Wall adherence detection device and method for ventricular assist device, ventricular assist system, storage medium and equipment

Abstract

The invention relates to an adherence detection device and method for a ventricular assist device, a ventricular assist system, a storage medium and equipment, and the device comprises a data collection module which is configured to collect ultrasonic signals obtained by a plurality of ultrasonic sensors; the plurality of ultrasonic sensors are circumferentially arranged on the periphery of the ventricular auxiliary device; the data processing module is configured to pre-process the ultrasonic signals and determine the distance value between each ultrasonic sensor and the ventricular wall based on the pre-processed signals; and the adherence detection module is configured to judge whether the ventricular assist device is in an adherence state or not based on the distance value.

Description

Technical Field

[0001] The present invention relates to medical devices for cardiac surgery, and in particular to a wall adhesion detection device, method, ventricular assist system, storage medium and equipment for a ventricular assist device. Background Art

[0002] The Percutaneous Ventricular Assist Device (PVAD) is a minimally invasive artificial heart device that provides pulsatile blood flow support for patients with impaired cardiac function. This device is primarily suitable for a variety of clinical scenarios, including acute myocarditis that is ineffective with conventional treatment, cardiomyopathy with shock, refractory heart failure, cardiogenic shock caused by acute myocardial infarction, and perioperative support for high-risk percutaneous coronary intervention.

[0003] However, existing interventional ventricular assist catheter pumps have the risk of the catheter pump head sticking to the wall. Taking left ventricular assist as an example, within the left ventricle, the catheter pump head may be close to the ventricular wall due to heartbeat or blood flow impact, resulting in wall adhesion. Wall adhesion not only hinders blood flow, but may also cause serious complications such as ventricular perforation. At present, there is a lack of real-time detection methods for the wall adhesion status of catheter pumps in clinical practice. The position of the catheter pump head mainly relies on X-ray fluoroscopy or echocardiography for intraoperative positioning, but these methods cannot provide real-time, continuous monitoring. After surgery, pump head displacement or wall adhesion is also difficult to detect in time, increasing the risk to patients.

[0004] Therefore, how to achieve real-time and accurate monitoring of the distance between the catheter pump and the ventricular wall, thereby improving the safety and performance of the interventional ventricular assist catheter pump, has become a technical problem that urgently needs to be solved. Summary of the Invention

[0005] The present invention discloses a device and method for detecting wall adhesion of a ventricular assist device, a ventricular assist system, a storage medium and equipment, aiming to solve the technical problems existing in the prior art.

[0006] The present invention adopts the following technical solutions:

[0007] In one aspect, an embodiment of the present invention provides a device for detecting adhesion of a ventricular assist device to the wall, comprising:

[0008] - a data acquisition module configured to acquire ultrasonic signals acquired by a plurality of ultrasonic sensors; the plurality of ultrasonic sensors are circumferentially arranged on the periphery of the ventricular assist device;

[0009] a data processing module configured to pre-process the ultrasonic signal and determine the distance value between each ultrasonic sensor and the ventricular wall based on the pre-processed signal;

[0010] -A wall-adherence detection module, configured to determine whether the ventricular assist device is in a wall-adherence state based on the distance value.

[0011] In a second aspect, an embodiment of the present invention provides a method for detecting adhesion of a ventricular assist device to the wall, the method comprising:

[0012] collecting ultrasonic signals acquired by a plurality of ultrasonic sensors, wherein the plurality of ultrasonic sensors are circumferentially arranged on the periphery of the ventricular assist device;

[0013] preprocessing the ultrasonic signal, and determining the distance value between each ultrasonic sensor and the ventricular wall based on the preprocessed signal;

[0014] Based on the distance value, it is determined whether the ventricular assist device is in an adherent state.

[0015] In a third aspect, an embodiment of the present invention further provides a ventricular assist system, which includes the wall adhesion detection device as described above.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the storage medium stores at least one instruction, and the at least one instruction is loaded and executed by a processor to implement the above-mentioned adhesion detection method.

[0017] In a fifth aspect, an embodiment of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the above-mentioned wall adhesion detection method.

[0018] One embodiment of the above invention has the following advantages or beneficial effects:

[0019] The present invention mainly provides a device, method, ventricular assist system, storage medium and equipment for detecting the adhesion of a ventricular assist device to the wall. By arranging multiple ultrasonic sensors circumferentially around the periphery of the ventricular assist device, ultrasonic signals are collected and processed in real time, and the distance between the ventricular assist device and the ventricular wall can be accurately measured. Furthermore, the embodiment of the present invention can measure the difference in the distance change between the ventricular assist device and the ventricular wall during the cardiac cycle, and correct the distance change difference in combination with the patient's ventricular wall thickness information, so as to facilitate a more accurate judgment of the adhesion status later.

[0020] Furthermore, by setting different adherence determination thresholds and combining them with the corrected distance change difference, the present embodiment can accurately distinguish between non-adherence, imminent adherence, and adhered states. Furthermore, duration monitoring is combined with further confirmation of adherence to ensure the reliability of the detection results. Furthermore, the present invention can optionally visually display the location and degree of adherence through three-dimensional spatial modeling, and promptly issue an alarm when adherence or imminent adherence is detected.

[0021] Compared with the existing technology, the technical solution of the present invention overcomes the shortcomings of traditional X-ray fluoroscopy or echocardiography that cannot provide real-time continuous monitoring, and avoids the problems of insufficient positioning accuracy and poor anti-interference ability of a single sensor. By considering the individual differences in ventricular wall thickness for data correction, the accuracy and reliability of wall adhesion detection are significantly improved, and serious complications such as blood flow obstruction or ventricular perforation caused by catheter pump adhesion to the wall can be effectively prevented, thereby improving the safety of ventricular assist devices in clinical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments, which constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are provided to explain the present invention and do not constitute an undue limitation of the present invention. In the drawings:

[0023] Figure 1 A schematic structural diagram of a ventricular assist device provided by one embodiment of the present invention;

[0024] Figure 2 A schematic structural diagram of a device for detecting adherence to a ventricular assist device according to an embodiment of the present invention;

[0025] Figure 3 A flowchart of a method for detecting wall adhesion of a ventricular assist device provided in accordance with one embodiment of the present invention.

[0026] Driving motor 11, proximal flow chamber 12, cannula 13, distal flow chamber 14, pigtail tube 15, ultrasonic sensor 16, conductive cable 17, data acquisition module 21, data processing module 22, wall adhesion detection module 23, three-dimensional modeling module 24, alarm module 25. DETAILED DESCRIPTION

[0027] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. In the description of the present invention, it should be noted that the term "or" is generally used in the sense of including "and / or" unless the content clearly indicates otherwise.

[0028] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. In addition, in the description of this application, the terms "first," "second," etc. are used only to distinguish descriptions and should not be understood to indicate or imply relative importance.

[0029] Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0030] Existing interventional ventricular assist devices have safety risks of accidental contact with the ventricular wall during clinical applications and lack the ability to monitor distance in real time, resulting in possible ventricular wall damage that cannot be detected and prevented in a timely manner.

[0031] In order to solve the problems existing in the prior art, the embodiment of the present invention provides a device for detecting the wall of a ventricular assist device, such as Figure 2 The device includes a data acquisition module 21, a data processing module 22 and a wall adhesion detection module 23, wherein the data acquisition module 21 is configured to: collect ultrasonic signals obtained by multiple ultrasonic sensors 16, and the multiple ultrasonic sensors 16 are circumferentially arranged on the periphery of the ventricular assist device; the data processing module 22 is configured to: pre-process the ultrasonic signals and determine the distance value between each ultrasonic sensor 16 and the ventricular wall based on the pre-processed signals; the wall adhesion detection module 23 is configured to: determine whether the ventricular assist device is in a wall adhesion state based on the distance value.

[0032] like Figure 1 In a preferred embodiment, the ventricular assist device is a catheter pump, and its structure is sequentially provided with a pigtail tube 15, a distal flow chamber 14, a cannula 13, a proximal flow chamber 12 and a drive motor 11 from the distal end to the proximal end. Preferably, at least two ultrasonic sensors 16 are circumferentially arranged at the distal end of the cannula 13 or the proximal end of the distal flow chamber 14. The ultrasonic sensor 16 is used to transmit ultrasonic waves and receive ultrasonic waves reflected back from the ventricular wall to detect the distance between the ventricular assist device and the ventricular wall in real time; preferably, the ultrasonic sensor 16 is connected to the tail of the drive motor 11 through a conductive cable 17, and the conductive cable 17 extends along the cannula 13 and leads out of the drive motor 11, and is used to transmit the signal collected by the ultrasonic sensor 16 to the data acquisition module 21.

[0033] Specifically, the distal flow chamber 14 and the proximal flow chamber 12 refer to chamber structures in the ventricular assist device used to guide blood flow. When the ventricular assist device is used to assist the right heart, the distal flow chamber 14 serves as a blood outflow chamber for delivering blood to the right ventricle, while the proximal flow chamber 12 serves as a blood inflow chamber for receiving blood from venous return. When the ventricular assist device is used to assist the left heart, the distal flow chamber 14 serves as a blood inflow chamber for receiving blood from the left ventricle, while the proximal flow chamber 12 serves as a blood outflow chamber for delivering blood to the aorta.

[0034] Preferably, 2 to 6 ultrasonic sensors 16 are evenly arranged circumferentially at the distal end of the cannula 13 or the proximal end of the distal flow chamber 14. In this embodiment, the arrangement of 6 ultrasonic sensors 16 is taken as an example for explanation. At this time, the data acquisition module 21 obtains the ultrasonic signals obtained by the 6 ultrasonic sensors 16 respectively through the conductive cable 17.

[0035] In a preferred embodiment, the ultrasonic sensor 16 emits short-pulse, high-frequency ultrasonic waves toward the ventricular wall, such as ultrasonic waves with a pulse width of 0.1-1 μs and a frequency of 15 MHz. At this time, it can provide an axial resolution of 0.1 mm to accurately identify millimeter-level distance changes, thereby more accurately determining whether the interventional ventricular assist device has come into contact with the ventricular wall; but the penetration depth is relatively limited, at about 3 cm. However, considering the actual size of the ventricular cavity and the working environment of the device, this depth is sufficient to cover the monitoring range required for normal operation, while also minimizing the influence of signal noise and multipath reflection, thereby improving the stability and reliability of the measurement.

[0036] In a preferred embodiment, each ultrasonic sensor 16 transmits ultrasonic waves and receives reflected signals within a preset time window. In this embodiment, this preset time window can be set based on the VAD's operating environment, heart rate, and required data acquisition accuracy, and its specific value is not limited. Those skilled in the art may adjust the preset time window based on actual application requirements, system computing power, and detection accuracy requirements to achieve a balance between real-time performance and signal quality.

[0037] Preferably, the data acquisition module 21 is configured to collect ultrasonic signals from each of the six ultrasonic sensors 16 over at least one complete cardiac cycle. Specifically, the data acquisition module 21 individually identifies, stores, and processes the signals from each ultrasonic sensor 16 to facilitate subsequent processing and calculations by the data processing module 22. Furthermore, by ensuring that data acquisition covers at least one complete cardiac cycle, the dynamic changes in the distance between the ventricular wall and the VAD during a complete cardiac contraction and relaxation process can be captured, providing a comprehensive data foundation for accurately determining the wall adhesion status.

[0038] In a preferred embodiment, the data processing module 22 converts the raw signal acquired by the ultrasonic sensor 16 into distance data. Specifically, after the ultrasonic sensor 16 transmits an ultrasonic wave and receives a reflected echo, it automatically calculates the distance between the ultrasonic sensor 16 and the ventricular wall based on the ultrasonic wave's propagation speed in blood and the time interval between transmission and reception, using a signal processing algorithm adapted for the ultrasonic sensor 16. This signal processing process is similar to the signal processing principles of fiber optic sensors in the prior art. It automatically converts the measured signal into the required distance data using a pre-set algorithm adapted for the ultrasonic sensor 16, eliminating the need for complex manual calculations by the operator. The corresponding pre-set algorithm varies depending on the specific ultrasonic sensor 16 and is not specifically defined in this embodiment.

[0039] When the ultrasonic sensor 16 detects the distance between the ventricular assist device and the ventricle, it is easily affected by the following factors:

[0040] 1) Heartbeat: The human heart rate ranges from 60 to 120 beats per minute, so the frequency of the noise signal generated by the heartbeat is 1 to 2 Hz and is periodically distributed.

[0041] 2) Blood flow interference: Since the blood flow velocity and vascular status are uncertain during blood flow, the noise signal brought by blood flow is relatively random and easily superimposed on the distance signal;

[0042] 3) Temperature effect: Here we consider that the human body temperature is constant at 37°C, and the propagation speed of ultrasound in the blood at this temperature is 1540m / s.

[0043] Based on the above analysis, when processing data, data processing module 22 primarily needs to consider eliminating interference from heartbeats and blood flow. Since the noise signal caused by blood flow is random, conventional high-pass filtering cannot completely filter out the noise. In a preferred embodiment, data processing module 22 is configured to preprocess the ultrasonic signal using an extended Kalman filter (EKF) algorithm. This algorithm can simultaneously process periodic and random noise to eliminate noise interference in the ultrasonic signal and signal jitter caused by cardiac motion, thereby improving the accuracy and stability of distance measurement.

[0044] The distance data after the extended Kalman filter is expressed as: d' i =f i (d i ), where f(x) is the extended Kalman filter function, d i These are original distance data between the ultrasonic sensors 16 and the ventricular wall after sampling by 6 ultrasonic sensors 16 , i=1, 2, …, 6.

[0045] Since the data points sampled by the six ultrasonic sensors 16 are discrete and there are monitoring blind spots between adjacent ultrasonic sensors 16, in a preferred embodiment, the data processing module 22 is further configured to: estimate the distance value between the position on the outer surface of the ventricular assist device where the ultrasonic sensor 16 is not arranged and the ventricular wall based on the distance values measured by multiple ultrasonic sensors 16 through a spatial interpolation algorithm.

[0046] Specifically, the data processing module 22 can transform the discrete data into a continuous annular distance distribution based on a spatial interpolation algorithm: d=h(d' i ), where function g(x) is the interpolation function, d' i These are the filtered distance data of the six ultrasonic sensors 16 , i=1, 2, …, 6.

[0047] In a preferred embodiment, the spatial interpolation algorithm uses radial basis functions (RBFs). By constructing basis functions centered on the location of ultrasound sensor 16, the circumferential distance distribution of the VAD is estimated. This algorithm is capable of processing unevenly distributed data points and accurately reflects local feature variations while maintaining data smoothness. Through RBF interpolation, data processing module 22 expands the discrete distance values originally present at only six ultrasound sensor 16 locations to a 360-degree omnidirectional distance distribution around the VAD, effectively covering blind spots in monitoring.

[0048] In a preferred embodiment, the ventricular assist device (VAD) is adhered to the ventricular wall based on the distance value output by the data processing module 22. Specifically, the distance value can be a filtered distance value obtained by any ultrasound sensor 16 after extended Kalman filtering, or an interpolated distance value at any location around the ventricular assist device (VAD) obtained using a spatial interpolation algorithm. If any distance value remains zero for a predetermined period of time, the ventricular assist device is determined to be adhered to the ventricular wall.

[0049] In another preferred embodiment, taking into account the contraction and relaxation of the heart, the filtered distance data in the data processing module 22 should also show a certain periodic change with the contraction and relaxation of the heart. In this case, the data processing module 22 is configured to: determine the maximum value d' of the distance between the ventricular assist device and the ventricular wall in any cardiac cycle i，max and minimum value d' i，min , then based on the maximum value d' i，max and minimum value d' i，min Determine the distance change difference, the distance change difference is: Δd=d' i，max -d' i，min(where i = 1, 2, ..., 6). When the ventricular assist device is attached to the wall, Δd will decrease. Therefore, preferably, the wall adhesion detection module 23 is configured to: set a wall adhesion determination threshold, and determine the wall adhesion state of the ventricular assist device based on the comparison result of the distance change value and the wall adhesion determination threshold. More preferably, the wall adhesion detection module 23 is configured to: preset a first wall adhesion determination threshold, and when Δd is less than or equal to the first wall adhesion determination threshold, it is determined that the ventricular assist device is attached to the wall. Specifically, the first wall adhesion determination threshold is set to the distance change difference when the ventricular assist device is in the wall adhesion state, and this threshold is set based on experimental or clinical experience.

[0050] Furthermore, when the patient's heart contracts and relaxes normally, the Δd calculated by the six ultrasonic sensors 16 should be a set of values with small fluctuations. When the patient's heart contracts and relaxes abnormally, such as when the patient's ventricular wall is thickened or thin, the heart's contraction and relaxation capabilities become weaker, and the calculated Δd is smaller. At this time, the wall adhesion detection module 23 directly judges whether the ventricular assist device is adhered to the wall based on the difference in distance changes, which may lead to misjudgment.

[0051] In order to correct the influence of the patient's ventricular wall thickness on the adhesion test results, in a preferred embodiment, the data processing module 22 is further configured to: determine the maximum value d' of the distance between the ventricular assist device and the ventricular wall within one cardiac cycle i，max and minimum value d' i，min , based on the maximum value d' i，max and minimum value d' i，min A distance change difference Δd is determined, a correction factor α is determined based on the patient's ventricular wall thickness information, and then the correction factor α is applied to the distance change difference Δd to obtain a corrected distance change difference Δd'.

[0052] Preferably, the correction factor α is determined based on the ratio between the patient's ventricular wall thickness D and the standard ventricular wall thickness D0, wherein the patient's ventricular wall thickness D can be obtained in the preoperative evaluation stage, and the standard ventricular wall thickness D0 is set based on experiments or clinical experience; when the patient's ventricular wall thickness D is greater than the standard ventricular wall thickness D0, the correction factor α should be large, so that Δd falls into the correct range. At this time, the form of the function f can be That is, at this time, the correction factor α and the ratio of the two There is a positive correlation; when the patient's ventricular wall thickness D is less than the standard ventricular wall thickness D0, it means that the patient's ventricular wall is thinner, and the correction factor α should also be increased to amplify Δd. At this time, the form of the function f can be That is, the correction factor is the inverse of the ratio of the two There is a positive correlation.

[0053] Preferably, the corrected distance change difference Δd' = α * Δd, and the adhesion detection module 23 determines whether the ventricular assist device is in adhesion based on the corrected distance change difference Δd'. Adaptively correcting the distance change difference Δd based on ventricular wall thickness effectively compensates for adhesion errors caused by individual patient differences in cardiac contraction and relaxation capacity, improving the system's clinical applicability and reliability. In this case, the adhesion detection module 23 is configured to preset a first adhesion determination threshold and determine adhesion when Δd' is less than or equal to the first adhesion determination threshold.

[0054] Preferably, to avoid various risks associated with VAD adhesion, the adhesion detection module 23 may further set a second adhesion determination threshold, which is greater than the first adhesion determination threshold. Specifically, the second adhesion determination threshold is set to the difference in distance change when the VAD is about to adhere to the wall. This threshold is set based on experimental or clinical experience.

[0055] Specifically, by setting a first and second adhesion threshold, a three-interval determination mechanism is formed: if the corrected distance change difference is greater than the second adhesion threshold, it indicates a non-adhesion interval; if the corrected distance change difference is greater than the first adhesion threshold but less than or equal to the second adhesion threshold, it indicates a near-adhesion interval; and if the corrected distance change difference is less than or equal to the first adhesion threshold, it indicates an adhered interval. By grading the thresholds and determining adhesion separately, more detailed adhesion status information can be provided to clinicians, facilitating early warning and timely intervention.

[0056] Preferably, the adhesion detection module 23 is configured as follows:

[0057] When the corrected distance change difference Δd' is greater than the second wall attachment determination threshold, it is determined that the ventricular assist device is in a non-wall attachment state;

[0058] When the corrected distance change difference Δd' is between the second adhesion determination threshold and the first adhesion determination threshold, it is determined that the ventricular assist device is in a state of imminent adhesion;

[0059] When the corrected distance change difference Δd' is between the second adhesion determination threshold and the first adhesion determination threshold, but the distance between any ultrasonic sensor 16 and the ventricular wall is always 0, it is determined that the ventricular assist device is in the adhered state;

[0060] When the corrected distance change difference Δd′ is less than or equal to the first adhesion determination threshold, it is determined that the ventricular assist device is in the adhered state.

[0061] In a preferred embodiment, the wall adhesion detection module 23 is further configured to monitor the duration of the ventricular assist device being in a state about to be adhered to the wall or in a state already adhered to the wall. When the duration exceeds a preset time threshold, it is confirmed that the ventricular assist device is in a stable state about to be adhered to the wall or in a state already adhered to the wall.

[0062] Preferably, the preset time threshold is set to five cardiac cycles. On the one hand, the determination result within a single cardiac cycle may fluctuate due to factors such as transient noise, changes in body position or respiratory cycle. By extending the observation time to five cardiac cycles, these temporary interference factors can be effectively filtered out; on the other hand, the time of five cardiac cycles is long enough to ensure that the observed adhesion phenomenon is clinically persistent rather than instantaneous; at the same time, the time is not too long to ensure timely clinical intervention after the discovery of a persistent adhesion state, thereby preventing the occurrence of potential complications due to delayed treatment. In addition, the data sampling volume of five cardiac cycles is sufficient to support statistical reliability judgments, reduce the incidence of false positive and false negative results, and improve the specificity and sensitivity of adhesion detection.

[0063] By combining the corrected distance change difference judgment and duration monitoring, the wall adhesion detection device can provide accurate and timely wall adhesion status information, provide a reliable basis for clinical intervention decisions, and effectively reduce the risks associated with ventricular assist device wall adhesion.

[0064] In a preferred embodiment, the wall adhesion detection device may further include a three-dimensional modeling module 24. This module 24 is configured to construct a three-dimensional spatial relationship model between the ventricular wall and the ventricular assist device based on the distance values output by the data processing module 22. Preferably, the distance values required by the three-dimensional modeling module 24 are the distance values measured by the six ultrasound sensors 16 and the distance values estimated using a spatial interpolation algorithm.

[0065] Preferably, the three-dimensional modeling module 24 is also configured to: fuse the distance values measured by the six ultrasound sensors 16 with the distance values estimated by the spatial interpolation algorithm, construct a three-dimensional spatial relationship model, and determine whether the ventricular assist device is in a wall-attached state based on the three-dimensional spatial relationship model.

[0066] Specifically, the three-dimensional modeling module 24 constructs a three-dimensional spatial relationship model between the ventricular wall and the ventricular assist device by combining the circumferential distance distribution data after filtering and spatial interpolation with the geometric parameters of the ventricular assist device, and updates it in real time to more intuitively display the real-time position and orientation of the ventricular assist device in the ventricle, as well as the relative spatial relationship between the ventricular wall and the ventricular assist device.

[0067] In a preferred embodiment, the 3D modeling module 24 can be configured to utilize a surface reconstruction algorithm to expand the circumferential distance data into the ventricular wall surface in three-dimensional space. Specifically, the 3D modeling module 24 can first determine the central axis of the ventricular assist device as a reference coordinate system. Based on this, the 3D modeling module 24 maps the distance values in various directions into three-dimensional space to form point cloud data of the ventricular wall. Subsequently, the module can use surface fitting to convert the discrete point cloud into a continuous ventricular wall surface model.

[0068] Preferably, when VAD adhesion is detected, the 3D modeling module 24 uses color coding to display the adhesion location and degree of adhesion, such as red indicating adhesion, yellow indicating near-adhesion, and green indicating non-adhesion. This visualization helps clinicians intuitively understand the adhesion status of the VAD within the ventricle, providing a more direct basis for clinical adjustments and preventive measures.

[0069] Preferably, the three-dimensional modeling module 24 can not only be used to determine the wall adhesion state, but also provide additional clinical auxiliary diagnosis information, such as volume changes of the ventricular cavity, identification of abnormal wall motion areas, etc.

[0070] In a preferred embodiment, the adhesion detection device may further include an alarm module 25 configured to generate an alarm when it determines that the ventricular assist device is in adhesion or is about to adhere. Preferably, the alarm includes, but is not limited to, audio and visual alarms, text prompts, and graphical displays, to ensure that medical staff are promptly aware of the risk of adhesion.

[0071] Furthermore, the alarm module 25 is configured to display specific information on the external control device regarding the location of the ventricular assist device, indicating that it is about to adhere or has adhered. Specifically, the alarm module 25 combines the adhesion location data provided by the adhesion detection module 23 with the three-dimensional spatial relationship model constructed by the three-dimensional modeling module 24, and presents this information intuitively on the display interface of the external control device. This display includes a three-dimensional schematic diagram of the ventricular assist device, with areas of adhesion or impending adhesion marked with different colors, providing clinicians with more comprehensive information on the adhesion status.

[0072] Preferably, the alarm module 25 is also configured to automatically adjust the alarm level based on the severity of the adhesion. When an impending adhesion condition is detected, a low-level warning is triggered; when adhesion is detected, a high-level alarm is triggered; and when adhesion persists beyond a preset safety limit, an emergency alarm is triggered, the highest level. Different alarm levels use different sound and light patterns and display methods, allowing medical staff to quickly determine the urgency of the adhesion condition and take appropriate intervention measures.

[0073] In this embodiment, the various functional modules of the adhesion detection device, including the data acquisition module 21, data processing module 22, adhesion detection module 23, 3D modeling module 24, and alarm module 25, are integrated into an external control device connected to the VAD. As the main executive body of the adhesion detection device, the external control device is responsible for receiving raw data collected by the ultrasound sensor 16 and performing data processing and analysis functions such as filtering, spatial interpolation, and adhesion determination. It also provides a human-computer interface to intuitively display the VAD's positional status and adhesion information, and issues alarms when necessary.

[0074] An embodiment of the present invention further provides a ventricular assist system, which includes a ventricular assist device and an external control device. The wall adhesion detection device is integrated into the external control device, and its corresponding functional modules are implemented through a software program.

[0075] like Figure 3 One embodiment of the present invention further provides a method for detecting adhesion of a ventricular assist device to the wall, the method comprising the following steps:

[0076] Step S320 , collecting ultrasonic signals acquired by a plurality of ultrasonic sensors, wherein the plurality of ultrasonic sensors are circumferentially arranged on the periphery of the ventricular assist device.

[0077] In a preferred embodiment, 2 to 6 ultrasonic sensors 16 are evenly arranged circumferentially at the distal end of the cannula 13 or the proximal end of the distal flow chamber 14 , preferably 6.

[0078] In a preferred embodiment, ultrasonic signals acquired by the six ultrasonic sensors 16 within at least one complete cardiac cycle are collected, and more preferably, ultrasonic signals within at least five cardiac cycles are collected.

[0079] Step S340 , preprocessing the ultrasonic signal, and determining the distance value between each ultrasonic sensor 16 and the ventricular wall based on the preprocessed signal.

[0080] In a preferred embodiment, the ultrasonic signal is preprocessed by the extended Kalman filter (EKF) algorithm to eliminate noise interference and signal jitter caused by cardiac motion in the ultrasonic signal, thereby improving the accuracy and stability of the distance measurement. The distance data after the extended Kalman filter is expressed as: d' i =f i (d i ), where f(x) is the extended Kalman filter function, d i These are original distance data between the ultrasonic sensors 16 and the ventricular wall after sampling by 6 ultrasonic sensors 16 , i=1, 2, …, 6.

[0081] In a preferred embodiment, since the data points sampled by the six ultrasonic sensors 16 are discrete and there are monitoring blind spots between adjacent ultrasonic sensors 16, the following is also included:

[0082] Step S341: Using a spatial interpolation algorithm, the distance between the ventricular wall and the location on the circumference of the ventricular assist device where no ultrasound sensor is located is estimated based on the distance values measured by multiple ultrasound sensors. At this point, the discrete data can be converted into a continuous annular distance distribution: d = g(d' i ), where function g(x) is the interpolation function, d' i These are the filtered distance data of 6 sensors, i=1, 2,…, 6.

[0083] In a preferred embodiment, it also includes:

[0084] Step S342: determine the maximum value d' of the distance between the ventricular assist device and the ventricular wall in any cardiac cycle. i，max and minimum value d' i，min , then based on the maximum value d' i，max and minimum value d' i，min Determine the distance change difference, the distance change difference is: Δd=d' i，max -d' i，min (where i = 1, 2,…, 6).

[0085] In a preferred embodiment, it also includes:

[0086] Step S343 : determining a correction factor α based on the patient's ventricular wall thickness information, and then applying the correction factor α to the distance change difference Δd to obtain a corrected distance change difference Δd′.

[0087] Preferably, the corrected distance change difference Δd′=α*Δd.

[0088] Preferably, the correction factor α is determined based on the ratio between the patient's ventricular wall thickness D and the standard ventricular wall thickness D0. When the patient's ventricular wall thickness D is greater than the standard ventricular wall thickness D0, the correction factor α should be large, so that Δd falls into the correct range. At this time, the function f can be in the form of That is, at this time, the correction factor α and the ratio of the two There is a positive correlation; when the patient's ventricular wall thickness D is less than the standard ventricular wall thickness D0, it means that the patient's ventricular wall is thinner, and the correction factor α should also be increased to amplify Δd. At this time, the form of the function f can be That is, the correction factor is the inverse of the ratio of the two There is a positive correlation.

[0089] Step S360: Based on the distance value, determine whether the ventricular assist device is in an adherent state.

[0090] In a preferred embodiment, whether the VAD is in an adherent state is directly determined based on a distance value. Specifically, the distance value can be a filtered distance value obtained by any ultrasound sensor 16 after being processed by an extended Kalman filter, or an interpolated distance value at any location around the VAD obtained using a spatial interpolation algorithm. When any distance value is zero and remains for a predetermined period of time, the VAD is determined to be in an adherent state.

[0091] In a preferred embodiment, a first adhesion determination threshold is preset. When Δd is less than or equal to the first adhesion determination threshold, the device is considered to be adhered to the wall. Specifically, the first adhesion determination threshold is set as the difference in distance change when the ventricular assist device is in the adhered state. This threshold is set based on experimental or clinical experience.

[0092] In a preferred embodiment, whether the ventricular assist device is in an adherent state is determined based on the corrected distance change difference Δd'. Preferably, a first adherence determination threshold is preset, which is set to the distance change difference when the ventricular assist device is in an adherent state. When Δd' is less than or equal to the first adherence determination threshold, the ventricular assist device is determined to be in an adherent state.

[0093] In a preferred embodiment, a second adhesion determination threshold is set, and the second adhesion determination threshold is greater than the first adhesion determination threshold. Specifically, the second adhesion determination threshold is set as the distance change difference when the ventricular assist device is about to adhere to the wall, and this threshold is set based on experimental or clinical experience. At this time, when the corrected distance change difference Δd' is greater than the second adhesion determination threshold, the ventricular assist device is determined to be in a non-adhesive state; when the corrected distance change difference Δd' is between the second adhesion determination threshold and the first adhesion determination threshold, the ventricular assist device is determined to be in a about-to-adhesive state; when the corrected distance change difference Δd' is between the second adhesion determination threshold and the first adhesion determination threshold, but the distance value between any ultrasonic sensor 16 and the ventricular wall is always 0, the ventricular assist device is determined to be in an already adhered state; when the corrected distance change difference Δd' is less than or equal to the first adhesion determination threshold, the ventricular assist device is determined to be in an already adhered state. Preferably, when the ventricular assist device is in the imminent attachment state or the already attached state for more than a preset time threshold, it is confirmed that the ventricular assist device is in the stable imminent attachment state or the already attached state. Preferably, the preset time threshold is set to five cardiac cycles.

[0094] In a preferred embodiment, it also includes:

[0095] Step S350: Construct a three-dimensional spatial relationship model between the ventricular wall and the ventricular assist device based on the distance values obtained in steps S340 and S341. Preferably, the distance values are distance values measured by the six ultrasound sensors 16 and distance values estimated by a spatial interpolation algorithm.

[0096] Preferably, the distance values measured by the six ultrasound sensors 16 are fused with the distance values estimated using a spatial interpolation algorithm to construct a three-dimensional spatial relationship model, which is updated in real time. Based on this three-dimensional spatial relationship model, whether the ventricular assist device is adhered to the wall is determined. When adherence to the wall is detected, the external control device displays the location and degree of adherence and issues an alarm.

[0097] Step S380: When the VAD is determined to be in or nearing attachment, an alarm is generated. Specifically, the system displays the specific location of the VAD nearing or already attached on an external control device, providing clinicians with more comprehensive information on the device's attachment status.

[0098] One embodiment of the present application provides a computer-readable storage medium, wherein the storage medium stores at least one instruction, and the at least one instruction is loaded and executed by a processor to implement the above-mentioned adhesion detection method.

[0099] An embodiment of the present application provides an electronic device, comprising a processor and a memory, wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the above-mentioned wall adhesion detection method.

[0100] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0101] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are protected by the present invention.

Claims

1. A device for detecting adhesion of a ventricular assist device, characterized in that: include: - a data acquisition module, configured to collect ultrasonic signals acquired by a plurality of ultrasonic sensors; A plurality of said ultrasound sensors are circumferentially arranged on the periphery of the ventricular assist device; - a data processing module configured to pre-process the ultrasonic signal and determine the distance value between each of the ultrasonic sensors and the ventricular wall based on the pre-processed signal; - A wall-adherence detection module, configured to determine whether the ventricular assist device is in a wall-adherence state based on the distance value.

2. The device for detecting adherence to the wall of a ventricular assist device according to claim 1, wherein: The data acquisition module is configured to acquire the ultrasonic signals acquired by 2 to 6 ultrasonic sensors uniformly arranged circumferentially around the periphery of the ventricular assist device; The ultrasonic signal is obtained by the ultrasonic sensor transmitting ultrasonic waves toward the ventricular wall and receiving the signal reflected from the ventricular wall.

3. The wall adhesion detection device for a ventricular assist device according to claim 1, characterized in that: The data processing module is configured to pre-process the ultrasonic signal through extended Kalman filtering to eliminate noise interference in the ultrasonic signal and signal jitter caused by cardiac motion.

4. The wall adhesion detection device for a ventricular assist device according to claim 1, characterized in that: The data processing module is further configured to: determine a change difference in the distance between the ventricular assist device and the ventricular wall within one cardiac cycle; The adhesion detection module is further configured to set an adhesion determination threshold and determine the adhesion state of the ventricular assist device based on a comparison result between the distance change value and the adhesion determination threshold.

5. The wall adhesion detection device for a ventricular assist device according to claim 4, characterized in that: The data processing module is further configured to: determining a maximum value and a minimum value of the distance between the ventricular assist device and the ventricular wall during a cardiac cycle; determining the distance change difference based on the maximum value and the minimum value; determining a correction factor based on the patient's ventricular wall thickness information; The correction factor is applied to the distance change difference to obtain a corrected distance change difference.

6. The device for detecting adherence to the wall of a ventricular assist device according to claim 5, characterized in that: The correction factor is determined based on the ratio between the patient's ventricular wall thickness and the standard ventricular wall thickness; when the patient's ventricular wall thickness is greater than the standard ventricular wall thickness, the correction factor is positively correlated with the ratio between the two; When the patient's ventricular wall thickness is smaller than the standard ventricular wall thickness, the correction factor is positively correlated with the inverse of the ratio of the two.

7. The wall adhesion detection device for a ventricular assist device according to claim 5, characterized in that: The adhesion detection module is configured as follows: setting a second adhesion determination threshold and a first adhesion determination threshold, wherein the second adhesion determination threshold is greater than the first adhesion determination threshold; When the corrected distance change difference is greater than the second adhesion determination threshold, determining that the ventricular assist device is in a non-adhesive state; When the corrected distance change difference is between the second adhesion determination threshold and the first adhesion determination threshold, it is determined that the ventricular assist device is in a state of imminent adhesion; When the corrected distance change difference is between the second adhesion determination threshold and the first adhesion determination threshold, but the distance value between any one of the ultrasound sensors and the ventricular wall is always 0, it is determined that the ventricular assist device is in the adhered state; When the corrected distance change difference is less than or equal to the first adhesion determination threshold, it is determined that the ventricular assist device is in the adhered state.

8. The device for detecting adherence to the wall of a ventricular assist device according to claim 7, wherein: The adhesion detection module is further configured to monitor the duration of the ventricular assist device being in a state about to be adhered to the wall or in a state already adhered to the wall, and when the duration exceeds a preset time threshold, confirm that the ventricular assist device is in a stable state about to be adhered to the wall or in a state already adhered to the wall.

9. The device for detecting adherence to the wall of a ventricular assist device according to claim 1, wherein: It also includes a three-dimensional modeling module configured to construct a three-dimensional spatial relationship model between the ventricular wall and the ventricular assist device based on the distance value.

10. The wall adhesion detection device for a ventricular assist device according to claim 9, characterized in that: The data processing module is further configured to estimate the distance value between the position on the outer surface of the ventricular assist device where the ultrasonic sensor is not arranged and the ventricular wall based on the distance values measured by multiple ultrasonic sensors through a spatial interpolation algorithm.

11. The device for detecting adherence to the wall of a ventricular assist device according to claim 9, wherein: The three-dimensional modeling module is also configured to fuse the distance values measured by the multiple ultrasound sensors with the distance values estimated by the spatial interpolation algorithm to construct the three-dimensional spatial relationship model, and determine whether the ventricular assist device is in a wall-attached state based on the three-dimensional spatial relationship model.

12. The device for detecting adherence to the wall of a ventricular assist device according to any one of claims 1 to 11, characterized in that: Also includes: The alarm module is configured to generate an alarm prompt when it is determined that the ventricular assist device is in a wall-attached state or is about to be in a wall-attached state.

13. A method for detecting adhesion of a ventricular assist device, characterized in that: The method comprises: collecting ultrasonic signals acquired by a plurality of ultrasonic sensors, wherein the plurality of ultrasonic sensors are circumferentially arranged on the periphery of the ventricular assist device; preprocessing the ultrasonic signal, and determining the distance value between each of the ultrasonic sensors and the ventricular wall based on the preprocessed signal; Based on the distance value, it is determined whether the ventricular assist device is in an adherent state.

14. A ventricular assist system, characterized in that: It comprises the wall adhesion detection device as described in any one of claims 1 to 11.

15. A computer-readable storage medium, characterized in that The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the adhesion detection method according to claim 13.

16. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the wall adhesion detection method according to claim 13.

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