Cardiovascular assistance system to quantify cardiac function and promote cardiac recovery

Abstract

The systems, devices and methods presented herein use a heart pump to obtain measurements of cardiovascular function. The heart pump described herein can operate in parallel with the heart and unload from the heart. The system can quantify the operation of the natural heart by measuring certain parameters / signals such as pressure or motor current, and then calculate and display one or more indicators of cardiovascular function. These indicators, such as left ventricular end-diastolic pressure (LVEDP), left ventricular pressure and contractility, etc., provide the user with valuable information about the patient's cardiac function and the state of recovery.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Application No. 62 / 396,628, filed on September 19, 2016, the contents of which are hereby incorporated by reference herein in their entirety. Background Art

[0003] Cardiovascular (CV) disease is a leading cause of morbidity, mortality, and healthcare burden worldwide, with approximately 7 million cases of heart failure and many more cases of myocardial infarction in the United States alone. Acute and chronic CV conditions reduce quality of life and life expectancy. Multiple treatment modalities have been developed for CV disease, ranging from drugs to mechanical devices and ultimately transplantation. Temporary cardiac support devices such as ventricular assist devices provide hemodynamic support and promote cardiac recovery.

[0004] There are many types of temporary cardiac assist devices with varying degrees of support and invasiveness, ranging from intra-aortic balloon pumps (IABPs) to extracorporeal membrane oxygenation (ECMO) devices to surgically implanted left ventricular assist devices (LVADs). These devices typically reside outside the ventricles or bypass the ventricles and do not work in parallel with or directly support cardiac function. They also do not provide clinicians with quantifiable metrics that can guide the level of cardiac support required for a particular patient. Some ventricular assist devices are inserted percutaneously into the heart and can operate in parallel with the native heart to supplement cardiac output, such as the IMPELLA® series of devices (Abiomed, Inc., Danvers MA).

[0005] The amount of support (e.g., the volumetric flow rate of blood delivered by the pumping device) and / or the duration of support required for each patient may vary. It has been proposed that changes in the motor current required to maintain rotor speed can be used to understand pump placement or pump function, but these proposals have failed to effectively process the motor current data to measure cardiac function. For example, U.S. Patent No. 6,176,822 describes measuring motor current to aid in proper positioning of a pump, and U.S. Patent No. 7,022,100 mentions calculating blood pressure based on the relationship between the torque of a motor used to drive the rotor and the motor current. However, motor current alone provides only limited insight into a patient's overall cardiac function, and existing measurements such as aortic pressure do not correlate with a patient's overall cardiac function. Therefore, a more direct and quantitative estimate of cardiac function is needed to help clinicians determine how much support a device should provide or when to terminate the use of a cardiac assist device. Summary of the invention

[0006] The systems, devices and methods described herein enable a support device residing in an organ to assess the function of the organ. In particular, these systems, devices and methods enable a cardiac assist device such as a percutaneous ventricular assist device to be used to assess the function of the heart based on measurements of device performance and measurements of one or more hemodynamic parameters. Using a cardiac assist device to assess the function of the heart can allow the degree / level of support provided by the assist device (e.g., the flow rate of blood pumped by a pumping device) to be tailored to the needs of a particular patient. For example, changes in device performance (or the absolute performance of the device) can be detected, and the detected performance is used to determine whether the patient's heart is deteriorating or improving and to what extent. Based on the detected performance, the degree of support is adjusted. For example, the degree of support can be increased when the patient's heart function deteriorates, or the degree of support can be reduced when the patient's heart function recovers and returns to a baseline of normal heart function. This allows clinicians to respond to changes in heart function to promote heart recovery, which can allow patients to gradually wean themselves off treatment. In addition, an assessment of heart function used to better understand heart function can indicate when it is appropriate to terminate the use of a cardiac assist device. Although some of the embodiments presented herein relate to cardiovascular assist devices that are implanted across the aortic valve and reside partially in the left ventricle, the concepts can be applied to devices in the heart, cardiovascular system, or other areas of the body.

[0007] In addition, the cardiac assist device of the present invention can continuously or nearly continuously monitor and evaluate cardiac function while the device is in the patient's body. This may be advantageous compared to methods that estimate cardiac function only at specific time intervals. For example, continuous monitoring can allow real-time detection of cardiac deterioration, which is faster than prior art methods. The cardiac device can be inserted using minimally invasive surgery without damaging the organ. In addition, if the cardiac assist device is already in the patient's body, cardiac function can be measured without the need to introduce additional catheters into the patient's body.

[0008] The systems, devices, and methods presented herein determine cardiac function parameters indicative of native cardiac function from measurements of intravascular pressure and pump parameters ("parameters" may represent signals and / or operational states of the cardiovascular system and / or cardiac pump). Cardiac function may be quantified in several different ways using the devices and techniques presented herein, including one or more of left ventricular end-diastolic pressure (LVEDP), contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, and / or cardiac cycle flow state. In some applications, these cardiac parameters are determined based in part on a lag between a pressure measurement (e.g., the pressure difference between aortic pressure and left ventricular pressure, or aortic pressure, or other pressure measured in the vasculature or in a device inserted into the vasculature) and a motor current measurement, which allows detection of the phase of the cardiac cycle corresponding to a given pair of pressure and current measurements. From these measurements, the user can determine important information about cardiac function and, in some cases, cardiac assist device performance, including the occurrence of pumping events.

[0009] In one aspect, a heart pump system includes: a catheter; a motor; a rotor operatively coupled to the motor; and a pump housing at least partially surrounding the rotor so that actuating the motor drives the rotor and pumps blood through the pump housing. The heart pump system also includes a sensor that detects hemodynamic parameters over time, and a controller. The controller detects motor parameters over time, receives input of the hemodynamic parameters detected over time from the sensor, and determines a relationship between the detected hemodynamic parameters and motor parameters, such as a relationship between the hemodynamic parameters measured over time and the motor parameters measured over time. For example, the controller can store the detected motor parameters and hemodynamic parameters in a memory, and can associate the motor parameters and hemodynamic parameter data so that they match in time. The controller uses a polynomial best fit algorithm to characterize the relationship between the detected hemodynamic parameters and motor parameters, and stores the characterized relationship in a memory. For example, the controller can characterize the relationship by fitting all or part of the data (e.g., a portion of the hemodynamic parameter data, such as pressure measurements, and a portion of the motor parameter data, such as motor current measurements) to an appropriate equation, such as an ellipse fit, a polynomial equation, or an Euler equation.

[0010] In some embodiments, the motor parameter is current delivered to the motor, power delivered to the motor, or motor speed. In some embodiments, the controller determines at least one cardiovascular metric by extracting an inflection point, a local slope change, or a curvature change from the characterized relationship between the detected hemodynamic parameter and the motor parameter. In some embodiments, the at least one cardiovascular metric is at least one of contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular pressure, preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, cardiac cycle volume load state, or cardiac cycle flow state. In some embodiments, the at least one cardiovascular metric is left ventricular end diastolic pressure (LVEDP).

[0011] In some embodiments, the hemodynamic parameter is aortic pressure and the motor parameter is current, and characterizing the relationship includes fitting an equation to at least a portion of the data representing the measured current and the head pressure calculated from the measured current and the aortic pressure. In some embodiments, the controller determines the LVEDP point from the equation fit to at least a portion of the current and head pressure data, and accesses a lookup table to determine the actual LVEDP value from the LVEDP point in the head pressure data. In some embodiments, determining the LVEDP point includes identifying an inflection point, a local slope change, or a curvature change in the equation fit to at least a portion of the current and head pressure data.

[0012] In some embodiments, the controller determines the cardiac cycle phase from the relationship between the detected hemodynamic parameters and the motor parameters. In some embodiments, the controller describes a hysteresis curve based on the relationship between the detected hemodynamic parameters and the motor parameters, and selects a sampling time on the hysteresis curve corresponding to the cardiac cycle phase.

[0013] In some embodiments, determining the phase of the cardiac cycle includes: detecting that the cardiac cycle phase is in diastolic relaxation when the sampling time corresponds to a segment of the hysteresis curve corresponding to an increased pressure head; detecting that the cardiac cycle phase is in diastolic filling when the sampling time corresponds to the following segment of the hysteresis curve, that is, the segment corresponds to a decreased pressure head after diastolic relaxation to a point distinguished by a rapid change in slope or curvature or an identified inflection point; or detecting that the cardiac cycle phase is in cardiac contraction when the sampling time corresponds to a segment of the hysteresis curve with decreased pressure head from the inflection point to the minimum pressure head.

[0014] In some embodiments, the motor parameter and the hemodynamic parameter are detected during a portion of a cardiac cycle. In other embodiments, the motor parameter and the hemodynamic parameter are detected during one or more cardiac cycles. In some embodiments, the motor maintains a substantially constant speed of the rotor during actuation of the rotor. In some embodiments, the controller stores the at least one cardiovascular indicator in a memory having at least one previously determined cardiovascular indicator. In some embodiments, the heart pump system further comprises an integrated motor positioned proximate a distal end of the catheter proximal to the heart pump.

[0015] In another aspect, a heart pump system includes: a catheter; a motor; a rotor operatively coupled to the motor; and a pump housing at least partially surrounding the rotor so that actuating the motor drives the rotor and pumps blood through the pump housing. The heart pump system also includes a pressure sensor that detects aortic pressure over time, and a controller. The controller detects motor parameters over time, receives aortic pressure from the sensor over time, stores a relationship between the motor parameters and aortic pressure in a memory, determines a time period in which an inflection point indicative of LVEDP can be found, and identifies an inflection point in aortic pressure based on the determined time period.

[0016] In some embodiments, determining a time period in which an inflection point indicative of LVEDP can be found includes identifying a time period in which the received motor parameter changes. In some embodiments, the controller further determines LVEDP from a dynamic curve lookup table stored in a memory based on an inflection point in aortic pressure. In some embodiments, the controller receives an ECG signal, and determining a time period in which an inflection point indicative of LVEDP can be found includes identifying a time period in which the ECG signal indicates an end cycle of diastole.

[0017] In some embodiments, the motor parameter is one of a motor current, a change in motor current, a variability of motor current, and a net integrated area of ​​motor current and pressure. In some embodiments, the controller also determines a cardiac cycle phase from a relationship between a motor parameter and aortic pressure, and the cardiac cycle phase is determined using one or more of ECG data, hemodynamic parameters, motor parameters, and a slope of motor speed and / or aortic pressure. In some embodiments, the motor is configured to maintain a substantially constant rotor speed during actuation of the rotor. In some embodiments, the heart pump further comprises an integrated motor sized and configured for insertion into the patient's vascular system.

[0018] In another aspect, a heart pump system includes a heart pump and an electronic controller. The heart pump includes a motor, a rotor operatively coupled to the motor, and a sensor of a hemodynamic parameter. The controller is configured to measure motor parameters, such as current delivered to the motor, power delivered to the motor, or motor speed, and to measure the hemodynamic parameter over time using the sensor. The controller is configured to determine and describe a hysteresis curve over time based on an input representing the motor parameter and an input representing the hemodynamic parameter, the hysteresis curve being determined according to a best fit algorithm or other suitable processing algorithm, and to scale the fitted hysteresis curve based on a measured patient heart parameter, such as aortic pressure, to determine left ventricular pressure.

[0019] In some embodiments, the controller is configured to determine at least one cardiovascular indicator by extracting an inflection point value from a scaled hysteresis curve. In some adjustments, the at least one cardiovascular indicator is left ventricular end-diastolic pressure. In some embodiments, determining or characterizing the hysteresis curve includes selecting a polynomial expression to fit the hysteresis curve and using the controller to process data representing motor parameters and hemodynamic parameters (e.g., from sensor measurements) to calculate the curve. For example, data representing motor parameters and measured hemodynamic parameters can be stored in the controller as data arrays in tables within a database in a memory or server, and the controller can access these data tables to obtain the data to calculate the hysteresis curve. The stored data can be accessed by the controller or a user at a later time.

[0020] In some embodiments, the hemodynamic parameter is pressure head. In some embodiments, the at least one cardiovascular indicator is at least one of contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular end-diastolic pressure, preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, cardiac cycle volume load state and / or cardiac cycle flow state. In some embodiments, the motor maintains a constant speed of the rotor during the measurement of the motor parameter.

[0021] In some embodiments, the controller is further configured to determine the cardiac phase from the hysteresis curve. In some embodiments, the cardiac phase is determined using one or more of ECG data, pressure measured at a pressure sensor, motor parameters and motor speed, aortic pressure slope, and respiratory changes. In some embodiments, determining the cardiac phase includes selecting a segment of the hysteresis curve corresponding to the sampling time based on the measurement results of the motor parameters and the pressure head at the sampling time, the segment corresponding to one of relaxation, contraction, ejection, and filling. In some embodiments, determining the cardiac phase also includes detecting that the cardiac phase is diastole when the sampling time corresponds to a segment with high pressure of the hysteresis curve, and detecting that the cardiac phase is systole when the sampling time corresponds to a segment with low pressure of the hysteresis curve.

[0022] In another aspect, a heart pump system includes a motor, a rotor operatively coupled to the motor, a pressure sensor, and a controller. The controller is configured to measure motor parameters, measure head pressure over time using the pressure sensor, describe a hysteresis curve based on a hysteresis between the motor parameters and head pressure over time according to a best fit algorithm, scale the fitted hysteresis curve based on measured aortic pressure to determine left ventricular pressure, determine at least one cardiovascular indicator by extracting an inflection point from the scaled hysteresis curve, and display the at least one cardiovascular indicator on a display screen of the controller.

[0023] In some embodiments, the at least one cardiovascular indicator is left ventricular end-diastolic pressure. In some embodiments, describing the hysteresis curve includes selecting a polynomial expression to fit the hysteresis curve. In some embodiments, the at least one cardiovascular indicator is at least one of contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular end-diastolic pressure, preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, cardiac cycle volume load state and / or cardiac cycle flow state. In some embodiments, the motor parameter is motor current, change in motor current, variability of motor current, or net integrated area of ​​motor current and pressure. In some embodiments, the motor maintains a constant rotor speed during the measurement of the motor parameter.

[0024] In some embodiments, the controller is further configured to determine the cardiac phase from the hysteresis curve. In some embodiments, the cardiac phase is determined using one or more of ECG data, pressure measured at the pressure sensor, motor parameters and motor speed, aortic pressure slope, and respiratory changes. In some embodiments, determining the cardiac phase includes accessing the hysteresis curve, selecting a segment of the curve corresponding to the sampling time based on the measurement results of the motor parameters and the pressure head and the sampling time, and determining the corresponding cardiac phase of relaxation, contraction, ejection, or filling based on the segment.

[0025] In some embodiments, the motor has a diameter of less than about 21 French. In some embodiments, the at least one cardiac indicator is at least one of contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular end-diastolic pressure, preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, cardiac cycle volume load state and / or cardiac cycle flow state. In some embodiments, the controller is configured to automatically adjust the level of support provided by the heart pump when the at least one cardiac indicator indicates a change in the patient's cardiac state, wherein the patient's cardiac state is defined by at least one of a change in contractility, a change in volume load, a change in preload, a change in afterload, a change in heart rate and a change in pulse pressure. In some embodiments, the controller is configured to automate the level of support or method provided by the heart pump to enhance and improve natural heart function, wherein the automated support level or method includes at least one of changing the volume flow of blood delivered by the heart pump, changing the frequency and / or amplitude of the automatic blood flow pulsation, and changing the rotational speed of the rotor. In some embodiments, the motor maintains a constant motor speed during the measurement of the motor parameter.

[0026] In some embodiments, determining the cardiac phase includes accessing a graph of pressure as a function of motor parameters, wherein the graph forms a hysteresis loop, and using measurements of the motor parameters and pressure at sampling times to identify segments of the hysteresis loop corresponding to the sampling times, wherein each segment corresponds to a cardiac phase. In some embodiments, the cardiac phase is determined using ECG data. In some embodiments, the cardiac phase is determined using pressure measured at a pressure sensor. In some embodiments, determining the cardiac phase also includes detecting that the cardiac phase is diastole if the sampling time corresponds to a segment of the hysteresis loop with high pressure, and detecting that the cardiac phase is systole if the sampling time corresponds to a segment of the hysteresis loop with low pressure.

[0027] In some embodiments, the controller is configured to generate a graph of pressure and motor parameter measurements, wherein the motor parameter is a first coordinate of the graph and the pressure is a second coordinate of the graph, or to monitor the relationship of the motor parameter and the pressure system. In some embodiments, the blood pump is transcutaneous. In some embodiments, the motor is implantable. In some embodiments, the heart pump system is configured such that when the rotor is placed in the aorta, the pressure sensor is located within the aorta. In some embodiments, the heart pump system is an intravascular heart pump system.

[0028] On the other hand, a heart pump system includes a heart pump and a controller. The heart pump includes a motor, a rotor operatively coupled to the motor, and a sensor for hemodynamic parameters, such as a pressure sensor. The controller is configured to measure motor parameters and hemodynamic parameters through the sensor, determine the cardiac phase, determine at least one cardiac indicator indicating cardiac function, and display the at least one cardiac indicator on a display screen of the controller. For example, the controller can be configured to measure motor parameters of the current delivered to the motor or the power delivered to the motor, measure the pressure at the pressure sensor, determine the cardiac phase, determine at least one cardiac indicator indicating cardiac function, and display the at least one cardiac indicator on a display screen of the controller. The cardiac indicator indicating cardiac function can be determined using a predetermined pressure-motor curve, and the determination of the at least one cardiac indicator can be based on the hysteresis between the motor parameter and the pressure.

[0029] In some embodiments, the measured pressure is one of aortic pressure or the pressure difference between aortic pressure and left ventricular pressure. In some embodiments, the at least one cardiac indicator is at least one of contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular end-diastolic pressure, preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, cardiac cycle volume load state and / or cardiac cycle flow state. In some embodiments, the controller is configured to automatically adjust the support level provided by the heart pump when the at least one cardiac indicator indicates a change in the patient's heart state, wherein the patient's heart state is defined by at least one of a change in contractility, a change in volume load, a change in preload, a change in afterload, a change in heart rate and a change in pulse pressure. In some embodiments, the controller is configured to automate the support level or method provided by the heart pump to enhance and improve natural heart function, wherein the automated support level or method includes changing the volume flow of blood delivered by the heart pump, changing the frequency and / or amplitude of automatic blood flow pulsation, and changing the rotational speed of the rotor. In some embodiments, the motor maintains a constant motor speed during the measurement of the motor parameter.

[0030] In some embodiments, determining the cardiac phase includes accessing a graph of pressure as a function of motor parameters, wherein the graph forms a hysteresis loop, and using measurements of the motor parameters and pressure at sampling times to determine a segment of the hysteresis loop corresponding to the sampling time, wherein each segment corresponds to a cardiac phase. In some embodiments, the cardiac phase is determined using ECG data. In some embodiments, the cardiac phase is determined using pressure measured at a pressure sensor. In some embodiments, determining the cardiac phase also includes detecting that the cardiac phase is diastole if the sampling time corresponds to a segment of the hysteresis loop with high pressure, and detecting that the cardiac phase is systole if the sampling time corresponds to a segment of the hysteresis loop with low pressure.

[0031] In some embodiments, the controller is configured to generate a graph of pressure and motor parameter measurements, wherein the motor parameter is a first coordinate of the graph and pressure is a second coordinate of the graph, or to monitor the relationship of the motor parameter and the pressure system. In some embodiments, the blood pump is transcutaneous. In some embodiments, the motor is implantable. In some embodiments, the heart pump system is configured such that when the rotor is placed in the aorta, the pressure sensor is located within the aorta. In some embodiments, the motor parameter is one of a motor current, a change in motor current, a variability in motor current, and a net integrated area of ​​motor current and pressure. In some embodiments, the heart pump system is an intravascular heart pump system.

[0032] In another aspect, a heart pump system includes a heart pump and a controller. The heart pump includes a motor, a rotor operatively coupled to the motor, and a pressure sensor. The controller is configured to measure a motor parameter, wherein the motor parameter is a current delivered to the motor or a power delivered to the motor, measure a pressure at the pressure sensor, determine a cardiac phase, determine at least one cardiac indicator indicative of cardiac function, determine at least one recommendation for a change in operating the heart pump based on the at least one cardiac indicator, and display the at least one recommendation on a display screen of the controller. The cardiac indicator indicative of cardiac function is determined using a predetermined pressure-motor curve, and the determination of the at least one cardiac indicator is based on a hysteresis between the motor parameter and the pressure.

[0033] In some embodiments, at least one recommendation includes changing the rotational speed of the rotor, changing the power delivered to the motor, and / or removing the heart pump from the patient. In some embodiments, the at least one cardiac indicator is contractility, stroke volume, ejection fraction, chamber expansion, chamber hypertrophy, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular end-diastolic pressure, preload state, afterload state, heart rate, and cardiac recovery. In some embodiments, the controller is configured to automatically adjust the support level provided by the heart pump when the at least one cardiac indicator indicates a change in the patient's cardiac state, wherein the patient's cardiac state is defined by at least one of a change in contractility, a change in volume load, a change in preload, a change in afterload, a change in heart rate, and a change in pulse pressure. In some embodiments, the controller is configured to automate the support level or method provided by the heart pump to enhance and improve natural heart function, wherein the automated support level or method includes changing the volume flow of blood delivered by the heart pump, changing the frequency and / or amplitude of automatic blood flow pulsation, and changing at least one of the rotational speed of the rotor. In some embodiments, the motor maintains a constant motor speed during the measurement of the motor parameters.

[0034] In some embodiments, determining the cardiac phase includes accessing a graph of pressure as a function of motor parameters, wherein the graph forms a hysteresis loop, and using measurements of the motor parameters and pressure at sampling times to identify segments of the hysteresis loop corresponding to the sampling times, wherein each segment corresponds to a cardiac phase. In some embodiments, the cardiac phase is determined using ECG data. In some embodiments, the cardiac phase is determined using pressure measured at a pressure sensor. In some embodiments, determining the cardiac phase also includes detecting that the cardiac phase is diastole if the sampling time corresponds to a segment of the hysteresis loop with high pressure, and detecting that the cardiac phase is systole if the sampling time corresponds to a segment of the hysteresis loop with low pressure.

[0035] In some embodiments, the controller is configured to generate a graph of pressure and motor parameter measurements, wherein the motor parameter is a first coordinate of the graph and pressure is a second coordinate of the graph, or to monitor the relationship of the motor parameter and the pressure system. In some embodiments, the blood pump is transcutaneous. In some embodiments, the motor is implantable. In some embodiments, the heart pump system is configured such that when the rotor is placed in the aorta, the pressure sensor is located within the aorta. In some embodiments, the motor parameter is one of a motor current, a change in motor current, a variability in motor current, and a net integrated area of ​​motor current and pressure. In some embodiments, the heart pump system is an intravascular heart pump system.

[0036] On the other hand, a heart pump system includes a heart pump and a controller. The heart pump includes a rotor, a motor coupled to the rotor, a blood inlet, and a pressure sensor. The controller communicates with the motor and the pressure sensor. The controller is configured to measure motor parameters at a sampling time, measure the pressure at the pressure sensor at the sampling time, and determine whether the blood inlet is blocked based on the measurement results of the motor parameters and the pressure at the sampling time, wherein the occlusion of the blood inlet is determined using hysteresis in the measurement of the motor parameters and the pressure at the pressure sensor. In some embodiments, the controller is configured to display a warning parameter in response to determining that the blood inlet is blocked. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The foregoing and other objects and advantages will be apparent from the following detailed description considered in conjunction with the accompanying drawings, in which like reference numerals refer to like parts throughout, and in which:

[0038] Figure 1 A prior art catheter-based intravascular heart pump system positioned in the heart is shown;

[0039] Figure 2 A prior art LVAD heart pump system is shown positioned in the heart;

[0040] Figure 3 shows an illustrative heart pump system configured to estimate a cardiovascular parameter in accordance with certain embodiments;

[0041] Figure 4 A process for determining cardiac parameters indicative of cardiac function according to certain embodiments is shown;

[0042] Figure 5 A process for calculating an indicator of cardiac function according to certain embodiments is shown;

[0043] Figure 6 shows a process for determining LVEDP from measured motor parameter signals and sensor signals using various gating processes according to certain embodiments;

[0044] Figure 7 The process of applying the gating algorithm to determine the LVEDP is shown;

[0045] Figure 8 Graphs showing aortic pressure, left ventricular pressure, and motor current over time;

[0046] Fig. 9 A process for applying a gating algorithm based on ECG data to determine LVEDP is shown;

[0047] Fig.10A diagram showing the measured and algorithmically calculated LVEDP changes over time;

[0048] Fig.11 shows a diagram of LVEDP calculated from patient data illustrating the accuracy of the LVEDP determined using the gating method;

[0049] Fig.12 shows a graph of head pressure versus motor current based on data from a porcine animal model;

[0050] Fig.13 shows a graph of head pressure versus motor current from a porcine model using a spline curve fit to the area of ​​the hysteresis loop;

[0051] Fig.14 shows a graph of pressure head versus hysteresis parameter after applying a hysteresis gate to segment data collected from a porcine animal model;

[0052] Fig.15 A diagram showing the variation of the pressure head with the motor hysteresis parameter;

[0053] Fig.16 A graph showing the change in head pressure with motor current before and after administration of beta-blocker in a porcine animal model;

[0054] Fig.17 A smooth curve showing a graph of head pressure versus motor current;

[0055] Fig.18A shows a graph of head pressure versus motor current before and during the transition to myocardial infarction;

[0056] Fig.18B Graphs showing changes in heart power index and motor current with samples measured over time before and during myocardial infarction;

[0057] Fig.19 A graph showing a series of simulated loop data with different contractility under constant load;

[0058] Fig. 20A An exemplary user interface for a heart pump controller displaying measurements over time is shown;

[0059] Fig. 20B shows an exemplary user interface for a heart pump controller according to some embodiments; and

[0060] Fig.21A process for detecting aspiration in an intravascular heart pump and determining the cause of the aspiration is shown in accordance with certain embodiments. DETAILED DESCRIPTION

[0061] In order to provide a comprehensive understanding of the systems, methods, and devices described herein, certain illustrative embodiments will be described. Although the embodiments and features described herein are specifically described for use in conjunction with a percutaneous heart pump system, it will be understood that all of the components and other features outlined below may be combined with one another in any suitable manner and may be adapted and applied to other types of cardiac therapies and cardiac assist devices, including cardiac assist devices implanted using surgical incisions, and the like.

[0062] The systems, devices and methods described herein enable a support device that resides completely or partially in an organ to assess the function of the organ. In particular, these systems, devices and methods enable a cardiac assist device such as a percutaneous ventricular assist device to be used to assess the function of the heart. For example, the cardiac state can be measured or monitored by tracking the electromechanical controller values ​​of a ventricular assist device located in the patient's heart. Because the device maintains a constant rotor speed in response to pressure changes in the heart chamber by changing the motor current, motor parameters and pressures, such as motor current and aortic pressure, are continuously measured, providing a continuous, real-time and accurate determination of cardiac function such as left ventricular pressure. Using a cardiac assist device to assess the function of the heart can warn health professionals of changes in cardiac function and allow the degree of support / level provided by the assist device (i.e., the flow rate of blood pumped by the device) to be adapted to the needs of a particular patient. For example, the degree of support can be increased when the patient's cardiac function deteriorates, or the degree of support can be reduced when the patient's cardiac function recovers and returns to the baseline of normal cardiac function. This can allow the device to dynamically respond to changes in cardiac function to promote cardiac recovery, and can allow patients to gradually wean themselves from treatment. Additionally, assessment of cardiac function may also indicate when it is appropriate to terminate use of a cardiac assist device. Although some embodiments presented herein relate to a cardiac assist device that is implanted across the aortic valve and resides partially in the left ventricle, these concepts may be applied to devices in the heart, cardiovascular system, or other areas of the body.

[0063] In addition, the heart assist device of the present invention can continuously or nearly continuously monitor and evaluate heart function while the device is in the patient. This can be advantageous compared to methods that can only estimate heart function at specific time intervals. For example, continuous monitoring can allow for more rapid detection of heart deterioration. Additionally, if the heart assist device is already in the patient, heart function can be measured without the need to introduce an additional catheter into the patient.

[0064] The assessment of cardiac function by the heart assist device proposed herein is achieved at least in part by the minimally invasive nature of the heart assist device. Unlike some invasive heart assist devices that shunt blood out of the heart, the heart assist device proposed herein resides in the heart and works in parallel with the natural ventricular function. This allows the heart assist device proposed herein to be sensitive enough to detect natural ventricular function, which is different from some more invasive devices. Therefore, these systems, devices and methods enable the heart assist device to be used not only as a support device, but also as a diagnostic and predictive tool. The heart assist device can basically be used as an active catheter, which extracts information about cardiac function by being hydraulically coupled to the heart. In some embodiments, the heart assist device operates at a constant level (e.g., a constant rotational speed of the rotor) while measuring the power delivered to the assist device. In certain embodiments, the speed of the rotor of the heart assist device can be varied (e.g., as a delta function, a step or a ramp function) to further detect natural heart function.

[0065] Cardiac function parameters indicative of native heart function may be determined from measurements of intravascular and / or ventricular pressure and pump parameters / signals ("parameters" may represent signals and / or operating states of a heart pump). For example, cardiac parameters may be determined from aortic pressure and pump motor current. A model of a combined heart and heart pump system may be used to make this determination. In one method of cardiac function determination, the model includes accessing a predetermined curve. The model may be a lookup table or a predetermined / normalized pump performance curve or calibration curve or any other suitable model. The lookup table may include a set of curves showing the power required to maintain rotational speed, and the pressure head is determined based on the pump flow, and a set of curves related to the pressure head and the flow characteristics of the heart are also determined. For example, the lookup table may indicate that a specific aortic pressure and motor current correspond to a specific left ventricular end-diastolic pressure (LVEDP). In another method of cardiac function determination, the performance of the pump is represented by showing the pressure head as a function of the motor current consumption of the pump, which serves as a surrogate for the power or load on the pump. The relationship between the motor current consumption and the pressure head during the cardiac cycle describes a hysteresis curve or loop. Heart state and function, including LVP and LVEDP, can be extracted from the relationship between motor current consumption and pressure head. In addition to or in addition to LVEDP, cardiac function can be quantified in several different ways using the heart assist device proposed herein. For example, cardiac function can be expressed as contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, LVEDP, preload state, afterload state, heart rate and / or cardiac recovery.

[0066] To accurately determine these cardiac parameters, the lag between the pressure measurement (e.g., the difference between the aortic pressure and the left ventricular pressure, or the aortic pressure alone) and the motor current measurement can be taken into account. This lag can be accounted for by detecting the phase of the cardiac cycle corresponding to a given pair of pressure and current measurements. This can be done using at least two methods that distinguish diastolic filling from other phases of the cardiac cycle. Both methods identify key points that indicate the beginning and end of diastolic filling. The first method uses the aortic pressure waveform and identifies key features in the curve, such as the dicrotic notch, etc., to indicate the beginning of diastolic filling. The method can also use the beginning of aortic filling to indicate the end of diastolic ventricular filling. The second method uses ECG data timed with pressure tracking to identify two key features that demarcate diastolic filling. These features are preferably the beginning of the QRS complex wave and the end of the T wave. If there is noise in the signal, the peak of the QRS complex wave (R wave) and the peak of the T wave can be more reliably detected. Furthermore, in some embodiments, the lag between the pressure and motor parameter measurements can itself be used to determine the phase of the cardiac cycle.

[0067] The systems, devices, and methods proposed herein also take into account changes in heart rate. If not considered, changes in heart rate may affect the resolution of the waveform and, therefore, the accuracy of cardiac parameter estimation. For example, a higher heart rate at a given sampling frequency results in fewer samples per cardiac cycle. The number of samples per cardiac cycle is crucial for capturing key features such as dicrotic notches for explaining hysteresis and key points in pressure waveforms such as LVEDP. If the number of samples is too low, these features may be missed because the number of samples in the area of ​​interest is reduced. However, in some embodiments, by performing waveform analysis cycle by cycle instead of during a fixed time period, sensitivity to heart rate can be reduced or eliminated. For example, in some embodiments, calculations are performed within 10-30 seconds and averaged to reduce the impact of artifacts. For certain indicators such as LVEDP, such averaging is possible because they do not have very high beat-to-beat variability at least in short time periods (e.g., ~1 minute). Using multiple cycles allows the number of samples in the area of ​​interest to be independent of heart rate. In addition, aggregating multiple measurements can improve the resolution of the phase of the cardiac cycle. Moreover, the effect of undersampling can be further offset by increasing the sampling period.

[0068] The systems, devices, and methods presented herein also detect suction events that occur when the pump inlet is completely or partially occluded. Conventional suction detection systems are not sensitive enough to detect minor suction events. In contrast, the systems, devices, and methods presented herein can detect minor suctions, as well as when suction occurs during the cardiac cycle. These determinations can be based on the hysteresis of the motor current-aortic pressure curve. This improved method can detect suction more quickly and provide the user with information on how to prevent or reduce persistent or worsening suction. In addition, in some embodiments, these systems, methods, and devices can predict suction events by detecting adverse cardiac cycle flow states that may lead to suction events.

[0069] Figure 1 An exemplary prior art heart assist device is shown positioned in a heart 102. The heart 102 includes a left ventricle 103, an aorta 104, and an aortic valve 105. An intravascular heart pump system includes a catheter 106, a motor 108, a pump outlet 110, a cannula 111, a pump inlet 114, and a pressure sensor 112. The motor 108 is coupled to the catheter 106 at its proximal end and to the cannula 111 at its distal end. The motor 108 also drives a rotor (not visible in the figure) that rotates to pump blood from the pump inlet 114 through the cannula 111 to the pump outlet 110. The cannula 111 is positioned across the aortic valve 105 so that the pump inlet 114 is located within the left ventricle 103 and the pump outlet 110 is located within the aorta 104. This configuration allows the intravascular heart pump system 100 to pump blood from the left ventricle 103 into the aorta 104 to support cardiac output.

[0070] The intravascular heart pump system 100 pumps blood from the left ventricle into the aorta in parallel with the natural cardiac output of the heart 102. Blood flow through a healthy heart averages about 5 liters / minute, and blood flow through the intravascular heart pump system 100 can be a similar or different flow rate. For example, the flow rate through the intravascular heart pump system 100 can be 0.5 liters / minute, 1 liter / minute, 1.5 liters / minute, 2 liters / minute, 2.5 liters / minute, 3 liters / minute, 3.5 liters / minute, 4 liters / minute, 4.5 liters / minute, 5 liters / minute, greater than 5 liters / minute, or any other suitable flow rate.

[0071] The motor 108 of the intravascular heart pump system 100 can be varied in a variety of ways. For example, the motor 108 can be an electric motor. The rotor 108 can be operated at a constant rotational speed to pump blood from the left ventricle 103 to the aorta 104. Operating the motor 108 to maintain a constant rotor speed generally requires supplying different amounts of current to the motor 108 because the load on the motor 108 changes during different phases of the cardiac cycle of the heart 102. For example, when the mass flow rate of blood entering the aorta 104 increases (e.g., during systole), the current required to operate the motor 108 increases. Therefore, this change in motor current can be used to help characterize cardiac function, as will be further discussed with respect to the following figures. The motor current can be measured, or alternatively, the magnetic field current can be measured. The use of the motor current to detect the mass flow rate can be facilitated by the position of the motor 108, which is aligned with the natural direction of blood flow from the left ventricle 103 into the aorta 104. Using the motor current to sense the mass flow rate may also be facilitated by the small size and / or low torque of the motor 108 . Figure 1 The motor 108 has a diameter of approximately 4 mm, but any suitable motor diameter may be used as long as the rotor-motor mass is small enough to be affected by the inertia of the pulsating blood. The rotor-motor mass can be affected by the pulsating mass flow of blood to produce a discernible and characterizable effect on the motor parameters. In some embodiments, the diameter of the motor 108 is less than 4 mm.

[0072] In some embodiments, one or more motor parameters other than current are measured, such as the power delivered to the motor 108, the speed of the motor 108, or the electromagnetic field, etc. In some embodiments, Figure 1 The motor 108 in the patient is operated at a constant speed. In some embodiments, the motor 108 can be outside the patient's body and can drive the rotor through an elongated mechanical transmission element, such as a flexible drive shaft, a drive cable, or a fluid coupling.

[0073] The pressure sensor 112 of the intravascular heart pump system 100 can be an integrated component (as opposed to a separate diagnostic catheter) and can be configured to detect pressure at various locations of the system 100, such as a location adjacent to the proximal end of the motor 108, etc. In some embodiments, the pressure sensor 112 of the intravascular heart pump system 100 can be disposed on the cannula 111, on the catheter 106, on a portion of the system 100 outside the patient's body, or at any other suitable location. When the intravascular heart pump system 100 is properly positioned in the heart 102, the pressure sensor 112 can detect the blood pressure in the aorta 104, or for a right heart support device, can detect the pressure in the inferior vena cava (IVC) or the pulmonary artery. The blood pressure information can be used to properly place the intravascular heart pump system 100 in the heart 102. For example, the pressure sensor 112 can be used to detect whether the pump outlet has passed through the aortic valve 105 into the left ventricle 103, which will only circulate blood within the left ventricle 103, rather than delivering blood from the left ventricle 103 to the aorta 104. Figure 1 The pressure sensor in the embodiment detects the absolute pressure at a certain point in the patient's vasculature, such as in the aorta. In other embodiments, the pressure sensor detects the absolute pressure in the pulmonary artery or venous system. In other embodiments, the pressure sensor detects the pressure head or delta pressure in the system, which can be equal to the aortic pressure minus the left ventricular pressure.

[0074] In addition to assisting in the placement of the intravascular heart pump system 100, one or more algorithms may be applied to the data obtained by the pressure sensor 112 in order to detect the cardiac phase of the heart 102. For example, the data obtained by the pressure sensor 112 may be analyzed to detect the dicrotic notch, which indicates the onset of diastolic filling. The dicrotic notch is a small downward deflection in the arterial pulse or pressure contour immediately after the closure of the semilunar valves. This feature may be used as a marker for the end of systole or the ejection phase. Because the measured head pressure typically contains more noise features than the measured motor current, the motor current may be used to "gate" time periods in which the dicrotic notch may be identified, and then the corresponding time periods of the measured head pressure may be identified and analyzed. Other features may also be detected as an indication of LVEDP, such as changes in motor speed, the presence of R peaks in the ECG data, or changes in the curvature or local slope of a parameter over time.

[0075] The intravascular heart pump system 100 can be inserted into the heart 102 in various ways, such as by percutaneous insertion, etc. For example, the intravascular heart pump system can be inserted through the femoral artery (not shown), through the axillary artery (not shown), through the aorta 104, across the aortic valve 105 and into the left ventricle 103. In some embodiments, the intravascular heart pump system 100 is inserted into the heart 102 by surgery. In some embodiments, the intravascular heart pump system 100 or a similar system suitable for the right heart is inserted into the right heart. For example, a right heart pump similar to the intravascular heart pump system 100 can be inserted through the inferior vena cava, bypassing the right atrium and right ventricle, and extending into the pulmonary artery. In some embodiments, the intravascular heart pump system 100 can be positioned for operation in a vascular system outside the heart 102 (e.g., in the aorta 104). By minimally invasively residing in the vascular system, the intravascular heart pump system 100 is sensitive enough to allow characterization of native heart function. Additionally, surgically implanted devices such as the LVAD described below will be sensitive to changes in native heart function, but the intravascular heart pump 100 is not as sensitive.

[0076] Figure 2 An exemplary prior art heart assist device 201 is shown located outside of a heart 202. The heart 202 includes a left ventricle 203 and an aorta 204. The heart assist device 201 includes a motor 208, an inflow conduit 207, an outflow conduit 209, a first sensor 212a, a second sensor 212b, a third sensor 212c, and a catheter 206. The inflow conduit 207 is coupled to a first side of the motor 208 at a first end 213 and to the apex of the left ventricle 203 at a second end 215. The outflow conduit 209 is coupled to a second side of the motor 208 at a first end 217 and to the ascending aorta 204 at a second end 219. The motor 208 also drives a rotor (not visible in the figure) that rotates to pump blood from the apex of the left ventricle 203 through the inflow conduit 207 into the outflow conduit 209 and discharge the blood into the aorta 204. Heart assist device 201 is configured to pump blood from left ventricle 203 to ascending aorta 204 to support cardiac output.

[0077] Heart assist device 201 pumps blood from left ventricle 203 into aorta 204, bypassing the aortic valve (not visible) and delivering blood through inflow conduit 207 and outflow conduit 209 around heart 202 rather than within heart 202. Figure 1Blood flow through the heart assist device 201 can deliver a similar or greater flow rate than the flow rate of the prior art intravascular heart pump system 100. The heart assist device 201 can be surgically implanted in the patient such that the second end 219 of the outflow conduit 209 and the second end 215 of the inflow conduit 207 are surgically implanted into the heart 202 at the ascending aorta 204 and the left ventricle 203, respectively. The motor 208 can be connected to a console (not shown) located outside the patient's body through the catheter 206 via a drive line (not shown). The rotor (not shown) can be operated at a constant or substantially constant speed. The power supplied to the motor 208 can be monitored at the console to determine the flow rate of the pump or other characteristics of the pump performance.

[0078] The first sensor 212a, the second sensor 212b, and the third sensor 212c may be similar to Figure 1 The pressure sensor 112 in the heart assist device 201. The sensors 212a-c can be pressure sensors for determining the blood pressure in the aorta 204 or the blood pressure in the left ventricle 203, or can be positioned to determine the blood pressure and blood flow through the inflow conduit 207 and the outflow conduit 209. The blood pressure in the aorta 204 or the left ventricle 203 can be displayed to the user and / or can be used to determine the operating parameters of the heart assist device 201. The blood flow or pressure within the inflow conduit 207 and the outflow conduit 209 can also be displayed to the user and used to monitor the heart assist device 201. The first sensor 212a can also be a sensor of the power of the pump motor 208 that can be used to determine the pump flow through the heart assist device 201.

[0079] Figure 3 An illustrative heart pump system 300 is shown that is configured to estimate a heart parameter indicative of heart function in accordance with some embodiments. The heart pump system 300 may be used with Figure 1 Intravascular heart pump system 100 or Figure 2 The heart pump system 300 may be similar or identical to the heart assist system 201 of the present invention. The heart pump system 300 may be operated intracardiac, partially intracardiac, extracardiac, partially extracardiac, partially extravascular, or at any other suitable location in the patient's vascular system. The heart pump system 300 includes a heart pump 302 and a control system 304. All or part of the control system 304 may be in a controller unit separate / remote from the heart pump 302. In some embodiments, the control system 304 is internal to the heart pump 302. The control system 304 and the heart pump 302 are not shown to scale.

[0080] Heart pump 302 may include catheter 306, motor 308, rotor 310, and pressure sensor 312. Motor 308 may be coupled to a distal region of catheter 306, and as previously mentioned, may alternatively be located outside the patient's body and may be in communication with motor 308 via a drive shaft, drive cable, or fluid connection. Motor 308 is also coupled to rotor 310 such that operation of motor 308 causes rotor 310 to rotate and pump blood. Pressure sensor 312 may be positioned along the catheter at a plurality of locations inserted into the patient's cardiovascular system such that pressure sensor 312 may detect blood pressure when heart pump 302 is inserted into the patient's vascular system. Where heart pump 302 is, for example, Figure 1 In an embodiment of the intravascular heart pump 302 of the intravascular heart pump system 100, the heart pump 302 can be delivered to the left ventricle, and when the intravascular heart pump 302 is appropriately positioned in the left ventricle, the pressure sensor 312 can sense the aortic pressure. In some embodiments, the pressure sensor 312 is located in a chamber or vessel separated from the chamber of interest by a valve. For example, when the rotor 310 is located in the aorta, the pressure sensor 312 can be located in the aorta, or the pressure sensor 312 can be located in the inferior vena cava or superior vena cava together with the rotor 310, and the outlet of the pump is in the pulmonary artery. In some embodiments, the heart system is configured so that when the inlet of the pump is placed in the left ventricle, the rotor 310 is located in the aorta.

[0081] The control system 304 may include a controller 322, a current sensor 314, and a cardiac parameter estimator 316. The controller 322 supplies current to the motor 308 via an electrical connection 326, such as through one or more wires. The current supplied to the motor 308 via the electrical connection 326 is measured by the current sensor 314. The load experienced by the motor 308 of the mechanical pump is the pressure head, or the difference between the aortic and left ventricular pressures. The heart pump 302 experiences a nominal load during steady-state operation at a given pressure head, and changes from this nominal load are the result of changes in external load conditions, such as the dynamics of left ventricular contraction. Changes to dynamic load conditions change the motor current required to operate the rotor 310 at a constant or substantially constant speed. The motor can be operated at the speed required to maintain the rotor 310 at a set speed. As a result, the motor current drawn by the motor to maintain the rotor speed can be monitored and used to understand the underlying cardiac state. By simultaneously monitoring head pressure relative to motor current using pressure sensor 312 during the cardiac cycle, the cardiac state can be quantified and understood even more accurately to generate a hysteresis loop of quantitative pump performance that can be visually assessed to determine changes in cardiac state and function. A cardiac parameter estimator 316 receives a current signal from current sensor 314 and a pressure signal from pressure sensor 312. The cardiac parameter estimator 316 uses these current and pressure signals to characterize the function of the heart. The cardiac parameter estimator 316 can access a stored lookup table to obtain additional information to characterize the function of the heart based on the pressure and current signals. For example, the cardiac parameter estimator 316 can receive aortic pressure from pressure sensor 312, and using a lookup table, the aortic pressure can be used to determine delta pressure.

[0082] The controller 322 may store the current signal from the current sensor 314 and the pressure signal from the pressure sensor 312 in a database in a memory or server (not shown). The database and memory may be external to the controller 322 or contained within the controller 322. The controller 322 may store the signals as an array in a database with specific associated addresses and may also record time with the signals. The controller 322 may also store determined cardiac parameters such as LVEDP in the memory for comparison with previously stored cardiac parameters. The controller 322 accesses the hysteresis curve by accessing the address of the database in the memory. Based on the address, the controller 322 selects a first array in which a plurality of data points corresponding to motor parameters measured over time are stored. The controller 322 also selects a second array in which a plurality of data points corresponding to pressure or other physiological parameters measured over time are stored. The controller 322 associates a first data point corresponding to a motor parameter at each time point at which a measurement is made with a second data point corresponding to a physiological parameter. The controller 322 may then display the matching data points to the user as a hysteresis curve on a screen or other display. Alternatively, the controller 322 may iterate through the matching data points to calculate the cardiac parameters.

[0083] The cardiac parameter estimator 316 can characterize cardiac function and determine cardiac parameters according to two different methods. In the first method, the cardiac parameter estimator 316 uses a predetermined pressure-current curve to extract information about cardiac function and cardiac parameters. Using this method, the cardiac parameter estimator 316 compares the power required to maintain the rotational speed of the pump rotor 310 and the pressure head defined as the pressure gradient across the pump to a predetermined performance curve showing power and pressure head as a function of pump flow, and to a predetermined system curve (a predetermined pressure-current curve) that relates pressure head and motor current. Using the performance and system curves, the cardiac parameter estimator 316 characterizes the pump behavior in order to extract information about cardiac parameters and cardiac function.

[0084] In a second approach, the cardiac parameter estimator 316 uses a best fit algorithm to determine cardiac parameters that are related to cardiac function. The cardiac parameter estimator 316 accesses a modified representation of pump performance by varying the head according to the motor current draw. The motor current draw serves as a proxy for the power or load on the pump. The load on the pump at a given rotor RPM is determined by the fluid motor torque described by the equation τ = H · d, where the torque τ is determined by the head H and the volumetric displacement per revolution d. The torque is directly related to the power requirement of the pump by the equation:

[0085]

[0086] Among them, the electric power requirement (P electrical ) is the product of voltage (V) and current (I), and is related to pump torque (τ), rotational speed (ω), and combined electrical and mechanical efficiency (η). Because motor speed and efficiency are relatively constant and known, fluid motor torque can be determined from the electrical power of the pump. The relationship between power and motor current may vary depending on the design of the pump, but motor current is an operationally measured value for most pumps. Motor current is generally directly related to torque, and therefore, to the load on the pump.

[0087] Head pressure is the load felt by a mechanical pump, and head pressure is the difference between aortic and left ventricular pressures, which varies throughout the cardiac cycle as external blood flow generated by cardiac contraction increases. Pump operation in the pulsating environment of the heart alternates between steady-state ventricular filling and ventricular ejection. The motor current required to produce a specific RPM of the rotor depends on both head pressure and the state of the heart, and this results in a hysteresis loop as the motor undergoes active cardiac contraction followed by ventricular filling during relaxation. The resulting motor current hysteresis is a complete representation of the mechanical pump performance curve because it integrates the effects of external flow and pressure changes.

[0088] Traditionally, methods for measuring LVEDP are indirect and discontinuous. A common method for measuring LVEDP is by using a Swan-Ganz catheter, where LVEDP is inferred through the catheter by wedging an inflated balloon into the pulmonary artery and using the pulmonary vascular system and the left atrium as a fluid column to obtain the pressure in the left ventricle during diastole. The measurement is indirect and often includes significant measurement errors, noise, and lacks reliability. In addition, because the balloon in the pulmonary artery cannot remain inflated, the measurement is discontinuous. An alternative method for measuring LVEDP historically is to use a pressure sensor catheter inserted into the left ventricle of the heart. This captures the entire pulsatile pressure waveform through several cardiac cycles; but the catheter cannot be left in the patient's body or at the bedside for a long time. Other methods for non-invasively predicting LVEDP have been developed using Doppler echocardiography or ultrasound. Unfortunately, they are also prone to the same problems and cannot provide continuous pressure estimates over a long period of time.

[0089] For a specific rotor speed, LVEDP can be determined from the motor current consumed and the pressure head. Assuming that the motor current changes corresponding to slight motor speed changes at the end of diastole are linear, these changes can be corrected by linear scaling according to the following equation:

[0090]

[0091] Where, the speed-corrected motor current (i c) is equal to the measured motor current (i m ) multiplied by the ratio of the desired fixed motor speed (ω0) and the actual motor speed (ω). This is a safe assumption since the motor speed variation is minimal (±0.5%). For example, the relationship between motor current and pressure head can be characterized by fitting an equation to the data. The speed-corrected motor current (i c ), and subsequently, this relationship can be fitted to a higher order polynomial, for example by using R 2 Optimize to produce a fourth-order polynomial with head as a function of motor current. Alternatively, any best fit algorithm can be applied to the plot of the measured head and motor current to estimate the hysteresis loop. For example, the plot of the parameters can be fitted to an ellipse or an angled or truncated ellipse to estimate the shape of the hysteresis loop. Then, the equation determined by the best fit algorithm can be used to extract information about cardiac function, for example, LVP can be extracted from the inflection point of the hysteresis curve, and the phases of filling, relaxation and ejection can be identified. Other parameters can be determined by points on the hysteresis loop, the size or shape of the hysteresis loop, changes in the size and shape of the hysteresis loop, local slope changes, curvature changes, or areas within the hysteresis loop. In addition, the fitted coefficients can then be used to predict the LVEDP for a given corrected motor current at a given motor RPM setting. These parameters enable healthcare professionals to better understand the patient's current cardiac function and provide appropriate cardiac support.

[0092] Other cardiac parameters indicative of cardiac function may also be determined by the cardiac parameter estimator 318 based on comparison of measured values ​​to a lookup table or the shape and value of a hysteresis loop formed by motor parameters and pressure measured during the cardiac cycle. For example, changes in contractility may be related to changes in pressure slope (dP / dt) during cardiac contraction. Cardiac output is determined based on the flow rate of blood through and through the pump. Stroke volume is an index of left ventricular function and has the formula SV= CO / HR, where SV is stroke volume, CO is cardiac output, and HR is heart rate. Stroke work is the work done by the ventricle to eject a certain amount of blood and can be calculated from stroke volume according to the equation SW = SV * MAP, where SW is stroke work, SV is stroke volume, and MAP is mean arterial pressure. Cardiac work is calculated by multiplying the stroke work and heart rate. Cardiac power output is a measure of cardiac function calculated in watts using the equation CPO = mAoP * CO / 451, where CPO is cardiac power output, mAoP is mean aortic pressure, CO is cardiac output, and 451 is a constant used to convert mmHG x L / min to watts. Ejection fraction can be calculated by dividing the stroke volume by the amount of blood in the ventricle. Other parameters, such as chamber pressure, preload state, afterload state, cardiac recovery, flow load state, variable volume load state, and / or cardiac cycle flow state, etc., can be calculated from these values ​​or determined by examining the hysteresis loop.

[0093] An active catheter mounted heart pump within the left ventricle provides access to direct and continuous LVEDP measurement during the most critical time, which is when the device will be in use. This diagnostic measurement can be obtained by utilizing parameters from the device without additional intervention. In addition, the device can obtain diagnostic indicators that combine more than a single point in the cardiac cycle. Although useful, LVEDP only maintains a single time point throughout the cardiac cycle. A more comprehensive indicator that includes information from the entire cardiac cycle can give more information about the state of the heart and be more representative of the actual state of the heart.

[0094] A predetermined pressure-current curve can be measured using a simulated circulatory loop, animal data, or clinical data. For example, a simulated circulatory loop (MCL) with different contraction, preload, and afterload conditions can be used to define the limits of pump performance, while animal models can be used to characterize biological variability and pathology. The use of the MCL for characterization and the animal model for validation is an effective means of correlating the performance of the heart pump 302 with cardiac function. Although the baseline motor current may vary between pumps, the current measurements from each pump can be normalized to generate a normalized current waveform. In some embodiments, the heart pumps are individually binned based on their current response within a range of 30 mA to normalize the calculation of the approximate flow rate.

[0095] By accounting for hysteresis effects in the pressure-current curves, cardiac phase information can significantly improve the accuracy of the cardiac parameter estimator 316. As will be discussed further below, the pressure-current curves may exhibit hysteresis due to the phase of the cardiac cycle. Therefore, in order to accurately compare pressure and current data points, the phase of the heart must be considered. Otherwise, pressure and current data collected during systole may be compared to non-similar reference pressure and current data collected during diastole, for example, which may skew the estimate of the cardiac parameters.

[0096] When the heart pump 302 is implanted in the heart, the estimation of the heart parameters by the heart parameter estimator 316 can be continuous or nearly continuous. This can be advantageous over conventional catheter-based methods that only allow sampling of heart function at specific times. For example, continuous monitoring can allow for more rapid detection of heart deterioration. Additionally, if a heart assist device is already in the patient, heart function can be measured without the need to introduce an additional catheter into the patient.

[0097] After the cardiac parameters are estimated by the cardiac parameter estimator 316, the cardiac parameters are output to the controller 322. The controller 322 in turn provides a control signal for driving the motor 308. In some embodiments, the controller 322 operates the motor 308 at a fixed set point. The set point may be a fixed rotational speed or flow rate. For example, the controller may provide a varying voltage to maintain a constant rotational speed of the rotor 310 through the motor 308, regardless of the preload and / or afterload. The controller 322 may also allow the user to change the rotational speed of the rotor 310, and in some embodiments, the user to change the speed of the motor 308. For example, the user may select a new set point (e.g., by setting a new desired flow rate or rotational speed), or may select a time-varying input signal (e.g., a delta function, a step function, a ramp function, or a sine curve). In some embodiments, the fixed set point may be the amount of power delivered to the motor 308. In certain embodiments, the cardiac parameters estimated by the cardiac parameter estimator 316 are displayed to the physician, and the physician manually adjusts the set point of the motor at the controller 322.

[0098] The controller 322 may adjust the set points sent to the controller 322 based on the cardiac parameters estimated by the cardiac parameter estimator 316. For example, the degree / level of support (i.e., the speed of the rotors and therefore the volume flow rate of blood delivered by the device) may be increased as cardiac function deteriorates, or may be decreased as cardiac function recovers. This may allow the device to dynamically respond to changes in cardiac function to promote cardiac recovery and gradually wean the patient off therapy.

[0099] Figure 4 A process 400 for determining cardiac parameters indicative of cardiac function is shown. The process 400 may be used Figure 1 Intravascular heart pump system 100, Figure 2 Heart assist devices 201, Figure 3 The heart pump system 300 or any other suitable heart pump is performed. In step 402, the motor of the heart pump is operated. The motor can be operated at a rotational speed required to maintain a constant or substantially constant rotational speed of the rotor. In step 404, the current delivered to the motor is measured and the motor speed is measured. The current can be measured using a current sensor (e.g., current sensor 314) or by any other suitable means. In step 406, the aortic pressure is measured. The aortic pressure can be measured by a pressure sensor coupled to the heart pump, by a separate catheter, by a non-invasive pressure sensor, or by any other suitable sensor. The pressure sensor can be an optical pressure sensor, an electric pressure sensor, a MEMS sensor, or any other suitable pressure sensor. In some embodiments, in addition to or as an alternative to measuring the aortic pressure, the ventricular pressure is measured.

[0100] In some embodiments, additional steps may be performed after measuring the current delivered to the motor and the aortic pressure. For example, in some embodiments, the aortic pressure may be scaled by a factor determined from a lookup table to find the pressure differential over time. In some embodiments, the measured current and pressure data are smoothed to provide a less noisy signal.

[0101] In step 408, a segment of the hysteresis loop formed by the measured current delivered to the motor and the measured aortic pressure is determined, which corresponds to a certain phase of the heart. The segmentation and phase estimation can act as a filter for the pressure and current signals because it can allow the pressure and current signals to be compared with the pressure and current signals occurring during the corresponding phase of the cardiac cycle. The segmentation and phase estimation can be based on the pressure information received in step 406, and can involve locating a reference point in the pressure information indicating the phase of the heart. In some embodiments, a dicrotic notch in the pressure signal is detected to indicate the beginning of diastolic filling. The dicrotic notch is a small downward deflection in the arterial pulse or isobar immediately after the closure of the semilunar valves. The dicrotic notch can be used as a marker for the end of the cardiac systolic period, and therefore, approximately the beginning of the cardiac diastolic period.

[0102] In some embodiments, the segmentation or phase estimation is based entirely or partially on ECG data. The ECG data can be timed using pressure tracking. The features in the ECG used to estimate the cardiac phase can be the beginning of the QRS complex and the end of the T wave. If there is noise in the ECG signal, it may be more reliable to detect the peak of the QRS complex (e.g., R wave) and the peak of the T wave. The R peak of the QRS waveform can also be used to identify the timing of various parameters, such as the time period of the LVEDP to be found, because the R peak corresponds to the end cycle of the diastolic period. In the phase estimation method using a pressure signal or an ECG signal, the offset with the detected features can be used to more accurately identify the filling phase, because the actual filling occurs slightly before or after these identified landmarks. The combination of the two methods based on the pressure signal and based on the ECG can allow for more reliable identification of the cardiac phase. The weight between the two methods can be optimized using a data set with known filling time parameters, known left ventricular pressure, and a high signal-to-noise ratio.

[0103] In addition to ECG data, segmentation and cardiac phase estimates may also be based in whole or in part on motor parameters or motor speed, aortic pressure slope, respiratory changes, or any other suitable physiological or device parameters. In some embodiments, segmentation and cardiac phase estimates are determined based on any single one of these parameters or based on a combination of any number of parameters therein.

[0104] In step 410, the hysteresis loop is described mathematically, and the LVEDP is determined based on the mathematical description. The hysteresis loop can be characterized by fitting an equation to the data, such that the loop is described by a polynomial function based on the Euler equations describing an ellipse, for example, and the ellipse fit can be used to calculate the LVEDP. In addition, mathematical fitting of the hysteresis loop also enables comparison of the size, shape, and area of ​​the loop or segments of the loop over time, as well as analysis of changes in local slope or curvature of segments of the loop to measure changes in cardiac parameters.

[0105] In some embodiments, a lookup table is referenced to determine cardiac parameters indicative of cardiac function based on motor parameters, pressure, and cardiac phase. In some embodiments, the table may embody a predetermined pressure-current curve.

[0106] At step 412, cardiac parameters are calculated. Determining cardiac parameters may involve determining points on the hysteresis loop based on mathematical fitting, integrating the area of ​​a segment of the hysteresis loop, or mapping the measured current and pressure to cardiac parameters using a lookup table. The segments of the hysteresis loop may be segmented based on Euler equation ellipse fitting and bilateral lines, such as segmenting about Fig.13 As further described, the ellipse is made up of a plurality of segments, each of which has at least one straight side. The segments may be translated and rotated before integration by the Riemann sum.

[0107] The cardiac phase information extracted from the hysteresis loop can be binary (e.g., diastole or systole) or more granular (e.g., systole, diastolic relaxation, and diastolic filling). The cardiac phase can be one of cardiac ejection, diastolic filling, and diastolic relaxation. The determined cardiac parameters can be contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular end-diastolic pressure (LVEDP), preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, cardiac cycle volume load state, and / or cardiac cycle flow state. Left ventricular end-diastolic pressure (LVEDP) is a single-point measurement that physicians often use to assess cardiac health. In many cases of heart failure, LVEDP is significantly elevated, indicating ventricular overload. This is primarily due to a shift in the Frank-Starling relationship caused by changes in the end-diastolic pressure-to-volume ratio (EDPVR). As a patient gets closer to heart failure, the Frank-Starling curve shifts downward so that a given pressure (preload) results in a lower stroke volume. Because of this shift, at a given cardiac output for the patient, assuming all other conditions remain relatively constant, the LVEDP can indicate the state of the heart. Measuring these changes in LVEDP can be valuable in monitoring a patient's progression toward heart failure or recovery, allowing clinicians to adjust the required treatment accordingly.

[0108] Alternatively, if a reference table is used, the lookup table can accept pressure, motor current, and cardiac phase as its inputs. A predetermined pressure-current curve can be measured using a simulated circulatory loop, animal data, or clinical data. For example, a simulated circulatory loop (MCL) with different contraction, preload, and afterload conditions can be used to define the limits of pump performance, while animal models can be used to characterize biological variability and pathology. The use of MCLs for characterization and animal models for validation is an effective means of correlating the performance of a cardiac pump with cardiac function. Although the baseline motor current may vary between pumps, each pump can be normalized to produce a normalized current waveform.

[0109] The cardiac phase information from step 408 can significantly improve the accuracy of cardiac parameter estimation by accounting for hysteresis effects in the pressure-current curves. The pressure-current curves exhibit hysteresis due to the phase of the cardiac cycle. Therefore, in order to accurately compare pressure and current data points, the phase of the heart must be considered. Otherwise, pressure and current data collected during systole may be compared to non-similar reference pressure and current data collected during diastole, for example, which may skew the estimation of cardiac parameters.

[0110] In step 414, cardiac parameters are output. When the heart pump is implanted in the heart, the output and / or determination of the cardiac parameters can be continuous or nearly continuous. This can be advantageous over conventional catheter-based methods that only allow sampling of cardiac function at specific times during the cardiac cycle or at discrete points in time. For example, continuous monitoring of cardiac parameters can allow for more rapid detection of cardiac deterioration. Continuous monitoring of cardiac parameters can show changes in cardiac condition over time, such as by outputting a continuous lag parameter associated with the phase of the heart that can show differences as cardiac condition changes. Additionally, if a cardiac assist device is already in the patient, cardiac function can be measured without the need to introduce an additional catheter into the patient. The cardiac parameters can be output using any suitable user interface or report, such as the following regarding Fig. 20A and Fig. 20B Describes the user interface.

[0111] In some embodiments, the power delivered to the motor is adjusted based on cardiac parameters. The power delivered to the motor can be adjusted automatically by a controller (e.g., controller 322) or manually (e.g., by a healthcare professional). The level of support can be increased as the patient's cardiac function deteriorates, or can be decreased as the patient's cardiac function recovers, allowing the patient to gradually wean off therapy. This can allow the device to dynamically respond to changes in cardiac function to promote cardiac recovery. It can also be used to intermittently adjust pump support and diagnose how the heart is responding, for example, diagnosing whether it can take over pumping function from a cardiac pumping device.

[0112] Figure 5 A process for calculating an indicator of cardiac function and adjusting the level of support provided by a cardiovascular assist device is shown. In step 502, a pump controller is operated. In step 504, a hysteresis parameter and a motor speed are measured. The hysteresis parameter can be a parameter of the motor of the heart pump (e.g., motor current or motor power). In step 506, a hemodynamic parameter is measured. For example, in some embodiments, aortic pressure is measured. In step 508, a lookup table of hemodynamic parameters based on hysteresis parameters is queried or referenced to determine ΔP or pressure difference. An exemplary lookup table 2011 is shown as having a column "Hysteresis Parameter" for stored hysteresis parameter values ​​and a column "ΔP" for the pressure difference between the ventricle and the aorta. In some embodiments, the table can be based on a predetermined pressure-current curve. The cardiac parameters can be determined by mapping the measured current and pressure to the cardiac parameters.

[0113] Predetermined pressure-current curves can be measured using simulated circulatory loops, animal data, or clinical data. For example, simulated circulatory loops (MCLs) with different contraction, preload, and afterload conditions can be used to define the limits of pump performance, while animal models can be used to characterize biological variability and pathology. The use of MCLs for characterization and animal models for validation is an effective means of correlating the performance of a cardiac pump with cardiac function. Although the baseline motor current may vary between pumps, each pump can be normalized to produce a normalized current waveform. In some embodiments, cardiac pumps are individually picked based on their current response within a range of 30 mA to normalize the calculation of the approximate flow rate.

[0114] At step 510, the cardiac cycle phase is determined. This determination of the cardiac cycle phase can be performed using a piecewise spline curve. Fig.13 As discussed, the segmented spline depicts the area of ​​the total hysteresis loop. The hysteresis loop can be segmented into a known number of curve fitting splines. Each spline fit to the curve of the hysteresis loop represents a cardiac cycle phase. For example, in a hysteresis loop fit with three splines, the first spline can indicate the diastolic relaxation phase, the second spline can indicate the diastolic filling, and the third spline can indicate the cardiac systolic phase. In this case, the meeting point of the second spline and the third spline is the LVEDP. Phase estimation can act as a filter for pressure and current signals because it can allow the pressure and current signals to be compared with the pressure and current signals occurring during the corresponding phase of the cardiac cycle. Phase estimation can be based on the pressure information received in step 2006 and can involve locating a reference point in the pressure information indicating the cardiac phase. In some embodiments, a dicrotic notch in the pressure signal is detected to indicate the beginning of diastolic filling. The dicrotic notch is a small downward deflection in the arterial pulse or isobar immediately after the closure of the semilunar valve. The dicrotic notch can be used as a marker for the end of systole and, therefore, the approximate beginning of diastole.

[0115] By accounting for hysteresis effects in the pressure-current curves, the cardiac phase information from step 510 can significantly improve the accuracy of cardiac parameter estimates. Because the pressure-current curves exhibit hysteresis due to the phase of the cardiac cycle, the phase of the heart must be considered in order to accurately compare pressure and current data points. Otherwise, pressure and current data collected during systole may be compared to non-similar reference pressure and current data collected during diastole, for example, which may skew the estimate of cardiac parameters.

[0116] In step 512, the cardiac chamber pressure is output. In some embodiments, the measured cardiac chamber pressure is the pressure of the left ventricle. In certain embodiments, the measured cardiac chamber pressure is the pressure of the right ventricle. In step 514, the coefficient of contractility is output. The contractility score provides an indication of cardiac function. More specifically, the contractility score represents the inherent strength and vigor of cardiac contraction during cardiac contraction. If the contractility of the heart is greater, the heart's stroke volume will be greater. For example, when the heart's stroke volume is approximately 65 mL, moderate contractility may occur. When the heart's stroke volume exceeds 100 mL, high contractility may occur. When the heart's stroke volume is less than 30 mL, low contractility may occur. The contractility score can be represented numerically and / or graphically. The contractility score can be dimensionless. In step 516, the coefficient of volume load is output. In step 518, additional state indicators are output.

[0117] In step 520, the cardiac chamber pressure determined in step 512 is used to determine the left ventricular end-diastolic pressure (LVEDP). This calculation can be performed by determining the left ventricular pressure from step 512 corresponding to the end of the diastolic period. In almost all cases of acute myocardial infarction, LVEDP tends to be significantly elevated, especially for patients with heart failure. This is primarily due to a shift in the Frank-Starling relationship caused by a change in the end-diastolic pressure-to-volume ratio (EDPVR). As the patient approaches heart failure, the Frank-Starling curve shifts downward so that a given pressure results in a lower stroke volume. Therefore, at a given cardiac output of the patient, assuming all other conditions remain relatively constant, the LVEDP can indicate the state of the heart. Measuring these changes in LVEDP can be valuable for monitoring a patient's progression toward heart failure or recovery, allowing clinicians to adjust the required treatment accordingly.

[0118] In step 522, the level of support provided by the assist device is assessed. In some embodiments, the assessment is automated. In certain embodiments, the assessment is performed at least in part by a healthcare professional. In some embodiments, additional information regarding hemodynamic parameters and support levels is provided to allow a clinician to adjust the support level to optimize patient outcomes. In some embodiments, the level of support provided by the cardiovascular assist device is titrated by changing the power delivered to the motor, changing the motor speed, and / or changing the flow rate, or any other suitable change that results in a change in the level of support of the cardiovascular assist device. In step 526, a patient cardiac assessment is output. The patient cardiac assessment may be displayed on a user interface, such as Fig. 20A User Interface 2000 or Fig. 20B2001 of the user interface. In some embodiments, the assessment is a report that can be sent to a healthcare professional. In some embodiments, a recommendation for a level of support to be provided to the patient's heart is output. In some embodiments, the assessment is a report that can be sent to a healthcare professional. The recommendation for the level of support can be optimized to provide hemodynamic support. The recommendation for the level of support can be based on an internal algorithm or table. The recommendation for the level of support can include guidance for achieving the recommended level of support, including changing the volumetric flow delivery provided by the pump, changing the level (size and / or frequency) of automatic pulsations based on rapid changes, and / or changing the level of pump speed (e.g., the rotational speed of the motor or the rotational speed of the rotor) in short or long bursts to provide increased flow. In some embodiments, the recommendation can be automatically repeated. Figure 5 The process 500 provides closed loop control for the cardiac assist device. By titrating the treatment according to the patient's needs, the recovery of the heart can be promoted. If the evaluation in step 526 indicates that the heart has recovered sufficiently, the treatment can be terminated or the healthcare professional can be prompted to consider terminating the treatment.

[0119] Figure 6 A process 600 for determining LVEDP from measured motor parameter signals and sensor signals is shown. LVEDP can be calculated according to one of several procedures. At step 602, motor parameters are received over a period of time. As described herein, measurements of motor parameters may include motor current, power, speed, or torque of the motor. At step 604, input signals from sensors are received over a period of time. The signals from the sensors may be any hemodynamic parameter, such as aortic pressure, etc. At step 606, a decision is made as to whether to use an internal gating method.

[0120] If the decision is no, the process 600 follows path 607 to step 608 where the received ECG input 609 is used to gate the input hemodynamic and motor parameters. The ECG input from step 609 is analyzed and a time period of the ECG data is identified in which the presence of an inflection point indicating the end cycle of diastole or an R peak in the QRS waveform indicates that the LVEDP will be found in that time period. The hemodynamic parameters measured in the corresponding time period are then analyzed to find a point corresponding to the LVEDP. At step 610, the LVEDP is calculated from the identified points using a lookup table, and the relationship between the hemodynamic and motor parameters is characterized by determining a polynomial function fit to the hemodynamic and motor parameters.

[0121] If the decision at step 606 is that internal gating is to be used, process 600 follows path 611 to either step 612 or step 620 based on the desired information from the data. Either approach may be used to determine the LVEDP, but additional cardiac parameters may also be determined by the approach starting at step 620.

[0122] At step 612, a time period of a motor parameter is identified in which there is a change in the motor parameter. The time period is considered a gating window, and the change in the motor parameter indicates a change in the cardiac phase associated with the LVEDP. In some embodiments, the change in the motor parameter can be a decrease in motor speed due to a load change, an increase in motor current due to a load change, or any other characteristic change in the motor parameter due to cardiac changes. At step 614, the identified time period or gating window is used to identify a corresponding time period of the hemodynamic parameter in which the LVEDP is found. At step 616, an LVEDP calculation input is identified in the hemodynamic parameter by analyzing the hemodynamic parameter data in the identified time period and identifying changes in the hemodynamic parameter. At step 618, the LVEDP is calculated using a lookup table and a polynomial function.

[0123] At step 620, a hysteresis loop is formed from the motor parameters and sensor inputs and a polynomial algorithm that enables approximation of missing data points. The data collected from the motor parameters and sensor inputs describes the phase of the heart in the hysteresis loop. For example, if the motor parameter is the motor current and the sensor input is the aortic pressure, the polynomial algorithm allows the pressure head to be determined from the measured motor current and the aortic pressure, so that the hysteresis loop can be generated from the measured motor current and the calculated pressure head. At step 622, an elliptical geometric fit to the hysteresis loop is generated, for example, the hysteresis loop is fitted to the ellipse using the Euler equation. At step 624, the data forming the hysteresis loop is analyzed with respect to the ellipse fit to determine the main point deviation indicating the inflection point observed at the LVEDP value. At step 626, the LVEDP point is calculated from the determined inflection point using a lookup table and a polynomial function. For example, the inflection point can be determined by analyzing the hysteresis loop formed by the motor current and the pressure head, and the LVEDP can be calculated from the pressure head data at the inflection point. This LVEDP may then be output to the user, and additional cardiac indices may be determined to aid in understanding the patient's cardiac function.

[0124] Gating algorithms as described above are applied to the hemodynamic parameter data and pump or motor parameters to determine LVEDP, cardiac cycle phase, and other parameters. In each of the above approaches to calculating LVEDP, whether the gating is internal or external, the hemodynamic parameter data points identified using the gating technique can be used with a lookup table to find a dynamic LVEDP curve, and an LVEDP value can be output that can be used in the determination of other cardiac indices. Figure 7 A process for applying a gating algorithm to determine LVEDP is shown. The depicted process shows in more detail the determination of a gating window and the application of a gating algorithm to determine LVEDP, as described with respect to Figure 6 Gating is used to determine or isolate cardiac phase and / or left ventricular pressure (eg, LVEDP). Gating can be accomplished by examining device parameters and physiological parameters to locate local minima or maxima.

[0125] The controller measures a hysteresis parameter associated with the cardiac cycle and measures a device or motor parameter. The hysteresis parameter can be any cardiac hysteresis parameter discussed herein, and the device parameter can be any device parameter that varies with time and pulse. At step 702, the controller uses the input hysteresis parameter and the device parameter to generate a gating window. The gating algorithm includes a method for identifying the mean and standard deviation of data points that are related local minima through the gated data. The local minima of the device parameters and the physiological parameters are determined independently, and the algorithm returns the corresponding local minimum data points.

[0126] At step 704, a gating algorithm is applied to identify the LVEDP. The controller inputs the local minimum data points of the device parameters and the physiological parameters into a function describing the relationship between the hysteresis device parameters (e.g., motor current) and the physiological parameters (e.g., aortic pressure). The function is used to determine the points of the data associated with the LVEDP.

[0127] At step 706, the calculated LVEDP point is used in a dynamic curve lookup table to determine the LVEDP, and at step 708, the LVEDP is output from the system. The dynamic curve lookup table can convert the aortic pressure measurement for a particular cardiac cycle into a pressure difference in order to find the LVEDP value. Figure 7 LVEDP is shown as the output of the gating algorithm, but the gating algorithm can be used with any indicator calculation as described herein.

[0128] Figure 8 A graph 800 showing aortic pressure, left ventricular pressure, and motor current over time. Figure 8The data of the diagram 800 can be used to generate a pressure-current curve to estimate a cardiac parameter (e.g., left ventricular pressure) from pressure and current. Diagram 800 has an x-axis 802 in units of time and a y-axis 804 in units of pressure in mmHg or motor current in mA. Diagram 800 also includes an aortic pressure signal 806, a left ventricular pressure signal 808, and a motor current signal 810. The aortic pressure signal 806 can be obtained by Figure 3 Pressure sensor 312, Figure 1 The aortic pressure signal includes a dicrotic notch 812, which can be used to mark the beginning of diastolic filling. The motor current signal 810 can be obtained from Figure 3 The left ventricular pressure signal 808 may be generated using a dedicated catheter placed in the left ventricle, a pressure sensor mounted on the inlet side of the pump, or a pressure-current based estimate. The signals 806, 808, and 810 in the diagram 800 may be generated from data collected in an animal model or a human patient. The signals 806, 808, and 810 in the diagram 800 may be generated from data collected in a porcine heart while the pump motor is operating at 33,000 rpm.

[0129] As shown in the diagram 800, the motor current signal 810 varies with the cardiac phase. As the blood flow rate through the heart increases, the load on the pump and therefore the motor current signal 810 also increases. The motor current signal 810 increases while the left ventricular pressure signal 808 and the aortic pressure signal 806 increase. This may seem counterintuitive because the pressure difference across the aortic valve is decreasing, but in this pump configuration, the main determinant of the increased current is the increased load on the motor due to the higher mass flow rate. Higher mass flow rates occur during cardiac contraction, which leads to higher motor currents during cardiac contraction. In the conventionally expressed Bernoulli relationship, this increase in motor current is not obvious because the Bernoulli relationship is usually a mass or rate that is normalized to describe a stable ohmic system. Unlike a typical pumping environment, the heart generates phase and dynamic loads through the variable mass flow to which the heart pump (e.g., heat pump 302) responds. This results in a phase component in the motor current signal that dominates the effect of pressure changes described by Bernoulli. As a result, the motor current waveform represents the cardiac cycle dynamics and can be used to extract cardiac energy. Although the motor driver can use a control algorithm that adjusts the motor current immediately after a cardiac phase change, the effect of such a control algorithm on the motor current can be predicted so that changes in the motor current can still be used as an indicator of changes in the heart's contractile ability and stroke volume.

[0130] The motor current signal 810 can be used to extract the LVEDP from the left ventricular pressure signal 808. Using an algorithm, the motor current signal 810 is analyzed to determine the time period when the motor current signal 810 changes. For example, the motor current signal 810 drops sharply between the first time 811 and the second time 813. The left ventricular pressure signal 808 can be analyzed during the corresponding time period to accurately extract the LVEDP. By gating the left ventricular pressure signal 808 based on the motor current signal 810, the amount of data that needs to be analyzed to find the LVEDP is reduced, and the noise is reduced. This gating technique that utilizes changes in motor parameters can be used with a variety of motor parameters. For example, an increase in motor current indicating an increased load can indicate a time period during which the LVEDP can be identified. In addition, a decrease in motor speed in response to an increased load can also indicate a time period during which the LVEDP can be identified.

[0131] Fig. 9 A process 900 for applying an ECG-based gating algorithm to determine LVEDP is shown. The depicted process shows in more detail the use of ECG data to determine a gating window and the application of a gating algorithm to determine LVEDP, as described with respect to FIG. Figure 6 As described.

[0132] The process 900 begins with a patient monitor 902, which measures and records ECG data at step 904. The patient monitoring system 902 can be external to the pump system, or can be integrated into the pump system. The measured ECG data is transmitted to the pump controller 906, where the ECG data can be used to determine a gating window for identifying the LVEDP. At step 908, the pump controller generates an ECG-based gating window by identifying the segment of the ECG data where the R peak of the QRS waveform or the end cycle of the diastole is located. This can be achieved by fitting the data to a periodic equation and determining data points that deviate from the equation, or by identifying points in the data that correspond to the R peak. The gating window is the time period in the ECG data where the R peak or the end cycle of the diastole is found, but the time period does not need to be expressed in absolute time.

[0133] At step 910, the pump controller measures the aortic pressure, and at step 912, the pump controller measures the motor current. The ECG gating window identified at step 908, and the measured aortic pressure and motor current are used by the pump controller at step 914 to identify the LVEDP from the aortic pressure data. The controller analyzes the aortic pressure data points in the segment of the aortic pressure data corresponding to the ECG gating window to determine an aortic pressure value expressing the LVEDP. By gating the data, the LVEDP point can be determined more quickly and less data needs to be analyzed, thereby reducing the amount of processing time required.

[0134] At step 916, the pump controller accesses a dynamic curve lookup table to convert the determined aortic pressure point into an actual LVEDP. The actual LVEDP can be output from the gating algorithm for use by a healthcare professional. For example, the healthcare professional can adjust the pump speed by increasing or decreasing the pump speed based on the reported LVEDP value.

[0135] In some embodiments, the cardiac cycle phase estimation is also determined based entirely or partially on ECG data. The ECG data can be timed using pressure tracking. The features in the ECG used to estimate the cardiac phase can be the beginning of the QRS complex and the end of the T wave. If there is noise in the ECG signal, it may be more reliable to detect the peak of the QRS complex (e.g., R wave) and the peak of the T wave. In the phase estimation method using a pressure signal or an ECG signal, the offset from the detected features can be used to more accurately identify the filling phase, because the actual filling occurs slightly before or after these identified landmarks. The R peak of the QRS waveform can also be used to identify the time period in which a specific cardiac parameter such as LVEDP can be identified, because the R peak corresponds to the end cycle of the cardiac diastole. A combination of the pressure signal-based and ECG-based methods can allow for more reliable identification. The weight between the two methods can be optimized using a data set with a known filling time parameter, a known left ventricular pressure, and a high signal-to-noise ratio. In some embodiments, the phase estimation from the cardiac hysteresis loop corresponds to one of cardiac ejection, diastolic filling, and diastolic relaxation.

[0136] Fig.10A graph 1000 of measured and predicted LVEDP by MCL and animal model over time is shown. Graph 1000 has an x-axis 1002 showing time in seconds and a y-axis showing LVEDP in mmHg. Graph 1000 includes a first waveform 406, a second waveform 1008, and a third waveform 1010. The first waveform 1006 represents the LVEDP measured by a catheter in the left ventricle over time. The second waveform 1008 represents the LVEDP predicted by an algorithm developed to characterize the performance of a pump in a simulated circulatory loop (MCL) over time. The third waveform 1010 represents the LVEDP predicted by an algorithm developed to characterize the performance of a pump in a porcine animal model over time. Inset 1012 shows the correlation of the LVEDP measured in the left ventricle with the LVEDP predicted by the MCL and animal model for each measurement. Illustration 1012 has an x-axis 1014 showing the measured LVEDP in mmHg and a y-axis 1016 showing the predicted LVEDP in mmHg. Illustration 1012 also includes a plurality of data points 1018 representing measured-predicted pairs. Data points 1018 in illustration 1012 include unfilled points (e.g., 1020) representing pairs predicted by the animal-based algorithm to include the LVEDP, and star-shaped points (e.g., 1022) representing pairs predicted by the MCL-based algorithm to include the LVEDP. A correlation line 1024 is provided to guide the eye and to represent a 1-to-1 correlation, i.e., the predicted LVEDP is equal to the measured LVEDP.

[0137] Pump characterization was performed in both MCL and porcine animal models that were subjected to intervention to simulate disease. LVEDP was successfully tracked during IVC occlusion in both the animal and MCL models. The RMS error for the animal model was 0.90 mmHG. The RMS error for the MCL model was 0.35 mmHG. This suggests that pump characterization using the MCL may be superior because there is a one-way variance versus a two-way variance. Therefore, using the MCL for characterization and the animal model for validation may be an effective means of correlating the performance of a cardiac pump with cardiac function. Data from the MCL model and the animal model can be used to develop prediction algorithms and to develop predetermined pressure-current curves.

[0138] Fig.11 A graph of LVEDP calculated from patient data is shown, illustrating the accuracy of the LVEDP determined using a gating method. Graph 1100 includes an x-axis 1102 representing the number of heart beats and a y-axis 1104 representing the LVEDP calculated based on motor and physiological parameters. Graph 1100 includes a scatter plot 1103 of the LVEDP calculated at each beat of the heart, a line 1102 showing the reported pulmonary capillary wedge pressure (PCWP), and standard error bars 1101 for the reported PCWP line 1102.

[0139] Graph 1100 shows the actual recorded PCWP 1102 in a patient and the LVEDP 1103 calculated by retrospectively applying the algorithm to the patient data. Graph 1100 shows that the calculated LVEDP 1103 is within the standard error bars 1101 for the reported PWCP line 1102. PWCP is traditionally measured by wedging a pulmonary catheter and balloon into the arterial branch of the pulmonary artery. The calculated LVEDP 1103 is closest to the reported PWCP 1102 at the data point taken when the patient is exhaling, which is the same point in the patient where the wedge pressure was taken. When applied to the patient data, as shown in FIG. Fig.11 The calculated LVEDP 1103 shown in FIG. 1 is comparable to or better than the industry standard PWCP 1102 .

[0140] Fig.12 A scatter plot 1200 of head pressure versus motor current is shown. Graph 1200 demonstrates the effect of hysteresis on the pressure-current curve. Graph 1200 has an x-axis 1202 showing the current in mA and a y-axis 1204 showing the head pressure between the left ventricle and the aorta in mmHg. Graph 1200 also includes a plurality of data points 1206 representing current-pressure pairs collected from a porcine animal model. The data points in graph 1200 were generated when the motor was operated at 30,000 rpm. The data points 1206 approximately form a hysteresis loop. The shape of the scatter plot 1200 shows that the relationship between the current and the head pressure between the left ventricle and the aorta changes throughout the cardiac cycle. Due to hysteresis in the pressure-current curve, methods of gating measurements based on cardiac phase can help improve the accuracy of cardiac parameter estimates by ensuring that sample data points are compared to reference data points occurring in the same cardiac phase (e.g., systole or diastole).

[0141] Fig.13A scatter plot 1300 of head pressure versus motor current is shown. Graph 1300 has an x-axis 1302 showing current in mA and a y-axis 1304 showing head pressure between the left ventricle and the aorta in mmHg. Graph 1300 also includes a plurality of data points 1306 representing current-pressure pairs. The data points 1306 form a hysteresis loop and include a piecewise spline curve fit to the hysteresis loop, which illustrates the determination of the phase of the cardiac cycle. The hysteresis loop is segmented into three curve fit splines 1309, 1311, and 1313. Each spline represents a cardiac cycle phase. The first spline 1309 indicates a segment of the hysteresis loop recorded during diastolic relaxation (isovolumetric relaxation). The second spline 1311 represents a segment of the hysteresis loop recorded during diastolic filling. The third spline 1313 indicates the segment of the hysteresis loop recorded during systole (ventricular contraction). The point where the second spline 1311 and the third spline 1313 meet is the LVEDP 1315. The characteristic notch observed where the second spline 1311 and the third spline 1313 meet enables identification of the point of the LVEDP 1315. Arrows 1307 and 1314 show the direction of progression of the cardiac cycle.

[0142] A characteristic notch can be observed at the time point where the LVEDP occurs in the hysteresis loop, allowing visual identification of the point in the cardiac cycle, as well as identification of the LVEDP algorithm as an inflection point in the pressure head and motor current hysteresis loops. At the LVEDP inflection point, the motor current changes as the left ventricle changes from experiencing diastolic filling to active contraction. Determining the LVEDP inflection point from the hysteresis loop depends on the sampling rate at which the motor and pressure parameters are collected, and the calculation must account for the sampling rate or extrapolate the data to accurately determine the LVEDP inflection point. The phase estimate can act as a filter for the pressure and current signals as it can allow the pressure and current signals to be compared with those occurring during the corresponding phase of the cardiac cycle.

[0143] The points of the LVEDP 1315 can also be calculated from the diagram 1300 using a best fit algorithm. The points of the LVEDP 1315 can be calculated from the hysteresis loop using a polynomial equation and a best fit algorithm that describes the hysteresis data as an ellipse. The hysteresis loop can be estimated using an equation based on the Euler equation for steady fluid motion. The coefficients of the equation are calculated using multiple regression analysis from the following equation:

[0144]

[0145] where the coefficients are A, B, C, and D, i is the motor current, di / dt is the time derivative of the motor current, ω is the thermodynamic work, and d 2 i / d 2t is the second derivative of the motor current with respect to time. The last term in the equation is optional because it is very small. The final calculated equation describes the hysteresis loop and can be used to track changes in the size and shape of the loop over time, or changes in curvature or local slope over time, and to extract indicators of cardiac function including LVEDP.

[0146] From this equation, an ellipse 1321 is fitted to the hysteresis loop using geometric methods, and points of the LVEDP 1315 can be detected based on the relationship of the data points to the described ellipse. The distance between each point on the ellipse 1321 and the focus can be used to determine outlier data points from the ellipse fit according to the following equation:

[0147]

[0148] Where the r value is the distance from a point on the ellipse 1321 to each focus, and a is the length of the minor axis of the ellipse 1321. The values ​​of the data points outside the ellipse 1321 are evaluated for position, and the most clustered positions of the data points are determined by iterating the data. Clusters can be defined in a variety of ways, for example, a cluster can be defined as at least 3 points within 2 mA and 1.5 mmHg of each other.

[0149] By algorithmically determining the clusters of data points 1306 that form the two ends of the hysteresis loop, a bisecting line 1317 can be drawn through the ellipse 1321 that describes the hysteresis loop. Because the heart spends the greatest amount of time in these two phases and only travels briefly between them, most of the measured data points 1306 are in these two locations. A first cluster 1318 corresponding to peak relaxation and a second cluster 1319 corresponding to peak ejection are detected, and a line 1317 is drawn between the means of these two clusters 1318 and 1319. Line 1317 generally divides the ellipse 1321 and the hysteresis data into two halves, namely into a top section that includes the first spline 1309 (diastolic relaxation) and the corresponding generally higher pressure, and a bottom half that generally corresponds to higher pressure. The bottom section of the ellipse 1321 below the line 1317 includes the second spline 1311 (diastolic filling) and the third spline 1313 (systolic or ventricular contraction). The points of the LVEDP 1315 can be estimated from an ellipse fit of the data below line 1317 and the points with the highest deviation from the circle or ellipse 1321 fitted to the data are determined. In addition, other cardiac indices can be extracted from the data by segmenting the ellipse according to cardiac phase and each segment can be numerically integrated using a Riemann sum. Alternatively, any other suitable best fit algorithm can be used to estimate the hysteresis loop.

[0150] Left ventricular diastolic pressure and left ventricular end-diastolic pressure (LVEDP) can be used to determine the overall state of cardiac function. LVEDP is the pressure in the left ventricle at the end of ventricular filling and just before the ventricle contracts. In almost all cases of acute myocardial infarction, LVEDP tends to be significantly elevated, especially in patients with heart failure. This is primarily due to a shift in the Frank-Starling relationship, which describes the relationship between the contractile state of the heart and the LVEDP, caused by changes in the end-diastolic pressure-volume ratio (EDPVR). As a patient approaches heart failure, the Frank-Starling curve shifts downward so that a given pressure results in a lower stroke volume. Due to this shift, at a given cardiac output in the patient, assuming all other conditions remain relatively constant, the LVEDP can indicate the state of the heart. Measuring these changes in LVEDP can be valuable in monitoring a patient's progression toward heart failure or recovery, allowing clinicians to adjust the required treatment accordingly.

[0151] After determining the LVEDP point based on the ellipse fit, the actual LVEDP can be determined by accessing a lookup table. The predetermined pressure-current curve can be embodied in a lookup table that accepts pressure, motor current, and cardiac phase as its input. The cardiac phase information can be binary (e.g., diastole or systole) or more fine-grained (e.g., systole, diastolic relaxation, and diastolic filling). The output of the lookup table can be other parameters besides LVEDP, such as contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular end-diastolic pressure (LVEDP), preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, cardiac cycle volume load state and / or cardiac cycle flow state or any other suitable cardiac parameter, but the calculation of these parameters may require additional input.

[0152] Although Fig.13 A hysteresis curve formed by data points 1306 and a bisector 1317 is shown, but this is to illustrate the principles of the algorithm applied to the data. It is not necessary to actually create or depict a hysteresis loop to extract the LVEDP data. The controller can extract the LVEDP data by accessing and manipulating an array of stored data stored in a memory. The controller can store the measured data in a memory and can characterize the relationship between the measured aortic pressure and the motor parameters, for example, by fitting the data to an equation that describes how one parameter is related to another parameter, such as an ellipse fit, an Euler equation, or a polynomial expression. The equation characterizing the relationship between the data points is then used to extract information about the LVEDP points, and in some embodiments, the equation can also be used to extract information about additional cardiac parameters related to cardiac function.

[0153] Furthermore, it is not necessary to record or measure the motor and hemodynamic parameters of the entire cardiac cycle to extract LVEDP data. It is necessary to collect enough data points at the transition from the diastolic filling phase to the ventricular contraction phase of the cardiac cycle so that these points can be a fit to a portion of the elliptical curve and LVEDP points that deviate from the elliptical fit can be determined. Alternatively, one or more cardiac cycles can be recorded in order to accurately capture this portion of the curve.

[0154] In some embodiments, it may be beneficial to display a hysteresis loop formed by relating measured motor parameters and hemodynamic parameters to each other. The shape and size of the hysteresis loop, or changes in local slope or curvature, can provide important details about the patient's cardiac function. For example, these can be used by healthcare professionals to make decisions related to patient care, such as whether to increase or decrease pump support by changing the speed of the pump.

[0155] Fig.14 A scatter plot 1400 of head pressure versus hysteresis parameter after applying a hysteresis gate to segment the data is shown. Graph 1400 has an x-axis 1402 representing the hysteresis parameter and a y-axis 1404 representing the pressure difference between the left ventricle and the aorta in mmHg. Fig.14 The data in was collected from a porcine animal model. The hysteresis parameter can be a motor parameter, such as motor current expressed in mA. The hysteresis parameter can be a dimensionless or normalized parameter. Graph 1400 includes data points 1406 that have been divided into three groups, namely: a cardiac systolic region 1408, a diastolic filling region 1410, and a cardiac diastolic relaxation region 1412. Region 1408 corresponds to cardiac systole and includes data points 1409 that occur during cardiac systole. Region 1410 corresponds to diastolic filling and includes data points 1411 that occur during diastolic filling. Region 1412 corresponds to diastolic relaxation and includes data points 1413 that occur during diastolic relaxation. It can be used, for example Figure 3 A cardiac phase estimator, such as the cardiac phase estimator 318 of , groups the data points 1406 into a systolic region 1408 , a diastolic filling region 1410 , and a diastolic relaxation region 1412 .

[0156] Graph 1400 also includes a subgraph 1414 having an x-axis 1416 representing time and a y-axis 1418 representing aortic pressure. Subgraph 1414 shows an aortic pressure signal 1420 having various reference points 1422, 1424, 1426, and 1428 identified. Reference points 1422, 1424, 1426, and 1428 may be used to separate the aortic pressure signal 1420 into phases of the cardiac cycle, as shown by a systolic region 1430, a diastolic relaxation region 1432, and a diastolic filling region 1434. Separating the aortic pressure signal into regions 1430, 1432, and 1434 may be used to separate the data points 1406 into respective systolic regions 1408, diastolic relaxation regions 1412, and diastolic filling regions 1410. Dividing the data 1406 into these regions allows similar measurements to be compared so that the comparison is not biased by misalignment of cardiac phase between the sample and reference measurements. This can allow the estimation of cardiac parameters to be robust to system hysteresis.

[0157] Fig.15 A scatter plot 1500 of head pressure versus motor current is shown. Graph 1500 has an x-axis 1502 showing a motor hysteresis parameter and a y-axis 1504 showing head pressure between the left ventricle and the aorta in mmHg. Graph 1500 includes a first hysteresis loop 1507 showing a baseline hysteresis and a second hysteresis loop 1505 showing an exemplary change in the first hysteresis loop 1507. The second hysteresis loop 1505 includes measurable parameters determined from graph 1500, including a variable hysteresis parameter 1515, a variable head pressure parameter 1517, and a variable loop width parameter 1519. Changes in the second hysteresis loop 1505 can be caused by changes in cardiac performance in response to a medical event or in response to an external stimulus. Variable hysteresis parameter 1515, variable head parameter 1517, and variable loop width parameter 1519 may describe the variation between first hysteresis loop 1507 and second hysteresis loop 1505. Variable hysteresis parameter 1515 is measured along x-axis 1502. Variable head parameter 1517 is measured along y-axis. Variable loop width parameter 1519 is a measure of the widest portion of the hysteresis loop.

[0158] Fig.16A scatter plot 1600 of head pressure versus motor current before and after administration of a beta blocker in a porcine animal model is shown. The graph 1600 has an x-axis 1602 showing current in mA and a y-axis 1604 showing head pressure between the left ventricle and the aorta in mmHg. The graph 1600 also includes a plurality of data points 1606 representing current-pressure pairs. The data points in the graph 1600 were generated in a porcine heart while the motor was operating at 30,000 rpm. The data points 1606 approximately form a first hysteresis loop 1607 and a second hysteresis loop 1605. The first hysteresis loop 1607 has three regions 1612, 1610, and 1608. The first region 1612 includes data point 1613 and indicates diastolic relaxation. The second region 1610 includes data point 1611 and indicates diastolic filling. The third region 1608 includes data point 1609 and indicates cardiac contraction. The first hysteresis loop 1607 is generated during normal function of the heart. The second hysteresis loop 1605 is generated after the administration of a beta-blocker. The second hysteresis loop 1605 includes three regions 1616, 1618, and 1614. The first region 1616 includes data point 1615 and indicates diastolic relaxation. The second region 1618 includes data point 1617 and indicates diastolic filling. The third region 1614 includes data point 1619 and indicates cardiac contraction. The shape of the scatter plot 1600 shows that the relationship between the current and the pressure head between the left ventricle and the aorta changes throughout the cardiac cycle and during normal function (as in the hysteresis loop 1607) and after the administration of a beta-blocker (as in the hysteresis loop 1605). The second hysteresis loop 1605 has a lower maximum pressure difference than the first hysteresis loop 1607. In addition, the shape of the second hysteresis loop 1605 is different from the shape of the first hysteresis loop 1607. In particular, the first region 1616 of the second hysteresis loop 1605 is shifted downward and has a less defined curve than the corresponding first region 1612 of the first hysteresis loop 1607. The third region 1614 of the second hysteresis loop 1605 is also shifted upward relative to the corresponding third region 1608 of the first hysteresis loop 1607. In addition, the area enclosed by the first hysteresis loop 1607 is larger than the area enclosed by the second hysteresis loop 1605. The administration of beta-blockers causes changes in cardiac contractility. A trained physician can use the shape of the data points 1606, and the area of ​​the hysteresis loop formed by the data points, during multiple cardiac cycles to determine the morphological changes of the heart caused by the administration of beta-blockers, or to determine the level of heart failure.

[0159] Fig.17 Shows from Fig.16 The smooth curve obtained by the scatter plot of Fig.16Similar to the scatter plot 1600 in FIG. 1 , the graph 1701 has an x-axis 1702 showing the current in mA and a y-axis 1704 showing the pressure head between the left ventricle and the aorta in mmHg. The graph 1701 shows three curves, namely a baseline curve 1709, a curve 1705 showing low contractility, and a curve 1707 showing high contractility. For example, after the administration of a beta-blocker, such as in a low contractility state, Fig.17 The smooth curve allows healthcare professionals to visualize changes in cardiac behavior and can be used to extract meaningful changes in cardiac parameters and cardiac health status. Fig.16 and Fig.17 Included are hysteresis curves shown on the x-axis 1602 and 1702 for motor current in mA, but hysteresis curves may be plotted with any motor parameter that varies with time and beats on the x-axis.

[0160] Fig.18A A scatter plot 1800 of head pressure versus motor current is shown. The plot 1800 has an x-axis 1802 showing current in mA and a y-axis 1804 showing head pressure between the left ventricle and the aorta in mmHg. The plot 1800 also includes a plurality of data points 1806 representing current-pressure pairs. The data points 1806 form a first hysteresis loop 1808 and a second hysteresis loop 1810. The shape of the scatter plot 1800 shows that the relationship between current and head pressure between the left ventricle and the aorta varies throughout the cardiac cycle and during normal function (as in the hysteresis loop 1808) and during the transition to myocardial infarction (as in the hysteresis loop 1810). The first hysteresis loop 1808 indicates the heart cycle prior to myocardial infarction. The second hysteresis loop 1810 indicates the heart cycle during the transition to myocardial infarction. During myocardial infarction, the area enclosed by the second hysteresis loop 1810 is smaller than the area enclosed by the first hysteresis loop 1808. A trained physician can use the shape of the data points 1806 over multiple cardiac cycles to determine morphological changes in the heart during or after a myocardial infarction.

[0161] Fig.18BA graph 1801 showing cardiac dynamic index and motor current over a period of time is shown. Graph 1801 has an x-axis 1803 showing a plurality of samples taken, a first y-axis 1805 showing the dynamic index of the heart, and a second y-axis 1807 showing the average motor current in mA. The graph includes a first trace 1812 of cardiac dynamic index measured over the plurality of samples and a second trace 1810 of motor current over the same samples. The cardiac dynamic index is a new measure calculated from the hysteresis loop and is intended to provide the physician with information about the performance of the heart. In graph 1801, the motor current 1810 remains approximately constant over the measured samples. The cardiac dynamic index 1808 is shown in a low sample during the normal cycle of the heart, labeled "pre-MI" 1814. At sample number 500, the cardiac dynamic index 1812 decreases from approximately 3000 to approximately 2000 during a myocardial infarction (labeled "MI"), indicating a decrease in the pumping performance of the heart. The cardiac dynamic index is an indicator that can be used by a trained physician to monitor the performance of the heart during the normal cardiac cycle and during and after an event such as a myocardial infarction.

[0162] Fig.19 Examples of various cardiac parameters changing over time are shown, illustrating the diagnostic capabilities provided by visualizing the parameters. Each figure shows data generated from an animal model showing changes in area index, contractility, flow load state, and mean aortic pressure over time. Figure I 1900 includes an x-axis 1903 representing time in seconds, a first y-axis 1904 representing the normalized index as a percentage, and a second y-axis 1905 representing mean pressure in mmHg. Figure I includes tracking trajectories of area index 1910 (indicative of overall cardiac function), contractility index 1908, flow load state 1912, and mean aortic pressure 1906 during balloon occlusion of the inferior vena cava.

[0163] Graph II 1901 includes an x-axis 1913 representing time in seconds, a first y-axis 1914 representing a normalized index as a percentage, and a second y-axis 1915 representing mean pressure in mmHg. Graph II includes tracking traces of area index 1920, contractility index 1918, flow load state 1922, and mean aortic pressure 1916 after the use of beta blockers.

[0164] Graph III 1902 includes an x-axis 1923 representing time in seconds, a first y-axis 1924 representing a normalized index as a percentage, and a second y-axis 1925 representing mean pressure in mmHg. Graph III includes tracking traces of area index 1930, contractility index 1928, flow load state 1932, and mean aortic pressure 1926 after inotropes.

[0165] Fig.19 Figures I-III of FIGURES 1-3 illustrate the different responses of various measurable cardiac parameters in response to various cardiac events. For example, the reduction in cardiac function shown by the decrease in area index 1910 in FIGURE 1 is preceded by a decrease in flow load state index 1912, indicating that there is a problem with the amount of blood pumped by the heart. The decrease in area index 1920 in FIGURE II coincides with a decrease in contractility index 1918, indicating that the beta blocker administered to the animal model affects the contractility of the heart. The cardiac parameters shown in FIGURES I-III can be calculated from the hysteresis loops and displayed to illustrate changes in contractility state, flow load state, and overall cardiac function, and to determine the causes of these changes.

[0166] Understanding the trends of various cardiac parameters of a patient allows a trained medical professional to better meet the cardiac needs of the patient.The status of a patient's heart can be determined by a healthcare professional through changes and trends in various calculated cardiac parameters.

[0167] Fig. 20A An exemplary user interface of a heart pump controller is shown, which includes a waveform of a heart function indicator varying over time. The user interface 2000 can be used to control Figure 1 Intravascular heart pump system 100, Figure 2 Heart assist devices 201, Figure 3 The user interface 2000 includes a pressure signal waveform 2002, a motor current waveform 2004, a heart state waveform 2008, and a flow rate 2006. The pressure signal waveform 2002 represents the pressure measured by the pressure sensor of the blood pump (e.g., pressure sensor 312). The pressure signal waveform 2002 can be used by a healthcare professional to adjust the intravascular heart pump (e.g., Figure 1 The intravascular heart pump 100 in FIG. 2 is properly placed in the heart. The pressure signal waveform 2002 is used to verify the position of the intravascular heart pump by evaluating whether the waveform 2002 is an aortic or ventricular waveform. An aortic waveform indicates that the intravascular heart pump motor is in the aorta. A ventricular waveform indicates that the intravascular heart pump motor has been inserted into the ventricle, which is an incorrect position. A scale 2014 for the placement signal waveform is displayed on the left side of the waveform. The default scaling is 0-160 mmHg. It can be adjusted in increments of 20 mmHg. To the right of the waveform is a display 2003 which labels the waveform, provides the units of measurement, and displays the maximum and minimum values ​​and the average of the samples received.

[0168] The motor current waveform 2004 is a measure of the energy intake of the heart pump's motor. Energy intake varies with motor speed and the pressure difference between the inlet and outlet regions of the cannula, resulting in a variable volumetric load on the rotor. When used with intravascular heart pumps (e.g. Figure 1 When used with an intravascular heart pump 100 in the artery, the motor current provides information about the position of the catheter relative to the aortic valve. When the intravascular heart pump is properly positioned with an inlet region in the ventricle and an outlet region in the aorta, the motor current is pulsatile because the mass flow rate through the heart pump varies with the cardiac cycle. When the inlet and outlet regions are on the same side of the aortic valve, the motor current will be suppressed or flattened because the inlet and outlet of the pump are in the same chamber and there is no variation in the pressure differential, resulting in a constant mass flow rate and, subsequently, a constant motor current. The scale 2016 for the motor current waveform is shown on the left side of the waveform. The default scaling is 0-1000mA. The scaling can be adjusted in increments of 100mA. To the right of the waveform is a display 2005 which labels the waveform, provides the units of measurement, and displays the maximum and minimum values ​​and the average of the samples received. Although a pressure sensor and a motor current sensor may not be required to position a surgically implanted pump, for example Figure 2 The heart assist device 201 is shown, but these sensors may be used in such a device to determine additional characteristics of the native heart function for monitoring therapy.

[0169] The heart state waveform 2008 is a display of the heart state recorded over a certain period of time. The heart state can be displayed as a ratio of the contractility of the heart divided by the amount of blood pumped. The heart state can be calculated at discrete time points or continuously and displayed as a trend in the heart state waveform 2008 to provide the physician with an indication of the current performance of the heart relative to the performance of other time points in the patient's treatment. The scale 2018 for the heart state waveform 2008 is displayed on the left side of the heart state trend line. The default scaling is from 1-100 (unitless). The scaling can be adjusted to best display the heart state trend. On the right side of the heart state waveform 2008 is a display 2007 that marks the trend line, provides additional information about the heart's performance at the current time, and shows the current value of contractility and the amount received from the pump. Displaying this information as a trend line allows the physician to view the patient's historical heart state and make decisions based on the trend of the heart state. For example, the physician can observe a decrease or increase in the heart state over time from the heart state trend line and determine to change or continue treatment based on this observation.

[0170] The flow rate 2006 may be a target blood flow rate set by the user or an estimated actual flow rate. In certain modes of the controller, the controller will automatically adjust the motor speed in response to changes in afterload to maintain the target flow rate. In some embodiments, if flow calculation is not possible, the controller will allow the user to set a fixed motor speed as shown by the speed indicator 2008.

[0171] Fig. 20B An exemplary user interface 2001 for a heart pump controller according to some embodiments is shown. The user interface 2001 may be used to control Figure 1 Intravascular heart pump system 100, Figure 2 Heart assist devices 201, Figure 3 The user interface 2001 includes a pressure signal waveform 2022, a motor current waveform 2024, a flow rate 2026, a speed indicator 2028, a contractility score 2030, and a state score indicator 2032. The pressure signal waveform 2022 represents the pressure measured by the pressure sensor of the blood pump (e.g., pressure sensor 312). The pressure signal waveform 2022 can be used by a healthcare professional to adjust the intravascular heart pump (e.g., Figure 1 The intravascular heart pump 100 in FIG. 2 is properly placed in the heart. The pressure signal waveform 2022 is used to verify the position of the intravascular heart pump by evaluating whether the waveform 2022 is an aortic or ventricular waveform. An aortic waveform indicates that the intravascular heart pump motor is in the aorta. A ventricular waveform indicates that the intravascular heart pump motor has been inserted into the ventricle, which is an incorrect position. A scale 2034 for the placement signal waveform is displayed on the left side of the waveform. The default scaling is 0-160 mmHg. It can be adjusted in increments of 20 mmHg. To the right of the waveform is a display 2033 which labels the waveform, provides the units of measurement, and displays the maximum and minimum values ​​and the average of the samples received.

[0172] The motor current waveform 2024 is a measure of the energy intake of the heart pump's motor. Energy intake varies with motor speed and the pressure difference between the inlet and outlet regions of the cannula, resulting in a variable volumetric load on the rotor. When used with intravascular heart pumps (e.g. Figure 1When used with an intravascular heart pump 100 in the artery, the motor current provides information about the position of the catheter relative to the aortic valve. When the intravascular heart pump is properly positioned with an inlet region in the ventricle and an outlet region in the aorta, the motor current is pulsatile because the mass flow rate through the heart pump varies with the cardiac cycle. When the inlet and outlet regions are on the same side of the aortic valve, the motor current will be suppressed or flattened because the inlet and outlet of the pump are in the same chamber and there is no variation in the pressure differential, resulting in a constant mass flow rate and, subsequently, a constant motor current. A scale 2036 for the motor current waveform is displayed on the left side of the waveform. The default scaling is 0-1000mA. The scaling can be adjusted in increments of 100mA. To the right of the waveform is a display 2025 which labels the waveform, provides the units of measurement, and displays the maximum and minimum values ​​and the average of the samples received. Although a pressure sensor and a motor current sensor may not be required to position a surgically implanted pump, for example Figure 2 The heart assist device 201 is shown, but these sensors may be used in such a device to determine additional characteristics of the native heart function for monitoring therapy.

[0173] The flow rate 2026 may be a target flow rate set by the user or an estimated actual flow rate. In certain modes of the controller, the controller will automatically adjust the motor speed in response to changes in afterload to maintain the target flow rate. In some embodiments, if flow calculation is not possible, the controller will allow the user to set a fixed motor speed as shown by the speed indicator 2028.

[0174] The contractility score 2030 provides an indication of cardiac function. More specifically, the contractility score represents the inherent strength and vigor of the heart's contractions during systole. If the heart's contractility is greater, the heart's stroke volume will be greater. For example, moderate contractility may occur when the heart's stroke volume is approximately 65 mL. High contractility may occur when the heart's stroke volume exceeds 100 mL. Low contractility may occur when the heart's stroke volume is less than 30 mL. The contractility score may be represented numerically and / or graphically. The contractility score may be dimensionless. Changes in contractility may be determined by changes in the pressure slope (dP / dt) during systole. The state score indicator 2032 also provides an indication of cardiac function. The state score indicator may be an indication of volume load, pressure of cardiac pressure, or another indicator of cardiac function.

[0175] Fig. 20A and Fig. 20BThe location of the indicators in the controller, the depiction of the indicators on the controller, and the identification and number of indicators and recommendations are intended to be illustrative. The number of indicators and indications, the location of the same indicators and indications on the console, and the indicators displayed may vary from those shown here. The indicators displayed to the user may be contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, LVEDP, preload state, afterload state, flow load state, variable volume load state, cardiac cycle volume load state, cardiac cycle flow state, heart rate and / or cardiac recovery defined by any or all of the foregoing cardiac-related parameters, trends over time and specific thresholds, or any other suitable indicator derived from hysteresis parameters associated with a cardiac assist device placed or partially placed in an organ of the patient.

[0176] Fig.21 A process for detecting aspiration in an intravascular heart pump and determining the cause of aspiration is shown. Aspiration occurs when an inlet to a heart assist device is occluded (e.g., by a valve leaflet or other anatomical structure) or when the blood volume or preload to the ventricle is reduced and is less than the output of the selected pump speed. Preventing aspiration can enable an intravascular heart assist device to operate safely at higher flow rates. Conventional aspiration detection techniques are not sensitive enough to detect minor aspirations, to detect when aspirations occur during the cardiac cycle, and to detect adverse cardiac cycle flow states that may lead to an aspiration event. Process 2100 can detect aspiration more quickly than conventional methods and can provide information to the user on how to prevent persistent or worsening aspirations.

[0177] In step 2102, pressure is detected from the cardiac assist device. In step 2104, rotor speed and motor current are detected. In step 2106, the phase of the cardiac cycle is determined. The phase estimate can act as a filter for the pressure and current signals because it can allow the pressure and current signals to be compared with the pressure and current signals occurring during the corresponding phase of the cardiac cycle. The phase estimate can be based on the pressure information received in step 2102 and can involve locating a reference point in the pressure information indicating the cardiac phase. In some embodiments, a dicrotic notch is detected in the pressure signal to indicate the beginning of diastolic filling. The dicrotic notch is a small downward deflection in the arterial pulse or isobar immediately after the closure of the semilunar valves. The dicrotic notch can be used as a marker for the end of the cardiac systole, and therefore, approximately the beginning of the cardiac diastole.

[0178] In some embodiments, the phase estimation is based entirely or partially on ECG data. The ECG data can be timed using pressure tracking. The features in the ECG used to estimate the cardiac phase can be the beginning of the QRS complex and the end of the T wave. If there is noise in the ECG signal, it may be more reliable to detect the peak of the QRS complex (e.g., R wave) and the peak of the T wave. In the phase estimation method using a pressure signal or an ECG signal, the filling phase can be more accurately identified using an offset from the detected features, because the actual filling occurs slightly before or after these identified landmarks. A combination of the two methods based on pressure signals and based on ECG can allow for more reliable identification. The weight between these two methods can be optimized using a data set with known filling time parameters, known left ventricular pressure, and a high signal-to-noise ratio.

[0179] In step 2108, a predetermined pressure curve is referenced to determine cardiac parameters indicative of suction. In some embodiments, the table may be based on a predetermined pressure-current curve. The cardiac parameters may be determined by mapping the measured current and pressure to the cardiac parameters. The reference table may be a lookup table that accepts pressure, motor current, and cardiac phase as its input. The cardiac phase information may be binary (e.g., diastole or systole) or more fine-grained (e.g., systole, diastolic relaxation, and diastolic filling). In step 2110, a suction event is detected. A suction event may be detected by determining a deviation from a normal predetermined pressure-current curve. The deviation may indicate an atypically low mass flow rate for the corresponding aortic pressure and cardiac phase. In some embodiments, a suction event is detected by changes in the hysteresis loop of the motor parameters and the pressure head. An early indication of a suction event is a collapse of the hysteresis loop. As the volume load decreases, the loop collapses, indicating that a suction event has begun.

[0180] In step 2112, the time in the cardiac cycle at which the aspiration event occurred is determined. For example, it can be determined whether the aspiration event occurred during systole or diastole. The method for stopping one or more aspiration events may depend on whether the aspiration event occurred during systole or diastole. In step 2114, a coefficient of volume loading is determined. Based on the coefficient of volume loading and determining when the aspiration occurred in the cardiac cycle, the root cause of the aspiration is determined. For example, the root cause may be aspiration of the valve leaflets. In step 2118, corrective measures are provided to the user to resolve the aspiration event. For example, the user can be prompted to reposition the heart assist device within the heart. In some embodiments, when the onset of an aspiration event is detected, an early detection warning of a possible aspiration event is activated.

[0181] In some embodiments, conditions leading to a suction event can be detected, for example, by detecting a reduction in the volume load experienced by the pump. The chamber blood volume of the pump can be detected using measurements of motor parameters at the pressure sensor and hysteresis in the pressure measurements, and the chamber blood volume can be compared to a set pump support level to determine if the chamber blood volume is severely reduced. When a suction event occurs, there can be a severe reduction in chamber blood volume, and detection of the reduction can provide an early warning or action prompt to prevent the suction event from continuing. In some embodiments, the action is automatic. In some embodiments, the action is recommended. In some embodiments, the automatic or recommended action is to reduce the level of support provided by the pump (e.g., reduce the rotor speed) to match the volume state.

[0182] Example embodiment 1:

[0183] The IMPELLA® percutaneous heart pump (Abiomed, Inc., Danvers, Massachusetts) was implanted in a simulated circulatory loop (MCL) consisting of the ventricle and aorta, and pressures were measured throughout the procedure. The IMPELLA® was operated at various performance levels and MCL fluid dynamic curves while the motor current was recorded. The LVP prediction algorithm was generated using pump characterization. Performance was validated in anesthetized pigs using the implanted IMPELLA®. Ischemic-like or hemorrhagic shock-like events were induced by balloon occlusion of the left anterior descending coronary artery or the inferior vena cava, respectively. The motor current of the IMPELLA® pump was recorded simultaneously as well as pressure signals in the pulmonary artery, left ventricle, and aorta.

[0184] Ischemia and shock were tracked over 4 minutes with minimal ventricular support by extreme changes. Changes in the motor current waveform reflected instability and shock. Left ventricular pressure (LVP) was predicted during hemorrhagic shock using characterizations from both MCL (RMS error ~0.3 mmHg) and pig (RMS error ~0.9 mmHg). In contrast, with maximal ventricular support, there was no hemodynamic compromise after >20 minutes of occlusion, and the motor current remained unchanged.

[0185] The results demonstrate coupling between cardiac and device function. Without adequate support, cardiac performance degrades and leads to hemodynamic collapse, which is tracked by the LVP algorithm. The success of the algorithm is attributed to the use of MCLs and porcine models during development. MCLs define the boundaries of pump performance, while animals characterize biological variability and pathology. This unified approach can be an effective means of defining the performance of any device, using MCLs for characterization and animals for validation.

[0186] The foregoing is merely illustrative of the principles of the present disclosure, and the device may be implemented by other embodiments than those described, which are provided for purposes of illustration and not limitation. It should be understood that the device disclosed herein, although shown for percutaneous insertion of a heart pump, may also be applicable to devices in other applications.

[0187] After reading this disclosure, variations and modifications will occur to those skilled in the art. The disclosed features may be implemented in any combination and sub-combination (including multiple dependent combinations and sub-combinations) with one or more other features described herein. The various features described or illustrated above, including any components thereof, may be combined or integrated in other systems. In addition, certain features may be omitted or not implemented.

[0188] In general, embodiments of the subject matter and functional operations described in this specification may be implemented in digital electronic circuits, or in computer software, firmware or hardware, including the structures disclosed in this specification and their structural equivalents, or in a combination of one or more of them. Embodiments of the subject matter described in this specification may be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a computer-readable medium, for execution by a data processing device or for controlling the operation of a data processing device. A computer-readable medium may be a machine-readable storage device, a machine-readable storage substrate, a memory device, a combination of substances that affect a machine-readable propagation signal, or a combination of one or more of them. The term "data processing device" encompasses all devices, apparatuses and machines for processing data, including, as examples, a programmable processor, a computer or multiple processors or computers. In addition to hardware, the device may also include code that creates an execution environment for the computer program in question, for example, code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them. A propagated signal is an artificially generated signal, for example, a machine-generated electrical, optical or electromagnetic signal generated to encode information for transmission to a suitable receiver device.

[0189] A computer program (also referred to as a program, software, software application, script, or code) may be written in any form of programming language, including compiled or interpreted languages, and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program may be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or portions of code). A computer program may be deployed to execute on one computer or on multiple computers located at one site or distributed across multiple sites and interconnected by a communications network.

[0190] The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output. The processes and logic flows can also be performed by special purpose logic circuits, and the device can also be implemented as special purpose logic circuits, such as FPGAs (field programmable gate arrays) or ASICs (application specific integrated circuits).

[0191] As an example, processors suitable for executing computer programs include both general and special-purpose microprocessors, and any one or more processors of any type of digital computer. Typically, the processor will receive instructions and data from a read-only memory or a random access memory or both. The basic elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, or be operably coupled to receive data from the mass storage device or transfer data to the mass storage device, such as a magnetic disk, a magneto-optical disk, or an optical disk. However, a computer need not have such a device.

[0192] Examples of changes, substitutions and alterations may be ascertained by those skilled in the art and may be made without departing from the scope of the information disclosed herein.All references cited herein are incorporated by reference in their entirety and constitute a part of this application.

Claims

1. A heart pump system comprising: catheter; motor; a rotor operatively coupled to the motor; a pump housing at least partially surrounding the rotor such that actuating the motor drives the rotor and pumps blood through the pump housing; as well as a pressure sensor configured to detect aortic pressure over time; as well as A controller configured to: Detect motor parameters over time, receiving the aortic pressure from the pressure sensor over time, storing the relationship between the motor parameter and the aortic pressure in a memory; determining a time period in which an inflection point of a curve based on the relationship can be found, wherein the inflection point indicates the LVEDP; as well as An inflection point of the curve is identified based on the determined time period.

2. The heart pump system according to claim 1, characterized in that Determining a time period in which an inflection point of a curve based on the relationship may be found includes identifying a time period in which the received motor parameter changes.

3. The heart pump system of claims 1 or 2, the controller further configured to determine the LVEDP based on the inflection point of the curve from a dynamic curve lookup table in the memory.

4. The heart pump system according to claim 1 or 2, characterized in that The controller is further configured to receive an ECG signal, and wherein determining a time period in which an inflection point of a curve based on the relationship may be found comprises identifying a time period in which the ECG signal indicates an end period of diastole.

5. The heart pump system according to claim 1 or 2, characterized in that The controller is also configured to determine at least one cardiac indicator from the stored pressure difference between the ventricle and the aorta, and wherein the cardiac indicator is at least one of contractility, stroke volume, ejection fraction, chamber pressure, stroke work, cardiac output, cardiac dynamic output, left ventricular pressure, preload state, afterload state, heart rate, cardiac recovery, flow load state, variable volume load state, cardiac cycle volume load state or cardiac cycle flow state.

6. The heart pump system according to claim 1 or 2, characterized in that The motor parameter is one of: motor current, change in motor current, variability of motor current, and net integrated area of ​​motor current and pressure.

7. The heart pump system of claim 1 or 2, wherein the controller is further configured to determine a cardiac cycle phase from the relationship between the motor parameter and the aortic pressure, wherein: The cardiac cycle phase is determined using ECG data, hemodynamic parameters, the motor parameters, and one or more of motor speed and / or the slope of the aortic pressure.

8. The heart pump system according to claim 1 or 2, characterized in that The motor is configured to maintain a constant rotor speed during actuation of the rotor.

9. The heart pump system according to claim 1 or 2, characterized in that The heart pump system also includes an integrated motor sized and configured for insertion into the vasculature of a patient.

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