observational findings associated with various disease states to establishing normal reference values stratified by age, race, and gender. Therefore, MWis expected to make its way into routine clinical practice, guiding clinicians on new treatment strategies for the foreseeable future.

[0031] The conventional method for calculating MW includes a single blood pressure (BP) measurement combined with two-dimensional (2D) GLS and Doppler measurements to create a pressure-strain loop (PSL). In various instances, the single blood pressure measurement was obtained from a sphygmomanometer, or blood pressure gauge, applied to a patient’s arm taken at a different time than the GLS and Doppler measurements. In various instances, the GLS and Doppler measurements were obtained using an ultrasound scanner made by General Electric, for instance. The construct of a pressure-strain loop for MW in this conventional method comprises the following measurements: (1) a blood pressure cuff measurement of the systolic peak pressure measured from the brachial artery; (2) echocardiography measurements of GLS; and (3) echocardiography measurement of cardiac event timing intervals between mitral valve opening and closure and aortic valve opening and closure by pulsed-wave Doppler.Pathology MW Application MW i itd with hihr rbbilit f idntif in n r ac pMW showed improvement after transcatheter edge-to-edge aortic valve repair, whereas GLS and LVEF did not.a e - pp ca on o n c nca prac ce

[0032] A disadvantage of the conventional MW method includes blood pressure measurements that do not accurately reflect the true relationship between arterial pressure and the heart’s contractility. Referring to the work by Russell et al. (A NOVEL CLINICAL METHOD FOR QUANTIFICATION OF REGIONAL LEFT VENTRICULAR PRESSURE–STRAIN LOOP AREA: A NON-INVASIVE INDEX OF MYOCARDIAL WORK, European Heart Journal (2012) 33, 724–733) in the validation of conventional MW, the limitations of the work include: (1) the only application of the noninvasive pressure curve proposed in the study was to serve as a pressure estimate when calculating PSL areas; and (2) the PSL has insufficient accuracy to measure LV diastolic pressure or peak rate of rise or fall in pressure. Additional observations, disadvantages, and limitations of the validation work by Russell et al. include: (1) the incorrect assumption that a single brachial artery systolic BP measurement for the construct of the PSL and MW is sufficient; (2) the PSL does not use measured pressures at end-diastole (Ped) or end- systole (Pes) but estimates them based on a linear echocardiography-Doppler measurement of event timing as described above; and (3) critical measurements for the construct of the PSL were empirical and may not accurately reflect the true relationship between pressure and strain.

[0033] The entire disclosure of A NOVEL CLINICAL METHOD FOR QUANTIFICATION OF REGIONAL LEFT VENTRICULAR PRESSURE–STRAIN LOOP AREA: A NON-INVASIVE INDEX OF MYOCARDIAL WORK, European Heart Journal (2012) 33, 724–733, is incorporated by reference herein. The entire disclosure of STATE-OF-THE-ART: NONINVASIVE ASSESSMENT OF LEFT VENTRICULAR FUNCTION THROUGH MYOCARDIAL WORK, Journal of the American Society of Echocardiography, October 2023, 1027-1042, is incorporated by reference herein.

[0034] Conventional blood pressure measurements from the arm’s brachial artery reflect the force against the vessels in a systemic arterial system. As the blood pressure increases, the heartworks harder to contract, increasing the myocardial oxygen consumption and contractile force. Disclosed herein are systems and methods that allow for the noninvasive measurement of simultaneous interaction between heart contractility and arterial pressure outside the living body. Also disclosed herein is a noninvasive method of measuring left ventricular (LV) myocardial work (MW) to assess the interaction between the body's arterial and heart function for measuring myocardial oxygen consumption and efficiency. A new application of MW as disclosed herein includes coupling arterial blood pressure measurements and myocardial strain measurements by two-dimensional (2D) echocardiography, as discussed below.

[0035] Further to the above, disclosed herein are new devices and processes, in various embodiments, that combine noninvasive blood pressure measurements by pulse-wave analysis (AtCor, Sphygmacore) and 2D GLS imaging by echocardiography to construct a pressure-strain loop (PSL). The inventors have named this improvement as Myocardial Work Quantification (MWQ). The PSL created from this approach allows for the generation of work, reflecting the heart's overall performance and related oxygen consumption when pumping against the systemic arterial tree. An example is provided in FIG.5, discussed further below, which demonstrates steps to create MWQ.

[0036] AtCor technology is currently used to assess vascular function and is disclosed, in at least one form, in AN ANALYSIS OF THE RELATIONSHIP BETWEEN CENTRAL AORTIC AND PERIPHERAL UPPER LIMB PRESSURE WAVES IN MAN, European Heart Journal (1993) 14, 160-167, by M. Karamanoglu, et al., the entire disclose of which is incorporated by reference herein. Among other things, this publication discloses, in at least one form, converting the brachial blood pressure to central aortic pressure and the general transfer function used. Embodiments are disclosed herein which use AtCor technology in combination with echocardiography that can be used to determine pressure-strain loops (PSLs). The combination of AtCor technology with echocardiography may expand the current application of vascular function to also include cardiac function namely by informing pressure strain, stroke work, and myocardial efficiency. The merging of blood pressure and echocardiographic data allows the detection of disease and quantification of changes in disease states in a non-invasive, in-office manner. While such evaluations may be made with CT and / or MRI studies, in some circumstances, implementation of such imaging modalities is limited due to cost and time required.

[0037] AtCor technology provides multiple values that are a direct and accurate measure of the myocardial work. AtCor technology can measure not only brachial artery blood pressure, but also central arterial pressure (CAP), pressure at end-diastole (Ped), and pressure at end-systole (Pes). All of these parameters are helpful in accurately measuring pressure and constructing a pressure-strain loop (PSL), in order to evaluate cardiovascular function. This will supplement current echocardiography imaging in creating an integrated, non-invasive cardiovascular toolkit for tailored medical therapy. This will reduce the inaccuracy and limitations in myocardial work measurement while avoiding invasive procedures, in order to deliver better patient care.

[0038] The entire disclosures of U.S. Patent No.11,006,842, entitled NON-INVASIVE BRACHIAL BLOOD PRESSURE MEASUREMENT, which issued on May 18, 2021, U.S. Patent No.7,479,111, entitled METHODS FOR MEASURING BLOOD PRESSURE WITH AUTOMATIC COMPENSATIONS, which issued on January 20, 2009, and U.S. Patent No. 8,469,895, entitled DERIVING CENTRAL AORTIC SYSTOLIC PRESSURE AND ANALYZING ARTERIAL WAVEFORM DATA TO DERIVE CENTRAL AORTIC SYSTOLIC PRESSURE VALUES, which issued on June 25, 2013, are incorporated by reference herein. The entire disclosures of U.S. Patent No.6,090,047, entitled ASSESSING CARDIAC CONTRACTILITY AND CARDIOVASCULAR INTERACTION, which issued on July 18, 2000, U.S. Patent Application Publication No.2015 / 0272512, entitled CENTRAL BLOOD PRESSURE ESTIMATION AND DEVICE THEREOF, which published on October 1, 2015, and U.S. Patent Application Publication No.2023 / 0131629, entitled SYSTEM AND METHOD FOR NON-INVASIVE ASSESSMENT OF ELEVATED LEFT VENTRICULAR END-DIASTOLIC PRESSURE (LVEDP), which published on April 27, 2023, are incorporated by reference herein. The entire disclosure of U.S. Patent No.8,235,910, entitled SYSTEMS AND METHODS FOR MODEL-BASED ESTIMATION OF CARDIAC EJECTION FRACTION, CARDIAC CONTRACTILITY, AND VENTRICULAR END-DIASTOLIC VOLUME, which issued on August 7, 2012, is incorporated by reference herein. The entire disclosures of U.S. Patent No.6,909,919, entitled CARDIAC LEAD INCORPORATING STRAIN GAUGE FOR ASSESSING CARDIAC CONTRACTILITY, which issued on June 21, 2005, U.S. Patent No.10,105,077, entitled METHOD AND SYSTEM FOR CALCULATING STRAIN FROM CHARACTERIZATION DATA OF A CARDIAC CHAMBER, which issued on October 23, 2018, and U.S. Patent No.8,121,687, entitled CARDIAC MOTIONCHARACTERIZATION BY STRAIN MEASUREMENT, which issued on February 21, 2012, are incorporated by reference herein.

[0039] With reference to FIG.1, a method 100 comprises steps for generating a clinical diagnosis of a patient. The method 100 comprises collecting strain data from an echocardiogram of a patient in step 110. The method 100 also comprises collecting data related to the blood pressure of the patient in step 120. Steps 110 and 120 are contemporaneous. The method 100 further comprises step 130 for creating a combined time-synchronized, or time-synced, data set from the data collected in steps 110 and 120. In at least one embodiment, the combined data set comprises a matrix of data including three columns – a first column comprising time values, a second column of data collected in step 110 at the time values in the first column, and a third column of data collected in step 120 at the time values in the first column. In various embodiments, step 130 is performed contemporaneously with steps 110 and 120 and, in other embodiments, step 130 is performed after steps 110 and 120 have been completed. The method 100 further comprises step 140 which comprises generating a clinical diagnosis of the patient from the time-synced data set created in step 130. In various embodiments, generating the clinical diagnosis of the patient in step 140 comprises analyzing the time-synced data set created in step 130. In certain embodiments, a portion of the analysis is performed by one or more computer-implemented algorithms and / or one or more devices while a portion of the analysis is performed by one or more clinicians. In at least one embodiment, the entire analysis is performed by one or more computer-implemented algorithms and / or one or more devices and the clinical diagnosis is entirely generated by one or more computer-implemented algorithms and / or one or more devices. In various embodiments, step 140 is performed contemporaneously with step 130 and, in other embodiments, step 140 is performed after step 130 has been completed.

[0040] With reference to FIG.2, a method 200 comprises steps for generating a clinical diagnosis of a patient. The method 200 comprises obtaining a strain waveform from an echocardiogram of a patient in step 210. The method 200 also comprises obtaining a blood pressure waveform of the patient in step 220. Steps 210 and 220 are contemporaneous. The method 200 further comprises step 230 for creating a time-synchronized, or time-synced, data set from the waveforms collected in steps 210 and 220. In at least one embodiment, the time-synced data set comprises a matrix of data including three columns – a first column comprising time values, a second column of data from the waveform obtained in step 210 at the time values in thefirst column, and a third column of data from the waveform obtained in step 220 at the time values in the first column. In various embodiments, step 230 is performed contemporaneously with steps 210 and 220 and, in other embodiments, step 230 is performed after steps 210 and 220 have been completed. The method 200 further comprises step 240 which comprises generating a clinical diagnosis of the patient from the time-synced data set created in step 230. In various embodiments, generating the clinical diagnosis of the patient in step 240 comprises analyzing the time-synced data set created in step 230. In certain embodiments, a portion of the analysis is performed by one or more computer-implemented algorithms and / or one or more devices while a portion of the analysis is performed by one or more clinicians. In at least one embodiment, the entire analysis is performed by one or more computer-implemented algorithms and / or one or more devices and the clinical diagnosis is entirely generated by one or more computer- implemented algorithms and / or one or more devices. In various embodiments, step 240 is performed contemporaneously with step 230 and, in other embodiments, step 240 is performed after step 230 has been completed.

[0041] With reference to FIG.3, a method 300 comprises steps for generating a clinical diagnosis of a patient. The method 300 comprises collecting strain data from an echocardiogram of a patient in step 310. The method 300 also comprises collecting data related to the blood pressure of the patient in step 320. Steps 310 and 320 are contemporaneous. The method 300 further comprises step 330 for creating a combined time-synchronized, or time-synced, data set from the data collected in steps 310 and 320. In at least one embodiment, the combined data set comprises a matrix of data including three columns – a first column comprising time values, a second column of data collected in step 310 at the time values in the first column, and a third column of data collected in step 320 at the time values in the first column. In various embodiments, step 330 is performed contemporaneously with steps 310 and 320 and, in other embodiments, step 330 is performed after steps 310 and 320 have been completed. The method 300 further comprises step 340 which comprises generating a pressure-strain loop from the time- synced data set created in step 330. The pressure-strain loop comprises both systolic and diastolic data points. In various embodiments, step 340 is performed contemporaneously with step 330 and, in other embodiments, step 340 is performed after step 330 has been completed. The method 300 further comprises step 350 which comprises generating a clinical diagnosis of the patient from the pressure-strain loop generated in step 340. In various embodiments,generating the clinical diagnosis of the patient in step 350 comprises analyzing the pressure- strain loop generated in step 340. In certain embodiments, a portion of the analysis is performed by one or more computer-implemented algorithms and / or one or more devices while a portion of the analysis is performed by one or more clinicians. In at least one embodiment, the entire analysis is performed by one or more computer-implemented algorithms and / or one or more devices and the clinical diagnosis is entirely generated by one or more computer-implemented algorithms and / or one or more devices. In various embodiments, step 350 is performed contemporaneously with step 340 and, in other embodiments, step 350 is performed after step 340 has been completed.

[0042] With reference to FIG.4, a method 400 comprises steps for generating a clinical diagnosis of a patient. The method 400 comprises collecting strain data from an echocardiogram of a patient in step 410. The method 400 also comprises collecting data related to the blood pressure of the patient in step 420. Steps 410 and 420 are contemporaneous. The method 400 further comprises step 430 for creating a combined time-synchronized, or time-synced, data set from the data collected in steps 410 and 420. In at least one embodiment, the combined data set comprises a matrix of data including three columns – a first column comprising time values, a second column of data collected in step 410 at the time values in the first column, and a third column of data collected in step 420 at the time values in the first column. In various embodiments, step 430 is performed contemporaneously with steps 410 and 420 and, in other embodiments, step 430 is performed after steps 410 and 420 have been completed. The method 400 further comprises step 440 which comprises generating a pressure-strain relationship from the time-synced data set created in step 430. In various embodiments, the pressure-strain relationship comprises at least a portion of a pressure-strain loop, for example. In at least one embodiment, the pressure-strain relationship comprises systolic data points, but not diastolic data points, for example. In various embodiments, step 440 is performed contemporaneously with step 430 and, in other embodiments, step 440 is performed after step 430 has been completed. The method 400 further comprises step 450 which comprises generating a clinical diagnosis of the patient from the pressure-strain relationship generated in step 440. In various embodiments, generating the clinical diagnosis of the patient in step 450 comprises analyzing the pressure- strain relationship generated in step 440. In certain embodiments, a portion of the analysis is performed by one or more computer-implemented algorithms and / or one or more devices while aportion of the analysis is performed by one or more clinicians. In at least one embodiment, the entire analysis is performed by one or more computer-implemented algorithms and / or one or more devices and the clinical diagnosis is entirely generated by one or more computer- implemented algorithms and / or one or more devices. In various embodiments, step 450 is performed contemporaneously with step 440 and, in other embodiments, step 450 is performed after step 440 has been completed.

[0043] A method 1000 for creating a pressure-strain loop (PSL) 5000 is illustrated in FIGS.5-9. Referring primarily to FIGS.5 and 6, the method 1000 comprises steps 2000 for acquiring strain data from an echocardiogram and processing the strain data, as discussed below. The method 1000 further comprises steps to obtain a blood pressure waveform form 3000 illustrated in FIG. 7, as discussed further below. In various instances, referring to FIG.7A, a blood pressure waveform 3000’ can be calculated from averaged data. In at least one instance, the blood pressure waveform 3000’ can comprise an average of several pulses, such as four consecutive pulses 3100a-3100d, for example. In various instances, referring to FIG.12, a blood pressure waveform 3000’’ can be obtained from a brachial cuff-based device. Referring to FIG.8, the method 1000 further comprises one or more steps to match the strain data with the blood pressure waveform 3000, as also discussed further below. Referring to FIG.9, the method 1000 further comprises steps to create the pressure-strain loop 5000 from the matched data, as also discussed further below.

[0044] With reference to FIGS.5, the creation of the PSL 5000 begins with the two-dimensional acquisition of the apical four-chamber (A), two-chamber (B), and three-chamber (C) views by echocardiography. Three images are selected and imported into the strain program. See also FIG. 9C. Once imported, the images included AMM (anatomical M-mode) analysis (D). Note the AMM cursor was decreased and placed across the anterior mitral valve leaflet in each view (arrows), allowing for zooming in on the leaflet motion. To the right are the corresponding AMM tracings. The program automatically selected the second of the three cardiac cycles, which allows for the editing of the end-diastolic start time to the end-diastolic end time (vertical lines with crossbar) for completion of one complete cardiac cycle. Once the vertical lines were set at valve leaflet closure, analysis of the endocardial contour was initiated (E). If required, semi-automation of the spline (line) included tracking on the sub-endocardial reflectors occurred. If required, the spline anchor points were moved to the ventricular side of the mitral valveannulus. Once the editing was completed, the final GLS analysis occurred (F). The GLS values and averages from the three views were exported in text format (G). The aortic pressure and GLS values and their timing were synchronized and matched (H), permitting the construction of a PSL 5000 (I).

[0045] Further to the above, referring to FIG.7, the blood pressure waveform 3000 is obtained via a tonometer, for example. In at least one embodiment, the blood pressure waveform 3000 is obtained by a pressure transducer, for example. In various embodiments, the blood pressure waveform 3000 is obtained by a Sphygmacor XCEL manufactured by Cardiex, for example. Referring to FIG.8, further to the above, a graph 4000 has been generated depicting the strain data as a curve 4200 and the blood pressure waveform data as a curve 4300 that are synchronized with respect to a time axis 4010. The graph 4000 further depicts the cardiac waveform 4100 during which the strain data 4200 the blood pressure data 4300 were taken which has also been synchronized with respect to the time axis 4010. Further to the above, referring to FIG.8, this synchronized data has been used to create the PSL 5000. The PSL 5000 is comprised of five data pair points, points A-E, but could be comprised of any suitable number of data pair points. The five data pair points A-E are plotted with respect to a horizontal strain axis 5010 and a vertical blood pressure axis 5020. Points A, B, and C are systolic data points while points D and E are diastolic data points. The points A, B, and C define a systolic curve 5100 of the PSL 5000 while points D and E define a diastolic curve 5200 of the PSL 5000. The systolic curve 5100 and the diastolic curve 5200 comprise linear segments, but could comprise any suitable configuration, such as curved segments, for example. The data pair point A represents the point in time when the aortic valve of the patient’s heart has opened in the cardiac waveform 4100. This point is represented as point AVO in FIG.9B. The data pair point B represents the point in time in which the systolic pressure is at a maximum in the cardiac waveform 4100, and the data pair point C represents the point in time in when the aortic valve of the patient’s heart has closed. These points are represented as points Psys and AVC, respectively, in FIG.9B. The data pair point D represents the point in time in which mitral valve of the patient’s heart is open. This point is represented by point MVO in FIG.9B. The data pair point E represents the point in time in which the mitral valve of the patient’s heart is closed. This point is represented by point MVC in FIG.9B.

[0046] Table 2 provided below provides a comparative analysis of conventional MW and the new MWQ. Conventional MW New MWQTable 2 - Comparative analysis of MW and MWQ

[0047] With reference to FIG.10, a device 7000 is configured to implement any one or more of the methods and / or algorithms disclosed herein. The device 7000 comprises a strain measurement system 7100 and a blood pressure measurement system 7200 that are in signal communication with and configured to supply data to a processor 7300. In various embodiments, the strain measurement system 7100 comprises an ultrasound scanner, for example. In at least one embodiment, the strain measurement system 7100 is configured to measure the strain of a left heart ventricle, for example. However, in other embodiments, the strain measurement system 7100 can be configured to measure the strain of any other suitable feature of a patient’s heart. In various embodiments, the blood pressure measurement system 7200 comprises a tonometer, for example. In various embodiments, the processor 7300 comprises a central processing unit and / or a graphics processing unit, for example. The device 7000 further comprises a memory device 7400 in signal communication with the processor 7300. The memory device 7400 is configured to store data that is accessible to the processor 7300 including, in various embodiments, data from the processor 7300. In various embodiments, the memory device 7400 comprises a random access memory (RAM) chip and / or a read-only memory (ROM) chip, for example. In various embodiments, the processor 7300 comprises an integral, or on-board, memory device. The device 7000 further comprises an input system 7500 configured to supply an input, data, and / or a control signal to the processor 7300. In various embodiments, the input system 7500 comprises a keyboard, a mouse, and / or a sensor, for example, in signal communication with at least one input gate of the processor 7300. The device 7000 further comprises a display system 7600 in signal communication with at least one output gate of the processor 7300. In various embodiments, the display system 7600 comprises a monitor, for example. In certain embodiments, the display system 7600 comprises a touch screen, for example, in signal communication with at least one input gate of the processor 7300. In various embodiments, the display system 7600 can be used to display the graph 4000 and / or the PSL 5000. The device 7000 further comprises an output system 7700 in signal communication with at least one output gate of the processor 7300. In various embodiments, the output system 7700 comprises at least one speaker, for example. The device 7000 further comprises a communications system 7800 in signal communication with the processor 7300. In various embodiments, the communications system 7800 comprises a wireless signal transmitter circuit configured to emit a data signal to an external device 7900 and / or a wireless signalreceiver circuit configured to receive a data signal from an external device 7900, for example. In various embodiments, the external device 7900 comprises a computer network and / or cloud, for example.

[0048] A laptop computer 8000 is illustrated in FIG.11 which can comprise the device 7000, or at least portions of the device 7000. As illustrated in FIG.11, a blood pressure measurement system 7200 is connected to and in communication with the laptop computer 8000. The blood pressure measurement system 7200 comprises a brachial cuff-based device that can be used to obtain a continuous blood pressure waveform 3000’’ illustrated in FIG.12, for example, of a patient P depicted in FIG.13, but can comprise any suitable blood pressure measurement system. The brachial cuff-based blood pressure measurement system 7200 comprises a cuff 7210 configured to surround the patient’s arm and a hose, or tube, 7220 extending at least partially through the cuff 7210 that is pressurized with air, for example, by a pump in a console 7230 of the blood pressure measurement system 7200. The console 7230 comprises one or more pressure sensors configured to detect the pressure of the air in the tube 7220. Owing to the contact between the cuff 7210 and the patient’s arm, the heartbeat of the patient, which is transmitted through the blood in the patient’s brachial artery via pressure pulses within the blood, causes pressure changes in the air in the tube 7220 which are detected by the pressure sensors in the console 7230. In various instances, a continuous blood pressure waveform 3000’’, for example, is the product of a series of pressure readings taken from the one or more pressure sensors of the console 7230. The pressure readings are sampled by a processor of the console 7230 at a rate which produces a sufficient resolution of the blood pressure waveform. In at least one instance, two or more blood pressure waveforms, from either the same location or different locations on a patient’s body, can be time-synced and the magnitude of the blood pressure waveforms can be averaged, and / or weighted in any suitable manner, to produce a calculated, or derived, pressure waveform. The processor of the console 7230 is in communication with the processor of the laptop computer 8000 via a wired and / or wireless connection and is configured to transmit the blood pressure waveform data to the processor of the laptop computer 8000. As discussed herein, the sampled pressure readings are time-synced with one or more continuous strain waveforms taken from the patient’s heart via a heart strain measurement system 7100 so that the time-synced data can be utilized to analyze a condition of the patient. This time syncingoccurs in the laptop computer 8000 but could, in various embodiments, be performed in the blood pressure measurement system 7200 and / or the heart strain measurement system 7100.

[0049] Further to the above, the blood pressure waveform can be comprised of pressure measurements and / or measurements related to the blood pressure. In various instances, the blood pressure waveform can be derived and / or otherwise constructed from electrical measurements taken from one or more strain gauges, thermal measurements taken from one or more thermal imaging devices, and / or electrical data take from one or more vibration transducers, for example.

[0050] Further to the above, referring to FIG.13, a heart strain measurement system 7100 is connected to and in communication with the laptop computer 8000 that can be used to obtain an echocardiogram 8100, for example, illustrated in FIG.14 of the patient P. Further to the above, the size of the heart H, the size of a chamber of the heart H, and / or the position of one or more features of the heart H depicted in the echocardiogram 8100 can be continuously measured in real-time to create one or more strain waveforms. In various instances, a patient’s heart has certain anatomical features that move when the heart is beating and this movement can be used to determine the strain within the heart. In at least one instance, a chamber of the patient’s heart, such as the left ventricle, for example, has opposing walls comprised of myocardium, or heart muscle, which move relative to one another as the heart muscle contracts and relaxes. Speckle tracking echocardiography (STE) is a technique used to evaluate cardiac mechanics by tracking the movement of "speckles" in 2D gray-scale images of the myocardium that can be produced by the heart strain measurement system 7100. These speckles are formed by the interference of ultrasound waves emitted from the heart strain measurement system 7100, for example, that are scattered from structures smaller than the ultrasound wavelength within the heart. Among other things, STE allows for the measurement of myocardial strain, which refers to the amount of lengthening, shortening, and / or thickening of myocardial fibers during the cardiac cycle. Global longitudinal strain (GLS) derived from speckle tracking echocardiography (STE) assesses the longitudinal deformation of the left ventricle (LV), for example, and expresses longitudinal shortening as a percentage (change in length as a proportion to baseline length). In various instances, a strain measurement can be calculated by comparing a first image of a patient’s heart, or a portion of their heart, and a second, or subsequent, image. In at least one such instance, a first distance is measured from the first image between a first point, or speckle, on a left ventriclewall and a second point, or speckle, on an opposite, or another, wall of the left ventricle. In other embodiments, the first speckle and the second speckle can be on the same wall. Then, a second distance is measured from the second image between the first speckle and the second speckle. The difference between the first measured distance and the second measured distance is then calculated and divided by the first measure distance, for instance, to arrive at a unitless strain value. Multiplying this unitless stain value by 100% can convert it into a percentage. In many instances, normal global longitudinal strain (GLS) in the left ventricle (LV) typically ranges from -16% to -23%, for example. However, it's important to note that GLS can vary based on age, sex, and other factors. In many instances, GLS tends to be lower in older individuals than in younger ones.

[0051] Further to the above, the distance between the first speckle and the second speckle can be measured in each image in a series of images, analyzed, and compared to develop a continuous strain waveform. As discussed above, this series of images can be taken using an ultrasound scanner, for example. In various embodiments, the ultrasound scanner comprises a frame, a sound wave emitter, such as a transducer comprising piezoelectric elements, for example, and a sound wave receiver, such as an acoustic sensor, for example. In various instances, the frequency, or frequencies, of the sound waves emitted by the transducer are above that of human hearing, but any suitable frequency, or frequencies, can be used. The ultrasound scanner further comprises a processor in communication with the transducer and the acoustic sensor that is configured to, among other things, receive data from the acoustic sensor, calculate the strain values as described above, and convey the strain values to the processor of the laptop 8000. In other instances, the ultrasound scanner transmits the unprocessed data from the acoustic sensor to the processor of the laptop 8000 which performs the strain calculations described above. In various embodiments, the interconnection between the ultrasound scanner of the heart strain measurement system 7100 and the laptop 8000 can be wired and / or wireless.

[0052] As described above, the strain, or percentage change in distance, between two points in the patient’s heart, such as two points in the walls of the left ventricle, for example, can be time- synced with the corresponding blood pressure data. In various instances, the strain between more than two points in the patient’s heart can be evaluated and time-synced with the blood pressure data. For instance, two measured distances can be taken from a first image and two corresponding measured distances can be taken from a second image and then compared toderive at least two different strain values, and so forth. In at least one instance, the distance between a first speckle and a second speckle can be evaluated and another distance between the first speckle and a third speckle can be evaluated. In another instance, the distance between a first speckle and a second speckle can be evaluated and another distance between a third speckle and a fourth speckle can be evaluated. In various instances, the calculated strain values can be simultaneously and contemporaneously correlated with the blood pressure data. In at least one instance, the strain values can be averaged, and / or otherwise processed, for example, before being synchronized with the blood pressure data. In various instances, first strain data can be collected with respect to a first axis and second strain data can be collected with respect to a second axis. The first axis can be orthogonal to the second axis, or not orthogonal. In certain instances, first strain data can be collected with respect to a first axis, second strain data can be collected with respect to a second axis, and third strain data can be collected with respect to a third axis. The first axis, the second axis, and / or the third axis can be orthogonal, or not orthogonal.

[0053] It should be understood that the blood pressure measurements and the strain measurements discussed herein may have time stamps associated therewith that the processor can use to synchronize this data. In some instances, the time stamps can be perfectly synchronized while, in other instances, the time stamps can be substantially synchronized within an acceptable time error margin. Whether the time stamps are perfectly synchronized or substantially synchronized, the terms synchronized data and / or time-correlated data cover all such situations.

[0054] Combining CAP and its derivates and noninvasive measurements of MW is now possible through MWQ. We are pursuing this research because we now have the technology to provide insights into the early disease of the cardiovascular system, warranting intervention, and therapeutics. In addition, our novel algorithms may better detect cardiovascular disease than the current methodology. The application of the PSL for MWQ can address a myriad of disease states, from diagnosis to treatment strategies, including cardio-oncology, systemic arterial hypertension, heart failure, coronary artery disease, hypertrophic cardiomyopathy, dilated cardiomyopathy, amyloidosis, and valvular heart disease. See Table 1.

[0055] While the foregoing description and drawings represent exemplary embodiments of the present disclosure, it will be understood that various additions, modifications and substitutionsmay be made therein without departing from the spirit and scope and range of equivalents of the accompanying claims. In particular, it will be clear to those skilled in the art that the present invention may be embodied in other forms, structures, arrangements, proportions, sizes, and with other elements, materials, and components, without departing from the spirit or essential characteristics thereof. In addition, numerous variations in the methods / processes described herein may be made within the scope of the present disclosure. One skilled in the art will further appreciate that the embodiments may be used with many modifications of structure, arrangement, proportions, sizes, materials, and components and otherwise, used in the practice of the disclosure, which are particularly adapted to specific environments and operative requirements without departing from the principles described herein. The presently-disclosed embodiments are therefore to be considered in all respects as illustrative and not restrictive. The appended claims should be construed broadly, to include other variants and embodiments of the disclosure, which may be made by those skilled in the art without departing from the scope and range of equivalents.

Claims

CLAIMS 1. A method for evaluating a condition of a patient, comprising: collecting left ventricular global strain data from an echocardiogram of the patient; collecting blood pressure data from a blood pressure waveform generated by the patient’s heart; matching the left ventricular global strain data and the blood pressure data with respect to time; and analyzing the time-matched strain data and blood pressure data to assess the condition of the patient.

2. The method of claim 1, further comprising creating matched data pairs between the left ventricular global strain data and the blood pressure data with respect to time.

3. The method of claim 2, further comprising generating a pressure-strain loop using the matched data pairs.

4. The method of claim 3, further comprising displaying the pressure-strain loop on a display.

5. The method of any one of claims 1-3, further comprising generating a graph correlating the left ventricular global strain data and the blood pressure data with respect to time.

6. The method of claim 5, further comprising displaying the graph on a display.

7. The method of any one of claims 1-6, wherein the condition comprises a cardiovascular disease.

8. The method of any one of claims 1-7, further comprising generating a clinical diagnosis using the time-matched strain data and blood pressure data.

9. A device capable of implementing any one of the methods of claims 1-8.

10. A method for evaluating a condition of a patient, comprising: obtaining distance data from an echocardiogram of the patient’s heart; obtaining blood pressure data from the patient at the same time that the distance data is obtained; calculating strain data from the distance data; synchronizing the strain data and the blood pressure data with respect to time; and analyzing the synchronized strain data and blood pressure data.

11. The method of claim 10, wherein the distance data are measurements taken from the left ventricle of the patient’s heart.

12. The method of any one of claims 10 and 11, further comprising generating a clinical diagnosis using the synchronized strain data and blood pressure data.

13. The method of any one of claims 10-12, further comprising: creating matched data pairs between the strain data and the blood pressure data with respect to time; and generating a pressure-strain loop using the matched data pairs.

14. The method of any one of claims 10-13, further comprising generating a clinical diagnosis using the time-matched strain data and blood pressure data.

15. A system for evaluating a condition of a patient, comprising: a first device configured to obtain distance-related data of the patient’s heart; a blood pressure measurement device configured to obtain blood pressure-related data from the patient; and a controller configured to correlate the distance-related data and the blood pressure- related data with respect to time.

16. The system of claim 15, wherein the first device comprises an imaging device.

17. The system of claim 15 or 16, wherein the blood pressure measurement device comprises a sphygmomanometer.

18. The system of any one of claims 15-17, wherein the controller is configured to analyze the time-correlated strain data and blood pressure data to assess the condition of the patient, and wherein the condition comprises a cardiovascular disease.

19. The system of any one of claims 15-18, wherein the controller comprises a processor in communication with the imaging device and the blood pressure measurement device.

20. The system of claim 19, wherein the controller is configured to: create matched data pairs between the strain data and the blood pressure data with respect to time; and generate a pressure-strain loop using the matched data pairs.

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