Left atrial appendage occlusion preoperative system and method

Abstract

The present disclosure teaches determining a recommended LAA occlusion device size based on a simulation of deployment of a plurality of occlusion devices having LAA anatomy. An input image of a LAA anatomy of a patient is received. Multiple simulations run to provide device interaction, plugging, and anchoring options for multiple anchoring sites and device sizes. A gap between the simulated deployment devices is analyzed based on the leakage path, and a recommended plugging device size is determined based on the simulated gap.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of priority to U.S. Provisional Application No. 63 / 398,772, filed on August 17, 2022, under 35 U.S.C. §119, the entire disclosure of which is incorporated herein by reference. Technical Field

[0003] The present disclosure generally relates to left atrial appendage (LAA) occlusion. More particularly, but not exclusively, the present disclosure relates to pre-planning the size and placement of LAA occlusion devices. Background Art

[0004] The size and shape of the human left atrial appendage (LAA) vary greatly from patient to patient, making it difficult for physicians to determine the appropriate LAA occlusion device size and deployment location. Computed tomography (CT)-based preplanning allows physicians to assess a patient's LAA prior to surgery. However, available CT-based preplanning tools provide limited information. Therefore, more advanced preplanning tools than those routinely available are needed. Summary of the invention

[0005] This summary is provided to introduce a selection of concepts in a simplified form that are further described in the detailed description below. This summary is not necessarily intended to identify key features or essential features of the claimed subject matter, nor is it intended to be an aid in determining the scope of the claimed subject matter.

[0006] The present disclosure provides a LAA occlusion pre-planning method and system that solves the shortcomings of conventional solutions. For example, the pre-planning method and system according to the present disclosure can provide key information to doctors, such as the interaction between the occlusion device and the LAA, the sealing of the occlusion device, the anchoring of the occlusion device, etc.

[0007] In general, the present disclosure provides receiving an image of a patient's LAA anatomy (e.g., from a CT-based preoperative image, or the like) as input. Multiple simulations are run to provide options for device interaction, occlusion, and anchoring for multiple anchoring sites and device sizes. In some examples, the simulation can provide a recommendation for an ideal occlusion device size based on the simulated LAA interaction, sealing, and anchoring results.

[0008] In certain examples, the present disclosure provides a method for pre-planning left atrial appendage (LAA) occlusion; the method comprising: receiving an image including an indication of a patient's LAA; receiving an indication of a landing zone of an occluding device; simulating deployment of the occluding device in the patient's LAA; simulating sealing of the patient's LAA by the deployed occluding device; simulating anchoring of the occluding device in the patient's LAA; and generating a graphical representation of the sealing and anchoring of the occluding device in the patient's LAA.

[0009] The method may also include generating a graphical representation of the deployed occluding device in the patient's LAA. In some embodiments, generating a graphical representation of the deployed occluding device in the patient's LAA includes superimposing the simulated deployed occluding device with a graphical representation of the patient's LAA. The method may also include determining a recommended size for the occluding device based on the received image. The method may also include identifying a diameter of the orifice of the patient's LAA based on the received image; selecting an occluding device size within a threshold expanded diameter of the orifice diameter from a set of occluding device sizes; and identifying the selected occluding device size as a recommended occluding device. The method may also include simulating the deployment of the occluding device in the patient's LAA for an occluding device having a recommended size. The method may also include simulating the deployment of the occluding device in the patient's LAA for an occluding device having a size different from the recommended size. The method may also include generating a graphical representation of the deployed occluding device in the patient's LAA, the graphical representation including superimposing a simulated deployed occluding device having a recommended size with a graphical representation of the patient's LAA, and superimposing a simulated deployed occluding device having a different size with a graphical representation of the patient's LAA. In some embodiments, generating a graphical representation of the seal of the deployed occluding device in the patient's LAA includes generating multiple images that include an indication of the patient's LAA and an indication of a contact surface, the contact surface representing contact between the deployed occluding device and the patient's LAA. In some embodiments, the multiple images include an indication of the patient's LAA, an indication of the contact surface, and an indication of a leakage path. The method may also include generating a rotatable model from the multiple images. In some embodiments, generating a graphical representation of the anchoring of the occluding device in the patient's LAA includes generating an image of a simulated deployed occluding device that includes an indication of an anchor of the occluding device and a representation of a junction of the anchor with tissue of the patient's LAA. In some embodiments, the representation of the junction of the anchor includes a color map.

[0010] In some embodiments, the present disclosure may be implemented as a computer-readable storage medium comprising instructions that, when executed by a processor of a computing device, cause the processor to implement any of the methods described herein. In some embodiments, the present disclosure may be implemented as a computer comprising a processor; and a memory comprising instructions that, when executed by the processor, cause the computing system to implement any of the methods described herein.

[0011] In some examples, the present disclosure may be implemented as a computing system comprising: a processor; and a memory comprising instructions that, when executed by the processor, cause the computing system to: receive an image comprising an indication of a patient's LAA; receive an indication of a landing zone for an occluding device; simulate deployment of the occluding device in the patient's LAA; simulate sealing of the patient's LAA by the deployed occluding device; simulate anchoring of the occluding device in the patient's LAA; and generate a graphical representation of the sealing and anchoring of the occluding device in the patient's LAA.

[0012] In some embodiments, the computing system includes instructions that, when executed by a processor, cause the computing system to generate a graphical representation of an occluding device deployed in the patient's LAA. In some embodiments, the computing system includes instructions that, when executed by a processor, cause the computing system to generate a graphical representation of the deployed occluding device in the patient's LAA, including overlaying the simulated deployed occluding device with the graphical representation of the patient's LAA. In some embodiments, the computing system includes instructions that, when executed by a processor, cause the computing system to determine a recommended size of the occluding device based on the received image.

[0013] In some examples, the present disclosure includes a computer-readable storage medium containing instructions that, when executed by a processor of a computing device, cause the processor to receive an image including an indication of a patient's LAA; receive an indication of a landing zone for an occluding device; identify a diameter of an orifice of the patient's LAA based on the received image; select an occluding device size from a set of occluding device sizes that is within a threshold expanded diameter of the orifice diameter; identify the selected occluding device size as an occluding device; simulate deployment of the occluding device in the patient's LAA; simulate sealing of the patient's LAA by the deployed occluding device; simulate anchoring of the occluding device in the patient's LAA; and generate a graphical representation of the sealing and anchoring of the occluding device in the patient's LAA.

[0014] In some embodiments, a computer readable storage medium includes instructions that, when executed by a processor, cause a computing system to simulate deployment of an occluding device in a patient's LAA for an occluding device having a recommended size. In some embodiments, a computer readable storage medium includes instructions that, when executed by a processor, cause a computing system to simulate deployment of an occluding device in a patient's LAA for an occluding device having a size different from the recommended size. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To facilitate identification of any element or activity discussed, the highest-order digit or digits in a reference number refer to the figure number in which the element is first introduced.

[0016] Figure 1 A LAA occlusion planning system according to one or more embodiments of the present disclosure is shown.

[0017] Figure 2 A logic flow is shown according to one or more embodiments of the present disclosure.

[0018] Figure 3A An image of a LAA is shown in accordance with one or more embodiments of the present disclosure.

[0019] Figure 3B An image of a LAA is shown in accordance with one or more embodiments of the present disclosure.

[0020] Figure 4A and Figure 4B A simulated seal of an occlusion device according to one or more embodiments of the present disclosure is shown.

[0021] Figure 5A , Figure 5B , Figure 5C and Figure 5D Leakage paths according to one or more embodiments of the present disclosure are shown.

[0022] Fig. 6A , Figure 6B and Figure 6C A simulated seal of an occlusion device according to one or more embodiments of the present disclosure is shown.

[0023] Figure 7 Leakage paths according to one or more embodiments of the present disclosure are shown.

[0024] Figure 8 is a graph of leakage paths according to one or more embodiments of the present disclosure.

[0025] Fig.9A and Fig. 9B A simulated anchor engagement is shown in accordance with one or more embodiments of the present disclosure.

[0026] Fig.10 Example computer-readable storage media in accordance with one or more embodiments of the present disclosure are shown.

[0027] Fig.11 An example computing device is shown in accordance with one or more embodiments of the present disclosure. DETAILED DESCRIPTION

[0028] The foregoing generally summarizes the features and technical advantages of the present disclosure, so that the following detailed description of the present disclosure is better understood. It should be appreciated by those skilled in the art that the disclosed embodiments can be easily used as a basis for modifying or designing other structures to achieve the same purpose of the present disclosure. When considered in conjunction with the accompanying drawings, the novel features of the present disclosure, including its organization and method of operation, and further purposes and advantages will be better understood from the following description. However, it should be clearly understood that each figure provided is only for the purpose of illustration and description and is not intended to be a definition of the limitation of the present disclosure.

[0029] Figure 1 1 shows a LAA occlusion planning system 100 according to one or more non-limiting examples of the present disclosure. Generally speaking, the LAA occlusion planning system 100 is a system for planning LAA occlusion using an occlusion device. For example, Watchman It is a LAA occlusion device. Patients with non-valvular atrial fibrillation can undergo LAA occlusion therapy, such as by implanting an occlusion device in the LAA to reduce the risk of LAA thromboembolism. The present disclosure can be used to pre-plan surgery for occluding the LAA with such a device.

[0030] The LAA occlusion planning system 100 includes a computing device 102. Optionally, the LAA occlusion planning system 100 includes an imager 104 and a display device 106. In an example, the computing device 102 can receive an image or a set of images representing the anatomical structure of the patient's LAA. For example, the computing device 102 can receive a LAA image 118 from the imager 104. In some embodiments, the imager 104 can be a CT imager that is arranged to generate an image including an indication (or representation) of the patient's LAA. Based in part on the LAA image 118, the computing device 102 can generate a simulated LAA occlusion image 132 that includes an indication of a simulated occlusion device deployment within the patient's LAA (e.g., the LAA represented in the LAA image 118).

[0031] Although the present disclosure uses CT imaging to describe illustrative embodiments, the imager 104 can be any of a LAA imaging device, such as a fluoroscopic imaging device, an ultrasound imaging device, a computed tomography (CT) imaging device, a magnetic resonance (MR) imaging device, a positron emission tomography (PET) imaging device, or a single photon emission computed tomography (SPECT) imaging device.

[0032] The imager 104 may generate an information element or data including an indication of the LAA image 118. The computing device 102 is communicatively coupled to the imager 104 and may receive data including an indication of the LAA image 118 from the imager 104. Typically, the LAA image 118 may include an indication of shape data and / or appearance data of the LAA. The shape data may include landmarks, surfaces, and boundaries of the three-dimensional surface of the LAA. In some examples, the LAA image 118 may be constructed from a two-dimensional (2D) or three-dimensional (3D) image of the LAA. In some embodiments, the LAA image 118 may be a medical image stored in a medical imaging database and subject to medical image access control. The term "image" is used herein for clarity of presentation and means that the LAA image 118 represents the structure and anatomical structure of the LAA. However, it should be understood that the term "image" is not restrictive. That is, the LAA image 118 may not be a conventionally used image, or more precisely, an image that is visible and interpretable to humans. For example, the LAA image 118 may be a point cloud, a parametric model, or other morphological description of the anatomical structure of the LAA. Furthermore, the LAA image 118 may be a single image or a series of images.

[0033] In general, display device 106 can be a digital display arranged to receive rendered image data and display the data in a graphical user interface. Computing device 102 can be any of a variety of computing devices. In some embodiments, computing device 102 can be incorporated into a console of display device 106 and / or implemented by it. In some embodiments, computing device 102 can be a workstation or server that is communicatively coupled to imager 104 and / or display device 106. In other embodiments, computing device 102 can be provided by a cloud-based computing device, such as provided by a computing-as-a-service system that can be accessed through a network (e.g., the Internet, an intranet, a wide area network, or the like). Computing device 102 may include processor 108, memory 110, input and / or output (I / O) device 112 and network interface 114.

[0034] Processor 108 may include circuitry or processor logic, such as any of a variety of commercially available processors. In some examples, processor 108 may include multiple processors, a multi-threaded processor, a multi-core processor (whether the multiple cores coexist on the same or separate dies), and / or some other type of multi-processor architecture by which multiple physically separate processors are linked together in some manner. Additionally, in some examples, processor 108 may include a graphics processing portion, and may include dedicated memory, multi-threaded processing, and / or some other parallel processing capabilities. In some examples, processor 108 may be an application specific integrated circuit (ASIC) or a field programmable integrated circuit (FPGA).

[0035] The memory 110 may include logic, a portion of which includes an integrated circuit array, forming a non-volatile memory to store data persistently, or forming a combination of non-volatile memory and volatile memory. It should be understood that the memory 110 may be based on any of a variety of technologies. In particular, the integrated circuit array included in the memory 120 may be arranged to form one or more types of memory, such as dynamic random access memory (DRAM), NAND memory, NOR memory, or the like.

[0036] I / O device 112 may be any of a variety of devices for receiving input and / or providing output. For example, I / O device 112 may include a keyboard, a mouse, a joystick, a foot pedal, a display other than display device 106 (e.g., touch, non-touch, or the like), a tactile feedback device, an LED, or the like.

[0037] The network interface 114 may include logic and / or features that support a communication interface. For example, the network interface 114 may include one or more interfaces that operate according to various communication protocols or standards to communicate through a direct or network communication link. Direct communication may be implemented via the communication protocol or standard described in one or more industry standards (including descendants and variants). For example, the network interface 114 may facilitate communication on a bus, such as a high-speed peripheral component interconnect (PCIe), a high-speed non-volatile memory (NVMe), a universal serial bus (USB), a system management bus (SMBus), a SAS (e.g., a serially connected small computer system interface (SCSI)) interface, a serial AT connection (SATA) interface, etc. In addition, the network interface 114 may include logic and / or features that implement communication through various wired or wireless network standards (e.g., 802.11 communication standards). For example, the network interface 114 may be arranged to support wired communication protocols or standards, such as Ethernet, etc. As another example, the network interface 114 may be arranged to support wireless communication protocols or standards, such as Wi-Fi, Bluetooth, ZigBee, LTE, 5G, etc.

[0038] The memory 110 may include instructions 116, LAA images 118, landing zones 120, occlusion device models 122, LAA models 124, deployment simulations 126, sealing simulations 128, anchoring simulations 130, and simulated LAA occlusion images 132. During operation, the processor 108 may execute the instructions 116 so that the computing device 102 receives the LAA images 118 from the imager 104 via the input and / or output (I / O) device 112 and receives the landing zone 120 from the physician. The processor 108 may also execute the instructions 116 to identify the recommended size of the occlusion device, simulate the deployment, sealing, and anchoring of the recommended occlusion device. In addition, the processor 108 may execute the instructions 116 to generate a simulated LAA occlusion image 132 and cause 132 to be displayed on the display device 106.

[0039] In general, the occlusion device model 122 and the LAA model 124 can be finite elements and can be used with any of a variety of finite element methods (FEM), such as applied element method (AEM), augmented FEM (A-FEM), generalized FEM, hybrid FEM, variable polynomial, hpk-FEM, extended FEM (XFEM), scaled boundary FEM (SBFEM), smoothed FEM (SFEM), meshless method, discontinuous Galerkin method, stretched mesh method, finite element limit analysis, loubignac iteration, crystal plasticity FEM (CPFEM) or virtual element method (VEM), etc.

[0040] In other examples, the occlusion device model 122 and the LAA model 124 may be machine learning models, particularly models suitable for image recognition and processing, such as neural networks, convolutional neural networks, K-nearest neighbors, decision trees, or support vector machines.

[0041] In some examples, the processor 108 can execute instructions 116 to solve equations represented by the occlusion device model 112 and the LAA model 124 given the LAA image 118 and the landing zone 120 (e.g., where the occlusion device model 122 and the LAA model 124 are finite elements) to determine the deployment simulation 126, the sealing simulation 128, and the anchoring simulation 130. In other examples, the processor 108 can execute instructions 116 to generate outputs from the occlusion device model 112 and the LAA model 124 given the LAA image 118 and the landing zone 120 (e.g., where the occlusion device model 122 and the LAA model 124 are machine learning models) to infer the deployment simulation 126, the sealing simulation 128, and the anchoring simulation 130. For some examples, although not shown in this figure, one or more occlusion device models 122 and / or LAA models 124 may be provided for each “simulation” (eg, deployment simulation 126 , sealing simulation 128 , or anchoring simulation 130 ).

[0042] The processor 108 may execute the instructions 116 to generate (eg, process, render, or the like) a simulated LAA occlusion image 132 from the deployment simulation 126 , the sealing simulation 128 , and / or the anchoring simulation 130 .

[0043] The above content will be described in more detail below, for example, in conjunction with Figure 2 200 in. In some examples, the LAA occlusion planning system 100 may be equipped with only the computing device 102. That is, the LAA occlusion planning system 100 may include the computing device 102, and a user of the LAA occlusion planning system 100 may provide an imager 104 and a display device 106 that are compatible with the computing device 102. In another example, the LAA occlusion planning system 100 may include only the instructions 116, the occlusion device model 122, and the LAA model 124, which may be executed by a similar computing system (e.g., a cloud computing service or the like) to generate the simulated LAA occlusion image 132 outlined herein.

[0044] It is noteworthy that the LAA occlusion planning system 100 includes custom components that are specifically configured, programmed, and / or arranged to perform the logic flows and methods detailed herein. For example, the processor 108 can be preconfigured to perform FEM using finite elements (e.g., the occlusion device model 122 and the LAA model 124). As another example, the processor 108 can be preconfigured to infer output from a machine learning model (e.g., the occlusion device model 122 and the LAA model 124).

[0045] Furthermore, the occlusion device model 122 and the LAA model 124 are pre-programmed with the detailed logic flows, methods, and techniques discussed herein and are not conventional or general purpose computing components.

[0046] Figure 2 200 according to some embodiments of the present disclosure. The logic flow 200 may be implemented to generate a preoperative planning image for LAA occlusion based on preoperative imaging. For example, the logic flow 200 may be provided to generate a simulated LAA occlusion image 132 given the LAA image 118. Although reference is made to the LAA occlusion planning system 100 and Figure 1 The logic flow 200 is described, but the example is not limited thereto. The logic flow 200 may be composed of Figure 1 The system is implemented by the components depicted in FIG.

[0047] Logic flow 200 may proceed to block 202. At block 202, “RECEIVE AN IMAGE COMPRISING AN INDICATION OF THE LAA ANATOMY OF THE PATIENT,” an image comprising an indication of the LAA anatomical structure of the patient is received. For example, the LAA image 118 may be received by the computing device 102 from the imager 104. The processor 108 may execute instructions 116 to receive the LAA image 118 from the imager 104.

[0048] Continuing with block 204, "Receive an indication of a landing zone in the LAA, an occlusion device," a landing location within the patient's LAA is received. For example, the landing zone 120 may be received by the computing device 102 (e.g., received from a physician via an input and / or output (I / O) device 112). As a specific example, the processor 108 may execute instructions 116 to cause the LAA image 118 to be displayed on the display device 106, and the landing zone 120 may be received from a physician, e.g., via a touch screen gesture, via mouse input, etc.

[0049] Continuing with block 206, “Determine a recommended size of the occlusion device based on the image and the desired landing zone,” the recommended size of the occlusion device is determined based on the image and the landing zone. In some examples, several occlusion devices may be available and represented by the occlusion device model 122, for example, occlusion devices having sizes between 20 and 40 millimeters (mm). In some examples, the processor 108 may execute instructions 116 to identify a size based on an orifice diameter of the LAA represented in the LAA image 118 at the landing zone 120. In some embodiments, at block 206, the processor 108 may execute instructions 116 to determine a recommended size or initial starting size for a simulation, where the final recommended size may be based on a simulation described herein (e.g., at blocks 212 and 214, etc.).

[0050] In some examples, the recommended occlusion device is identified based on determining the maximum LAA diameter at the landing zone and selecting an occlusion device having a diameter similar to the maximum LAA diameter at the landing zone when compressed 10% to 30%.

[0051] Continuing with block 208, “Simulate Occlusion Device Deployment,” deployment of the determined occlusion device size (and optionally one or more other sizes) in the patient's LAA is simulated. For example, a deployment simulation 126 is generated based on the LAA image 118, the landing zone 120, the occlusion device model 122, and the LAA model 124. More specifically, the processor 108 may execute instructions 116 to generate the deployment simulation 126 from the LAA image 118, the landing zone 120, the occlusion device model 122, and / or the LAA model 124. As a specific example, the processor 108 may execute instructions 116 to solve equations represented by the finite element representation of the occlusion device model 122 and the LAA model 124 to simulate how the determined size of the occlusion device responds to the anatomical structure of the LAA represented in the LAA image 118 given the landing zone 120 (e.g., expansion and deployment or the like). Furthermore, in some embodiments, the processor 108 may execute instructions 116 to solve equations represented by the finite element representations of the occlusion device model 122 and the LAA model 124 to simulate how alternative sizes of the occlusion device (e.g., larger and smaller occlusion device sizes, all occlusion device sizes, or the like) respond (e.g., expand and deploy, etc.) to the anatomy of the LAA represented in the LAA image 118 given the landing zone 120. In some embodiments, the processor 108 may execute instructions 116 to generate a surface mesh (e.g., a stereolithography (STL) mesh, etc.) of the LAA from the LAA image 118, which is then converted to a FEA mesh.

[0052] Continuing with block 210, “Simulate Occlusion Device Sealing,” sealing of the determined occlusion device size in the patient's LAA is simulated. For example, a sealing simulation 128 is generated based on the LAA image 118, the landing zone 120, the occlusion device model 122, the LAA model 124, and the deployment simulation 126. More specifically, the processor 108 may execute instructions 116 to generate the sealing simulation 128 based on the LAA image 118, the landing zone 120, the occlusion device model 122, the LAA model 124, and / or the deployment simulation 126. As a specific example, the processor 108 may execute instructions 116 to solve equations represented by the finite element representations of the occlusion device model 122 and the LAA model 124 to simulate how an expanded and deployed occlusion device (e.g., having a determined size and optionally an alternative size) seals (or forms a seal with) the anatomical structure of the LAA represented in the LAA image 118 given the landing zone 120 and the deployment simulation 126.

[0053] Continuing with block 212, "Simulate Occlusion Device Anchoring," anchoring of the determined occlusion device size in the patient's LAA is simulated. For example, the anchoring simulation 130 is generated based on the LAA image 118, the landing zone 120, the occlusion device model 122, the LAA model 124, and the deployment simulation 126. More specifically, the processor 108 may execute instructions 116 to generate the anchoring simulation 130 based on the LAA image 118, the landing zone 120, the occlusion device model 122, the LAA model 124, and / or the deployment simulation 126. As a specific example, the processor 108 may execute instructions 116 to solve equations represented by the finite element representation of the occlusion device model 122 and the LAA model 124 to simulate how an expanded and deployed occlusion device (e.g., having a determined size and optionally an alternative size) is anchored in the anatomical structure of the LAA represented in the LAA image 118 given the landing zone 120 and the deployment simulation 126.

[0054] Continuing with block 214, “Generate multiple images including indications of deployment, sealing, and anchoring,” images including indications of deployment, sealing, and anchoring are generated. For example, a simulated LAA occlusion image 132 may be generated based on the LAA image 118, the landing zone 120, the deployment simulation 126, the sealing simulation 128, and / or the anchoring simulation 130. The processor 108 may execute instructions 116 to generate a simulated LAA occlusion image 132 from the LAA image 118, the landing zone 120, the deployment simulation 126, the sealing simulation 128, and / or the anchoring simulation 130. In some examples, the processor 108 executes instructions 116 to generate 132 based on superimposing the LAA represented in the LAA image 118 with a simulated deployed occlusion device, simulated sealing, and / or simulated anchoring. As described above, in some embodiments, multiple simulations (e.g., recommended occlusion device sizes and alternative occlusion device sizes) are simulated. Thus, the simulated LAA occlusion images 132 may include a plurality of images representing various simulations of various occlusion device sizes.

[0055] Figure 3A and Figure 3BLAA image 300a and LAA image 300b are shown accordingly. LAA image 300a and LAA image 300b are representative images of the LAA, which may be similar to the above-described LAA image 118. For example, LAA image 300a and LAA image 300b are CT images of the patient's LAA, which may be received by computing device 102 from imager 104, as described above. As previously described, in some embodiments, LAA image 118 may be a series of images (e.g., multiple views, angles, etc.) of the patient's LAA. The anatomical structure of the LAA and a model from the LAA model 124 may be determined based on multiple LAA images 118. For example, points in the image representing a particular LAA anatomical structure may be identified, and a model from the LAA model 124 having similar (e.g., identical, within a threshold distance, etc.) points may be selected for use.

[0056] Figure 4A and Figure 4B Simulated deployment image 400a and simulated deployment image 400b are shown accordingly. Simulated deployment image 400a and simulated deployment image 400b represent images of deployment of an occlusion device in the LAA, which may be similar to one of the simulated LAA occlusion images 132 described above. For example, simulated deployment image 400a includes LAA 402, which is a graphical representation of a patient's LAA (e.g., based on LAA image 118), and a graphical representation of a deployed occlusion device 404a of a recommended size. Similarly, simulated deployment image 400a includes LAA 402 and a graphical representation of a deployed occlusion device 404b of an alternative size.

[0057] Figure 5A , Figure 5B , Figure 5C and Figure 5D Simulated sealing images 500a, 500b, 500c and 500d are shown accordingly. Simulated sealing images 500a, 500b, 500c and 500d represent the sealing or contact of the occluding device to the LAA anatomical structure. For example, simulated sealing images 500a, 500b, 500c and 500d include a graphical representation of the sealing or contact of the LAA402 and the occluding device (recommended size or alternative size) to the boundary of the LAA. In some examples, this can be shown by several views (for example, 4 in this case). These images include a contact surface 502 (which indicates (for example, represents) the sealing of the occluding device to the LAA) and a leak path 504 (which indicates (for example, represents) the gap in the contact between the occluding device and the LAA402).

[0058] In some examples, the simulated sealing images 500a, 500b, 500c, and 500d can be provided as part of the simulated LAA occlusion image 132. In other examples, the simulated sealing images 500a, 500b, 500c, and 500d can be represented in a 3D model that can be manipulated (e.g., rotated, etc.) to show all angles of the LAA 402, including the contact surface 502 and any leak paths 504. As another example, the simulated LAA occlusion image 132 can include a video that includes image frames, such as the simulated sealing images 500a, 500b, 500c, and 500d, to provide a graphical representation of the boundaries of the LAA 402, which shows the contact surface 502 and the leak paths 504.

[0059] In some examples, a simulated sealing image can be generated based on a two-dimensional (2D) cross-sectional view of a deployed occlusion device at a desired landing zone. In such a 2D cross-sectional view, the outlines of the LAA anatomy and the occlusion device can be identified or indicated, and any "gaps" between the LAA anatomy and the occlusion device can be highlighted (e.g., indicated by color, graphics, etc.).

[0060] Fig. 6A A simulated anchor engagement image 600 is shown. The simulated anchor engagement image 600 includes an indication of a deployed occlusion device of a recommended size (or an alternative size). It should be understood that a LAA occlusion device typically includes an anchor to engage the tissue of the LAA, which "holds" the occlusion device in place until the LAA tissue grows into and around the occlusion device. For example, the simulated anchor engagement image 600 shows a deployed occlusion device 404a with an anchor 602. In addition, the simulated anchor engagement image 600 includes a graphical representation (or indication) of the engagement of the tip of each anchor 602. For example, the simulated anchor engagement image 600 includes a color map showing the penetration distance of each anchor 602 into the tissue of the LAA402. In other examples, the simulated anchor engagement image 600 may include a color map showing the contact force of each anchor 602 on the tissue of the LAA402.

[0061] Figure 6B In more detail, the Fig. 6A 604 of a simulated anchor engagement image 600. As can be more clearly seen from this figure, the anchor engagement portion 606 of each anchor 602 of the deployed occlusion device 404a is shown as a color map (or heat map) that indicates (or represents) the engagement of the anchor 602 with the tissue of the LAA 402 (e.g., penetration depth, contact force, etc.).

[0062] In some examples, the simulated sealing images 500a, 500b, 500c, and 500d can be provided as part of the simulated LAA occlusion image 132. In other examples, the simulated sealing images 500a, 500b, 500c, and 500d can be represented in a 3D model that can be manipulated (e.g., rotated, etc.) to show all angles of the LAA 402, including the contact surface 502 and any leak paths 504. As another example, the simulated LAA occlusion image 132 can include a video that includes image frames, such as the simulated sealing images 500a, 500b, 500c, and 500d, to provide a graphical representation of the boundaries of the LAA 402, which shows the contact surface 502 and the leak paths 504.

[0063] In some embodiments, processor 108 may execute instructions 116 to determine an optimal size for a LAA occlusion device based on several simulated sealing images. Fig. 6A , Figure 6B and Figure 6C Pairs of sealing images 600a, 600b, and 600c are shown accordingly. These pairs of sealing images depict the simulated sealing of the LAA occlusion devices 602a, 602b, and 602c to the LAA anatomical structure 604. Based on these pairs of images or based on the FAE simulation and image data, the processor 108 can execute instructions 116 to determine the path loop with the minimum gap area (e.g., around the LAA occlusion device 602a, etc.). The minimum gap area and / or the minimum gap path can be reported to the user (e.g., via the display device 106, etc.). In some embodiments, the processor 108 can execute instructions 116 to determine the minimum gap area based on hydraulic diameter or flow resistance using simulated sealing.

[0064] For example, Figure 7 The LAA anatomy 702 and leak path 704 are shown based on a simulated deployed occlusion device (not shown). Figure 8 A graph 800 is shown showing the gap of the leak path 704 plotted at 804 versus the distance along the leak path 704 on the x-axis 802. In some examples, the total leak path 704 gap can be integrated (e.g., the area under the graph 800, etc.), and the plugging device with the smallest total leak path gap can be identified as the optimal or recommended plugging device size. In some embodiments, the integrated leak path gap can be normalized for the plugging device size (e.g., 35 mm, 37 mm, 40 mm, etc.).

[0065] Fig.9AA simulated anchor engagement image 900 is shown. The simulated anchor engagement image 900 includes an indication of a deployed occlusion device of a recommended size (or an alternative size). It should be understood that a LAA occlusion device typically includes an anchor to engage the tissue of the LAA, which "holds" the occlusion device in place until the LAA tissue grows into and around the occlusion device. For example, the simulated anchor engagement image 900 shows a deployed occlusion device 404a with an anchor 902. In addition, the simulated anchor engagement image 900 includes a graphical representation (or indication) of the engagement of the tip of each anchor 902. For example, the simulated anchor engagement image 900 includes a color map showing the penetration distance of each anchor 902 into the tissue of the LAA402. In other examples, the simulated anchor engagement image 900 may include a color map showing the contact force of each anchor 902 on the tissue of the LAA402.

[0066] Fig. 9B In more detail, the Fig.9A 904 of an exploded view of a simulated anchor engagement image 900. As can be more clearly seen from this figure, the anchor engagement portion 906 of each anchor 902 of the deployed occlusion device 404a is shown as a color map (or heat map) indicating (or representing) the engagement of the anchor 902 with the tissue of the LAA 402 (e.g., penetration depth, contact force, etc.). In some embodiments, the penetration depth can be identified and reported (e.g., marking a potential preformed area, etc.). In another example, the number of engaged anchors (e.g., greater than a threshold level, etc.) can be identified and reported (e.g., indicating potential stability of deployment, etc.).

[0067] Fig.10A computer-readable storage medium 1000 is shown. The computer-readable storage medium 1000 may include any non-transient computer-readable storage medium or machine-readable storage medium, such as an optical, magnetic or semiconductor storage medium. In various embodiments, the computer-readable storage medium 1000 may include an article of manufacture. In some embodiments, 700 may store computer-executable instructions 1002 that can be executed by a circuit (e.g., a processor 108, etc.). For example, the computer-executable instructions 1002 may include instructions for implementing operations described in relation to the logic flow 200, the instructions 116, the occlusion device model 122 and / or the LAA model 124. Examples of computer-readable storage media 1000 or machine-readable storage media may include any tangible medium capable of storing electronic data, including volatile memory or non-volatile storage, removable or non-removable memory, erasable or non-erasable memory, writable or rewritable memory, etc. Examples of computer-executable instructions 1002 may include any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, object-oriented code, visualization code, etc.

[0068] Fig.11 A diagram of a machine 1100 in the form of a computer system is shown in which a set of instructions for causing the machine to perform any one or more of the methodologies discussed herein may be executed. More specifically, Fig.11 A diagram of a machine 1100 in the form of an example computer system is shown in which instructions 1108 (e.g., software, programs, applications, applet, applications, or other executable code) may be executed to cause the machine 1100 to perform any one or more of the methodologies discussed herein. For example, the instructions 1108 may cause the machine 1100 to perform Figure 2 More generally, the instructions 1108 may cause the machine 1100 to provide pre-operative planning for a LAA occlusion procedure, e.g., receiving the LAA image 118 and generating a deployment simulation 126, a sealing simulation 128, an anchoring simulation 130, and / or a simulated LAA occlusion image 132, as described above.

[0069] Instructions 1108 convert a general unprogrammed machine 1100 into a specific, specially programmed machine 1100, which is configured to perform the functions described and shown in a specific manner. In an alternative embodiment, the machine 1100 operates as a standalone device, or can be coupled (e.g., networked) to other machines. In a networked deployment, the machine 1100 can operate as a server machine or a client machine in a server-client network environment, or as a peer machine in a peer (or distributed) network environment. The machine 1100 may include, but is not limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a PDA, an entertainment media system, a cellular phone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a network application, a network router, a network switch, a bridge, or any machine capable of sequentially or otherwise executing instructions 1108, which specify the actions to be taken by the machine 1100. Further, while a single machine 1100 is illustrated, the term "machine" shall also be taken to include any collection of machines 200 that individually or jointly execute instructions 1108 to perform any one or more of the methodologies discussed herein.

[0070] The machine 1100 may include a processor 1102, a memory 1104, and an I / O component 1142, which may be configured to communicate with each other, such as via a bus 1144. In an example embodiment, the processor 1102 (e.g., a central processing unit (CPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPU), a digital signal processor (DSP), an ASIC, a radio frequency integrated circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor 1106 that may execute instructions 1108 and a processor 1110. The term "processor" is intended to include multi-core processors, which may include two or more independent processors (sometimes referred to as "cores") that may execute instructions simultaneously. Although Fig.11 Multiple processors 1102 are shown, but the machine 1100 may include a single processor with a single core, a single processor with multiple cores (eg, a multi-core processor), multiple processors with a single core, multiple processors with multiple cores, or any combination thereof.

[0071] The memory 1104 may include a main memory 1112, a static memory 1114, and a storage unit 1116, all of which may be accessed by the processor 1102, such as via a bus 1144. The main memory 1104, the static memory 1114, and the storage unit 1116 store instructions 1108 that embody any one or more of the methodologies or functions described herein. During execution of the instructions by the machine 1100, the instructions 1108 may also reside, completely or partially, within the main memory 1112, within the static memory 1114, within a machine-readable medium 1118 within the storage unit 1116, within at least one of the processors 1102 (e.g., within a cache of the processor), or within any suitable combination thereof.

[0072] I / O components 1142 may include a variety of components to receive input, provide output, generate output, send information, exchange information, capture measurements, etc. The specific I / O components 1142 included in a particular machine will depend on the type of machine. For example, a portable machine such as a mobile phone may include a touch input device or other such input mechanism, while a headless server machine may not include such a touch input device. It should be understood that I / O components 1142 may include Fig.11 1142 are grouped according to function only to simplify the following discussion, and the grouping is by no means limiting. In various example embodiments, the I / O components 1142 may include output components 1128 and input components 1130. The output components 1128 may include visual components (e.g., displays such as plasma display panels (PDPs), light emitting diode (LED) displays, liquid crystal displays (LCDs), projectors, or cathode ray tubes (CRTs)), acoustic components (e.g., speakers), tactile components (e.g., vibration motors, resistive mechanisms), other signal generators, etc. The input components 1130 may include alphanumeric input components (e.g., keyboards, touch screens configured to receive alphanumeric input, optical keyboards, or other alphanumeric input components), point-based input components (e.g., mice, touch pads, trackballs, joysticks, motion sensors, or other pointing instruments), tactile input components (e.g., physical buttons, touch screens or other tactile input components that provide location and / or force of touch or touch gestures), audio input components (e.g., microphones), etc.

[0073] In further example embodiments, the I / O component 1142 may include a biometric component 1132, a motion component 1134, an environment component 1136, or a position component 1138, as well as various other components. For example, the biometric component 1132 may include a component for detecting expressions (e.g., hand expressions, facial expressions, vocal expressions, body postures, or eye tracking), measuring biosignals (e.g., blood pressure, heart rate, body temperature, sweating, or brain waves), identifying people (e.g., voice recognition, retinal recognition, facial recognition, fingerprint recognition, or EEG-based recognition), etc. The motion component 1134 may include an acceleration sensor component (e.g., an accelerometer), a gravity sensor component, a rotation sensor component (e.g., a gyroscope), etc. Environmental component 1136 may include, for example, an illumination sensor component (e.g., a photometer), a temperature sensor component (e.g., one or more thermometers that detect ambient temperature), a humidity sensor component, a pressure sensor component (e.g., a barometer), an acoustic sensor component (e.g., one or more microphones that detect background noise), a proximity sensor component (e.g., an infrared sensor that detects nearby objects), a gas sensor (e.g., a gas detection sensor that detects dangerous gas concentrations to ensure safety or measures pollutants in the atmosphere), or other components that can provide indications, measurements, or signals corresponding to the surrounding physical environment. Position component 1138 may include a position sensor component (e.g., a GPS receiver component), an altitude sensor component (e.g., an altimeter or barometer that detects air pressure, from which altitude can be derived), an orientation sensor component (e.g., a magnetometer), etc.

[0074] Communication can be implemented using a variety of technologies. I / O components 1142 may include communication components 1140, which are operable to couple machine 1100 to network 1120 or device 1122 via coupling 1124 and coupling 1126, respectively. For example, communication components 1140 may include a network interface component or another suitable device that interfaces with network 1120. In further examples, communication components 1140 may include wired communication components, wireless communication components, cellular communication components, near field communication (NFC) components, Parts (e.g. Low power consumption), Components and other communication components to provide communication via other modes. Device 1122 can be another machine or any of a variety of peripheral devices (e.g., a peripheral device coupled via USB).

[0075] In addition, the communication component 1140 can detect an identifier or include components that can be used to detect an identifier. For example, the communication component 1140 can include a radio frequency identification (RFID) tag reader component, an NFC smart tag detection component, an optical reader component (e.g., an optical sensor for detecting one-dimensional bar codes (such as universal product codes (UPC) bar codes), multi-dimensional bar codes (such as quick response (QR) codes), Aztec codes, data matrix, data glyphs, MaxiCode, PDF417, Hypercode, UCC RSS-2D bar codes, and other optical codes) or an acoustic detection component (e.g., a microphone for identifying a tag audio signal). In addition, various information can be derived via the communication component 1140, such as a location via Internet Protocol (IP) geolocation, a location via Internet Protocol (IP), ... The location of signal triangulation, the location of an NFC beacon signal via detection that can indicate a specific location, etc.

[0076] Various memories (i.e., memory 1104, main memory 1112, static memory 1114, and / or memory of processor 1102) and / or storage unit 1116 may store one or more sets of instructions and data structures (e.g., software) embodying or used by any one or more of the methods or functions described herein. When executed by processor 1102, these instructions (e.g., instructions 1108) cause various operations to implement the disclosed embodiments.

[0077] As used herein, the terms "machine storage medium," "device storage medium," and "computer storage medium" have the same meaning and may be used interchangeably in this disclosure. These terms refer to a single or multiple storage devices and / or media (e.g., centralized or distributed databases and / or associated caches and servers) that store executable instructions and / or data. Accordingly, these terms should be considered to include, but are not limited to, solid-state memory, optical and magnetic media, including memory internal or external to the processor. Specific examples of machine storage media, computer storage media, and / or device storage media include nonvolatile memory, including, for example, semiconductor memory devices such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), FPGAs, and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM optical disks. The terms "machine storage medium," "computer storage medium," and "device storage medium" expressly exclude carrier waves, modulated data signals, and other such media, at least some of which are included in the term "signal media" discussed below.

[0078] In various example embodiments, one or more portions of network 1120 may be an ad hoc network, an intranet, an extranet, a VPN, a LAN, a WLAN, a WAN, a WWAN, a MAN, the Internet, a portion of the Internet, a portion of a PSTN, a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, 1120, or a portion of network 1120, may include a wireless or cellular network, and coupling 1124 may be a code division multiple access (CDMA) connection, a global system for mobile communications (GSM) connection, or another type of cellular or wireless coupling. In this example, coupling 1124 may implement any of various types of data transmission technologies, such as single carrier radio transmission technology (1xRTT), evolution data optimized (EVDO) technology, general packet radio service (GPRS) technology, enhanced data rates for GSM evolution (EDGE) technology, third generation partnership project (3GPP) including 3G, fourth generation wireless (4G) network, universal mobile telecommunications system (UMTS), high speed packet access (HSPA), world wide interconnection for microwave access (WiMAX), long term evolution (LTE) standards, other standards defined by various standards development organizations, other remote protocols, or other data transmission technologies.

[0079] Instructions 1108 may be sent or received over network 1120 using a transmission medium via a network interface device (e.g., a network interface component included in communication component 1140) and using any of several well-known transmission protocols (e.g., Hypertext Transfer Protocol (HTTP)). Similarly, instructions 1108 may be sent or received to device 1122 using a transmission medium via coupling 1126 (e.g., a peer-to-peer coupling). The terms "transmission medium" and "signal medium" have the same meaning and may be used interchangeably in this disclosure. The terms "transmission medium" and "signal medium" shall be deemed to include any intangible medium that may store, encode, or carry instructions 1108 for execution by machine 1100, and include digital or analog communication signals or other intangible media to facilitate the communication of such software. Thus, the terms "transmission medium" and "signal medium" shall be deemed to include any form of modulated data signal, carrier wave, etc. The term "modulated data signal" refers to a signal that has one or more of its characteristics set or changed so as to encode information in the signal.

[0080] Terms used herein should be given their ordinary meaning in the relevant art or the meaning indicated by the context in which they are used, but if an explicit definition is provided, that meaning shall prevail.

[0081] References to "one embodiment" or "an embodiment" herein do not necessarily refer to the same embodiment, although they may be the same. Unless the context clearly requires otherwise, throughout the specification and claims, the words "including", "including", etc. should be interpreted as inclusive, not exclusive or exhaustive; that is, in the sense of "including but not limited to", words used in the singular or plural also include the plural or singular accordingly, unless expressly limited to one or more. In addition, the words "herein", "above", "below" and words of similar meaning used in this application refer to the entire application, not any part of this application. When the claims use the word "or" to refer to a list of two or more items, the word covers all the following interpretations of the word: any item in the list, all items in the list, and any combination of items in the list, unless expressly limited to one or another. Any term not expressly defined herein has the ordinary meaning commonly understood by one or more persons skilled in the relevant art.

Claims

1. A method for pre-planning left atrial appendage (LAA) occlusion, comprising: receiving an image including an indication of a LAA of a patient; receiving instructions for landing zones for blocking equipment; simulating deployment of the occlusion device in the LAA of the patient; simulating sealing of the patient's LAA by a deployed occlusion device; simulating anchoring of the occlusion device in the LAA of the patient; as well as A graphical representation of the sealing and anchoring of the occlusion device in the patient's LAA is generated.

2. The method of claim 1, comprising generating a graphical representation of the deployed occlusion device in the LAA of the patient.

3. The method of claim 2, generating a graphical representation of the deployed occluding device in the patient's LAA, comprising superimposing the simulated deployed occluding device with the graphical representation of the patient's LAA.

4. The method according to any one of claims 1 to 3, comprising determining a recommended size of the occluding device based on the received images.

5. The method according to claim 4, comprising: identifying a diameter of an orifice of the LAA of the patient based on the received image; selecting an occluding device size from a group of occluding device sizes that is within a threshold expanded diameter of the diameter of the orifice; and The selected occluding device size is identified as the recommended occluding device. 6 . The method of claim 4 , comprising simulating deployment of the occluding device in the LAA of the patient for an occluding device having the recommended size. 7 . The method of claim 6 , comprising simulating deployment of the occluding device in the LAA of the patient for an occluding device having a size different than a recommended size.

8. The method of claim 6, comprising generating a graphical representation of the deployed occluding device in the patient's LAA, comprising superimposing a simulated deployed occluding device having a recommended size with the graphical representation of the patient's LAA, and superimposing a simulated deployed occluding device having a different size with the graphical representation of the patient's LAA.

9. The method of any one of claims 1 to 8, generating a graphical representation of the seal of the deployed occluding device in the patient's LAA, comprising generating a plurality of images including an indication of the patient's LAA and an indication of a contact surface representing contact between the deployed occluding device and the patient's LAA.

10. The method of claim 9, the plurality of images comprising an indication of the patient's LAA, an indication of the contact surface, and an indication of a leak path. The method of claim 10 , comprising generating a rotatable model from the plurality of images.

12. According to the method described in any one of claims 1 to 11, a graphical representation of the anchoring of the occlusion device in the LAA of the patient is generated, including generating an image of the simulated deployed occlusion device, the image including an indication of an anchor of the occlusion device and a representation of the junction of the anchor with the tissue of the LAA of the patient.

13. The method according to claim 12, wherein: The representation of the joint of the anchor includes a color map.

14. A computer-readable storage medium comprising instructions which, when executed by a processor of a computing device, cause the processor to implement the method of claim 1.

15. A computing system comprising: processor; and A memory comprising instructions that, when executed by the processor, cause the computing system to implement the method of claim 1.

Images