Intravascular image boundary detection in response to location within a region and associated systems, devices, and methods

Abstract

An apparatus includes processor circuitry configured to communicate with an intravascular imaging catheter. The processor circuitry is configured to output a first screen display to a display in communication with the processor circuitry, the first screen display including an intravascular image obtained by the intravascular imaging catheter, wherein the intravascular image includes a vascular lumen and vascular tissue. The processor circuitry is further configured to: receive a single user input on the intravascular image identifying a location within a region of interest; and automatically determine the boundary of the region of interest in response to the single user input, wherein the boundary surrounds the location identified by the single user input. The processor circuitry is further configured to output a second screen display to the display, the second screen display including the intravascular image and the boundary of the region of interest superimposed on the intravascular image.

Description

Technical Field

[0001] This disclosure generally relates to intravascular imaging using intravascular imaging catheters, and particularly to generating computer-recognized boundaries (e.g., vascular lumen boundaries) of regions of interest in intravascular images in response to a user’s recognition of the location within a region of interest (e.g., inside a vascular lumen). Background Technology

[0002] Intravascular ultrasound (IVUS) imaging, as a diagnostic tool, is widely used in interventional cardiology to evaluate diseased blood vessels (e.g., arteries) within the body to determine the need for treatment, guide intervention, and / or assess its effectiveness. An IVUS device comprises one or more ultrasound transducers that are inserted into the blood vessel and guided to the area to be imaged. The transducers emit ultrasound energy to create an image of the vessel of interest. Discontinuities caused by tissue structures (e.g., layers of the vessel wall), red blood cells, and other features of interest partially reflect ultrasound waves. The echoes of the reflected waves are received by the transducers and transmitted to the IVUS imaging system. The imaging system processes the received ultrasound echoes to produce a cross-sectional image of the vessel at the device's location.

[0003] Peripheral vascular procedures (such as angioplasty and stenting in peripheral veins (inferior vena cava, iliac vein, femoral vein), IVC filter removal, endovascular aneurysm repair (EVAR) and fenestrated stent endovascular aortic repair (FEVAR) procedures (as well as similar procedures in terms of abdominal features), plaque resection, and thrombectomy) are procedures that utilize IVUS. Different diseases or medical procedures can produce physical characteristics with varying sizes, structures, densities, water content, and accessibility to imaging sensors. For example, deep vein thrombosis (DVT) produces blood cell clots, while postthrombotic syndrome (PTS) creates a network or other residual structural effect in the vessel with a composition similar to the vessel wall itself, and may therefore be difficult to distinguish from the vessel wall. Stents are dense (e.g., metallic) objects that can be placed in a vessel or lumen to keep the vessel or lumen open to a specific diameter. Compression occurs when anatomical structures outside the vessel or lumen collide with it and cause it to constrict.

[0004] Pre-treatment decisions (e.g., whether and where to place a stent) can depend on accurate measurements (and / or other anatomical measurements) of the vascular lumen area at a series of locations across the vessel during the procedure itself. Similarly, post-treatment decisions (e.g., whether a stent has been accurately placed and expanded, whether additional stents are needed, etc.) also rely on accurate measurements taken during the procedure. Tools exist to help users measure regions of interest in IVUS images. These tools rely on the user's experience and visual interpretation of the images, and also on their dexterity and familiarity with tools used for measuring areas (e.g., trackballs, mice, etc.).

[0005] In deep vein anatomy, image interpretation becomes more challenging due to reduced image resolution in the far field and ringing and other image artifacts. Therefore, some systems currently attempt to provide users with automated measurement results. However, users still require a way to correct the results of these automated algorithms, or even to redraw the measurements from scratch on the region of interest. The variability in how users handle the provided tools and therefore in redrawing or correcting contours can lead to significant variability in the resulting measurement results. In fast-paced environments such as operating rooms (ORs), where patients are on the operating table, time can be critical. Sometimes, physicians are also assisted by additional technicians who may be working shifts in the OOR. Physicians may choose to leave the sterile area or perform measurements within the sterile area using the protective sleeve on the device. Deep vein anatomy can also be quite complex, and not all features are visible to the naked eye; users often adjust image settings such as brightness, contrast, and gamma (clarity) for better interpretation. In ORs, catheterization labs, or similar environments, clinicians or assistant technicians may face considerable pressure to perform measurements quickly and efficiently.

[0006] Even when using the same images, all these factors increase the variability of measurements produced on an IVUS imaging system.

[0007] The information included in the background section of this specification, including any references cited herein and any descriptions or discussions thereof, is included for technical reference purposes only and should not be considered as subject matter constituting a constraint on the scope of this disclosure. Summary of the Invention

[0008] According to at least one embodiment of this disclosure, a context-sensitive intravascular measurement system is provided that enables a user to request automatic boundary detection and measurement of specific anatomical structures, whether on a single tomographic image or along an entire region displayed longitudinally (ILD) of the image. The context-sensitive intravascular measurement system also enables a user to request automatic correction of previously established anatomical boundaries or to automatically complete partial contours manually drawn by a clinician to ensure that computer-generated boundaries are correct. Accurate measurement of the vessel lumen or other anatomical features or regions of interest stems from the correctness of the computer-generated boundaries. The context-sensitive intravascular measurement system includes a user interface (UI) capable of touch or click input on IVUS images or other intravascular cross-sectional images (e.g., optical coherence tomography or OCT), and image analysis performed on the underlying raw image data for spectral characteristics or image analysis performed using pattern recognition through deep learning. Therefore, this disclosure advantageously provides a tool for rapidly obtaining desired measurement results in a robust and repeatable manner. The context-sensitive intravascular measurement system has specific, but not exclusive, use for ultrasound imaging of occluded vessels before and after stent placement.

[0009] A system of one or more computers can be configured to perform specific operations or actions by means of software, firmware, hardware, or combinations thereof installed on the system, which, in operation, causes the system to perform actions. One or more computer programs can be configured to perform specific operations or actions by means of instructions that, when executed by a data processing device, cause the device to perform actions. One general aspect includes an apparatus comprising processor circuitry configured to communicate with an intravascular imaging catheter. The processor circuitry is further configured to: output a first screen display to a display in communication with the processor circuitry, the first screen display including an intravascular image obtained by the intravascular imaging catheter, wherein the intravascular image includes a vascular lumen and vascular tissue; receive a single user input on the intravascular image identifying a location within a region of interest; automatically determine the boundary of the region of interest in response to the single user input, wherein the boundary surrounds the location identified by the single user input; and output a second screen display to the display, the second screen display including the intravascular image and the boundary of the region of interest superimposed on the intravascular image. Other embodiments in this regard include corresponding computer systems, apparatuses, and computer programs recorded on one or more computer storage devices, each of which is configured to perform the actions of the method.

[0010] Implementations may include one or more of the following features. In some aspects, the display may include a touchscreen display, wherein a single user input may include a single touch or click at a location within a region of interest on an intravascular image. In some aspects, to automatically determine the boundary of the region of interest, processor circuitry is configured to: determine the area of ​​the region of interest within the intravascular image; and generate a boundary surrounding the area of ​​the region of interest. In some aspects, processor circuitry is further configured to associate a location identified by a single user input with a first sub-region of the intravascular image, wherein, to automatically determine the boundary of the region of interest, processor circuitry is configured to: identify a second sub-region adjacent to the first sub-region; and, based on a comparison between parameters of the first sub-region and parameters of the second sub-region, include the second sub-region as part of the area of ​​the region of interest or part of the boundary of the region of interest. In some aspects, the first sub-region and the second sub-region may each include one or more pixels of the intravascular image. In some aspects, processor circuitry is configured to: include the second sub-region as part of the area of ​​the region of interest when a comparison indicating that the parameters of the second sub-region match those of the first sub-region; and include the second sub-region as part of the boundary of the region of interest when a comparison indicating that the parameters of the second sub-region do not match those of the first sub-region. In some aspects, the processor is configured to include a first sub-region as part of the area of ​​the region of interest. In some aspects, a second sub-region is in contact with the first sub-region. In some aspects, to automatically determine the boundary of the region of interest, the processor circuitry is configured to: identify additional sub-regions adjacent to the first sub-region; and include the additional sub-regions as part of the area of ​​the region of interest or part of the boundary of the region of interest, wherein the processor circuitry is configured to: iteratively identify and include the additional sub-regions for each of a plurality of additional sub-regions. In some aspects, the distance of the plurality of sub-regions from the first sub-region increases. In some aspects, the processor circuitry is configured to terminate the iteration when the boundary of the region of interest completely surrounds the first sub-region. In some aspects, the first screen display does not include an initial boundary superimposed on the intravascular image, such that the boundary of the region of interest is added to the intravascular image in the second screen display. In some aspects, the first screen display may include an initial boundary superimposed on the intravascular image, such that the boundary of the region of interest in the second screen display may include a modification of the initial boundary. In some aspects, the modification may include making the area of ​​the region of interest indicated by the boundary of the region of interest in the second screen display smaller than the area of ​​the region of interest indicated by the initial boundary in the first screen display. Implementations of the described techniques may include hardware, methods or processes, or computer software on a computer-accessible medium.

[0011] One general aspect includes an apparatus comprising processor circuitry configured to communicate with an intravascular imaging catheter. The processor circuitry is configured to: output a first screen display to a display in communication with the processor circuitry, the first screen display including an intravascular image obtained by the intravascular imaging catheter, wherein the intravascular image includes a vascular lumen and vascular tissue; receive user input on the intravascular image, drawing only a first portion of the boundary of a region of interest; automatically determine a second portion of the boundary of the region of interest in response to the user input, such that the first and second portions together define the entire boundary of the region of interest; and output a second screen display to the display, the second screen display including the intravascular image and the boundary of the region of interest superimposed on the intravascular image. Other embodiments of this aspect include corresponding computer systems, apparatuses, and computer programs recorded on one or more computer storage devices, each configured to perform actions of the method.

[0012] Implementations may include one or more of the following features. In some aspects, the display may include a touchscreen display, wherein user input that only draws a first portion may include touch and drag input along the boundary of the region of interest on an intravascular image. In some aspects, to automatically determine a second portion of the boundary of the region of interest, processor circuitry is configured to: determine a first parameter on a first side of the first portion of the boundary of the region of interest; determine a second parameter on an opposite second side of the first portion of the boundary of the region of interest; determine a relationship between the first parameter and the second parameter; and generate a second portion of the boundary of the region of interest to maintain this relationship along the second portion of the boundary of the region of interest. Implementations of the described techniques may include hardware, methods or processes, or computer software on a computer-accessible medium.

[0013] One general aspect includes an apparatus comprising processor circuitry configured to communicate with an intravascular imaging catheter. The processor circuitry is configured to: output a first screen display to a display in communication with the processor circuitry, the first screen display including a longitudinal cross-sectional image of a blood vessel, wherein the longitudinal cross-sectional image is generated based on multiple radial cross-sectional images of the blood vessel obtained from the intravascular imaging catheter, wherein the longitudinal cross-sectional images of the blood vessel include a lumen and vascular tissue; receive user input on the longitudinal cross-sectional image to identify regions within a region of interest, and automatically determine, in response to the user input, the boundaries of regions of interest in a subset of the multiple cross-sectional images associated with the region identified by the user input on the longitudinal cross-sectional image; and output a second screen display to the display, the second screen display including: the longitudinal cross-sectional image; the subset of radial cross-sectional images; and the boundaries of the regions of interest superimposed on the radial cross-sectional images. Other embodiments of this aspect include corresponding computer systems, apparatuses, and computer programs recorded on one or more computer storage devices, each computer system, apparatus, and computer program being configured to perform actions of the method.

[0014] Implementations may include one or more of the following features. In some aspects, the display may include a touchscreen display, wherein user input for identifying the region may include touch and drag input or click and drag input within the lumen of a blood vessel on an intravascular image. In some aspects, to automatically determine the boundary of the region of interest, processor circuitry is configured for each radial cross-sectional image of a subset: associating a portion of the region identified by the user input with the corresponding radial cross-sectional image; mapping the portion of the region identified by the user input to a first sub-region within the region of interest; including the first sub-region as part of the area of ​​the region of interest; identifying additional sub-regions adjacent to the first sub-region; including the additional sub-regions as part of the area of ​​the region of interest or part of the boundary of the region of interest, wherein the processor circuitry is configured to: iteratively identify and include the additional sub-regions for each of a plurality of additional sub-regions. Implementations of the described techniques may include hardware, methods or processes, or computer software on a computer-accessible medium.

[0015] This summary is provided to present the selection of concepts in a simplified form, which are further described in the detailed description below. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to limit the scope of the claimed subject matter. A broader presentation of the features, details, uses, and advantages of the context-sensitive intravascular measurement system as defined in the claims is provided in the following written description of various embodiments of this disclosure and illustrated in the accompanying drawings. Attached Figure Description

[0016] Illustrative embodiments of this disclosure will be described with reference to the accompanying drawings, in which: Figure 1 This is a schematic diagram of an intraluminal imaging system based on various aspects of this disclosure.

[0017] Figure 2 The illustration shows blood vessels (e.g., arteries and veins) in the human body.

[0018] Figure 3 The illustration shows a blood vessel containing compression.

[0019] Figure 4 The illustration shows a blood vessel containing compression and in which a stent is expanded to restore flow.

[0020] Figure 5 This is a schematic diagram of a processor circuit according to an embodiment of the present disclosure.

[0021] Figure 6 The following are illustrations of IVUS images, image portrait display (ILD), and screen displays of selection or addition tools, in accordance with various aspects of this disclosure.

[0022] Figure 7 It is a screen display showing the automatically identified lumen boundaries in an IVUS image, based on various aspects of this disclosure.

[0023] Figure 8 This is a schematic diagram view of an exemplary method for measuring and adding area in the form of a flowchart, based on various aspects of this disclosure.

[0024] Figure 9 This is a schematic diagram view in flowchart form of exemplary univariate comparison steps according to various aspects of this disclosure.

[0025] Figure 10A This is a schematic diagram view in flowchart form of exemplary multivariate comparison steps according to various aspects of this disclosure.

[0026] Figure 10B This is a schematic diagram view of an exemplary multivariate comparison and identification method in flowchart form based on various aspects of this disclosure.

[0027] Figure 11 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0028] Figure 12 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0029] Figure 13It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0030] Figure 14 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0031] Figure 15 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0032] Figure 16 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0033] Figure 17 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0034] Figure 18 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0035] Figure 19 The screen display shows an IVUS image, an image portrait display (ILD), and a deselection or subtraction tool, in accordance with various aspects of this disclosure.

[0036] Figure 20 It is a screen display showing the automatically identified lumen boundaries in an IVUS image, based on various aspects of this disclosure.

[0037] Figure 21 This is a schematic diagram of an exemplary method for subtracting lumen area in the form of a flowchart, based on various aspects of this disclosure.

[0038] Figure 22 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0039] Figure 23 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0040] Figure 24 The following are illustrations of IVUS images, image vertical display (ILD), and screen displays of drawing tools, in accordance with various aspects of this disclosure.

[0041] Figure 25 It is a screen display showing IVUS images, image longitudinal display (ILD), and automatically completed drawing of lumen boundaries, in accordance with various aspects of this disclosure.

[0042] Figure 26A This is a schematic diagram of an exemplary method for automatically completing lumen boundaries in the form of a flowchart, based on various aspects of this disclosure.

[0043] Figure 26B This is a schematic diagram of an exemplary method for automatically completing lumen boundaries in the form of a flowchart, based on various aspects of this disclosure.

[0044] Figure 27 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0045] Figure 28 It is a grid showing the values ​​of image parameters in an IVUS image frame according to various aspects of this disclosure.

[0046] Figure 29 The following are illustrations of IVUS images, image portrait display (ILD), and screen displays of selection or addition tools, in accordance with various aspects of this disclosure.

[0047] Figure 30 The screen display showing IVUS images and image portrait display (ILD) is based on various aspects of this disclosure.

[0048] Figure 31 This is a schematic diagram of an exemplary method for automatically completing lumen boundaries in the form of a flowchart, based on various aspects of this disclosure. Detailed Implementation

[0049] Embodiments of this disclosure provide systems, methods, and associated apparatus for performing automated tasks that overcome one or more of the limitations described above. A context-sensitive intravascular measurement system is provided that allows a user to request automated measurements of the cross-sectional area of ​​a specific anatomical structure (e.g., the lumen of a vessel or other region of interest), whether on a single radial cross-sectional image or a tomographic image (e.g., intravascular ultrasound (IVUS) or optical coherence tomography (OCT)) or across the entire area displayed longitudinally (ILD) of the image. The context-sensitive intravascular measurement system also allows the user to request automated correction of previous anatomical measurements or to automatically complete partial contours manually drawn by a clinician (e.g., using a mouse, trackball, touchscreen, etc.).

[0050] Context-sensitive endovascular measurement systems combine easy-to-use tools with AI / deep learning capabilities that allow for the automatic selection of regions to calculate area statistics based on intravascular images of anatomical areas within the deep vein space. Many factors can cause variability in measurements produced by endovascular or intraluminal imaging systems, even measurements performed by the same clinician on the same image. Context-sensitive endovascular measurement systems offer a simple way to perform these corrections or even measurements from scratch with minimal user interaction. This also helps users achieve clinical diagnoses faster and with less variation, leading to reduced costs, increased throughput, and improved results.

[0051] Quick selection tools are available in commercial image editing software, but they are not configured to interpret IVUS or OCT images, are insensitive to variables such as depth, texture, spectral density, spatial frequency, or virtual histology, and are not configured for use on computational systems commonly used in operating rooms or catheterization labs. Additional challenges overcome by context-sensitive intravascular measurement systems include usability and time. Furthermore, context-sensitive intravascular measurement systems can be scaled up by retraining to improvements on IVUS images and are relatively insensitive to factors such as inter-catheter variability, which could otherwise lead to measurement variability.

[0052] The main components of a context-sensitive intravascular measurement tool include: A user interface (UI) that enables touch or click input on IVUS images or other radial cross-sectional or tomographic images (e.g., intravascular OCT images). This may include the ability to drag a finger or mouse across a single tomographic image or across a series of images in a longitudinal view (e.g., a longitudinal cross-sectional image or image longitudinal display (ILD)).

[0053] The image analysis component analyzes the spectral characteristics of the underlying raw image data or performs pattern recognition using deep learning.

[0054] Context-sensitive intravascular measurement systems are software tools that can be integrated into existing intravascular or intraluminal imaging systems via software updates, or can be included in new systems.

[0055] The apparatus, systems, and methods described herein may include one or more features described in the following applications: U.S. Provisional Applications filed October 26, 2018, US62 / 750983, US62 / 751268, US62 / 751289, US62 / 750996, US62 / 751167, and US62 / 751185, each of which is incorporated herein by reference in its entirety as if fully set forth herein.

[0056] The apparatus, systems, and methods described herein may also include one or more features described in the following applications: U.S. Provisional Application US62 / 642847, filed March 14, 2018; U.S. Provisional Application US62 / 712009, filed July 30, 2018; U.S. Provisional Application US62 / 711927, filed July 30, 2018; and U.S. Provisional Application US62 / 643366, filed March 15, 2018, each of which is incorporated herein by reference in its entirety as if fully set forth herein.

[0057] Context-sensitive intravascular measurement systems have specific, but not exclusive, uses for measuring the diameter of the vessel lumen before and after stent placement and expansion in occluded areas.

[0058] This disclosure greatly facilitates the measurement of anatomical structures by improving the speed, accuracy, and repeatability of obtaining measurement results. Implemented on digital IVUS catheters or digital IVUS guidewires that communicate with processors such as patient interface modules (PIMs) and / or IVUS imaging consoles, the context-sensitive intravascular measurement systems disclosed herein provide practical improvements in the management of vascular diseases. This improved anatomical measurement technique transforms most manual processes that rely on expertise and dexterity into a process that can be performed repeatedly at high speeds without the general need for extensive training of clinicians. This unconventional approach improves the functionality of ultrasound imaging systems by simplifying the process of performing anatomical measurements.

[0059] Context-sensitive intravascular measurement systems can be implemented as processes that are at least partially viewable on a display and operated by a control process executed on a processor that accepts user input from a keyboard, mouse, touchscreen interface, or other user interface and communicates with one or more ultrasound transducers. In this respect, the control process performs certain specific operations in response to different inputs or selections made at different times. Some outputs of the context-sensitive intravascular measurement system can be printed, displayed on a display, or otherwise transmitted to a human operator. Certain structures, functions, and operations of the processor, display, sensors, and user input system are known in the art, while other structures, functions, and operations are described herein to specifically implement novel features or aspects of this disclosure.

[0060] These descriptions are provided for illustrative purposes only and should not be construed as limiting the scope of context-sensitive intravascular measurement systems. Certain features may be added, removed, or modified without departing from the spirit of the claimed subject matter.

[0061] To facilitate an understanding of the principles of this disclosure, reference will now be made to embodiments illustrated in the accompanying drawings, and these embodiments will be described using specific language. However, it should be understood that this is not intended to limit the scope of this disclosure. Any changes and further modifications to the described devices, systems, and methods, as well as any further applications of the principles of this disclosure, are fully contemplated and included within this disclosure, as would normally occur to those skilled in the art to which this disclosure pertains. In particular, it is fully contemplated that features, components, and / or steps described with respect to one embodiment may be combined with features, components, and / or steps described with respect to other embodiments of this disclosure. However, for the sake of brevity, multiple iterations of these combinations will not be described separately.

[0062] Figure 1 This is a schematic diagram illustrating an intraluminal imaging system according to various aspects of this disclosure. In some embodiments, the intraluminal imaging system 100 may be an intravascular ultrasound (IVUS) imaging system. The intraluminal imaging system 100 may include an intraluminal device 102, a patient interface module (PIM) 104, a console or processing system 106, a monitor 108, and an external imaging system 132, which may include angiography, ultrasound, X-ray, computed tomography (CT), magnetic resonance imaging (MRI), or other imaging techniques, equipment, and methods. The size and shape of the intraluminal device 102 are defined and / or structurally otherwise arranged to be positioned within a patient's body lumen. For example, in various embodiments, the intraluminal device 102 may be a catheter, guidewire, guiding catheter, pressure guidewire, and / or flow guidewire. In some cases, the system 100 may include additional components and / or may be available without them. Figure 1 The system is implemented with one or more of the elements shown in the figure. For example, system 100 may omit the external imaging system 132.

[0063] The intraluminal imaging system 100 (or intravascular imaging system) can be any type of imaging system suitable for use in a patient's lumen or vascular system. In some embodiments, the intraluminal imaging system 100 is an intravascular ultrasound (IVUS) imaging system. In other embodiments, the intraluminal imaging system 100 may include a system configured for forward-looking intravascular ultrasound (FL-IVUS) imaging, intravascular photoacoustic (IVPA) imaging, intracardiac echocardiography (ICE), transesophageal echocardiography (TEE), and / or other suitable imaging modalities.

[0064] It should be understood that system 100 and / or device 102 can be configured to acquire any suitable intraluminal imaging data. In some embodiments, device 102 may include imaging components of any suitable imaging modality, such as optical imaging, optical coherence tomography (OCT), etc. In some embodiments, device 102 may include any suitable non-imaging components, including pressure sensors, flow sensors, temperature sensors, optical fibers, reflectors, mirrors, prisms, ablation elements, radio frequency (RF) electrodes, conductors, or combinations thereof. Generally, device 102 may include imaging elements to acquire intraluminal imaging data associated with lumen 120. The size and shape of device 102 may be set (and / or configured) for insertion into a patient's blood vessel or lumen 120.

[0065] System 100 can be deployed in a catheter insertion laboratory with a control room. Processing system 106 can be located in the control room. Optionally, processing system 106 can be located elsewhere, such as within the catheter insertion laboratory itself. The catheter insertion laboratory may include a sterile area, while its associated control room may be sterile or non-sterile, depending on the procedure to be performed and / or the healthcare facility. The catheter insertion laboratory and control room can be used to perform any number of medical imaging procedures, such as angiography, fluoroscopy, CT, IVUS, virtual histology (VH), forward-looking IVUS (FL-IVUS), intraluminal photoacoustic (IVPA) imaging, fractional flow reserve (FFR) measurement, coronary flow reserve (CFR) measurement, optical coherence tomography (OCT), computed tomography, intracardiac echocardiography (ICE), forward-looking ICE (FLICE), intraluminal palpation imaging, transesophageal echocardiography, fluoroscopy, and other medical imaging modalities or combinations thereof. In some embodiments, device 102 can be controlled from a remote location (e.g., a control room), for example, without requiring an operator to be physically present with the patient.

[0066] Intraluminal device 102, PIM 104, monitor 108, and external imaging system 132 can be directly or indirectly communicatively coupled to processing system 106. These components can be communicatively coupled to medical processing system 106 via wired connections (e.g., standard copper or fiber optic links) and / or via wireless connections using IEEE 802.11 Wi-Fi, Ultra-Wideband (UWB), FireWire, Wireless USB, or another high-speed wireless networking standard. Processing system 106 can be communicatively coupled to one or more data networks, such as a TCP / IP-based local area network (LAN). In other embodiments, different protocols may be utilized, such as Synchronous Optical Network (SONET). In some cases, processing system 106 can be communicatively coupled to a wide area network (WAN). Processing system 106 can utilize network connectivity to access various resources. For example, processing system 106 can communicate via network connectivity with a Medical Digital Imaging and Communication (DICOM) system, a Picture Archiving and Communication (PACS) system, and / or a Hospital Information System (HIS).

[0067] From a macroscopic perspective, the intraluminal ultrasound imaging device 102 emits ultrasonic energy from a transducer array 124 included in a scanner assembly 110, which is mounted near the distal end of the intraluminal device 102. The ultrasonic energy is reflected by tissue structures in the medium surrounding the scanner assembly 110 (e.g., lumen 120), and the ultrasonic echo signals are received by the transducer array 124. The scanner assembly 110 generates one or more electrical signals representing the ultrasonic echoes. The scanner assembly 110 may include one or more individual ultrasonic transducers and / or the transducer array 124 in any suitable configuration, such as a planar array, a curved array, a circumferential array, a ring array, etc. For example, in some instances, the scanner assembly 110 may be a one-dimensional or two-dimensional array. In some instances, the scanner assembly 110 may be a rotating ultrasound device. The effective area of ​​the scanner assembly 110 may include one or more transducer materials and / or one or more ultrasonic elements (e.g., one or more rows, columns, and / or one or more orientations) that can be uniformly or independently controlled and activated. The effective area of ​​the scanner assembly 110 can be patterned or structured in various basic or complex geometries. The scanner assembly 110 can be configured in a side-view orientation (e.g., ultrasonic energy emitted perpendicular to and / or orthogonal to the longitudinal axis of the intraluminal device 102) and / or a front-view orientation (e.g., ultrasonic energy emitted parallel to and / or along the longitudinal axis). In some instances, the scanner assembly 110 is structurally arranged to emit and / or receive ultrasonic energy at an angle relative to the longitudinal axis in a proximal or distal direction. In some embodiments, ultrasonic energy emission can be electronically manipulated by selectively triggering one or more transducer elements of the scanner assembly 110.

[0068] The ultrasonic transducer of the scanner assembly 110 may be a piezoelectric micromechanical ultrasonic transducer (PMUT), a capacitive micromechanical ultrasonic transducer (CMUT), a single crystal, lead zirconate titanate (PZT), PZT composite material, other suitable transducer types, and / or combinations thereof. In embodiments, the ultrasonic transducer array 124 may include any suitable number of individual transducer elements or acoustic elements between 1 and 1000 acoustic elements, including, for example, 2 acoustic elements, 4 acoustic elements, 36 acoustic elements, 64 acoustic elements, 128 acoustic elements, 500 acoustic elements, 812 acoustic elements, and / or other larger and smaller values ​​of acoustic elements.

[0069] The received echo signal is transmitted from PIM 104 to processing system 106, where the ultrasound image (including flow information) is reconstructed and displayed on monitor 108. The console or processing system 106 may include a processor and memory. Processing system 106 may be operable to facilitate the features of the intraluminal imaging system 100 described herein. For example, the processor may execute computer-readable instructions stored on a non-transient tangible computer-readable medium.

[0070] PIM 104 facilitates signal communication between processing system 106 and scanner assembly 110 included in in-lumen device 102. This communication may include: providing commands to one or more integrated circuit controller chips within in-lumen device 102 to select one or more specific elements on transducer array 124 to be used for transmission and reception; providing a transmit trigger signal to one or more integrated circuit controller chips to activate transmitter circuitry to generate electrical pulses to excite the selected transducer array elements; and / or receiving amplified echo signals received from the selected transducer array elements via an amplifier included on one or more integrated circuit controller chips. In some embodiments, PIM 104 performs preliminary processing of the echo data before relaying the data to processing system 106. In examples of such embodiments, PIM 104 performs data amplification, filtering, and / or aggregation. In one embodiment, PIM 104 also supplies high-voltage and low-voltage DC power to support the operation of in-lumen device 102, including circuitry within scanner assembly 110.

[0071] Processing system 106 receives echo data from scanner assembly 110 via PIM 104 and processes the data to reconstruct an image of tissue structures in the medium surrounding scanner assembly 110. Generally, device 102 can be used within any suitable anatomical structure and / or body lumen of the patient. Processing system 106 outputs image data such that an image of a blood vessel or lumen 120 (e.g., a cross-sectional IVUS image of lumen 120) is displayed on monitor 108. Lumen 120 can represent natural and artificial fluid-filled or fluid-surrounded structures. Lumen 120 can be within the patient's body. Lumen 120 can be a blood vessel, such as an artery or vein in the patient's vascular system, including the cardiac vascular system, peripheral vascular system, neurovascular system, renal vascular system, and / or any other suitable lumen within the body. For example, device 102 can be used to examine any number of anatomical locations and tissue types, including but not limited to: organs, including the liver, heart, kidneys, gallbladder, pancreas, and lungs; ducts; intestines; nervous system structures, including the brain, dural sac, spinal cord, and peripheral nerves; the urinary tract; and valves and / or other systems of the body within the blood, chambers, or other parts of the heart. In addition to natural structures, device 102 can be used to examine man-made structures, such as, but not limited to, heart valves, stents, shunts, filters, and other devices.

[0072] The controller or processing system 106 may include processing circuitry having one or more processors that communicate with memory and / or other suitable tangible computer-readable storage media. The controller or processing system 106 may be configured to perform one or more aspects of this disclosure. In some embodiments, the processing system 106 and the monitor 108 are separate components. In other embodiments, the processing system 106 and the monitor 108 are integrated into a single component. For example, system 100 may include a touchscreen device comprising a housing having a touchscreen display and a processor. System 100 may include any suitable input device (e.g., a touchpad or touchscreen display, keyboard / mouse, joystick, buttons, etc.) for a user to select options displayed on the monitor 108. The processing system 106, monitor 108, input devices, and / or combinations thereof may be referred to as the controller of system 100. The controller may communicate with device 102, PIM 104, processing system 106, monitor 108, input devices, and / or other components of system 100.

[0073] In some embodiments, the intraluminal device 102 includes features similar to those of conventional solid-state IVUS catheters, such as those disclosed in U.S. Patent 7,846,101, which is incorporated herein by reference in its entirety. For example, the intraluminal device 102 may include a scanner assembly 110 near the distal end of the intraluminal device 102 and a transmission harness 112 extending along the longitudinal body of the intraluminal device 102. The cable or transmission harness 112 may include multiple conductors, including one, two, three, four, five, six, seven, or more conductors.

[0074] The transmission harness 112 terminates at the proximal end of the in-lumen device 102 at a PIM connector 114. The PIM connector 114 electrically couples the transmission harness 112 to the PIM 104 and physically couples the in-lumen device 102 to the PIM 104. In an embodiment, the in-lumen device 102 also includes a guidewire outlet 116. Thus, in some instances, the in-lumen device 102 is a rapid exchange catheter. The guidewire outlet 116 allows a guidewire 118 to be inserted distally to guide the in-lumen device 102 through the lumen 120.

[0075] Monitor 108 may be a display device, such as a computer monitor or other type of screen. Monitor 108 may be used to display selectable prompts, instructions, and visualizations of imaging data to a user. In some embodiments, monitor 108 may be used to provide a user with a process-specific workflow to complete an intraluminal imaging procedure. This workflow may include performing pre-stent planning to determine the lumen status and stent potential, and performing post-stent checks to determine the status of the stent that has been positioned in the lumen.

[0076] External imaging system 132 can be configured to acquire X-ray, radiographic, angiography / venography (e.g., using contrast agents), and / or fluoroscopy (e.g., without contrast agents) images of the patient's body (including blood vessels 120). External imaging system 132 can also be configured to acquire computed tomography images of the patient's body (including blood vessels 120). External imaging system 132 may include an external ultrasound probe configured to acquire ultrasound images of the patient's body (including blood vessels 120) while positioned externally to the body. In some embodiments, system 100 includes other imaging modalities (e.g., MRI) to acquire images of the patient's body (including blood vessels 120). Processing system 106 is capable of utilizing images of the patient's body in conjunction with intraluminal images acquired by intraluminal device 102.

[0077] Figure 2Blood vessels (e.g., arteries and veins) in the human body are shown. For example, veins in the human body are marked. Aspects of this disclosure may relate to the peripheral vascular system, such as veins in the trunk or legs.

[0078] Occlusion can occur in arteries or veins. Occlusion can generally refer to any blockage or other structural arrangement that restricts fluid flow through a lumen (e.g., an artery or vein), for example, in a manner detrimental to the patient's health. For example, occlusion narrows the lumen, reducing the cross-sectional area of ​​the lumen and / or the available space for fluid flow through it. In cases where the anatomy is a blood vessel, occlusion may result from compression (e.g., from an external vessel), plaque buildup leading to narrowing, including but not limited to plaque components such as fibrous, fibrolipin (fibrofatty), necrotic core, calcified (dense calcium), and different stages of blood and / or thrombus (e.g., acute, subacute, chronic, etc.). In some instances, occlusion may be referred to as thrombosis, stenosis, and / or lesion. Generally, the composition of an occlusion will depend on the type of anatomy being assessed. A healthier portion of the anatomy may have a uniform or symmetrical profile (e.g., a cylindrical profile with a circular cross-sectional profile). An occlusion may not have a uniform or symmetrical profile. Therefore, the diseased or compressed portion of an anatomical structure with occlusion will have an asymmetrical and / or otherwise irregular profile. The anatomical structure may have one or more occlusions.

[0079] The accumulation of occlusions (e.g., thrombi, deep vein thrombosis or DVT, chronic total occlusion or CTO, etc.) is one way in which the cross-sectional area of ​​veins in the peripheral vascular system (e.g., trunk, abdomen, groin, leg) can be reduced. Other anatomical structures that come into contact with veins can also reduce their cross-sectional area, thereby restricting blood flow through them. For example, arteries or ligaments in the trunk, abdomen, groin, or leg can compress veins, altering their shape and reducing their cross-sectional area. This reduction in cross-sectional area due to contact with other anatomical structures can be termed compression, as the vein wall is compressed due to contact with the artery or ligament.

[0080] Figure 3 The illustration shows a blood vessel 300 containing compression 330. Compression 330 occurs outside the vessel wall 310 and can restrict the flow of blood 320. Compression can be caused by other anatomical structures outside the blood vessel 300, including but not limited to tendons, ligaments, or adjacent lumens.

[0081] Figure 4The illustration depicts a vessel 300 containing compression 330 and in which a stent 440 expands to restore flow. The stent 440 displaces and stops the compression 330, pushing the vessel wall 310 outward, thereby reducing the restriction on blood flow 320. Other treatment options for relieving occlusion may include, but are not limited to, thrombectomy, ablation, angioplasty, and medication. However, in most cases, accurate and timely intravascular imaging of the affected area, as well as a precise and detailed understanding of the location, orientation, length, and volume of the affected area before, during, or after treatment, may be highly desirable.

[0082] Figure 5 This is a schematic diagram of processor circuitry 550 according to various aspects of this disclosure. Processor circuitry 550 may be implemented in intraluminal imaging system 100 or other devices or workstations (e.g., third-party workstations, network routers, etc.), or on a cloud processor or other remote processing unit to implement the method as needed. As shown, processor circuitry 550 may include processor 560, memory 564, and communication module 568. These components may communicate directly or indirectly with each other (e.g., via one or more buses).

[0083] Processor 560 may include any combination of a central processing unit (CPU), digital signal processor (DSP), ASIC, controller or general-purpose computing device, reduced instruction set computing (RISC) device, application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other related logic devices, including mechanical computers and quantum computers. Processor 560 may also include another hardware device, firmware device, or any combination thereof configured to perform the operations described herein. Processor 560 may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors cooperating with a DSP core, or any other such configuration.

[0084] Memory 564 may include cache memory (e.g., the cache memory of processor 560), random access memory (RAM), magnetoresistive RAM (MRAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, solid-state memory devices, hard disk drives, other forms of volatile and non-volatile memory, or combinations of different types of memory. In embodiments, memory 564 includes a non-transient computer-readable medium. Memory 564 may store instructions 566. Instructions 566 may include instructions that, when executed by processor 560, cause processor 560 to perform the operations described herein. Instructions 566 may also be referred to as code. The terms “instruction” and “code” should be interpreted broadly to include any type of computer-readable statement(s). For example, the terms “instruction” and “code” may refer to one or more programs, routines, subroutines, functions, procedures, etc. “Instruction” and “code” may include a single computer-readable statement or a number of computer-readable statements.

[0085] The communication module 568 may include any electronic circuitry and / or logic circuitry to facilitate direct or indirect data communication between the processor circuitry 550 and other processors or devices. In this regard, the communication module 568 may be an input / output (I / O) device. In some instances, the communication module 568 facilitates direct or indirect communication between the processor circuitry 550 and / or various components of the intraluminal imaging system 100. The communication module 568 can communicate within the processor circuitry 550 via a variety of methods or protocols. Serial communication protocols may include, but are not limited to, the US Serial Protocol Interface (US SPI), internal integrated circuits (I... 2 C) Recommended standards RS-232, RS-485, Controller Area Network (CAN), Ethernet, ARINC 429, MODBUS, MIL-STD-1553, or any other suitable method or protocol. Parallel protocols include, but are not limited to, Industry Standard Architecture (ISA), Advanced Technology Attachment (ATA), Small Computer System Interface (SCSI), Peripheral Component Interconnect (PCI), IEEE 488, IEEE 1284, and other suitable protocols. Where appropriate, serial and parallel communication may be bridged by a Universal Asynchronous Receiver Transmitter (UART), a Universal Synchronous Receiver Transmitter (USART), or other suitable subsystems.

[0086] External communication (including but not limited to software updates, firmware updates, preset sharing between the processor and a central server, or readings from a circular ultrasound imaging array) can be achieved using any suitable wireless or wired communication technology, such as cable interfaces (e.g., Universal Serial Bus (USB), Micro USB, Lightning, or FireWire), Bluetooth, Wi-Fi, ZigBee, Li-Fi, or cellular data connections (e.g., 2G / GSM (Global System for Mobile Communications), 3G / UMTS (Universal Mobile Telecommunications System), 4G, LTE, WiMax, or 5G). For example, Bluetooth Low Energy (BLE) radios can be used to establish connections to cloud services for data transfer and for receiving software patches. The controller can be configured to communicate with remote servers or local devices (e.g., laptops, tablets, or handheld devices) or may include a display capable of showing status variables and other information. Information can also be transferred on physical media such as USB flash drives or Memory Sticks.

[0087] It should also be understood that one or more steps in the above method can be performed by one or more components of the ultrasound imaging system, such as a processing system, multiplexer, beamformer, signal processing unit, image processing unit, or any other suitable component of the system. For example, activating the scan sequence can be performed by a processor communicating with a multiplexer configured to select or activate one or more elements of an ultrasound transducer array. In some embodiments, generating an ultrasound image may include beamforming the incoming signal from the ultrasound imaging device and processing the beamformed signal by an image processor. The system's processing components may be integrated within the ultrasound imaging device, contained in an external console, or may be separate components.

[0088] Figure 6 This disclosure illustrates an IVUS image 610, an image longitudinal display (ILD) 620, and a screen display 600 showing a selection or addition tool 650, according to various aspects of the present disclosure. Visible in the IVUS image 610 and ILD 620 are a first vessel lumen 630a and a second vessel lumen 630b. A position indicator 640 indicates the current position of the IVUS image frame 610 within the ILD 620. In the example, the user uses a mouse, trackball, touchscreen, etc., to move the selection or addition tool 650 to the desired anatomical feature to be measured. Figure 6 In the example shown, this is the second blood vessel lumen 630b. Clicking on lumen 630b using the add tool 650 will instruct the context-sensitive intravascular measurement system to measure lumen 630b. Depending on the implementation, the boundary 710 of the blood vessel lumen 630b can be automatically determined in response to user input, without requiring separate user input to instruct the processor circuitry to determine the boundary.

[0089] This disclosure uses vascular lumens as an exemplary anatomical region of interest for selection and measurement (e.g., distinguishing the vascular lumen from the vascular tissue surrounding / defining the lumen). However, it should be noted that other anatomical structures besides vascular lumens can also be selected using the additive tools, including but not limited to vessel walls, occlusions (e.g., clots, reticular formations, calcifications, stenosis, compression, etc.), collaterals, tumors and other abnormalities, adjacent anatomical structures, and / or other regions of interest. In general, aspects of this disclosure are applicable to any pair of adjacent anatomical regions of interest that need to be distinguished.

[0090] Figure 7 The screen display 700 shows the automatically identified lumen boundary 710 of the lumen 630b in IVUS image 610, according to various aspects of this disclosure. Visible are the first lumen 630a, the second lumen 630b, and the position indicator 640. When an add tool is clicked on the lumen, the context-sensitive intravascular measurement system automatically detects or generates the lumen boundary 710 and measurement results 720. Depending on the implementation, the measurement results 720 may include, for example, area (e.g., in square micrometers), eccentricity, semi-major axis and semi-minor axis (also referred to as minimum and maximum diameters), average diameter, and / or other geometric parameters as needed. Also visible are the frame number 730 and the total number of frames 740.

[0091] In the example, screen display 700 is an update of screen display 600 and can be the same as screen display 600, except that screen display 700 is updated to additionally include the boundary of the blood vessel lumen as an overlay, wherein the identified boundary completely surrounds or encloses the location identified by the user input.

[0092] Figure 8 This is a schematic diagrammatic view of an exemplary method 800 for measuring and adding area, in flowchart form, based on various aspects of this disclosure. It should be understood that the steps of method 800 can be... Figure 8 The steps may be performed in different orders as shown, additional steps may be provided before, during, and after the steps, and / or some of the steps described may be replaced or eliminated in other embodiments. One or more steps of method 800 may be performed by one or more devices and / or systems (e.g., components of system 100, processing system 106, and / or processor circuitry 550) described herein.

[0093] In step 810, method 800 includes receiving user input from a screen display 805 containing an image of the blood vessel, specifically within the lumen of the vessel of interest. The location of the user's click identifies an input sub-region within the lumen of the blood vessel. Depending on the implementation, the sub-region may be a single pixel or a group of pixels of configurable or non-configurable size. Then, execution proceeds to step 815.

[0094] Steps 815 to 828 are used to verify that the user input is actually within the lumen area. Steps 815 to 828 may be omitted in some instances. The lumen area may be, for example, a region of the intravascular image located at or near the center of the image, which is visually distinguishable from the surrounding vessel wall or tissue area within the image.

[0095] In step 815, method 800 includes determining image parameters for the input sub-region. Depending on the implementation, these parameters may include one or more of the brightness, contrast, and / or depth of pixels in the sub-region, or may include composite or derived characteristics such as spectrum, spatial frequency, or texture / smoothness (e.g., the degree of variation between adjacent pixels or sub-regions). Then, execution proceeds to step 820.

[0096] In step 820, method 800 includes comparing the parameters of the input sub-region with predetermined parameters of the vessel lumen. For example, the vessel lumen can be expected to return a weak echo and therefore appear black or dark gray with little variability in the ultrasound image, while the vessel wall can be relatively brighter and more variable. Then, execution proceeds to step 825.

[0097] In step 825, method 800 includes determining whether the parameters of the input sub-region match predetermined parameters of the lumen area. If yes, proceed to step 830. If no, proceed to step 828.

[0098] In step 828, method 800 includes outputting a prompt requesting new user input (e.g., touchscreen input, mouse, joystick or trackball input, keyboard input, etc.) located within the blood vessel lumen. Then, execution returns to step 810.

[0099] In step 830, method 800 includes determining that the input sub-region is a portion of the lumen area. Then, execution proceeds to step 835.

[0100] In step 835, method 800 includes identifying sub-regions adjacent to the input sub-region. Then, execution proceeds to step 840.

[0101] In step 840, method 800 includes determining image parameters (e.g., brightness, contrast, depth, spectrum, spatial frequency, texture / smoothness, etc.) of adjacent sub-regions. Then proceed to step 845.

[0102] In step 845, method 800 includes comparing image parameters of adjacent sub-regions with predetermined parameters of the lumen area and / or with parameters of the input sub-region. Then, execution proceeds to step 850.

[0103] In step 850, method 800 includes determining whether the parameters of the adjacent sub-region match the parameters of the lumen. If yes, proceed to step 855. If no, proceed to step 860.

[0104] In step 855, method 800 includes adding adjacent sub-regions with matching parameters as portions of the identified lumen area. Then, execution proceeds to step 865.

[0105] In step 860, method 800 includes adding adjacent sub-regions with mismatched parameters as portions of the identified lumen boundary. Then, execution proceeds to step 865.

[0106] In step 865, method 800 includes determining whether steps 850-860 identified at least one adjacent sub-region matching the lumen area. If yes, the lumen area is not completely surrounded by the boundary sub-region, and execution returns to step 835. If no, the lumen area is completely surrounded by the boundary sub-region, and if additional adjacent sub-regions are checked, the lumen area will not increase, and execution proceeds to step 870.

[0107] In step 870, method 800 includes calculating the lumen size based on the lumen boundary and / or lumen area. In this regard, aspects of this disclosure may include features described in the following documents: U.S. Patent Publication US2007 / 0201736, U.S. Patent US11272845, U.S. Patent US7463759, U.S. Patent US9295447, U.S. Patent US11744527, U.S. Patent Publication US2020 / 0029932, and U.S. Patent Publication US2019 / 0282211, each of which is incorporated herein by reference as if fully set forth herein. Then proceed to step 875.

[0108] In step 875, method 800 includes generating and outputting a screen display having the lumen boundary superimposed on the IVUS image and / or including the calculated dimensions. Method 800 is now complete.

[0109] Commonly, steps 830-865 determine the lumen boundary and / or lumen area. Although method 800 is described in relation to the measurement of the vascular lumen, the same method can be applied to identify and / or measure the vessel wall, stents, clots, or plaques, etc.

[0110] It should be noted that the flowcharts provided herein are for illustrative purposes; those skilled in the art will recognize numerous variations that still fall within the scope of this disclosure. For example, the logic of the flowchart may be shown as sequential. However, similar logic may be parallel, massively parallel, object-oriented, real-time, event-driven, cellular automata, or otherwise, while achieving the same or similar functionality. To execute the methods described herein, a processor may divide each step described herein into multiple machine instructions, and these instructions may be executed at a rate of hundreds, thousands, millions, or billions of instructions per second, either on a single processor or across multiple processors. Such rapid execution may be necessary to execute the method in real-time or near real-time as described herein. For example, real-time generation of a blood vessel lumen may involve analyzing multiple variables associated with each of hundreds or thousands of different pixels within a fraction of a second.

[0111] Figure 9 This is a schematic diagrammatic view of exemplary univariate comparison steps 825 or 850 in the form of a flowchart, based on various aspects of this disclosure.

[0112] In step 930, the univariate comparison step 825 or 850 includes determining the difference or separation (e.g., brightness, frequency, etc.) between the parameters of the adjacent sub-region 910 and the parameters of the lumen area 920. Then proceed to step 940.

[0113] In step 940, the univariate comparison step 825 or 850 includes determining whether the difference or separation falls within a specified threshold. If yes, proceed to step 950. If no, proceed to step 970.

[0114] In step 950, adjacent sub-regions are matched sub-regions. Then proceed to step 960.

[0115] In step 960, the univariate comparison step 825 or 850 includes adding adjacent sub-regions as part of the lumen area. The univariate comparison step 825 or 850 is now complete.

[0116] In step 970, the adjacent sub-regions are mismatched sub-regions (e.g., parts that are not part of the lumen). Then proceed to step 980.

[0117] In step 980, the univariate comparison step 825 or 850 includes adding adjacent sub-regions to the lumen boundary. The univariate comparison step 825 or 850 is now complete.

[0118] Figure 10A This is a schematic diagrammatic view of exemplary multivariate comparison steps 825 or 850 in the form of a flowchart, based on various aspects of this disclosure.

[0119] In step 1040, the trained machine learning (ML) model or neural network receives the following as inputs: parameters A for adjacent subregions I and II and known parameters A of the lumen, and parameters B for adjacent subregions I and II and known parameters B of the lumen.

[0120] In step 1045, the trained ML model (e.g., a classifier) ​​determines that the neighboring subregion I is a matching subregion (e.g., a portion of the lumen).

[0121] In step 1050, the matching sub-region is added as a portion of the lumen area.

[0122] In step 1055, the trained ML model determines that the adjacent sub-region II is a mismatched sub-region (e.g., not a part of the lumen).

[0123] In step 1060, mismatched sub-regions are added as portions of the lumen boundary or vessel wall.

[0124] Although the method is shown as having two parameters and two sub-regions, those skilled in the art will understand that any number of parameters and sub-regions can be used.

[0125] Figure 10B This is a schematic diagram view of an exemplary multivariate comparison and identification method 1070 in flowchart form, based on various aspects of this disclosure.

[0126] In step 1040, the trained machine learning model (e.g., a segmentation model) receives image frame 1075 containing at least parameter A for each pixel in the frame. Optionally, the ML model may also examine additional parameters (B, C, D, etc.).

[0127] In step 1085, the ML model outputs the location of the lumen boundary and / or lumen area in the image frame.

[0128] In step 1090, the system displays the lumen boundary superimposed on image frame 1075.

[0129] Figure 11 This is a grid 1100 illustrating the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Each number in the grid corresponds to a sub-region in the image frame. Figure 11 In the example shown, values ​​of 3 and below indicate the lumen of a blood vessel, while values ​​of 4 and above indicate the vessel wall of other tissues. Also visible is the input sub-region 1110, which has been selected by the user, and its parameter value of 2 indicates that the input sub-region is part of the lumen.

[0130] Figure 12 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 12 In the example shown, eight sub-regions 1210 that are adjacent to (e.g., close to or in contact with) the input sub-region 1110 have been identified for inspection.

[0131] Figure 13 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 13 In the example shown, all adjacent sub-regions have been identified as belonging to the lumen 1310 and have been added to its area.

[0132] Figure 14 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 14 In the example shown, sixteen sub-regions 1210 adjacent to the currently identified lumen area 1310 have been identified for inspection.

[0133] Figure 15 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 15 In the example shown, some neighboring subregions (e.g., those with parameter values ​​of 3 or less) have been added to the currently identified lumen area 1310, which is outlined using a temporary boundary 1510. Other neighboring subregions have been added to the vessel wall 1520, such that a portion 1530 of the temporary boundary 1510 now corresponds to the actual lumen boundary.

[0134] Figure 16 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 16 In the example shown, fifteen sub-regions 1210 adjacent to the currently identified lumen area 1310 have been identified. Sub-regions 1610 adjacent to the vessel wall sub-region 1520 but not adjacent to the identified lumen area 1310 are not examined.

[0135] Figure 17 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 17 In the example shown, some neighboring subregions (e.g., those with parameter values ​​of 3 or less) have been added to the currently identified lumen area 1310, which is outlined using a temporary boundary 1510. Other neighboring subregions have been added to the vessel wall 1520, such that even larger portions 1530 of the temporary boundary 1510 now correspond to the actual lumen boundary.

[0136] Figure 18A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 18 In the example shown, the entire vessel wall 1520 and the lumen area 1310 have been identified, such that the temporary lumen boundary 1510 now represents the actual lumen boundary and can be used to measure the lumen area and other parameters. It should be noted that this method utilizes these detection thresholds to prevent the second lumen 1810 from being identified as part of the original lumen 1310.

[0137] Figure 19 The screen display 1900 shows an IVUS image 610, an image longitudinal display (ILD) 620, and a deselection or subtraction tool 1950, according to various aspects of this disclosure. Visible in the IVUS image 610 and ILD 620 are a first vessel lumen 630a and a second vessel lumen 630b. A position indicator 640 indicates the position of the current IVUS image frame 610 within the ILD 620. Figure 19 In the example shown, the lumen boundary 1610 has been misidentified, causing it to surround the first lumen 630a, the second lumen 630b, and the abnormal dark area 1620, resulting in an abnormally large measurement result 720. Such misidentification may occur, for example, due to image artifacts, an inappropriately selected lumen identification threshold, or incorrect hand-drawing of the lumen boundary.

[0138] In the example, the user uses a mouse, trackball, touchscreen, etc., to move the deselection or subtraction tool 1950 to the desired anatomical feature to be removed from the measurement results. Figure 19 In the example shown, this is the second vessel lumen 630b. Clicking on lumen 630b with the subtraction tool 1950 will instruct the context-sensitive intravascular measurement system to remove the second lumen 630b from the measurement area. It should be noted that this may also result in the removal of the aberrant dark area 1620, because the IVUS image 610 does not include the identifiable boundary between the second lumen 630b and the aberrant dark area 1620.

[0139] Subtraction is not the only change that can be made to the cavity boundary. For example, add tool 650 (see...). Figure 6 ) can be used to... Figure 19 The subtraction method shown adds the area to the lumen in a similar way, or the correction can be drawn by hand (see below). Figures 24-25 ).

[0140] This disclosure uses vascular lumens as exemplary anatomical regions of interest for selection and measurement (e.g., distinguishing vascular lumens from the vascular tissue surrounding / defining the vascular lumen). However, it should be noted that other anatomical structures besides vascular lumens can also be selected using the subtraction tool, including but not limited to vessel walls, occlusions (e.g., clots, reticular formations, calcifications, stenosis, compression, etc.), collaterals, tumors and other abnormalities, adjacent anatomical structures, and / or other regions of interest. In general, aspects of this disclosure are applicable to any pair of adjacent anatomical regions of interest that need to be distinguished.

[0141] Figure 20 The screen display 700 shows the automatically identified lumen boundary 2010 of the lumen 630a in the IVUS image 610, according to various aspects of this disclosure. Visible are the first lumen 630a, the second lumen 630b, the abnormal dark area 1620, and the position indicator 640. When the subtract tool is clicked on the second lumen 630b, the context-sensitive intravascular measurement system automatically removes the second lumen 630b and the abnormal dark area 1620 from the identified lumen area and recalculates or redefines the lumen boundary 2010 and the measurement result 2020.

[0142] Figure 21 This is a schematic diagram of an exemplary lumen area subtraction method 2100 in the form of a flowchart, based on various aspects of this disclosure.

[0143] In step 2120, method 2100 includes receiving user input (e.g., from a touchscreen, keyboard, mouse, etc.) within the screen display 2110 of the IVUS image, indicating an input sub-region within which the user wishes to subtract from the identified lumen area. Then, proceed to step 2130.

[0144] In step 2130, method 2100 includes identifying the area to be subtracted from the identified lumen area. This can be, for example, employed in the manner described above. Figure 8 The same identification method described in [the document] is then executed. Proceed to step 2140.

[0145] In step 2140, method 2100 includes modifying the lumen boundary to remove the subtracted region. This could, for example, involve modifications similar to those described above. Figure 8 The same boundary recognition method described in [the document] is then executed, proceeding to step 2150.

[0146] In step 2150, method 2100 includes recalculating the lumen area and other dimensional parameters based on the modified lumen boundary and / or modified lumen area, as described above. Figure 8 As described in [the document]. Then proceed to step 2160.

[0147] In step 2160, method 2100 includes generating and outputting a screen display that overlays the modified lumen boundaries and / or recalculated lumen dimensions onto the IVUS image. This method is now complete.

[0148] Figure 22 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 22 In the example shown, the identified lumen area 1110 is unusually large, and therefore the user has identified the input sub-region 2210 within the portion 2220 of the identified lumen area 1110 that the user wishes to remove from the identified sub-region. It should be noted that in Figure 22 In the example shown, the identified lumen area 1110 includes sub-regions with parameter values ​​as high as 5, resulting in an abnormally large lumen area 1110.

[0149] Figure 23 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 23 In the example shown, by from Figure 22 The second lumen area 2310 and the vessel walls 2320 and 2330 are removed from the lumen area 1110, and the identified lumen area 1310 has been resized.

[0150] Figure 24 The screen display 2400 shows an IVUS image 610, an image longitudinal display (ILD) 620, and a drawing tool 2450, according to various aspects of this disclosure. Visible in the IVUS image 610 and ILD 620 are a first vessel lumen 630a and a second vessel lumen 630b. A position indicator 640 indicates the position of the current IVUS image frame 610 within the ILD 620. Figure 24 In the example shown, the user has drawn a partial curve or partial plot 2410 to trace the boundary of lumen 630a. A temporary completion line 2420 connects the endpoints of the partial curve 2410. Once the partial curve 2410 is long enough to distinguish the user's intent (e.g., outlining the entire lumen 630a, excluding lumen 630b and the tissue between lumens 630a and 630b), the context-sensitive intravascular measurement system is able to automatically complete the lumen boundary.

[0151] Figure 25The screen display 2500 shows an IVUS image 610, an image longitudinal display (ILD) 620, and an automatically completed lumen boundary drawing 2510, according to various aspects of this disclosure. Visible in the IVUS image 610 and ILD 620 are a first vessel lumen 630a and a second vessel lumen 630b. A position indicator 640 indicates the position of the current IVUS image frame 610 within the ILD 620. Figure 25 In the example shown, in Figure 24 The portion of the curve 2410 drawn by the user has been automatically completed by the context-sensitive intravascular measurement system, thus creating an automatically completed lumen boundary drawing 2510. Measurements can now be performed from this lumen boundary.

[0152] This disclosure uses vascular lumens as exemplary anatomical regions of interest for selection and measurement (e.g., distinguishing vascular lumens from the vascular tissue surrounding / defining the vascular lumen). However, it should be noted that other anatomical structures besides vascular lumens can also be automatically completed using automated completion tools, including but not limited to vessel walls, occlusions (e.g., clots, reticular formations, calcifications, stenosis, compression, etc.), collaterals, tumors and other abnormalities, adjacent anatomical structures, and / or other regions of interest. In general, aspects of this disclosure apply to any pair of adjacent anatomical regions of interest that need to be distinguished.

[0153] Figure 26A This is a schematic diagram of an exemplary method 2600 for automatic completion of lumen boundaries in the form of a flowchart, based on various aspects of this disclosure.

[0154] In step 2615, method 2600 includes receiving user input (e.g., from a touchscreen, keyboard, mouse, joystick, trackball, etc.) within a screen display 2610 of the IVUS image to identify a first portion (e.g., a hand-drawn portion) of the lumen boundary. Then, proceed to step 2620.

[0155] In step 2620, method 2600 includes determining IVUS image parameters (e.g., brightness, depth, frequency, etc.) on a first side and a second side of the first portion. If the first portion of the boundary is accurately drawn, the sub-region on the side immediately adjacent to the boundary should have lumen-like parameters (e.g., low brightness, etc.), and the sub-region on the opposite side immediately adjacent to the boundary should have vessel wall-like parameters (e.g., high brightness, etc.). Then proceed to step 2625.

[0156] In step 2625, method 2600 includes automatically determining the relationship between intrinsic parameters (e.g., lumen parameters) and extrinsic parameters (e.g., vessel wall parameters). In the example, extrinsic parameters may exceed a specific threshold, while intrinsic parameters may be within the threshold. Other possible relationships between intrinsic and extrinsic parameters include ratios, differences, averages, etc. Then execution proceeds to step 2630.

[0157] In step 2630, method 2600 includes determining a second portion of the boundary of the completed boundary (e.g., a second portion connecting the two endpoints of the first portion), and this second portion maintains the relationship identified in step 2625 (e.g., a boundary where the parameters of all sub-regions inside the boundary are below the identified threshold, and all sub-regions immediately adjacent to the outside of the boundary exceed the threshold), as follows: Figures 27-28 As described in [the document]. Then proceed to step 2635.

[0158] In step 2635, method 2600 includes calculating the lumen size based on the lumen boundary and / or the lumen area associated with the completed boundary. Then, execution proceeds to step 2640.

[0159] In step 2640, method 2600 includes generating and outputting a screen display that includes a first and a second portion of a boundary superimposed on an intravascular (e.g., IVUS) image and / or calculated dimensions. The method is now complete.

[0160] Figure 26B This is a schematic diagram of an exemplary method 2650 for automatic completion of lumen boundaries in the form of a flowchart, based on various aspects of this disclosure.

[0161] In step 2655, method 2650 includes receiving user input (e.g., from a touchscreen, keyboard, mouse, trackball, joystick, etc.) within a screen display 2610 of the IVUS image to identify a first portion (e.g., a hand-drawn portion) of the lumen boundary. Then, proceed to step 2660.

[0162] In step 2660, method 2650 includes determining IVUS image parameters on a first side and a second side of the first portion. For example, if the first portion of the boundary is accurately drawn, the sub-region on one side of the boundary should have lumen-like parameters, and the sub-region on the opposite side should have vessel wall-like parameters. Then proceed to step 2665.

[0163] In step 2665, method 2650 includes comparing the first side parameter and the second side parameter with predetermined parameters of the lumen area. Then, proceed to step 2670.

[0164] In step 2670, method 2650 includes identifying the first side or the second side as a portion of the lumen area (e.g., as described above in...). Figure 8 (As described in the text). Then proceed to step 2675.

[0165] In step 2675, method 2650 includes determining a second portion of the boundary (e.g., a second portion connecting the two endpoints of the first portion) of the completed boundary based on the portion of the first or second side identified as a lumen. Points located between the first and second sides can be identified as belonging to the boundary. Then, proceed to step 2680.

[0166] In step 2680, method 2650 includes calculating the lumen size based on the lumen boundary and / or the lumen area associated with the completed boundary. Then, execution proceeds to step 2685.

[0167] In step 2685, method 2650 includes generating and outputting a screen display that includes a first and a second portion of the boundary superimposed on an intravascular (e.g., IVUS) image and / or calculated dimensions. The method is now complete.

[0168] Figure 27 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 27 In the example shown, the lumen area 2710 is defined by a partially hand-drawn boundary 2410 and a temporary completion line 2420 connecting the endpoints of the partially hand-drawn boundary 2410. However, the defined lumen area 2710 does not represent the actual lumen area until a context-sensitive intravascular measurement system performs intelligent automatic boundary completion, as described below. Figure 28 As shown in the image.

[0169] Figure 28 A grid 1100 is a representation of the values ​​of image parameters in an IVUS image frame, according to various aspects of this disclosure. Figure 28 In the example shown, the lumen area 2810 is now defined by a partially hand-drawn boundary 2410 and an automatically completed boundary 2510, which separate the vessel wall sub-region 1510 from the lumen area 2810. It should be noted that region 2830 meets the criteria for inclusion in the lumen area (e.g., a parameter value of 3 or less), but is excluded by the hand-drawn partial boundary 2410. In some respects, once sufficient information is available to establish the user's intention to delineate that particular lumen, the automatically completed boundary 2510 can overwrite or correct such disputed portions of the hand-drawn partial boundary 2410, such that the entire lumen area is included in the final boundary.

[0170] Figure 29The screen display 2900 shows an IVUS image 610, an image longitudinal display (ILD) 620, and a selection or addition tool 650, according to various aspects of this disclosure. Visible in the IVUS image 610 and ILD 620 are a first vessel lumen 630a and a second vessel lumen 630b. A position indicator 640 indicates the position of the current IVUS image frame 610 within the ILD 620.

[0171] Also visible is the current image frame number 2950 and the total number of image frames 2960. In Figure 6 In the example shown, tool 650 is used to select a region in IVUS image 610. Figure 29 In the example shown, the add tool 650 is dragged along the ILD to highlight all IVUS image frames 610 within the region of interest 2920 of a specific vessel lumen. The position indicator 640 can move up and down along the ILD to display different image frames 610. If these frames contain a portion of the region of interest 2920, automatically calculated boundaries 2930 and measurements 2940 are displayed on the IVUS image frame 610 for the selected lumen.

[0172] It should be noted that, in some respects, the ILD can be horizontal rather than vertical. This disclosure uses the vascular lumen as an exemplary anatomical region of interest for selection and measurement (e.g., distinguishing the vascular lumen from the vascular tissue surrounding / defining the lumen). However, it should be noted that, in addition to the vascular lumen, other anatomical structures can also be selected using the ILD addition tool, including but not limited to vessel walls, occlusions (e.g., clots, reticular formations, calcifications, stenosis, compression, etc.), collaterals, tumors and other abnormalities, adjacent anatomical structures, and / or other regions of interest. In general, aspects of this disclosure apply to any pair of adjacent anatomical regions of interest that need to be distinguished.

[0173] Figure 30 The screen display 3000 shows an IVUS image 610 and an image longitudinal display (ILD) 620 according to various aspects of this disclosure. Visible in the IVUS image 610 and ILD 620 are a first vessel lumen 630a and a second vessel lumen 630b. A position indicator 640 indicates the position of the current IVUS image frame 610 within the ILD 620. Also visible are the region of interest 2920, frame number 2950, ​​lumen boundary 2930, and measurement result 2940. Because frame number 2950 is different from... Figure 29 The frame number shown indicates that IVUS image frame 610 comes from a different part of the region of interest, therefore the lumen boundary 2930 and measurement result 2940 differ. Figure 29 Those shown.

[0174] Figure 31 This is a schematic diagram of an exemplary method 3100 for automatic completion of lumen boundaries in the form of a flowchart, based on various aspects of this disclosure.

[0175] In step 3120, method 3100 includes receiving user input (e.g., from a touchscreen, mouse, keyboard, joystick, trackball, etc.) within the screen display 3110 of the first IVUS image A to identify the location inside the lumen boundary in the ILD. Then, proceed to step 3130.

[0176] In step 3130, method 3100 includes determining which IVUS image frames (or other tomographic images) correspond to user input (e.g., which images are represented in the touched portion of the ILD). Then, execution proceeds to step 3140.

[0177] In step 3140, method 3100 includes associating a portion of the user input with the current IVUS image frame for each IVUS image frame corresponding to the user input. Then, execution proceeds to step 3150.

[0178] In step 3150, method 3100 includes mapping a location inside the lumen area in the longitudinal view (e.g., from user input) to a corresponding location inside the lumen area in the current IVUS image frame. Then proceed to step 3160.

[0179] In step 3160, method 3100 includes determining the lumen boundary and lumen area in the IVUS image frame (e.g., as described above). Figure 8 (As described in the text). Then proceed to step 3170.

[0180] In step 3170, method 3100 includes calculating lumen size parameters based on lumen boundaries and / or lumen area. Then proceed to step 3180.

[0181] In step 3180, method 3100 includes generating and outputting a screen display having an ILD (with an indicator of the region of interest for user identification) and / or an IVUS image frame B (overlaid with the lumen boundary) and / or calculated dimensional parameters. The method is now complete.

[0182] Therefore, it can be seen that context-sensitive intravascular measurement systems advantageously allow users of intraluminal imaging systems to determine, for example, the dimensions of vascular anatomical structures with enhanced speed, accuracy, and repeatability, coupled with the ability to edit luminal boundaries through novel means. This technology can be applied to other types of ultrasound equipment besides IVUS, including but not limited to 2D or 3D external ultrasound, transesophageal echocardiography (TEE) or intracardiac echocardiography (ICE), and photoacoustic or photoacoustic imaging techniques such as optical coherence tomography (OCT). This technology can be used in either or both of veins and arteries, including coronary arteries. While the use of deep learning in context-sensitive intravascular measurement systems may be invisible for ad-hoc examinations, the workflow with a GUI interface can be highly visible.

[0183] The logical operations constituting embodiments of the technology described herein are referred to differently as operations, steps, objects, elements, components, modules, etc. Furthermore, it should be understood that these may occur, be performed, or be arranged in any order unless expressly required otherwise or a particular order is inherently necessary by the language of the claims.

[0184] All directional references, such as up, down, inside, outside, upward, downward, left, right, lateral, front, back, top, bottom, above, below, vertical, horizontal, clockwise, counterclockwise, proximal, and distal, are used only for identification purposes to aid the reader in understanding the claimed subject matter and do not impose limitations, particularly regarding the location, orientation, or use of context-sensitive intravascular measurement systems. Connection references (e.g., attachment, coupling, connection, engagement, or “communicating with”) should be interpreted broadly and, unless otherwise indicated, can include intermediate members between sets of elements and relative movement between elements. Therefore, a connection reference does not necessarily imply that two elements are directly connected and in a fixed relationship with each other. The term “or” should be interpreted as “and / or” rather than “exclusive or”. The word “comprising” does not exclude other elements or steps, and the quantifiers “a” or “an” do not exclude a plurality. Unless otherwise specified in the claims, the values ​​stated should be interpreted as illustrative only and should not be considered restrictive.

[0185] The foregoing specification, examples, and data provide a complete description of the structure and use of exemplary embodiments of the context-sensitive intravascular measurement system as defined in the claims. While various embodiments of the claimed subject matter have been described above with a degree of specificity or by reference to one or more individual examples, those skilled in the art will be able to make many changes to the disclosed embodiments without departing from the spirit or scope of the claimed subject matter.

[0186] Other embodiments are also contemplated. It is intended that everything contained in the above description and shown in the accompanying drawings be construed as illustrative of particular embodiments only and not as limiting. Changes in detail or structure may be made without departing from the essential elements of the subject matter as defined in the following claims.

Claims

1. An apparatus comprising: The processor circuitry is configured to communicate with the intravascular imaging catheter and is configured to: A first screen display is output to a display communicating with the processor circuitry. The first screen display includes intravascular images obtained by the intravascular imaging catheter, wherein the intravascular images include vascular lumens and vascular tissue. The system receives a single user input on the intravascular image to identify the location within the region of interest. The boundary of the region of interest is automatically determined in response to the single user input, wherein the boundary surrounds the location identified by the single user input; A second screen display is output to the display, the second screen display including the intravascular image and the boundary of the region of interest superimposed on the intravascular image.

2. The apparatus according to claim 1, in, The display includes a touchscreen display. The individual user input includes a single touch or click at the location within the region of interest on the intravascular image.

3. The apparatus according to claim 1, wherein, In order to automatically determine the boundaries of the region of interest, the processor circuit is configured to: Determine the area of ​​the region of interest within the intravascular image; and Generate the boundary of the area surrounding the region of interest.

4. The apparatus according to claim 3, in, The processor circuitry is configured to associate the location identified by the single user input with a first sub-region of the intravascular image. In order to automatically determine the boundary of the region of interest, the processor circuit is configured as follows: Identify a second sub-region adjacent to the first sub-region; Based on a comparison between the parameters of the first sub-region and the parameters of the second sub-region, the second sub-region is included as part of the area of ​​the region of interest or part of the boundary of the region of interest.

5. The apparatus according to claim 4, wherein, The first sub-region and the second sub-region each include one or more pixels of the intravascular image.

6. The apparatus according to claim 4, wherein, The processor circuit is configured as follows: When the comparison indicates that the parameter of the second sub-region matches the parameter of the first sub-region, the second sub-region is included as part of the area of ​​the region of interest. as well as When the comparison indicates that the parameter of the second sub-region does not match the parameter of the first sub-region, the second sub-region is included as part of the boundary of the region of interest.

7. The apparatus according to claim 4, wherein, The processor is configured to include the first sub-region as part of the area of ​​the region of interest.

8. The apparatus according to claim 4, wherein, The second sub-region is in contact with the first sub-region.

9. The apparatus according to claim 3, in, In order to automatically determine the boundaries of the region of interest, the processor circuit is configured to: Identify additional sub-regions adjacent to the first sub-region; as well as The additional sub-region is included as part of the area of ​​the region of interest or part of the boundary of the region of interest. The processor circuitry is configured to iteratively identify and include each of the plurality of additional sub-regions.

10. The apparatus according to claim 9, wherein, The distance between the multiple sub-regions and the first sub-region increases.

11. The apparatus according to claim 9, wherein, The processor circuit is configured to end the iteration when the boundary of the region of interest completely surrounds the first sub-region.

12. The apparatus according to claim 1, wherein, The first screen display does not include an initial boundary superimposed on the intravascular image, such that the boundary of the region of interest is added to the intravascular image in the second screen display.

13. The apparatus according to claim 1, wherein, The first screen display includes an initial boundary superimposed on the intravascular image, such that the boundary of the region of interest in the second screen display includes a modification of the initial boundary.

14. The apparatus according to claim 13, wherein, The change includes making the area of ​​the region of interest indicated by the boundary of the region of interest displayed on the second screen smaller than the area of ​​the region of interest indicated by the initial boundary of the region of interest displayed on the first screen.

15. An apparatus comprising: The processor circuitry is configured to communicate with the intravascular imaging catheter and is configured to: A first screen display is output to a display communicating with the processor circuitry. The first screen display includes intravascular images obtained by the intravascular imaging catheter, wherein the intravascular images include vascular lumens and vascular tissue. User input is received on the intravascular image, showing only the first portion of the boundary of the region of interest. A second portion of the boundary of the region of interest is automatically determined in response to the user input, such that the first portion and the second portion together define the entire boundary of the region of interest; A second screen display is output to the display, the second screen display including the intravascular image and the boundary of the region of interest superimposed on the intravascular image.

16. The apparatus according to claim 15, in, The display includes a touchscreen display. The user input for drawing only the first part includes touch and drag input along the boundary of the region of interest on the intravascular image.

17. The apparatus according to claim 15, wherein, In order to automatically determine the second portion of the boundary of the region of interest, the processor circuitry is configured to: Determine a first parameter on a first side of the first portion of the boundary of the region of interest; Determine a second parameter on the opposite second side of the first portion of the boundary of the region of interest; Determine the relationship between the first parameter and the second parameter; as well as Generate a second portion of the boundary of the region of interest to maintain the relationship along the second portion of the boundary of the region of interest.

18. An apparatus comprising: The processor circuitry is configured to communicate with the intravascular imaging catheter and is configured to: A first screen display is output to a display communicating with the processor circuitry. The first screen display includes a longitudinal cross-sectional image of a blood vessel, wherein the longitudinal cross-sectional image is generated based on multiple radial cross-sectional images of the blood vessel obtained by the intravascular imaging catheter, wherein the longitudinal cross-sectional image of the blood vessel includes the blood vessel lumen and blood vessel tissue. User input is received on the longitudinal cross-sectional image to identify regions within the region of interest. In response to the user input, the boundaries of the regions of interest in a subset of the multiple cross-sectional images associated with the regions identified by the user input on the longitudinal cross-sectional image are automatically determined; Output a second screen display to the display, the second screen display including: The longitudinal cross-sectional image; The radial cross-sectional images of the subset; and The boundary of the region of interest superimposed on the radial cross-sectional image.

19. The apparatus according to claim 18, in, The display includes a touchscreen display. The user input for identifying the region includes touch and drag input or click and drag input on the intravascular image inside the lumen of the blood vessel.

20. The apparatus according to claim 18, in, To automatically determine the boundaries of the region of interest, the processor circuitry is configured for each radial cross-sectional image of the subset: The portion of the region identified by the user input is associated with the corresponding radial cross-sectional image; The portion of the region identified by the user input is mapped to a first sub-region within the region of interest; The area of ​​the region of interest is included within the first sub-region. Identify additional sub-regions adjacent to the first sub-region; The additional sub-region is included as part of the area of ​​the region of interest or part of the boundary of the region of interest. The processor circuitry is configured to iteratively identify and include each of the plurality of additional sub-regions.

Images