WO2020093084A1

WO2020093084A1 - Ventricular function determination

Info

Publication number: WO2020093084A1
Application number: PCT/AU2019/050798
Authority: WO
Inventors: Christopher Simon HAYWARD; Pankaj Jain
Original assignee: St Vincent's Hospital Sydney Limited
Priority date: 2018-11-09
Filing date: 2019-07-30
Publication date: 2020-05-14

Abstract

Apparatus for use with a ventricular assist device that is assisting cardiac function of a biological subject, the apparatus including one or more electronic processing devices that determine pressure changes in the ventricle over one or more cardiac cycles using an aortic pressure derived from a measured blood pressure, a pump head pressure derived based on a pump flow rate and outlet fluid conduit pressure losses derived based on a pump flow rate, a fluid conduit diameter and haematocrit amount. The processing device(s) then determine volume changes in the ventricle at least in part using a pump blood flow derived based on a pump flow rate and an ejection volume based on an aortic valve opening duration, and use the pressure and volume changes to at least one of derive a ventricular function indicator indicative of ventricular function and control the ventricular assist device.

Description

VENTRICULAR FUNCTION DETERMINATION

Background of the Invention

[0001] The present invention relates to a method and apparatus for use with a ventricular assist device that is assisting cardiac function of a biological subject, and in particular to a method and apparatus for determining a ventricular function indicator and/or controlling operation of the ventricular assist device at least partially based on a determined ventricular function.

Description of the Prior Art

[0002] The reference in this specification to any prior publication (or information derived from it), or to any matter which is known, is not, and should not be taken as an acknowledgment or admission or any form of suggestion that the prior publication (or information derived from it) or known matter forms part of the common general knowledge in the field of endeavour to which this specification relates.

[0003] Patients with impaired left ventricular function typically have low cardiac output and consequent poor exercise capacity. Some patients with particularly severe dysfunction require mechanical left ventricular assistance to “bridge” them to heart transplantation. Recent advances in mechanical assistance devices have shown‘third-generation’ continuous flow pumps using a rotating impeller are both durable and reliable in providing cardiac output for patients with restoration of functional capacity and exercise capability to allow meaningful rehabilitation before transplantation.

[0004] Example third generation pumps from Ventrassist and HeartWare use an impeller rotating at a fixed speed (approximately 2000 rpm and 2700 rpm respectively) and rely on variations in preload and afterload to control pump output. Flow is related to head pressure, which equates to the difference between aortic and left ventricular pressure, with an increase in preload or decrease in afterload leading to an increase in output. Consequently, even at constant speed, flow through a continuous flow Ventricular Assist Device (cfLVAD) increases with activity, mainly as a result of increased preload. However, this increase is modest in comparison to the physiological response to exercise. The weak preload and strong afterload sensitivities in cfLVADs relative to normal hearts mean that patients implanted with these devices are restricted in their ability to increase cardiac output with exercise when compared to normal subjects.

[0005] Thus, even though cfLVADs lead to improvements in exercise capacity, fatigue remains a limiting factor. The peak VO2 (the maximum rate of oxygen consumption as measured during incremental exercise) achieved one to three months after pump insertion is only about half of the predicted value for normal subjects of the same age and gender and is significantly less than the predicted peak VO2 demonstrated three months post-transplant. Thus, functional capacity is limited in the cfLVAD patient.

[0006] At present, no cfLVAD in clinical use has a physiological pump flow controller incorporated into the device. Research is underway to develop a controller that can automatically adjust pump flow in response to changes in the patient’s haemodynamic state. In order to do this, inputs regarding pump and haemodynamic parameters are required. However, such information is difficult to obtain without implanting a sensor into the subject, which is impractical as a long-term solution. Implanted sensors create difficulties with thrombosis, malfunction, calibration and cost.

[0007] It has been demonstrated that pump flow parameters can be used to derive hemodynamic parameters. However, the derivation of the parameters depends on the opening state of the aortic valve, and so it is useful to be able to determine aortic valve state when a cfLVAD is in use for the purpose of blood pressure calculations, as well as to allow for measurement of contractility and relaxation using load independent algorithms. Additionally, some opening of the aortic valve is generally beneficial as this can lead to reduced instances of thromboembolic events, valve leaflet fusion, leaflet degradation and aortic valve insufficiency, and potentially also gastrointestinal bleeding events.

[0008] US20170239407 describes apparatus for use with a ventricular assist device that is assisting cardiac function of a biological subject, the apparatus including an electronic processing device that determines a flow rate of blood through the ventricular assist device, analyses the flow rate to determine a flow parameter value at least partially indicative of a change in the flow rate during diastole; and uses the flow parameter value to either derive at least one blood pressure parameter value at least partially indicative of a blood pressure in the biological subject or control the ventricular assist device.

[0009] " Assessment of Aortic Valve Opening During Rotary Blood Pump Support Using Pump Signals" by Marcus Granegger et al Artif Organs 20l4;38(4):290-297, “A novel non- invasive method to assess aortic valve opening in HeartMate II left ventricular assist device patients using a modified Karhunen-Loeve transformation” by Bishop et al, J Heart Lung Transplant 20 l0;29(l):27-31 and“Robust aortic valve non-opening detection for different cardiac conditions” by Ooi et al, Artif Organs 20l4;38(3):E57-E67 describes algorithms to determine opening of the aortic valve based on the shape of the systolic portion of the pump flow signal. However, a major limitation of these techniques is the binary classification into an open or closed aortic valve, and this in turn is of only limited assistance when calculating hemodynamic parameters.

[0010] US20180228955 describes apparatus for determining opening of an aortic valve of a biological subject, the apparatus including an electronic processing device that determines a pump speed of a ventricular assist device that is assisting cardiac function of the biological subject, analyses the pump speed to determine a pump speed indicator at least partially indicative of changes in pump speed and uses the pump speed indicator to determine an opening indicator indicative of opening of the aortic valve.

[0011] However, the above techniques only provide limited information regarding the operation of the heart.

[0012] It has been established that continuous-flow left ventricular assist devices demonstrate heightened afterload sensitivity compared to the native left ventricle. According to the pressure head-flow (HQ) relationship unique to each of these devices, an isolated increase in pressure at the outlet cannula results in diminished pump flow. Understanding pump performance and the pump-ventricle interaction in-vivo therefore requires a detailed understanding of all of the factors that contribute to pump afterload. One factor whose effect on pump outlet pressure is incompletely recognized is the pressure gradient across the outflow conduit between pump and aorta. [0013] " Estimation of left ventricular pressure in patients with a continuous flow LVAD" by Kim Pennings, Niels Petterson, Stephanie Schampaert, Sjoerd van Tuijl, Frans van de Vosse, Bas de Mol, Marcel Rutten, describes assessing dynamic left ventricular pressure, using the LVAD as a sensor, by calculating a pump pressure head, an aortic pressure and a pressure drop in the outflow graft. However, this relies on understanding properties of the outflow graft, including the resistance to flow generated within the graft, which is difficult to assess, meaning this cannot easily be used in practice.

[0014] Furthermore, it is increasingly recognized that steady state pump characteristics cannot be directly applied to the dynamic state as inertial effects are unaccounted for. Even when the aortic valve does not open, pump flow remains pulsatile due to the effect of cardiac contraction. It is therefore necessary to quantify the outflow conduit pressure gradient, and therefore the contribution of the outflow conduit to pump afterload, under physiological, pulsatile conditions.

Summary of the Present Invention

[0015] In one broad form, an aspect of the present invention seeks to provide an apparatus for use with a ventricular assist device that is assisting cardiac function of a biological subject, the apparatus including one or more electronic processing devices configured to: determine pressure changes in the ventricle over one or more cardiac cycles using: an aortic pressure derived from a measured blood pressure; a pump head pressure derived based on a pump flow rate; and, outlet fluid conduit pressure losses derived based on a pump flow rate, a fluid conduit diameter and haematocrit amount; determine volume changes in the ventricle at least in part using: a pump blood flow derived based on a pump flow rate; and, an ejection volume based on an aortic valve opening duration; and, use the pressure and volume changes to at least one of: derive a ventricular function indicator indicative of ventricular function; and, control the ventricular assist device.

[0016] In one broad form, an aspect of the present invention seeks to provide a method for use with a ventricular assist device that is assisting cardiac function of a biological subject, the method including, in one or more electronic processing devices: determining pressure changes in the ventricle over one or more cardiac cycles using: an aortic pressure derived from a measured blood pressure; a pump head pressure derived based on a pump flow rate; and, outlet fluid conduit pressure losses derived based on a pump flow rate, a fluid conduit diameter and haematocrit amount; determining volume changes in the ventricle at least in part using: a pump blood flow derived based on a pump flow rate; and, an ejection volume based on an aortic valve opening duration; and, using the pressure and volume changes to at least one of: derive a ventricular function indicator indicative of ventricular function; and, control the ventricular assist device.

[0017] In one broad form, an aspect of the present invention seeks to provide a computer program product for use with a ventricular assist device that is assisting cardiac function of a biological subject, the computer program product including computer executable code which when executed by one or more suitably programmed electronic processing devices, causes the electronic processing devices to: determine pressure changes in the ventricle over one or more cardiac cycles using: an aortic pressure derived from a measured blood pressure; a pump head pressure derived based on a pump flow rate; and, outlet fluid conduit pressure losses derived based on a pump flow rate, a fluid conduit diameter and haematocrit amount; determine volume changes in the ventricle at least in part using: a pump blood flow derived based on a pump flow rate; and, an ejection volume based on an aortic valve opening duration; and, use the pressure and volume changes to at least one of: derive a ventricular function indicator indicative of ventricular function; and, control the ventricular assist device.

[0018] In one embodiment the pressure volume indicator is a pressure volume loop.

[0019] In one embodiment the one or more electronic processing devices are configured to: compare a parameter value to at least one threshold, the parameter value being based on at least one of the pressure and volume changes; and, in response to results of the comparison, at least one of: selectively adjust blood flow through the ventricular assist device; and, selectively generate a notification.

[0020] In one embodiment the parameter value is indicative of at least one of: peak systolic ventricular pressure; stroke work; end diastolic pressure; and, stroke volume. [0021] In one embodiment the threshold is at least one of: indicative of a nominal range; determined based on a parameter value determined from a sample population; and, at least in part based on a parameter value previously determined for the subject.

[0022] In one embodiment the ventricular assist device includes a rotating impeller, and wherein the one or more electronic processing devices are configured to control blood flow through the ventricular assist device by adjusting a pump speed corresponding to a rate of rotation of the impeller.

[0023] In one embodiment the one or more electronic processing devices are configured to at least one of: record a parameter or indicator value; and, display a representation of a parameter or indicator value.

[0024] In one embodiment the one or more electronic processing devices are at least one of: at least part of a ventricular assist device controller; and, coupled to a ventricular assist device controller.

[0025] In one embodiment the one or more electronic processing devices are configured to determine the blood flow rate at least one of: in accordance with signals received from a sensor; by receiving flow rate data from a ventricular assist device controller; and, by calculating a flow rate based on rotation of a ventricular assist device impeller.

[0026] In one embodiment the aortic pressure is derived from a brachial arterial pressure waveform.

[0027] In one embodiment the aortic pressure is derived by filtering a brachial arterial pressure waveform.

[0028] In one embodiment the brachial arterial pressure waveform is measured using a blood pressure cuff.

[0029] In one embodiment the pump head pressure is derived based on the pump flow rate and a pressure head-flow (HQ) curve for the respective ventricular assist device. [0030] In one embodiment the fluid conduit pressure losses are derived based on an equation including terms based on: a pump flow rate; a pump flow rate gradient; a fluid conduit diameter; and, hematocrit.

[0031] In one embodiment the equation is derived using measurements performed using at least one of: a mock circulation loop; and, reference subjects.

[0032] In one embodiment the one or more processing devices are configured to determine volume changes in the ventricle using a measured ventricular end-diastolic volume.

[0033] In one embodiment the ventricular end-diastolic volume is determined using transthoracic echocardiography.

[0034] In one embodiment the pump blood flow is determined using an integral of pump flow rate over time.

[0035] In one embodiment the one or more processing devices are configured to: determine a pump speed of the ventricular assist device; analyse the pump speed to determine a pump speed indicator at least partially indicative of changes in pump speed; and, use the pump speed indicator to determine an opening indicator indicative of opening of the aortic valve.

[0036] In one embodiment the opening indicator is indicative of at least one of a degree, duration and timing of opening of the aortic valve.

[0037] In one embodiment the pump speed indicator is at least one of: indicative of rates of change of pump speed; and, a distribution based on rates of change of pump speed.

[0038] In one embodiment the distribution is at least one of: a frequency distribution; and, a power spectral density distribution.

[0039] In one embodiment the one or more electronic processing devices are configured to: compare the pump speed indicator to at least one threshold; and, determine the opening indicator in response to the results of the comparison. [0040] In one embodiment the pump speed indicator is a distribution, and wherein the one or more electronic processing devices are configured to determine the threshold based on a maximum value of the distribution.

[0041] In one embodiment the pump speed indicator is a power spectral density distribution and wherein the one or more electronic processing devices are configured to: determine a maximum power frequency corresponding to the frequency having a maximum power in the power spectral density distribution; and, determine the threshold based on the maximum power frequency.

[0042] In one embodiment the pump speed indicator is a distribution of rates of change of pump speed and wherein the one or more electronic processing devices are configured to: determine a portion of the distribution greater than the threshold; and, determine the opening indicator using the portion.

[0043] In one embodiment the one or more electronic processing devices are configured to: calculate an area under curve for the portion; and, use the area under curve to determine the opening indicator.

[0044] In one embodiment the one or more electronic processing devices are configured to: determine the flow rate of blood through the ventricular assist device; and, use the rate of flow of blood to identify individual cardiac cycles.

[0045] In one embodiment the one or more electronic processing devices are configured to identify individual cardiac cycles from flow rate minima.

[0046] It will be appreciated that the broad forms of the invention and their respective features can be used in conjunction and/or independently, and reference to separate broad forms is not intended to be limiting. Furthermore, it will be appreciated that features of the method can be performed using the system or apparatus and that features of the system or apparatus can be implemented using the method. Brief Description of the Drawings

[0047] Various examples and embodiments of the present invention will now be described with reference to the accompanying drawings, in which: -

[0048] Figure 1 is a schematic diagram of an example of apparatus for use with a ventricular assist device (VAD);

[0049] Figure 2 is a flow chart of an example of a method for determining a ventricular function indicator;

[0050] Figure 3 is a schematic diagram of an example of a ventricular function indicator in the form of a pressure volume loop;

[0051] Figure 4 is a flow chart of an example of a method of controlling a VAD based on a ventricular function;

[0052] Figure 5 is a flow chart of an example of a method for determining changes in ventricular pressure;

[0053] Figure 6 is an image illustrating an example of a measured outlet conduit diameter;

[0054] Figure 7 is a graph illustrating mean and peak outlet conduit pressure gradients for varying outlet conduit diameters;

[0055] Figures 8A and 8B are graphs illustrating examples of standardized coefficients for independent variables in linear regression models for mean and peak systolic gradient in lOmm Polyvinylchloride (PVC) and VAD outlet conduits respectively;

[0056] Figure 9 is a graph illustrating an example of mean conduit pressure gradient against mean pump flow for PVC and VAD conduits across varying pump speed, left ventricular (LV) contractility, conduit diameter and conduit length;

[0057] Figure 10A is a graph illustrating an example of mean and peak outlet conduit pressure gradients across an VAD conduit of varying minimal diameter; [0058] Figure 10B is a graph illustrating an example of mean conduit pressure gradient against mean pump flow for varying minimum VAD outlet conduit diameters;

[0059] Figure 10B is a graph illustrating an example of peak outlet conduit pressure gradient against peak pump flow for varying minimum VAD conduit diameters;

[0060] Figure 1 1 is a graph illustrating an example of a performance of a non-linear model for predicting instantaneous outlet conduit pressure gradients on testing data;

[0061] Figure 12 is a flow chart of an example of a method for determining changes in ventricle volume;

[0062] Figure 13 is a graph illustrating the calculation of pump blood flow over a cardiac cycle;

[0063] Figure 14 is a graph of an example of the frequency response of a VAD during aortic valve opening;

[0064] Figure 15 is a schematic diagram illustrating an example of changes in pressure volume loops following a change in VAD rotational speed;

[0065] Figure 16A is a graph illustrating an example of changes in left ventricular end diastolic volume following a change in VAD rotational speed;

[0066] Figure 16B is a graph illustrating an example of changes in peak systolic left ventricular pressure following a change in VAD rotational speed;

[0067] Figure 16C is a graph illustrating an example of changes in left ventricular stroke work following a change in VAD rotational speed;

[0068] Figure 16D is a graph illustrating an example of changes in maximum left ventricular pressure gradient following a change in VAD rotational speed;

[0069] Figure 17 is a schematic diagram illustrating an example of changes in pressure volume loops following administration of Milrinone; [0070] Figure 18A is a graph illustrating an example of changes in left ventricular end diastolic pressure following administration of Milrinone;

[0071] Figure 18B is a graph illustrating an example of changes in left ventricular end diastolic volume following administration of Milrinone;

[0072] Figure 18C is a graph illustrating an example of changes in maximum left ventricular pressure gradient following administration of Milrinone;

[0073] Figure 18D is a graph illustrating an example of changes in peak left ventricular elastance following administration of Milrinone;

[0074] Figure 19A is a schematic diagram illustrating an example of changes in pressure volume loops following a change in VAD rotational speed;

[0075] Figure 19B is a schematic diagram illustrating an example of changes in pressure volume loops in response to exercise stress; and,

[0076] Figure 19C is a schematic diagram illustrating an example of changes in pressure volume loops for patients undergoing left ventricular recovery.

Detailed Description of the Preferred Embodiments

[0077] An example of an apparatus for use with a VAD will now be described with reference to Figure 1.

[0078] In this example, the apparatus includes a processing system 100 that is coupled to a VAD 120, which is in turn connected to the heart 130 of a subject. In this example, the VAD is coupled via respective inlet and outlet cannulas 121, 122 to the left ventricle 131 and aorta 132, and is therefore functioning as a left ventricular assist device (LVAD), although this is not essential and similar techniques to those described can also be applied to right ventricular assist devices (RVADs) coupled to the right ventricle and pulmonary artery. The VAD is a continuous flow VAD (cfVAD) in which an impeller is continuously rotated within a cavity, to thereby pump blood from the ventricle into the aorta. The VAD 120 can be a standard VAD known in the art, such as a Heartware HVAD, Ventracor Ventrassist, or the like, and this will not therefore be described in further detail.

[0079] In this example, the processing system 100 is coupled to the VAD 120 via a controller 110, via a wired or wireless connection. The controller 110 operates to control the VAD and in particular control rotation of the impeller and optionally monitor operating characteristics of the VAD. This arrangement is not essential and alternatively the processing system 100 and controller 110 can be implemented as a single piece of hardware, although it will be appreciated that use of a separate processing system that interfaces with an existing controller can reduce regulatory requirements needed for implementation.

[0080] In use, the processing system 100 includes one or more electronic processing devices. For ease of illustration the remaining description will refer generally to a processing device, but it will be appreciated that multiple processing devices could be used, with processing distributed between the devices as needed, and that reference to the singular encompasses the plural arrangement and vice versa. The processing device is typically a microprocessor that is adapted to determine information regarding the flow rate of blood through the VAD 120 and then use this to either control operation of the VAD, or determine ventricular blood pressure parameter values, as will now be described with reference to Figure 2.

[0081] In this example, at step 200, the electronic processing device determines an aortic pressure derived from a measured blood pressure. This is typically performed non-invasively and can be performed in any appropriate manner, such as by processing blood pressure signals measured using a blood pressure cuff.

[0082] At step 210, the processing device determines a pump head pressure derived based on a pump flow rate. This is typically a standard calculation performed based on a known pump pressure head flow curve and a pump flow rate, although other suitable techniques could be used.

[0083] At step 220, the processing device determines outlet fluid conduit pressure losses derived based on the pump flow rate, a fluid conduit diameter and haematocrit amount. [0084] The flow rate can be determined in any suitable manner and can be obtained from sensors incorporated within the VAD 120, or alternatively could be derived from operating characteristics of the VAD 120, for example by monitoring rotation of the impeller as described for example in US-8,506,470. The flow rate could be calculated by the electronic processing device or alternatively could be received as flow rate data from the controller 110, depending on the preferred implementation.

[0085] The fluid conduit diameter could be determined based on information regarding the conduit or could be measured prior to implantation. More typically however, measurements are performed once the conduit is implanted in order to account for the particular configuration of the conduit within the patient. This can be achieved using any suitable measurement process, such as ultrasound optionally performed as part of a transthoracic echocardiogram, contrast enhanced Computer X-ray Tomography (CT) imaging, or the like. The haematocrit amount represents a ratio of the volume of red blood cells to the total volume of blood and can be measured and/or estimated using a variety of known techniques.

[0086] It will be appreciated that as the conduit diameter is typically static, this generally only needs to be measured a single time, whilst haematocrit amount is typically relative constant over short time frames and could therefore be measured periodically, such as once each time ventricular function is to be measured, whereas the flow rate is measured substantially constantly over the cardiac cycle.

[0087] The way the fluid conduit pressure losses are calculated will vary depending on the preferred implementation, but this is typically achieved using an equation derived using regression or other analysis techniques, based on measurements performed using different outlet fluid conduits operating under a range of different conditions. In this regard, it has been established that using an equation derived empirically from measurements performed on outlet conduits can provide a more effective assessment of the impact of the conduit configuration on pressure losses within the conduit, than relying on theoretical formulae, which are difficult to apply in practice.

[0088] The processing device combines the aortic pressure, pump pressure and outlet conduit pressure losses in order to derive pressure changes in ventricle over time at step 230. [0089] At step 240, the processing device determines a pump blood flow through the pump over the current cardiac cycle, based on a pump flow rate, for example by integrating the pump flow over time following the end of diastole. Again, the pump flow rate can be derived using sensors incorporated within the VAD 120, or alternatively could be derived from operating characteristics of the VAD 120.

[0090] At step 250, the processing device determines an ejection volume based on an aortic valve opening duration. This can be calculated in any appropriate manner, but typically relies on a known relationship between an aortic valve opening duration and ejection volume, with the aortic valve opening duration being determined based on an analysis of changes in pump speed. In one particular example, this is achieved by analyzing a pump speed waveform in the form of a frequency distribution, such as a power spectral density distribution, indicative of a distribution of the frequencies of the changes in pump speed, as will be described in more detail below. This technique is described in more detail in US20180228955, the contents of which are incorporated herein by cross reference.

[0091] At step 260, the processing device uses the pump flow and ejection volume in order to determine volume changes in the ventricle over the cardiac cycle.

[0092] At step 270, the processing device uses the pressure and volume changes to derive a ventricular function indicator, indicative of ventricular function. The form of the indicator can vary depending on the preferred implementation, but in one example, the indicator is in the form of a pressure volume loop, and an example loop is shown in Figure 3.

[0093] In this example, the loop shows changes in volume and pressure over a single cardiac cycle. In this regard, end of diastole 301 is followed by isovolumetric contraction, until the aortic valve opens at 302. Ejection of blood from the ventricle results in a decrease in ventricle volume until the end of systole is reached at 303. The ventricle then undergoes isovolumetric relaxation until the mitral valve opens at 304, and ventricle filling commences. It will be appreciated that the pressure volume loop shown in Figure 3 is an idealised loop and the shape and size of the loop will vary in practical situations. [0094] In any event, the shape, size and position of the loop can be used to provide important information regarding the functioning of the ventricle. For example, the point 311 represents the end diastolic volume (EDV), whilst the peak 312 represents the peak systolic ventricular pressure. The lateral extent 313 of the loop is indicative of stroke volume, whilst the area 314 of the loop represents the stroke work.

[0095] It will therefore be appreciated that the above described process uses information regarding operation of the pump, including the flow and pump speed, together with additional information including blood pressure, haematocrit amount and outlet conduit diameter, in order to derive information regarding operation of the ventricle. As these parameters can be measured non-invasively, this in turn allows important physiological information regarding ventricular function to be derived without requiring the need for a sensor to be implanted within the patient. This can be used to provide useful feedback to a clinician when assessing a patient.

[0096] Additionally, and/or alternatively, the processing device can use the pressure and volume changes at step 280 to control operation of the ventricular assist device 120. This can be used to adjust the pumping capacity of the VAD to accommodate changes in physiological status, for example to avoid suck-down events, provide additional pumping during exercise, or the like.

[0097] In this regard, the ventricular assist device generally includes a rotating impeller, in which case the electronic processing device controls blood flow through the ventricular assist device by causing a rate of rotation of the impeller to be adjusted. An example of this will now be described with reference to Figure 4.

[0098] In this example, at step 400 the electronic processing device monitors ventricular pressure and/or volume changes using the above described process. At step 410, the electronic processing device determines one or more parameters relating to the pressure and/or volume, such as values for one or more of peak systolic ventricular pressure, end diastolic pressure, stroke work, stroke volume or myocardial oxygen consumption. [0099] At step 420, it is determined if there has been a change in the flow parameter value. If not, no action is required, and the process returns to step 400. Otherwise, the process moves to step 420 to adjust the pump speed based on the changes.

[0100] For example, if the stroke work has increased, this can be indicative of ventricular function improving, in which case the speed of impeller rotation could be reduced to reflect that the ventricle is performing more work and requires less assistance.

[0101] In one example, the processing device compares a derived parameter to a threshold and then controls the pump based on the outcome of the comparison. For example, the threshold can be indicative of a nominal range, determined based on a parameter value determined from a sample population or at least in part based on a parameter value previously determined for the subject. Accordingly, in this example, in the event the measured parameter value falls outside a threshold range, a change in impeller speed could be performed to alter blood flow through the device and hence attempt to bring the parameter value back within the normal range. A similar technique could be used to generate a notification, for example to indicate that there is a blood pressure problem, suction event or the like, which can be useful in monitoring patient welfare and operation of the VAD.

[0102] The electronic processing device can also be adapted to record a parameter or indicator value, display a representation of a parameter or indicator value, allowing operation of the VAD and patient wellbeing to be recorded and subsequently reviewed. This can assist in identifying causes of adverse events, and hence taking action to mitigate these in future.

[0103] In any event, it will be appreciated that the above described method can be used to determine parameter values relating to ventricular function that cannot otherwise be derived without the need to implant sensors within the heart, which is extremely undesirable, as well as allowing the operation of the VAD to be controlled to thereby optimize the assistance provided to the heart.

[0104] A number of further features will now be described.

[0105] In the above described example, the processing system 100 includes at least one microprocessor 101, a memory 102, an optional input/output device 103, such as a keyboard and/or display, and an external interface 104, interconnected via a bus 105 as shown. In this example the external interface 104 can be utilised for connecting the processing system 100 to the controller 110 and optionally to peripheral devices, such as the communications networks, databases, or the like. Although a single external interface 104 is shown, this is for the purpose of example only and in practice, multiple interfaces using various methods (e.g. Ethernet, serial, USB, wireless or the like) may be provided.

[0106] In use, the microprocessor 101 executes instructions in the form of applications software stored in the memory 102 to allow flow rate data to be received from the controller 110 and used to calculate flow and other parameter or indicator values, as well as to generate control signals that can be transferred to the controller 110, allowing the operation of the VAD 120 to be controlled. The applications software may include one or more software modules, and may be executed in a suitable execution environment, such as an operating system environment, or the like.

[0107] Accordingly, it will be appreciated that the processing system 100 may be formed from any suitable processing system, such as a suitably programmed computer system, PC, web server, network server, or the like. However, it will also be understood that the processing system could be any electronic processing device such as a microprocessor, microchip processor, logic gate configuration, firmware optionally associated with implementing logic such as an FPGA (Field Programmable Gate Array), or any other electronic device, system or arrangement.

[0108] Additionally, and/or alternatively, the processing system 100 and controller 110 can be integrated into a single device. Thus, for example, the method of Figure 2 could be performed using an existing heart pump controller modified to allow for the flow and blood pressure parameter values to be calculated. This could be achieved using a firmware and/or software upgrade or the like, as will be appreciated by persons skilled in the art.

[0109] An example of the process for determining pressure changes within the ventricle will now be described in more detail with reference to Figure 5. [0110] In this example, at step 500 an outlet conduit diameter is measured, typically by performing an echocardiogram, CT scan, or similar. An example, CT scan is shown in Figure 6, highlighting that the diameter d is typically measured at the narrowest point. This process is performed after the pump has been implanted and does not need to be repeated each time measurements are performed, although if the pump remains in situ long-term, measurement of the conduit diameter may need to be repeated (such as at 6 monthly intervals) due to tissue ingrowth into the conduit.

[0111] At step 510, a haematocrit amount, such as a percentage, is measured using known techniques, with this typically being performed a single time prior to each measurement session.

[0112] At step 520, a blood pressure waveform is measured, with the resulting signal being passed to the processing system 100, which filters the waveform at step 530 and calculates an aortic pressure at step 540.

[0113] In this regard, as mentioned above, an aortic pressure can be derived from a measured pressure. In one example, the aortic pressure is derived from a brachial arterial pressure waveform, by filtering the waveform, for example using a low pass filter. The waveform can be measured non-invasively using a suitable blood pressure cuff type arrangement, such as a Sphygmocor Xcel™.

[0114] Simultaneously, at step 550, the pump flow rate is determined, with this typically being based on rotation of the impeller, with the flow rate being provided by the controller 110. An instantaneous flow rate gradient is calculated at step 560, with the flow rate and flow rate gradient being used in an equation together with the outlet conduit diameter and haematocrit amount to generate the conduit pressure losses at step 570. In particular, the fluid conduit pressure losses are derived based on an empirical equation derived from measurements performed using a mock circulation loop and/or reference subjects as will be discussed below.

[0115] Simultaneously, the pump flow rate is used together with the pump flow curve, to generate a pump head pressure at step 580. The pump head pressure is typically derived based on the pump flow rate and a pressure head-flow (HQ) curve for the respective ventricular assist device. An example of this is described in Granegger, M., et al., Development of a pump flow estimator for rotary blood pumps to enhance monitoring of ventricular function. Artif Organs, 2012. 36(8): p. 691-9, the contents of which is incorporated herein by cross reference.

[0116] The aortic pressure is generated by a combination of the pump head pressure less the outlet conduit losses and ventricular pressure, so that once the aortic pressure, pump pressure and conduit losses are known, these can be used to calculate the ventricular pressure using the equation:

VP = AP - (H - OCP)

where: VP = Ventricular Pressure

AP = Aortic Pressure

H = Pump Head

OCP = Outlet Conduit Pressure loss

[0117] As mentioned in the above example, the outlet conduit pressure loss is derived using an empirical formula, and an example of a process for deriving such an equation will now be described.

[0118] For the purpose of this example, a study was performed using a known mock circulation loop (MCL) incorporating HeartWare HVADs (Medtronic, Minneapolis, MN) for left and right ventricular support, and a total artificial heart pneumatic driver (SynCardia Systems, Tucson, A Z) to generate intraventricular pressure in systole via external compression of model left and right ventricles. Steady-state, continuous 50Hz measurements of LVAD speed and current, and pressures within the left ventricle (LV), proximal and distal conduit and proximal aorta were obtained. Calculation of instantaneous pump flow including correction for haematocrit amount was performed offline using a validated HVAD flow estimator algorithm. The MCL fluid was a 40% (w/w) Glycerol solution.

[0119] Initial experiments were conducted using a polyvinyl chloride (PVC) LVAD outflow conduit. Data were obtained at varying conduit diameter (8, 10 and 12.7mm), conduit length (30 and 40cm), pump speed (2200, 2600, 3000 and 3400RPM), left ventricular (LV) contractility (delivered pressure from Syncardia driver of 0, 120, 160, 200 and 240mmHg), hematocrit (30, 35 and 40%, achieved through variation in temperature of the Glycerol solution using a heat-bath) and heart rate (40, 80 and l20beats/min). RVAD speed, pulmonary vascular resistance (PVR) and systemic vascular resistance (SVR) were varied to maintain left atrial pressure and mean arterial pressure within physiological limits (0- 20mmHg and 80-90mmHg respectively). The range of each parameter was selected in order to reflect that encountered in clinical practice, rather than to obtain pre-specified pump flow rates.

[0120] Data were analyzed using multiple linear regression (MLR) to identify those variables that were significantly associated with peak and mean conduit pressure gradient. The PVC conduit was then replaced with a HeartWare HVAD Gelweave™ conduit, which was rendered waterproof by externally coating with a compliant silicone-based sealant. Those variables determined to be significant in the PVC experiments were reassessed. After completion of baseline (lOmm) PVC vs HVAD conduit experiments, a further variation in Gelweave conduit internal diameter (to 9 and 8mm) was achieved through external compression of the conduit at a single point close to its distal anastomosis with the aorta, to mimic the effect of conduit stenosis - either surgical or extrinsic. The required diameter was achieved by compressing around a cylinder of known diameter to the point where the cylinder was no longer able to be easily removed from the outflow graft. The dependent variables of interest were peak systolic gradient, mean gradient across the cardiac cycle, and instantaneous gradient.

[0121] In order to develop and validate a model for prediction of instantaneous gradient, the entire dataset was split randomly into training (70%) and testing (30%) subsets. Variables that had been shown to be predictive of mean and peak systolic gradient were included in the initial non-linear (quadratic) model, and coefficients determined through fitting of the training set. Each coefficient was then subject to a Student’s t-test, testing against the null hypothesis that the coefficient was zero. Those variables whose coefficients were non significant (p>0.05) in this model were excluded in a stepwise fashion. The final quadratic model was then assessed using the testing dataset. [0122] Data were processed in MATLAB (MathWorks, Natick, MA) and statistical analysis performed using Excel (Microsoft, Redmond, WA) and MATLAB. Statistical analysis was performed using multiple linear regression for peak and mean gradient, and non-linear regression for instantaneous gradient. A p-value of <0.05 was considered statistically significant.

[0123] Across the PVC conduit, diameter (d) was negatively and non-linearly associated with both mean and peak gradient as shown in Figure 7. Across the lOmm PVC conduit, both mean and peak gradient correlated linearly with mean pump flow (Qmean), systolic dQ/dt, conduit length and haematocrit amount (p<0.00l for each, r² = 0.954 (mean), r² = 0.927 (peak)). Heart rate did not correlate significantly with either mean or peak gradient. Mean gradient was most strongly predicted by mean flow, whereas peak gradient was most affected by peak systolic dQ/dt, as shown in Figure 8A.

[0124] Based on these results, the following variables were assessed using the HVAD conduit: d, Qmean, systolic dQ/dt, conduit length and haematocrit amount (Hct). When assessed at matched pump speeds and LV contractilities, there were no statistically significant differences between the PVC and HVAD conduit experiments in terms of mean pump flow (4.13 vs 3.98L/min, p=0.54), peak systolic dQdt (26.7 vs 25.9L/min/s, p=0.8 l), mean conduit gradient (19.5 vs 22.5mmHg, p=0. l6) or peak systolic gradient (39.8 vs 4l . lmmHg, p=0.70), as shown in Figure 9. Minimum HVAD conduit diameter was negatively and non-linearly associated with both mean and peak gradient, as shown in Figure 10A, in a flow-dependent fashion, as shown in Figures 10B and 10C. In MLR, mean gradient across the lOmm conduit correlated linearly with Qmean (p<0.00l), systolic dQdt (p<0.00l), conduit length (p=0.00l) and Hct (p<0.00l) (r² = 0.907) as shown in Figure 8B. Peak gradient correlated linearly with Qmean, systolic dQdt and conduit length (p<0.00l for each, r² = 0.925).

[0125] HQ curves were constructed in order to visualize the effects of taking into account conduit pressure gradient on this relationship. For baseline HQ curves, pressure head was measured across the pump alone, with the proximal (inlet) pressure recorded within the LV cavity, and the distal (outlet) pressure recorded immediately proximal to the outflow conduit. These showed a degree of hysteresis, which was reduced at higher pump speeds. The pressure head was then re-measured with the distal (outlet) pressure recorded immediately distal to the outflow conduit, in order to account for conduit pressure gradient. The resulting ‘pump-conduit’ HQ curves demonstrated increased hysteresis compared to the original ‘pump alone’ curves, with decreased systolic flow for a given pressure head at all pump speeds.

[0126] An initial quadratic model for predicting instantaneous pressure gradient across an HVAD conduit of varying minimum diameter and length, at varying pump speed, left ventricular contractility and pump speed was derived, and consisted of the following terms: hematocrit, pump speed, instantaneous flow, dQ/dt, 1 !{d† and flo\\/(ri)⁴.

[0127] Following exclusion of non-significant terms, the following equation was derived:

VP = k + a* h + b* dQ/dt + dcP + e*Q/c + fh² + g*Q² + i* dQ/dt² + f(QlcP)² where: VP = instantaneous ventricular pressure

/2=hematocrit (%)

Q= pump flow (L/min)

dQ ri/=dcrivativc of pump flow with respect to time (L/(min.s)) ri=minimum conduit diameter (mm)

t= time (s)

[0128] Values of the coefficients k, a, b, c, e. f. g. i,j, are specific to the experimental set-up and it would be appreciated that in practice that values would be derived by studying a reference population of HVAD users. Nevertheless, the resulting model was highly predictive of the instantaneous pressure gradient across the HVAD conduit in the testing dataset (r² = 0.83, RMSE 7.3), as shown in Figure 11.

[0129] This study raises a number of key findings. First, under pulsatile conditions, hemodynamically significant gradients are generated across an unobstructed HVAD outflow conduit. Second, conduit diameter has a significant, negative, non-linear effect on the magnitude of this gradient, while mean pump flow, systolic dQ/dt and conduit length each have positive, linear effects of varying degree. Third, the instantaneous outflow conduit gradient can be predicted with a high degree of accuracy using input variables that are readily obtainable in clinical practice.

[0130] Across the lOmm HVAD outflow conduit peak gradients were observed of up to 53.4mmHg and mean gradients of up to 33. lmmHg. With constriction of the distal conduit to 8mm diameter these values increased to 92.5mmHg and 62. lmmHg respectively. The implication of the hemodynamically significant gradients observed in the study is that additional afterload imposed on the pump may lead to a reduction in pump flow.

[0131] The most significant factors affecting conduit pressure gradient were conduit diameter, mean pump flow and systolic dQ/dt. Conduit diameter had a negative, non-linear effect that was flow-dependent, as demonstrated in Figures 10B and 10C, in keeping with the Hagen-Poiseuille equation. The non-linear effect of diameter was observed in both the PVC conduit experiments, in which the diameter was constant for the entire length of the conduit, and the HVAD conduit experiments, in which the distal conduit was constricted externally at one point only.

[0132] It can be inferred then, that significant increases in conduit pressure gradient in-vivo may occur as a result of focal processes such as thrombus formation, kinking or tissue ingrowth that reduce the effective conduit diameter at a single point, even when the absolute magnitude of this reduction is small. The reduction in pump flow demonstrated with the reported twisting of the HM3 conduit demonstrates the importance of these local factors on overall pump function. Given the non-linear effect of conduit diameter, it is possible that employing a larger calibre outflow conduit - such as that used in the Heartmate 3 device - may provide a degree of protection against conduit-driven reductions in pump flow.

[0133] The association between conduit pressure gradient and both mean pump flow and systolic dQ/dt can be accounted for by applying to the outflow conduit the principles of the four-element Windkessel model of the circulation. The positive association with mean pump flow most likely represents effects of resistance within the conduit, in keeping with the Hagen-Poiseuille equation. The positive association with systolic dQ/dt, meanwhile, is likely related to the effect of pulsatile inertance, whose effects in a cylindrical tube can be quantified as the differential of flow multiplied by fluid density and tube length, divided by cross-sectional area.

[0134] Comparison of HQ curves taking into account pressure head across the pump alone and pressure head across the entire pump-conduit system permits visualization of the effects of conduit resistance and inertance at different pump speeds. At all pump speeds, the baseline HQ curves demonstrated a degree of hysteresis, in keeping with findings from previous studies in dynamic circulatory systems. Taking into account the pressure gradient across the conduit resulted in increased size of the hysteresis loops at all pump speeds. As mentioned earlier, there was decreased systolic flow for a given pressure head at all pump speeds, reflecting the effects of both inertance and resistance within the conduit during this phase of the cardiac cycle.

[0135] These effects may have significant implications for the pump-patient interaction, the management of patients supported with cfLVADs and the design of future cfLVAD controllers. For a given set of loading conditions, pump flow can be augmented through either increased pump speed or increased ventricular contractility. As demonstrated, each of these mechanisms results in increased conduit pressure gradient, the former primarily via resistance effects and the latter via inertance effects. The result, therefore, is a negative feedback loop which may result in‘diminishing returns’ in terms of flow augmentation. These effects are likely to be particularly marked during exercise due to its effects on pump flow and may explain why a majority of patients continue to experience exertional heart failure symptoms on cfLVAD support despite adequate ventricular unloading at rest. This concept of diminishing returns also has important consequences for the design of ‘smart’ cfLVAD controllers, in which changes in pump output in response to physiological demands are driven by alterations in pump speed.

[0136] The results have implications for pump-related complications such as stroke and pump thrombus. There is a demonstrated association between systemic hypertension and both haemorrhagic and ischemic stroke, with a possible mechanism for the latter being reduced pump flow and therefore reduced pump washing. Via the same hypothesized mechanism, it is possible that increased conduit gradient may result in increased risk of thrombus formation within the pump via reduced diastolic pump flow.

[0137] In any event, the above technique uses a quadratic non-linear model, including the inverse of the fourth power of conduit diameter ( 1/ri⁴) an interaction term (Q/ri⁴) to predict instantaneous conduit pressure gradient with a high degree of accuracy. Each of the input variables in the model (conduit diameter, Q, dQdt, hematocrit, pump speed) is readily available in clinical practice.

[0138] Conduit diameter is most reliably estimated using contrast-enhanced computerized tomography (CT). Conduit length, despite being a significant predictor of peak and mean gradient in linear models, did not add to the accuracy of the model for instantaneous gradient and was therefore excluded due to the practical difficulty in measuring this variable in human subjects. Our derivation studies used 30 and 40cm lengths, which approximate clinical measurements. Accurate estimation of instantaneous conduit pressure gradient using our model may permit the use of aortic pressure and pump flow to calculate instantaneous left ventricular pressure, which would in turn provide significant insight into left ventricular systolic function and the adequacy of ventricular unloading.

[0139] An example of the process for determining volume changes within the ventricle will now be described in more detail with reference to Figure 12.

[0140] In this example, volume changes are measured relative to a measured ventricular end- diastolic volume (VDEV), which acts as a baseline. This can be achieved by performing transthoracic echocardiography at step 1200 and using results of this to calculate VDEV at step 1210.

[0141] At step 1220, the pump flow rate is determined, which as described above can be based on signals received from the controller 110 and/or based on a measured pump speed. The pump flow rate can be used to identify the cardiac cycle at step 1230. For example, the processing device can use the flow rate maxima and/or minima to determine a period of the cardiac cycle corresponding to diastole, for example by defining diastole as a period of the cardiac cycle from the flow rate minima to a proportion of the flow rate maxima. The proportion could be a mid-point, or a quarter of the flow rate maxima, however other proportions or time periods could be used, depending on the preferred implementation. For example, the end points used could be adjusted dynamically based on other measured parameters, such as heart rate or the like, thereby maximizing the length of time over which the gradient is calculated, whilst ensuring that the time period accurately corresponds to diastole and is not affected by onset of systole, plateaus in flow rate, or the like. Alternatively the cardiac cycle could be defined using the I^st, 2^nd or 3^rd derivative of the flow rate; for example, the onset of systole could be defined as the point where the 3^rd derivative crosses zero, representing a local maximum of the 2^nd derivative, while the end of systole could be defined as the local minimum of pump flow rate.

[0142] Following this, at step 1240, the flow rate is integrated from the end of diastole, to calculate the amount of blood flow out of the ventricle through the pump, from the point at which the ventricle was at the end diastolic volume (VDEV), and an example of this is shown in the highlighted section of the waveform in Figure 13.

[0143] Simultaneously, at step 1250, the pump speed is measured. The pump speed, and in particular the rate of rotation of the impeller, can be determined in any suitable manner and can be obtained from sensors incorporated within the VAD 120, or alternatively could be derived from operating characteristics of the VAD 120. The pump speed could be calculated by the electronic processing device or alternatively could be received as pump speed data from the controller 110, depending on the preferred implementation.

[0144] At step 1260, the electronic processing device analyses the pump speed to determine a pump speed indicator at least partially indicative of changes in pump speed. This can be achieved in any suitable manner, but typically involves using cardiac cycles corresponding to individual heart beats, as determined for example at step 1230, and then analysing these to determine rates of change of pump speed during the cardiac cycles. The pump speed indicator can be of any appropriate form, and could include a pump speed waveform, waveform gradient information, or the like. In one particular example, the pump speed waveform is in the form of a frequency distribution, such as a power spectral density distribution, indicative of a distribution of the frequencies of the changes in pump speed, in which case the electronic processing device performs a frequency transform on the pump speed data, such as a Fast Fourier Transform (FFT), to thereby determine the pump speed indicator.

[0145] At step 1270, the electronic processing device uses the pump speed indicator to determine opening of the aortic valve. In this regard, opening of the aortic valve allows blood to flow from the left ventricle into the aorta, thereby bypassing the VAD 120. This in turn causes a change in the pressure head across the VAD 120, thereby altering the pump flow. Whilst, the pump pressure head and consequently the pump flow also influences pump speed, this typically occurs at a different rate. Thus, a change in the pump speed, such as a change in the rate of rotation of an impeller, can be used to identify when the aortic valve opens. Accordingly, by analysing the pump speed indicator, this allows the electronic processing device to determine opening of the aortic valve.

[0146] In one example, the processing device compares the pump speed indicator to at least one threshold. The threshold can represent a particular rate of change of pump speed or frequency 1401 in the frequency distribution shown in Figure 14, above which the change is likely to have been caused by aortic valve opening as opposed to some other factor. Thus, this allows the processing device to examine the pump speed indicator and use this to set the threshold, making the threshold specific to the subject and even the current cardiac cycle. This helps reduce the likelihood of inaccurate assessment, whilst ensuring that the methodology works for a range of different subjects in a range of different conditions.

[0147] In one example, the processing device determines the threshold based on a maximum value in the distribution. In particular, the electronic processing device determines a maximum power frequency corresponding to the frequency having a maximum power in the power spectral distribution and determines the threshold based on the maximum power frequency. This can be performed for each individual beat, or alternatively can be performed based on a mean PSD calculated over a number of beats and is typically limited to frequencies below 3.5 Hz. The threshold is then determined to be twice the maximum value.

[0148] The electronic process device then uses the result of the comparison to determine the opening indicator. In one example, the processing device determines a portion of the distribution greater than the threshold and determines the opening indicator using this portion, for example by using this to assess and hence quantify the degree and/or duration of opening of the aortic valve. Specifically, the processing device can determine a portion of the frequency distribution above the threshold and then calculates an area under curve (AUC) for the portion, with the AUC correlating with the degree of opening.

[0149] At step 1280, an ejection volume is calculated. In one example, the ejection volume was calculated empirically using a relationship derived from a study performed on patients using echocardiography and pump speed measurements. In one particular example, the ejection volume was calculated using the equation:

EV= 10.3 * In (AUC) + 10.6

where: EV= ejection volume

[0150] Having determined the volume blood flowing through the pump and the ejected from the ventricle, this can be used in conjunction with the VDEV to calculate a current ventricle volume at step 1290.

[0151] Changes in ventricular volume and pressure can then be used to derive pressure volume curves, which can in turn be used to assist in understanding the functionality of the ventricle, as well as the ability to detect predictable haemodynamic changes induced by factors, such as pump speed changes and administration of an inotropic agent.

[0152] To assess this further, a study was performed with patients being assessed at different pump speeds, and pre- and post-administration of 50mcg/kg intravenous Milrinone.

[0153] Results of changes in pump speed are shown in Figure 15, which shows mean pressure volume loops at 2700RPM and 2300RMP at 1501 and 1502. Corresponding measurements for UVEDV, peak systolic left ventricular pressure, stroke work and maximum rate of change of pressure (dp/dt) are shown in Figures 16A to 16DB, with results 1601 for higher speed and results 1602 for lower speed. These results show an increase in pump speed is accompanied by a decrease in LVEDV and stroke work, and to a lesser degree peak systolic left ventricular pressure and maximum dp/dt, as a result of load being reduced on the ventricle due to the additional work performed by the pump. [0154] Results of application of Milrinone are shown in Figure 17, which shows mean pressure volume pre and post Milrinone at 1701 and 1702. Corresponding measurements for LVEDP, LVEDV, maximum dp/dt and peak LV elastance are shown in Figures 18A to 18D, with results pre- Milrinone 1801 and post- Milrinone 1802. These results show a decrease in LVEDP, LVEDV but increase in maximum dp/dt and elastance.

[0155] Figures 19A to 19C similarly show the impact of increasing pump speed, exercise and differences between subjects, highlighting that the above described techniques can be used to derive useful information regarding ventricular function, non-invasively.

[0156] Throughout this specification and claims which follow, unless the context requires otherwise, the word“comprise”, and variations such as“comprises” or“comprising”, will be understood to imply the inclusion of a stated integer or group of integers or steps but not the exclusion of any other integer or group of integers. As used herein and unless otherwise stated, the term "approximately" means ±20%.

[0157] Persons skilled in the art will appreciate that numerous variations and modifications will become apparent. All such variations and modifications which become apparent to persons skilled in the art, should be considered to fall within the spirit and scope that the invention broadly appearing before described.

Claims

THE CLAIMS DEFINING THE INVENTION ARE AS FOLLOWS:

1) Apparatus for use with a ventricular assist device that is assisting cardiac function of a biological subject, the apparatus including one or more electronic processing devices configured to:

a) determine pressure changes in the ventricle over one or more cardiac cycles using: i) an aortic pressure derived from a measured blood pressure;

ii) a pump head pressure derived based on a pump flow rate; and,

iii) outlet fluid conduit pressure losses derived based on a pump flow rate, a fluid conduit diameter and haematocrit amount;

b) determine volume changes in the ventricle at least in part using:

i) a pump blood flow derived based on a pump flow rate; and,

ii) an ejection volume based on an aortic valve opening duration; and,

c) use the pressure and volume changes to at least one of:

i) derive a ventricular function indicator indicative of ventricular function; and, ii) control the ventricular assist device.

2) Apparatus according to claim 1, wherein the pressure volume indicator is a pressure volume loop.

3) Apparatus according to claim 1 or claim 2, wherein the one or more electronic processing devices are configured to:

a) compare a parameter value to at least one threshold, the parameter value being based on at least one of the pressure and volume changes; and,

b) in response to results of the comparison, at least one of:

i) selectively adjust blood flow through the ventricular assist device; and, ii) selectively generate a notification.

4) Apparatus according to claim 3, wherein the parameter value is indicative of at least one of:

a) peak systolic ventricular pressure;

b) stroke work;

c) end diastolic pressure; and,

d) stroke volume.

5) Apparatus according to claim 3 or claim 4, wherein the threshold is at least one of: a) indicative of a nominal range;

b) determined based on a parameter value determined from a sample population; and, c) at least in part based on a parameter value previously determined for the subject.

6) Apparatus according to any one of the claims 1 to 5, wherein the ventricular assist device includes a rotating impeller, and wherein the one or more electronic processing devices are configured to control blood flow through the ventricular assist device by adjusting a pump speed corresponding to a rate of rotation of the impeller.

7) Apparatus according to any one of the claims 1 to 6, wherein the one or more electronic processing devices are configured to at least one of:

a) record a parameter or indicator value; and,

b) display a representation of a parameter or indicator value.

8) Apparatus according to any one of the claims 1 to 7, wherein the one or more electronic processing devices are at least one of:

a) at least part of a ventricular assist device controller; and,

b) coupled to a ventricular assist device controller.

9) Apparatus according to any one of the claims 1 to 8, wherein the one or more electronic processing devices are configured to determine the blood flow rate at least one of:

a) in accordance with signals received from a sensor;

b) by receiving flow rate data from a ventricular assist device controller; and, c) by calculating a flow rate based on rotation of a ventricular assist device impeller.

10) Apparatus according to any one of the claims 1 to 9, wherein the aortic pressure is derived from a brachial arterial pressure waveform.

11) Apparatus according to claim 10, wherein the aortic pressure is derived by filtering a brachial arterial pressure waveform.

12) Apparatus according to claim 10 or claim 11, wherein the brachial arterial pressure waveform is measured using a blood pressure cuff.

13) Apparatus according to any one of the claims 1 to 12, wherein the pump head pressure is derived based on the pump flow rate and a pressure head-flow (HQ) curve for the respective ventricular assist device.

14)Apparatus according to any one of the claims 1 to 13, wherein the fluid conduit pressure losses are derived based on an equation including terms based on: a) a pump flow rate;

b) a pump flow rate gradient;

c) a fluid conduit diameter; and,

d) hematocrit.

15)Apparatus according to claim 14, wherein the equation is derived using measurements performed using at least one of:

a) a mock circulation loop; and,

b) reference subjects.

16) Apparatus according to any one of the claims 1 to 15, wherein the one or more processing devices are configured to determine volume changes in the ventricle using a measured ventricular end-diastolic volume.

17) Apparatus according to claim 16, wherein the ventricular end-diastolic volume is determined using transthoracic echocardiography.

18) Apparatus according to any one of the claims 1 to 17, wherein the pump blood flow is determined using an integral of pump flow rate over time.

19) Apparatus according to any one of the claims 1 to 18, wherein the one or more processing devices are configured to:

a) determine a pump speed of the ventricular assist device;

b) analyse the pump speed to determine a pump speed indicator at least partially indicative of changes in pump speed; and,

c) use the pump speed indicator to determine an opening indicator indicative of opening of the aortic valve.

20) Apparatus according to claim 19, wherein the opening indicator is indicative of at least one of a degree, duration and timing of opening of the aortic valve.

21) Apparatus according to claim 19 or claim 20, wherein the pump speed indicator is at least one of:

a) indicative of rates of change of pump speed; and,

b) a distribution based on rates of change of pump speed.

22) Apparatus according to claim 21, wherein the distribution is at least one of:

a) a frequency distribution; and,

b) a power spectral density distribution. 23) Apparatus according to any one of the claims 19 to 22, wherein the one or more electronic processing devices are configured to:

a) compare the pump speed indicator to at least one threshold; and,

b) determine the opening indicator in response to the results of the comparison.

24) Apparatus according to claim 23, wherein the pump speed indicator is a distribution, and wherein the one or more electronic processing devices are configured to determine the threshold based on a maximum value of the distribution.

25) Apparatus according to claim 24, wherein the pump speed indicator is a power spectral density distribution and wherein the one or more electronic processing devices are configured to:

a) determine a maximum power frequency corresponding to the frequency having a maximum power in the power spectral density distribution; and,

b) determine the threshold based on the maximum power frequency.

26) Apparatus according to any one of the claims 23 to 25, wherein the pump speed indicator is a distribution of rates of change of pump speed and wherein the one or more electronic processing devices are configured to:

a) determine a portion of the distribution greater than the threshold; and,

b) determine the opening indicator using the portion.

27) Apparatus according to claim 26, wherein the one or more electronic processing devices are configured to:

a) calculate an area under curve for the portion; and,

b) use the area under curve to determine the opening indicator.

28) Apparatus according to any one of the claims 1 to 27, wherein the one or more electronic processing devices are configured to:

a) determine the flow rate of blood through the ventricular assist device; and, b) use the rate of flow of blood to identify individual cardiac cycles.

29) Apparatus according to claim 28, wherein the one or more electronic processing devices are configured to identify individual cardiac cycles from flow rate minima.

30)A method for use with a ventricular assist device that is assisting cardiac function of a biological subject, the method including, in one or more electronic processing devices: a) determining pressure changes in the ventricle over one or more cardiac cycles using: i) an aortic pressure derived from a measured blood pressure;

ii) a pump head pressure derived based on a pump flow rate; and,

b) determining volume changes in the ventricle at least in part using:

i) a pump blood flow derived based on a pump flow rate; and,

ii) an ejection volume based on an aortic valve opening duration; and,

c) using the pressure and volume changes to at least one of:

31) A computer program product for use with a ventricular assist device that is assisting cardiac function of a biological subject, the computer program product including computer executable code which when executed by one or more suitably programmed electronic processing devices, causes the electronic processing devices to:

ii) a pump head pressure derived based on a pump flow rate; and,

b) determine volume changes in the ventricle at least in part using:

i) a pump blood flow derived based on a pump flow rate; and,

ii) an ejection volume based on an aortic valve opening duration; and,

c) use the pressure and volume changes to at least one of: