Systems and methods for registering intravascular and extravascular data - Patents.com

Abstract

SUMMARY OF THE INVENTION Systems and methods for registering extravascular and intravascular data are provided herein.

Description

[Technical Field]

[0001] cross reference This application claims the benefit of U.S. Provisional Patent Application No. 63 / 414,360, filed October 7, 2022, and U.S. Provisional Patent Application No. 63 / 540,847, filed September 27, 2023, which are incorporated by reference herein in their entireties. [Background technology]

[0002] Various modalities, such as angiography (extravascular imaging) or other minimally invasive intravascular imaging modalities (e.g., intravascular ultrasound, optical coherence tomography), are utilized to image an individual's blood vessels. Although each imaging modality provides a unique perspective of the blood vessels compared to other imaging modalities, there has been minimal progress in real-time integration and / or co-registration of data types from various modalities to improve vascular clinical methods. Summary of the Invention

[0003]

[0003] Described herein are methods and systems for registering intravascular data to extravascular data to bridge the gap between intravascular and extravascular imaging modalities. In some embodiments, the extravascular imaging includes angiography. In some embodiments, the intravascular imaging includes optical coherence tomography, ultrasound, photoacoustic tomography, spectroscopy, fluorescence, or any combination thereof.

[0004] Aspects of the disclosure provided herein include a method for displaying an object, the method comprising: acquiring intravascular data and extravascular data; determining features in the intravascular data and features in the extravascular data; registering the features in the intravascular data and the features in the extravascular data; and displaying an object for the registered features in the intravascular data or the registered features in the extravascular data, wherein the object is overlaid on a display of real-time extravascular data. In some embodiments, the features in the intravascular data or the features in the extravascular data are selected manually. In some embodiments, the features in the intravascular data include locations in the intravascular data, and the features in the extravascular data include locations in the extravascular data. In some embodiments, the locations in the intravascular data and the locations in the extravascular data are selected automatically. In some embodiments, the object comprises a first object and a second object, and the first object and the second object are displayed relative to the registered locations in the intravascular data or the registered locations in the extravascular data. In some embodiments, the method includes determining a location to guide location of a foreign body. In some embodiments, the intravascular data includes at least one image. In some embodiments, the extravascular data includes at least one image. In some embodiments, the location within the intravascular data, the location within the extravascular location, the location guiding the location of the foreign body, or any combination thereof, is determined by a predictive model. In some embodiments, the predictive model includes a machine learning model. In some embodiments, the machine learning model includes a neural network algorithm. In some embodiments, the method includes guiding a catheter through a coronary artery to an object to treat coronary artery disease. In some embodiments, the catheter includes an atherectomy catheter. In some embodiments, the method includes guiding a catheter through a coronary artery to an object to diagnose coronary artery disease. In some embodiments, the catheter includes a catheter for measuring fractional flow reserve of a coronary artery.In some embodiments, the intravascular data includes optical coherence tomography (OCT), intravascular ultrasound (IVUS), photoacoustic (PA), near-infrared spectroscopy (NIRS), fluorescence, autofluorescence (AF), or any combination thereof. In some embodiments, the intravascular data is detected by a multimodal imaging system. In some embodiments, the multimodal imaging system includes an integrated OCT and NIRS imaging system. In some embodiments, the intravascular data is detected by a one-dimensional sensing system. In some embodiments, the one-dimensional sensing system includes a pressure sensing system. In some embodiments, the intravascular data includes a measurement of flow rate. In some embodiments, the real-time extravascular data is streamed directly from the x-ray system without transfer over a network to a processing unit configured to display objects superimposed on a display of the real-time extravascular data. In some embodiments, the locations within the intravascular data, the locations within the extravascular data, or the locations for guiding the location of a foreign body include the location of a blood vessel, any representation of a vascular network, a side branch of a blood vessel, an area for deploying a stent, coronary plaque, a guidewire, a guide catheter, a stent, a distal or proximal location of an intravascular imaging pullback, a balloon, a valve, a clip, an atherectomy device, an intravascular data device, or any combination thereof. In some embodiments, the extravascular data includes image data from x-ray, CT, magnetic resonance, ultrasound, fluoroscopy, or any combination thereof.In some embodiments, the method includes measuring cardiac cycle data from an external ECG signal, intravascular data, extravascular data, or any combination thereof, and the cardiac cycle data is used to improve the accuracy of registration of positions in the intravascular data and positions in the extravascular data relative to the real-time extravascular data by at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99% compared to not measuring the cardiac cycle data. In some embodiments, the positions in the extravascular data are derived from a priori selection, annotation, or a combination thereof from previous patient records. In some embodiments, the object includes fiducial markers, and the spatial positions of the fiducial markers are adjusted to account for motion artifacts when the real-time extravascular data is displayed. In some embodiments, the method includes measuring a distance from the catheter to an object. In some embodiments, the measured distance from the catheter to the object is displayed in real time using a visual representation. In some embodiments, the reference location in the extravascular data is a feature not shown in the intravascular data. In some embodiments, the reference location includes a radiopaque marker on the catheter. In some embodiments, the reference location includes a known correlation to the intravascular data. In some embodiments, the known correlation includes a distance. In some embodiments, the first object or the second object is displayed overlaid on the real-time extravascular data in one or more data views. In some embodiments, a first view of the one or more data views includes a display of the real-time extravascular data without a display of the first object or the second object, and a second view of the one or more data views includes a display of the real-time extravascular data with a display of the first object or the second object.In some embodiments, the view of the one or more data views includes a zoom view. In some embodiments, the display of the first object or the second object relative to the registered location in the intravascular data or the registered location in the extravascular data includes a first state in which the display of the first object or the second object is visible, or a second state in which the display of the first object or the second object is not visible. In some embodiments, the display of the first object or the second object superimposed on the real-time extravascular data is displayed on one or more monitors. In some embodiments, the one or more monitors include an internal monitor positioned to face an operator of the medical device, an external monitor positioned to face a medical professional using the medical device, or a combination of these monitor configurations. In some embodiments, the internal monitor and the external monitor include different view configurations. In some embodiments, the one or more monitors include at least two external monitors positioned to face a medical professional using the medical device, and the at least two external monitors include different view configurations. In some embodiments, the method includes displaying an indicator, the indicator including a metric representing a distance between the object and a target location in the real-time extravascular data. In some embodiments, the target location is determined by at least one intravascular image or at least one extravascular image. In some embodiments, the method includes processing vascular geometry of the extravascular data and displaying the processed vascular geometry within one or more data views. In some embodiments, the extravascular data or the intravascular data is acquired without or with variable use of contrast.

[0005] Another aspect of the disclosure provided herein includes a method including displaying an object relative to a feature of an endovascular data set or a feature of extravascular data, wherein the feature of the endovascular data set and the feature of the extravascular data are registered to the real-time extravascular data, and the object is overlaid on a display of the real-time extravascular data. In some embodiments, the feature in the endovascular data includes a location in the endovascular data set, and the feature of the extravascular data includes a location in the extravascular data. In some embodiments, the location in the endovascular data and the location in the extravascular data are automatically selected. In some embodiments, the object comprises a first object and a second object, and the first object and the second object are displayed relative to the registered location in the endovascular data or the registered location in the extravascular data. In some embodiments, the method includes determining a location between the first object and the second object to guide stent placement. In some embodiments, the endovascular data includes at least one image. In some embodiments, the extravascular data includes at least one image. In some embodiments, the location within the intravascular data, the location within the extravascular data, the location between the first object and the second object, or any combination thereof, is determined by a predictive model. In some embodiments, the predictive model includes a machine learning model. In some embodiments, the machine learning model includes a neural network algorithm. In some embodiments, the method includes guiding a catheter through a coronary artery to an object to treat coronary artery disease. In some embodiments, the catheter includes an atherectomy catheter. In some embodiments, the method includes guiding a catheter through a coronary artery to an object to diagnose coronary artery disease. In some embodiments, the catheter includes a catheter for measuring fractional flow reserve of the coronary artery. In some embodiments, the intravascular data includes data from optical coherence tomography (OCT), intravascular ultrasound (IVUS), photoacoustics (PA), near-infrared spectroscopy (NIRS), or any combination thereof.In some embodiments, the intravascular data is detected by a multimodal imaging system. In some embodiments, the multimodal imaging system includes an integrated OCT and NIRS imaging system. In some embodiments, the intravascular data is detected by a one-dimensional sensing system. In some embodiments, the one-dimensional sensing system includes a pressure sensing system. In some embodiments, the intravascular data includes a measurement of flow rate. In some embodiments, the real-time extravascular data is streamed directly from an x-ray system without transfer over a network to a processing unit configured to display objects superimposed on a display of the real-time extravascular data. In some embodiments, the location in the intravascular data, the location in the extravascular data, or the location between the first object and the second object includes the location of a side branch of a vessel, an area for stent deployment, coronary plaque, a guidewire, a guide catheter, a stent, a distal or proximal location of an intravascular imaging pullback, a balloon, a valve, a clip, an atherectomy device, an intravascular data device, or any combination thereof. In some embodiments, the extravascular data includes image data from x-ray, CT, magnetic resonance, ultrasound, fluoroscopy, or any combination thereof. In some embodiments, the method includes measuring cardiac cycle data from an external ECG signal, intravascular data, extravascular data, or any combination thereof, where the cardiac cycle data is used to improve the accuracy of registration of locations in the intravascular data and locations in the extravascular data to real-time extravascular data by at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99% compared to not measuring the cardiac cycle data. In some embodiments, the locations in the extravascular data are derived from a priori selection, annotation, or any combination thereof from previous patient records.In some embodiments, the object includes a fiducial marker, and the spatial position of the fiducial marker is adjusted to account for motion artifacts when the real-time extravascular data is displayed. In some embodiments, the method includes measuring a distance from the catheter to the object. In some embodiments, the distance from the catheter to the object is displayed in real time using a visual representation. In some embodiments, the reference location in the extravascular data is a feature not shown in the intravascular data. In some embodiments, the reference location includes a radiopaque marker on the catheter. In some embodiments, the reference location includes a known correlation to the intravascular data. In some embodiments, the known correlation includes a distance. In some embodiments, the first object or the second object is displayed overlaid on the real-time extravascular data in one or more data views. In some embodiments, a first view of the one or more data views includes a display of the real-time extravascular data without a display of the first object or the second object, and a second view of the one or more data views includes a display of the real-time extravascular data with a display of the first object or the second object. In some embodiments, a view of the one or more data views includes a zoom view. In some embodiments, the display of the first object or the second object relative to a location within the intravascular data or a location within the extravascular data includes a first state in which the display of the first object or the second object is visible or a second state in which the display of the first object or the second object is not visible. In some embodiments, the display of the first object or the second object superimposed on the real-time extravascular data is displayed on one or more monitors. In some embodiments, the one or more monitors include an internal monitor positioned to face an operator of the medical device, an external monitor positioned to face a medical professional using the medical device, or any combination thereof. In some embodiments, the internal monitor and the external monitor include different view configurations.In some embodiments, the one or more monitors include at least two external monitors positioned to face a medical professional using the medical device, the at least two external monitors including different view configurations. In some embodiments, the method includes displaying an indicator, the indicator including a metric representing a distance between an object and a target location within the real-time extravascular data. In some embodiments, the target location is determined by at least one intravascular image or at least one extravascular image. In some embodiments, the method includes processing vascular geometry of the extravascular data and displaying the processed vascular geometry within one or more data views. In some embodiments, the extravascular data or the intravascular data is acquired without or with variable use of a contrast agent. [Brief explanation of the drawings]

[0006] The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings (also referred to herein as "Figures" and "FIG.") [Figure 1A] 1 illustrates an intravascular imaging system and probe as described in certain embodiments herein. [Figure 1B] 1 illustrates an intravascular imaging system and probe as described in certain embodiments herein. [Figure 2] 1 shows a flow diagram of a method for registering intravascular and extravascular datasets as described in certain embodiments herein. [Figure 3A] 1 illustrates a view configuration with one or more data views displaying registered intravascular and extravascular data, as described in certain embodiments herein. [Figure 3B]1 illustrates a view configuration with one or more data views displaying registered intravascular and extravascular data, as described in certain embodiments herein. [Figure 3C] 1 illustrates a view configuration with one or more data views displaying registered intravascular and extravascular data, as described in certain embodiments herein. [Figure 4A] 1 shows a flow diagram of a method for guiding an intravascular device through a blood vessel by referencing registered intravascular and extravascular data, as described in certain embodiments herein. [Figure 4B] 1 shows a flow diagram of a method for guiding an intravascular device through a blood vessel by referencing registered intravascular and extravascular data, as described in certain embodiments herein. [Figure 4C] 1 shows a flow diagram of a method for guiding an intravascular device through a blood vessel by referencing registered intravascular and extravascular data, as described in certain embodiments herein. [Figure 4D] 1 shows a flow diagram of a method for guiding an intravascular device through a blood vessel by referencing registered intravascular and extravascular data, as described in certain embodiments herein. [Figure 5] 1 shows a flow diagram of a method for landmark guidance of an intravascular device indicated by a vascular cross-sectional view of extravascular data registered to intravascular data, as described in some embodiments herein. [Figure 6] 1 shows a flow diagram of a method for linearly processing non-linearly shaped extravascular vessel data, as described in certain embodiments herein. [Figure 7A] 1 illustrates one or more views of one or more user interfaces as described in certain embodiments herein. [Figure 7B] 1 illustrates one or more views of one or more user interfaces as described in certain embodiments herein. [Figure 7C]1 illustrates one or more views of one or more user interfaces as described in certain embodiments herein. [Figure 8A] 1 illustrates one or more data views displaying various perspectives of extravascular data and landmark overlays, as described in several embodiments herein. [Figure 8B] 1 illustrates one or more data views displaying various perspectives of extravascular data and landmark overlays, as described in several embodiments herein. [Figure 9A] 1 illustrates one or more views of a first monitor and a second monitor displaying an overlay of extravascular data and intravascular landmarks, as described in certain embodiments herein. [Figure 9B] 1 illustrates one or more views of a first monitor and a second monitor displaying an overlay of extravascular data and intravascular landmarks, as described in certain embodiments herein. [Figure 10] 1 illustrates a view of a user interface displaying a combination of extravascular data and intravascular landmarks registered to the extravascular data in one or more data views, as described in some embodiments herein. [Figure 11] 1 shows a diagram of a computer system configured to implement the methods of the present disclosure as described in some embodiments herein. [Figure 12] FIG. 1 shows a workflow diagram of a method for registering extravascular and intravascular data in real time without or with variable use of contrast agents, as described in some embodiments herein. [Figure 13] A-G show extravascular data processed and / or analyzed in real time for objects and / or landmarks used to register intravascular data to real-time extravascular data as described in some embodiments herein. [Figure 14]FIG. 1 illustrates a workflow diagram of a method for correcting, shifting, and / or adjusting the location and / or position of intravascular data registered to extravascular data without the use of contrast agents or with variable use of contrast agents, as described in some embodiments herein. [Figure 15] 1A-D show intravascular data registered to real-time extravascular data and adjustment of the registered intravascular data position over time as the registered extravascular data position changes due to patient movement, as described in some embodiments herein. [Figure 16] FIG. 1 shows a workflow diagram of a method for guiding and / or implanting an object at one or more location indicators within a registered extravascular and / or intravascular dataset collected and / or acquired without the use of a contrast agent (e.g., a variable contrast agent) that is overlaid on real-time extravascular data with a contrast agent, as described in some embodiments herein. [Figure 17] FIG. 1 illustrates a workflow diagram of a method for guiding and / or implanting an object at one or more location indicators within a registered extravascular and / or intravascular data set collected and / or acquired with contrast, overlaid on real-time extravascular data without contrast, as described in some embodiments herein. [Figure 18] 1 illustrates a workflow diagram of a method for guiding and / or implanting an object at one or more location indicators within a registered extravascular and / or endovascular data set collected and / or acquired without contrast, overlaid on real-time extravascular data without contrast, as described in some embodiments herein. DETAILED DESCRIPTION OF THE INVENTION

[0007] In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, like symbols typically identify like components unless the content dictates otherwise. The exemplary embodiments described in the detailed description, drawings, and claims are not intended to be limiting. Other embodiments may be utilized, and other changes may be made, without departing from the scope of the subject matter presented herein. It will be readily understood that aspects of the present disclosure, as generally described herein and illustrated in the drawings, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are expressly contemplated herein.

[0008] Although specific embodiments and examples are disclosed below, the subject matter of the present invention extends beyond the specifically disclosed embodiments to other alternative embodiments and / or uses thereof, as well as modifications and equivalents thereof. Accordingly, the claims appended hereto are not limited by any of the specific embodiments described below. For example, in any method or process disclosed herein, the acts or operations of the method or process may be performed in any suitable order and are not necessarily limited to any particular disclosed order. Various operations may be described in sequence as multiple separate operations in a manner that may be helpful in understanding a particular embodiment, but the order of description should not be construed to imply that these operations are order-dependent. Additionally, the structures, systems, and / or devices described herein may be embodied as integrated or separate components.

[0009] For purposes of comparing various embodiments, certain aspects and advantages of those embodiments are described. Not necessarily all such aspects or advantages are achieved by any particular embodiment. Thus, for example, various embodiments may be practiced in a manner that achieves or optimizes one advantage or group of advantages taught herein without necessarily achieving other aspects or advantages that may also be taught or suggested herein.

[0010] Overview Considering and / or evaluating only one of the intravascular or extravascular data does not fully represent the complex biological system of blood vessels and how to treat them. For example, x-ray angiography has been shown to be a useful tool for rapidly assessing vascular contours and macroscopic morphology to determine stenosed vessels requiring stent placement and for real-time guidance of vascular treatment. However, x-ray angiography data representations lack biochemical characterization of blood vessels (e.g., plaque type or plaque composition) or microanatomical characterization (e.g., the thin fibrous cap atheromatous structure of vulnerable plaque). As described by the systems and methods herein, the combination of intravascular and extravascular data of blood vessels can reduce image-guided (e.g., fluoroscopy-guided) interventional procedures (e.g., percutaneous coronary intervention and / or stent placement), increase the accuracy of placement and / or guidance of medical devices (e.g., stents, catheters, ablation devices), and ultimately, increase the effectiveness of treatment. In some cases, the accuracy can be increased by at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0011] In a typical intravascular vascular imaging procedure (e.g., intravascular ultrasound and / or intravascular optical coherence tomography), a region of a vessel is navigated under x-ray fluoroscopy, for example, by using radiopaque markers positioned relative to an imaging probe inserted into the vessel. Once the imaging probe is guided to the region of interest, it collects volumetric data of the vessel and is then removed from the individual. Unfortunately, the richness of the intravascular imaging dataset alone, without co-registration to the location of the dataset within the extravascular dataset, provides limited actionable insight for medical professionals. The systems and methods described herein provide a solution for registering and / or combining intravascular and extravascular datasets to realize the unexpected benefits of registration between the two datasets (e.g., during live image-based guidance).

[0012] The disclosure provided herein describes methods and systems for acquiring, correlating, registering, and / or displaying extravascular and intravascular data (e.g., image data, catheter pressure, spatial position of catheter, etc.) acquired during intravascular and / or extravascular procedures. In some cases, the methods and / or systems for acquiring, correlating, registering, and / or displaying extravascular and intravascular data can be performed and / or operated without the use of contrast agents. In some cases, the methods and / or systems for acquiring, correlating, registering, and / or displaying extravascular and intravascular data can be performed and / or operated using variable contrast agents, as described elsewhere herein. In some cases, variable use of contrast agents may include injecting and / or providing the contrast agent into the subject's vascular network for up to about 1 second or up to about 2 seconds. In some cases, the contrast agent may be provided at least once, at least twice, or at least three times during intravascular and / or extravascular data collection, as described elsewhere herein. In some cases, the extravascular and intravascular data may be registered, acquired, correlated, and / or displayed in real time. In some cases, real-time data registration, acquisition, correlation, and / or display may be completed at real-time data rates, which may include frequencies of about 25 Hz to about 120 Hz.In some cases, the real-time data transfer rate may be between approximately 25Hz and approximately 30Hz, approximately 25Hz and approximately 35Hz, approximately 25Hz and approximately 40Hz, approximately 25Hz and approximately 45Hz, approximately 25Hz and approximately 50Hz, approximately 25Hz and approximately 55Hz, approximately 25Hz and approximately 60Hz, approximately 25Hz and approximately 70Hz, approximately 25Hz and approximately 80Hz, approximately 25Hz and approximately 100Hz, approximately 25Hz and approximately 120Hz, approximately 30Hz and approximately 35Hz, approximately 30Hz and approximately 40Hz, approximately 30Hz and approximately 45Hz, approximately 30Hz and approximately 50Hz, approximately 30Hz and approximately Approximately 55Hz, approximately 30Hz to approximately 60Hz, approximately 30Hz to approximately 70Hz, approximately 30Hz to approximately 80Hz, approximately 30Hz to approximately 100Hz, approximately 30Hz to approximately 120Hz, approximately 35Hz to approximately 40Hz, approximately 35Hz to approximately 45Hz, approximately 35Hz to approximately 50Hz, approximately 35Hz to approximately 55Hz, approximately 35Hz to approximately 60Hz, approximately 35Hz to approximately 70Hz, approximately 35Hz to approximately 80Hz, approximately 35Hz to approximately 100Hz, approximately 35Hz to approximately 120Hz, approximately 40Hz to approximately 45Hz, approximately 40Hz to approximately 50Hz, approximately 40Hz to approximately 55 Hz, approximately 40Hz to approximately 60Hz, approximately 40Hz to approximately 70Hz, approximately 40Hz to approximately 80Hz, approximately 40Hz to approximately 100Hz, approximately 40Hz to approximately 120Hz, approximately 45Hz to approximately 50Hz, approximately 45Hz to approximately 55Hz, approximately 45Hz to approximately 60Hz, approximately 45H z~70Hz, 45Hz~80Hz, 45Hz~100Hz, 45Hz~120Hz, 50Hz~55Hz, 50Hz~60Hz, 50Hz~70Hz, 50Hz~80Hz, 50Hz~100Hz , about 50 Hz to about 120 Hz, about 55 Hz to about 60 Hz, about 55 Hz to about 70 Hz, about 55 Hz to about 80 Hz, about 55 Hz to about 100 Hz, about 55 Hz to about 120 Hz, about 60 Hz to about 70 Hz, about 60 Hz to about 80 Hz, about 60 Hz to about 100 Hz, about 60 Hz to about 120 Hz, about 70 Hz to about 80 Hz, about 70 Hz to about 100 Hz, about 70 Hz to about 120 Hz, about 80 Hz to about 100 Hz, about 80 Hz to about 120 Hz, or about 100 Hz to about 120 Hz. In some cases, real-time data rates may include about 25 Hz, about 30 Hz, about 35 Hz, about 40 Hz, about 45 Hz, about 50 Hz, about 55 Hz, about 60 Hz, about 70 Hz, about 80 Hz, about 100 Hz, or about 120 Hz.In some cases, real-time data rates may include at least about 25 Hz, about 30 Hz, about 35 Hz, about 40 Hz, about 45 Hz, about 50 Hz, about 55 Hz, about 60 Hz, about 70 Hz, about 80 Hz, or about 100 Hz. In some cases, real-time data rates may include at most about 30 Hz, about 35 Hz, about 40 Hz, about 45 Hz, about 50 Hz, about 55 Hz, about 60 Hz, about 70 Hz, about 80 Hz, about 100 Hz, or about 120 Hz.

[0013] In some cases, the real-time data rate may include, for example, a real-time imaging frequency at which intravascular and / or extravascular image data is acquired and / or displayed. In some examples, the extravascular and / or intravascular data may be displayed at the real-time imaging frequency. In some cases, the real-time imaging frequency may include, for example, at least about 30 imaging frames of intravascular and / or extravascular data displayed and / or acquired per second. In some cases, the real-time imaging frequency may include about 25 frames per second (fps) to about 120 fps.In some cases, the real-time imaging frequency may be about 25 fps to about 30 fps, about 25 fps to about 35 fps, about 25 fps to about 40 fps, about 25 fps to about 45 fps, about 25 fps to about 50 fps, about 25 fps to about 55 fps, about 25 fps to about 60 fps, about 25 fps to about 70 fps, about 25 fps to about 80 fps, about 25 fps to about 100 fps, about 25 fps to about 120 fps, about 30 fps to about 35 fps, about 30 fps to about 40 fps, about 30 fps to about 45 fps, about 30 fps to about 50 fps, about 30 fps to about 55 fps, approximately 30fps to approximately 60fps, approximately 30fps to approximately 70fps, approximately 30fps to approximately 80fps, approximately 30fps to approximately 100fps, approximately 30fps to approximately 120fps, approximately 35fps to approximately 40fps, approximately 35fps to approximately 45fps, approximately 35fps to approximately 50fps, approximately 35fps ps~55fps, approx.35fps~60fps, approx.35fps~70fps, approx.35fps~80fps, approx.35fps~100fps, approx.35fps~120fps, approx.40fps~45fps, approx.40fps~50fps, approx.40fps~55fps s, approx. 40fps to approx. 60fps, approx. 40fps to approx. 70fps, approx. 40fps to approx. 80fps, approx. 40fps to approx. 100fps, approx. 40fps to approx. 120fps, approx. 45fps to approx. 50fps, approx. 45fps to approx. 55fps, approx. 45fps to approx. 60fps, approx. 45fps to approx. 70fps, approx. 45fps to approx. 80fps, approx. 45fps to approx. 100fps, approx. 45fps to approx. 120fps, approx. 50fps to approx. 55fps, approx. 50fps to approx. 60fps, approx. 50fps to approx. 70fps, approx. 50fps to approx. 80fps, approx. 50fps to approx. 100fps , about 50 fps to about 120 fps, about 55 fps to about 60 fps, about 55 fps to about 70 fps, about 55 fps to about 80 fps, about 55 fps to about 100 fps, about 55 fps to about 120 fps, about 60 fps to about 70 fps, about 60 fps to about 80 fps, about 60 fps to about 100 fps, about 60 fps to about 120 fps, about 70 fps to about 80 fps, about 70 fps to about 100 fps, about 70 fps to about 120 fps, about 80 fps to about 100 fps, about 80 fps to about 120 fps, or about 100 fps to about 120 fps.In some cases, the real-time imaging frequency may include about 25 fps, about 30 fps, about 35 fps, about 40 fps, about 45 fps, about 50 fps, about 55 fps, about 60 fps, about 70 fps, about 80 fps, about 100 fps, or about 120 fps. In some cases, the real-time imaging frequency may include at least about 25 fps, about 30 fps, about 35 fps, about 40 fps, about 45 fps, about 50 fps, about 55 fps, about 60 fps, about 70 fps, about 80 fps, or about 100 fps. In some cases, the real-time imaging frequency may include at most about 30 fps, about 35 fps, about 40 fps, about 45 fps, about 50 fps, about 55 fps, about 60 fps, about 70 fps, about 80 fps, about 100 fps, or about 120 fps.

[0014] In some examples, the real-time data rate and / or real-time imaging frequency, as described elsewhere herein, can reduce imaging artifacts and / or noise (e.g., subject respiration, subject movement) by at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, or at least about 95% compared to devices, methods, and / or systems operating at less than the real-time data rate. In some cases, the real-time data rate and / or real-time imaging frequency, as described elsewhere herein, can increase the accuracy of navigating a device through a vessel and / or placing a device within a vessel in a region and / or location by at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, or at least about 95% compared to devices, methods, and / or systems operating at less than the real-time data rate and / or less than the real-time imaging frequency.

[0015] In some cases, extravascular imaging may include x-ray angiography with or without contrast and / or magnetic resonance imaging (MRI). In some cases, intravascular imaging may include optical coherence tomography, optical endoscopy, ultrasound, near-infrared spectroscopy, photoacoustic tomography, optical endoscopy, fluorescence, or any combination thereof. Each imaging modality alone provides specific data types, such as macroscopic or microscopic vascular structure, that cannot be provided by one imaging modality alone.

[0016] In some cases, systems described elsewhere herein can acquire intravascular data that can be annotated or marked with objects that can be registered to the intravascular data, the extravascular data, or a combination thereof, for example, by systems and / or devices described elsewhere herein. Objects (e.g., landmarks) established from the perspective of the intravascular data can be visualized, for example, superimposed on corresponding regions in the extravascular data set. In some cases, the visualization of the objects can be superimposed on real-time acquisition of the extravascular data. In some examples, the position of the objects and / or landmarks when superimposed on the extravascular data can be dynamically adjusted based on subject and / or patient movement and / or motion artifacts, e.g., breathing, slight tremors, etc. In some cases, movement and / or motion artifacts of the extravascular data, e.g., due to patient breathing, slight tremors, etc., can be removed from the extravascular data. In some examples, removing movement and / or motion artifacts of the extravascular data can increase the accuracy of the location of registered objects relative to the intravascular, extravascular, or any combination thereof data. In some cases, the increase in accuracy may include an increase in accuracy of at least about 1%, at least about 2%, at least about 3%, at least about 4%, at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least about 95%, or at least about 99% compared to the accuracy of the registered object's position without removing the movement and / or motion artifacts of the extravascular data.

[0017] In some cases, the methods and / or systems for acquiring, correlating, registering, and / or displaying extravascular and intravascular data described elsewhere herein may be implemented, performed, and / or used without contrast agents. Existing techniques for extravascular data collection, such as fluoroscopic angiography, require the use of iodine-based contrast agents to visualize the vascular network and the fluid dynamics of blood passing through, for example, coronary arteries, before, during, and / or after placement of an intravascular device (e.g., a cardiovascular stent). It has been found that prolonged or repeated washing of iodine through the vascular network can, in some instances, cause or result in allergic reactions or hyperthyroidism in some patients, as well as kidney damage and sometimes increased acute and chronic kidney injury. Therefore, minimizing the use of contrast agents during patient diagnosis and treatment is desirable for optimal patient outcomes. The disclosure provided herein describes methods and systems for correlating and / or registering intravascular data with extravascular data using, without, or variable use of contrast agents when acquiring extravascular data or when registering and / or correlating the extravascular data with the intravascular data in real time.

[0018] Imaging system The disclosure provided herein describes a system 100 for registering intravascular and extravascular data, as seen in FIG. 1 . System 100 may include an imaging system 101 and display shown in FIG. 1A configured to acquire intravascular data and register the intravascular data with extravascular data. In some examples, the intravascular data may include one or more intravascular images of a blood vessel. In some cases, the extravascular data may include one or more extravascular images (e.g., x-ray angiograms, MRIs, etc.) of blood vessel geometry, physiology, anatomical structure, or any combination thereof. In some cases, the imaging system may include a computer system (106, 1110) for processing the intravascular, extravascular, user-interaction, or any combination thereof data.

[0019] The user interaction data may include patient input data into the imaging system 101, where the data may include patient information, landmark designation, system operating mode selection, image processing functions, or any combination thereof. In some cases, the user may input data into the imaging system 101 using a mouse and / or keyboard electrically coupled to the computer system (106, 1110). The user may visualize a view (i.e., a user interface) configured to input data into the system via the first monitor 102 and / or the second monitor 104. In some cases, the first monitor 102 and / or the second monitor 104 may include a touchscreen interface and keyboard for interacting with, acquiring, or any combination thereof, the intravascular and / or extravascular data. In some cases, the user interaction data may include data resulting from the user interacting with the extravascular and / or intravascular data (e.g., rotating, zooming in, adjusting contrast, adjusting brightness, measuring distance, etc.). The computer system (106, 1110) may include or be in communication with an electronic display 1114 (e.g., the first monitor 102 and / or the second monitor 104) having one or more view configurations (i.e., user interface (UI)) 1116, as also shown in Figures 3A-10 described elsewhere herein, for viewing intravascular data, extravascular data, registered intravascular and extravascular data, and / or a combination of intravascular and extravascular data, or any combination thereof.

[0020] In some cases, the computer system (106, 1110) may include an input interface 105, which may include one or more input points and / or ports electrically coupled to the computer system (106, 1110). The input interface 105 may receive one or more data and / or streams of data from one or more imaging systems. For example, the input interface 105 may receive x-ray angiography data, and the computer system (106, 1110) may then register the x-ray angiography data to the intravascular data. In some cases, the input interface 105 may receive data from angiography-derived physiology, MRI, computed tomography, spatial location, intravascular sensors (e.g., intravascular physiology), or any combination thereof from one or more medical devices to be displayed and / or registered to the intravascular data. In some examples, the input interface 105 may receive data for registration to extravascular data wirelessly through a wireless communication platform such as ad hoc Wi-Fi, Bluetooth, radio frequency, or any combination thereof, as described elsewhere herein.

[0021] In some cases, the computer system (106, 1110) can process data using one or more processors 1104, as described elsewhere herein. In some examples, the one or more processors may comprise one or more graphical processing unit processors, integrated circuits, or any combination thereof. Graphical processing units provide the ability to process complex and large data sets due to their highly parallel processor architecture. For example, processing data with one or more graphical processing units provides the system with the ability to register intravascular data with a real-time stream of extravascular data, something that would not otherwise be achieved with conventional multi-core processors.

[0022] In some cases, the computer systems (106, 1110) may be configured to process intravascular and extravascular data and / or images. The computer systems (1100, 106) as seen in FIG. 11 may include a central processing unit and / or graphical processing unit (CPU and / or GPU; similarly, "processor" and "computer processor" herein) 1104, which may be a single-core or multi-core processor, or multiple processors for parallel processing. The computer systems (106, 1110) may further include memory or memory locations 1106 (e.g., random access memory, read-only memory, flash memory), an electronic storage unit 1102 (e.g., hard disk), a communication interface 1108 (e.g., network adapter) for communicating with one or more other devices, and peripheral devices 1110, such as cache, other memory, data storage, and / or electronic display adapters. The memory 1106, the storage unit 1102, the communication interface 1108, and peripheral devices (e.g., mouse, keyboard, etc.) 1110 can communicate with the CPU and / or GPU 1104 via a communication bus (solid lines) such as a motherboard. The storage unit 1102 can be a data storage unit (or data repository) for storing data. The computer systems (106, 1110) can be operably coupled to a computer network ("network") 1112 using the communication interface 1108. The network 1112 can be the Internet, an Internet and / or extranet, or an intranet and / or extranet in communication with the Internet. The network 1112 can, in some cases, be a telecommunications and / or data network. The network 1112 can include one or more computer servers, which can enable distributed computing, such as cloud computing.The network 1112 may, in some cases, implement a peer-to-peer network that may, with the aid of the computer systems (106, 1110), allow devices coupled to the computer systems (106, 1110) to act as clients or servers.

[0023] The CPU and / or GPU (1104) may execute a series of machine-readable instructions, which may be embodied in a program or software. The instructions may be directed to the CPU and / or GPU 1104, which may then program or otherwise configure the CPU / GPU 1104 to acquire and / or process data generated by the imaging system described elsewhere herein. In some embodiments, the computer system (106, 1110) central processing unit and / or graphical processing unit 1104 may execute machine-executable or machine-readable code, which may be provided in the form of software, for transferring data generated by the imaging system to a network and / or cloud 1112 for further processing, classification, data clustering, or any combination thereof. In some examples, the data may include intravascular and / or extravascular data described elsewhere herein. In some cases, the data may include image pixel data. In some examples, the pixel data may include image pixel data from optical coherence tomography, x-ray angiography, computed tomography, intravascular ultrasound, spectroscopy, MRI, or any combination thereof.

[0024] In some embodiments, the CPU and / or GPU 1104 may be part of a circuit, such as an integrated circuit. One or more other components of the system 1110 may be included in the circuit. In some cases, the circuit may comprise an application-specific integrated circuit (ASIC). The storage unit 1102 may store files, such as drivers, libraries, and saved programs. The storage unit 1102 may store data and / or images from acquired x-ray angiography, optical coherence tomography, intravascular ultrasound, near-infrared spectroscopy, photoacoustics, or any combination thereof. In some cases, the intravascular and / or extravascular data and / or images may be stored in the cloud, a medical system electronic medical record (e.g., EPIC), or any combination thereof. The computer system (106, 1110) may include one or more additional data storage units external to the computer system (106, 1110), such as located on a remote server that communicates with the computer system (106, 1110) via an intranet or the Internet 1112.

[0025] 1B, the imaging system 101 is in electrical and / or optical communication with the imaging probe actuator 110 and the imaging probe 112. The imaging system 101 may be in electrical and / or optical communication with the imaging probe actuator 110 through one or more electrical and / or optical communication wires 108. In some cases, the imaging probe 112 may be releasably coupled to the imaging probe actuator 110 such that a first imaging probe can be removed from the imaging probe actuator and replaced with a second imaging probe. In some examples, the imaging probe may comprise an intravascular imaging probe. The intravascular imaging probe may comprise an optical coherence tomography, intravascular ultrasound, reflectance, photoacoustic, near-infrared spectroscopy, fluorescence, or any combination thereof imaging probe. In some examples, the imaging probe may acquire, collect, and / or detect intravascular data from the lumen and / or body of the blood vessel. In some cases, the intravascular data may include two-dimensional (e.g., circular cross-sectional data) and / or volumetric intravascular data (i.e., one or more two-dimensional circular cross-sectional data as a function of the length of the optical axis of the imaging probe). In some cases, the imaging probe may comprise one or more radiopaque markers and / or indicia that can be visualized with an extravascular imaging modality, such as x-ray angiography, computed tomography, MRI, or any combination thereof.

[0026] In some examples, the imaging probe actuator 110 may rotate and / or translate the imaging probe 112 to acquire two-dimensional and / or three-dimensional intravascular data sets. In some cases, the probe may be rotated by a stepper motor coupled to an optic rotary joint, a DC brushless motor, or any combination thereof. In some cases, the imaging probe actuator 110 may translate the imaging probe 112 with a stage, which may comprise a linear and / or planar translation stage. The translation and rotation of the stage of the imaging probe actuator 110 may be set and / or adjusted by a user through one or more interfaces of the imaging system 101 described elsewhere herein. In some examples, the translation and rotation of the stage of the imaging probe actuator 110 may be determined and / or set by the system based on pre-established standard values ​​for a particular type of imaging procedure or frequently used settings.

[0027] Aspects of the systems and methods provided herein, such as computer systems (106, 1110), may be embodied in programming. Various aspects of the present technology may be considered "products" or "articles of manufacture," typically in the form of machine (or processor) executable code and / or associated data carried or embodied on some type of machine-readable medium. The machine-executable code may be stored in an electronic storage unit, such as memory (e.g., read-only memory, random-access memory, flash memory) or a hard disk. A "storage" type medium may include any or all of the tangible memory of a computer, processor, or its associated modules, such as various semiconductor memories, tape drives, disk drives, etc., which can provide non-transitory storage for software programs at any time. All or portions of the software may sometimes be communicated via the Internet or various other telecommunications networks. Such communication may, for example, enable loading of the software from one computer or processor to another, for example, from a management server or host computer to the computer platform of an application server. Thus, another type of medium that may have a software element includes light waves, radio waves, and electromagnetic waves, such as those used in physical interfaces between local devices, over wired and optical terrestrial communications networks and various air links. Physical elements that carry such waves, such as wired or wireless links, optical links, etc., may also be considered software-bearing media. As used herein, unless limited to non-transitory, tangible "storage" media, terms such as computer or machine "readable medium" refer to any medium that participates in providing instructions to a processor for execution. Thus, a machine-readable medium such as a computer-executable code may take many forms, including, but not limited to, a tangible storage medium, a carrier wave medium, or a physical transmission medium. Non-volatile storage media may include, for example, optical or magnetic disks, such as any of the storage devices in any computer, such as those that may be used to implement a database. Volatile storage media may include dynamic memory, such as the main memory of such a computer platform. Tangible transmission media include coaxial cables, copper wire, and fiber optics, including the wires that comprise a bus within a computer system. Carrier wave transmission media may take the form of electric or electromagnetic signals, or acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media for this purpose include, for example, floppy disks, flexible disks, hard disks, magnetic tape, any other magnetic media, CD-ROMs, DVDs or DVD-ROMs, any other optical media, punched cards paper tape, any other physical storage media with patterns of holes, RAM, ROM, PROMs and EPROMs, FLASH-EPROMs, any other memory chips or cartridges, carrier waves transmitting data or instructions, cables or links transmitting such carrier waves, or any other medium from which a computer can read programming code and / or data. Many of these forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to a processor for execution.

[0028] Computer Systems and Machine Learning Models In some embodiments, the system 100 disclosed herein may comprise a computer system (106, 1110) suitable for implementing machine learning algorithms and / or predictive models configured to analyze, process, segment, and / or label the extravascular and / or intravascular data collected by the imaging system 101, imaging probe 112, and imaging probe actuator 110 described elsewhere herein. In some cases, one or more intravascular and / or extravascular images can be generated from the intravascular and / or extravascular data. In some cases, the predictive models, e.g., machine learning models and / or machine learning algorithms, can analyze, extract, condense, reduce, predict, process, classify, segment, or any combination thereof, an operation performed on the intravascular and / or extravascular data.

[0029] In some embodiments, the systems disclosed herein may implement one or more machine learning algorithms and / or models to identify, classify, process, and / or segment regions of interest in the intravascular and / or extravascular data. In some embodiments, the systems disclosed herein may implement one or more machine learning algorithms to register one or more images of the first extravascular data to one or more reference images or one or more images of the second extravascular data. In some instances, the first extravascular data may be the same as the second extravascular data. In some instances, the first extravascular data may be different from the second extravascular data. For example, a machine learning algorithm may be trained using labeled intravascular and / or extravascular data such that, when provided with an input of unlabeled intravascular and / or extravascular data, the machine learning algorithm may classify each data point into one or more categories and / or features. In some instances, each data point may include a pixel or multiple pixels of intravascular and / or extravascular data. In some instances, the intravascular and / or extravascular data may be labeled by a user on the system. The labeled data may then be used to train one or more machine learning models on the system and / or in a remote cloud-based computing architecture. The remote cloud-based computing architecture may be refined by one or more systems via a wireless communication platform (i.e., Wi-Fi). In some embodiments, a human user may select and discard features before / during machine learning training / classification. In some cases, a computer may select and discard features. In some cases, features may be discarded based on a threshold.

[0030] In some cases, one or more categories and / or features of the labeled data may then be provided to one or more treatment parameter machine learning models and / or algorithms to determine proposed treatments and / or treatment parameters (e.g., what type of stent to place and the optimal spatial location to place the stent to achieve clinical effectiveness of the treatment). One or more treatment parameter machine learning models may be trained using the prior features and corresponding treatment effectiveness (i.e., whether a complication occurred after clinical intervention by the system) to create one or more trained treatment parameter machine learning models for predicting effective treatments. The spatial orientation of the labeled features and their relationship to each other may be other features determined and considered by the treatment parameter machine learning models. In some cases, one or more categories of data and / or features for the extravascular data may include background data, healthy vascular morphology, stenotic vascular morphology, or occluded vessels. In some cases, one or more categories of data for the intravascular data may include epithelial vascular tissue, intimal vascular tissue, adventitial vascular tissue, plaque within vascular tissue, vulnerable plaque within vascular tissue, or any combination thereof. In some cases, one or more categories and / or features of the intravascular data may include spectroscopic (e.g., in near-infrared) signatures of intravascular vascular tissue. For example, one or more categories and / or features may classify the composition of vascular plaque based on its spectroscopic signature. In some cases, one or more categories may include calcium or lipid spectroscopic signatures. In some cases, the machine learning model and / or algorithm may preprocess the intravascular and / or extravascular data before classifying features of the data. In some examples, preprocessing of the intravascular and / or extravascular data may include mathematical manipulation of the data to remove noise, smooth, average, sharpen, adjust brightness, and / or contrast, or any combination thereof. In some cases, features and / or categories of intravascular and / or extravascular data may be extracted without any preprocessing steps.

[0031] In some cases, machine learning algorithms may need to extract and derive relationships between features because traditional statistical techniques may not be sufficient. In some cases, machine learning algorithms may be used in conjunction with traditional statistical techniques. In some cases, traditional statistical techniques may provide preprocessed features to the machine learning algorithm.

[0032] In some embodiments, any number of features may be classified by a machine learning algorithm. The machine learning algorithm may classify at least one feature. In some cases, the plurality of features may include between about 1 feature and 5 features. In some cases, the plurality of features may include between about 5 features and 10 features. In some cases, the plurality of features may include between about 10 features and 50 features.

[0033] In some embodiments, the machine learning algorithm may be, for example, an unsupervised learning algorithm, a supervised learning algorithm, or a combination thereof. The unsupervised learning algorithm may be, for example, clustering, hierarchical clustering, k-means, mixture models, DBSCAN, the OPTICS algorithm, the VoxelMorph algorithm, anomaly detection, local outlier factor methods, neural networks, autoencoders, deep belief networks, Hebbian learning, generative adversarial networks, self-organizing maps, expectation-maximization algorithms (EM), methods of moments, blind signal separation techniques, principal component analysis, independent component analysis, nonnegative matrix factorization, singular value decomposition, or a combination thereof. The supervised learning algorithm may be, for example, a support vector machine, linear regression, logistic regression, linear discriminant analysis, decision trees, k-nearest neighbor algorithms, neural networks, similarity learning, or a combination thereof. In some embodiments, the machine learning algorithm may comprise a deep neural network (DNN). The deep neural network may comprise a convolutional neural network (CNN). The CNN may be, for example, U-Net, ImageNet, LeNet-5, AlexNet, ZFNet, GoogleNet, VGGNet, ResNet18, or ResNet. Other neural networks may be, for example, deep feedforward neural networks, recurrent neural networks, Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), autoencoders, variational autoencoders, adversarial autoencoders, denoising autoencoders, sparse autoencoders, Boltzmann machines, Restricted BMs (RBMs), deep belief networks, generative adversarial networks (GANs), deep residual networks, capsule networks, or attention / transformer networks.

[0034] In some examples, the machine learning model may include clustering, scalar vector machine, kernel SVM, linear discriminant analysis, quadratic discriminant analysis, neighborhood component analysis, manifold learning, convolutional neural network, reinforcement learning, random forest, naive Bayes, Gaussian mixture, hidden Markov model, Monte Carlo, restricted Boltzmann machine, linear regression, or any combination thereof. In some cases, the machine learning algorithm may include ensemble learning algorithms such as bagging, boosting, and stacking. The machine learning algorithm may be applied to the extracted features individually.

[0035] In some embodiments, the system may apply one or more machine learning algorithms and / or an ensemble of machine learning algorithms.

[0036] In some embodiments, the machine learning algorithm may have various parameters, such as a learning rate, a mini-batch size, a number of epochs to train, momentum, learning weight decay, or neural network layers.

[0037] In some embodiments, the learning rate may be between about 0.00001 and 0.1.

[0038] In some embodiments, the mini-batch size may be between about 16 and 128.

[0039] In some embodiments, the neural network can have neural network layers, and the neural network can have at least about 2 to 1000 or more neural network layers.

[0040] In some embodiments, the number of epochs to train may be at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 500, 1000, 10000, or more.

[0041] In some embodiments, the momentum may be at least about 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, or more, hi some embodiments, the momentum may be up to about 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, or less.

[0042] In some embodiments, the learning weight decay may be at least about 0.00001, 0.0001, 0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, or more. In some embodiments, the learning weight decay may be at most about 0.1, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01, 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001, 0.0001, 0.00001, or less.

[0043] In some embodiments, the machine learning algorithm may use a loss function, which may be, for example, regression loss, mean absolute error, mean bias error, hinge loss, Adam optimizer, and / or cross entropy.

[0044] In some embodiments, the parameters of the machine learning algorithm may be tuned with the assistance of a human and / or a computer system.

[0045] In some embodiments, the treatment parameter machine learning model and / or algorithm may prioritize certain features. The treatment parameter machine learning model and / or algorithm may prioritize features that may be more relevant to determining anatomical and / or physiological features to characterize variations in vascular geometry and composition. In some cases, the geometry and composition of the vessel may classify a portion of the vessel as diseased (e.g., thin fibrous cap atheroma, vulnerable plaque, unstable plaque, etc.). In some cases, features may be prioritized using a weighting system. In some cases, features may be prioritized with probability statistics based on the frequency and / or quantity of the feature's occurrence. The machine learning algorithm may prioritize features with the assistance of a human and / or a computer system.

[0046] In some embodiments, one or more features can be used in conjunction with machine learning or traditional statistical techniques to determine whether a segment of intravascular and / or extravascular data is likely to contain an artifact. The identified artifact may be the result of optical misalignment, subject motion during intravascular and / or extravascular data acquisition, laser power instability, laser pulse frequency jitter, subject motion due to breathing or slight tremors, or any combination thereof. In some cases, a motion sensor or other sensors may be used as additional input to the artifact reduction machine learning model and / or algorithm. In some cases, the identified artifact may be rejected for use in vascular anatomy and / or disease classification.

[0047] In some cases, machine learning algorithms may prioritize certain features to reduce computational cost, save processing power, save processing time, increase reliability, reduce random access memory usage, etc.

[0048] The methods described herein may be implemented by machine (e.g., computer processor) executable code stored on a non-transitory electronic storage medium of the computer system 1110, such as, for example, memory 1106 or electronic storage unit 1102. The machine-executable or machine-readable code may be provided in the form of software. During use, the code may be executed by the processor (i.e., CPU and / or GPU) 1104. In some examples, the code may be retrieved from the storage unit 1102 and stored in memory 1106 for easy access to the processor 1104. In some examples, the electronic storage unit 1102 may be eliminated, and the machine-executable instructions stored on memory 1106. The code may be pre-compiled and configured for use with a machine having a processor adapted to execute the code, or may be compiled during run-time. The code may be provided in a programming language that can be selected so that the code can be executed in a pre-compiled or compiled manner.

[0049] method In some cases, the disclosure provided herein describes methods for registering and / or processing intravascular and extravascular data.

[0050] In some cases, the method includes a method for displaying an object, comprising displaying the object relative to features of the endovascular dataset or features of the extravascular dataset, wherein the features of the endovascular dataset and the features of the extravascular dataset are registered to the real-time extravascular dataset, and the object is overlaid on a display of the real-time extravascular data.

[0051] In some cases, the method may include a method 200 of displaying an object, as seen in FIG. 2 . In some examples, the method may include acquiring extravascular data 202 and intravascular data 206, determining features of the extravascular data 204 and features of the intravascular data 208, registering the features of the intravascular data to the features of the extravascular data 210, and displaying an object for the registered features in the intravascular data or the registered features in the extravascular data 212, where the object is superimposed on a display of the real-time extravascular data. In some examples, the intravascular data includes at least one image. In some cases, the extravascular data includes at least one image. In some cases, the extravascular data may include data from an x-ray angiogram, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, fluoroscopy, or any combination or derivative thereof (e.g., angioFFR, CT-FFR, quantitative coronary angiography, CT-based plaque detection).

[0052] In some cases, the features in the endovascular data and the features in the extravascular data are manually selected (e.g., by a user, medical professional, surgeon, attending physician, nurse, etc.) or automatically selected by computer software (e.g., predictive models, machine learning models and / or algorithms) described elsewhere herein. In some examples, the features in the endovascular data include locations in the endovascular data, and the features in the extravascular data include locations in the extravascular data. In some examples, the objects include a first object and a second object, and the first object and the second object are displayed relative to the registered location of the endovascular data or the registered location of the extravascular data. In some examples, the objects may include fiducial markers, and the spatial locations of the fiducial markers may be adjusted to account for motion artifacts when the real-time extravascular data is displayed.

[0053] In some cases, the locations within the extravascular data may include locations derived from previous patient and / or subject recordings of "a prior selection," "annotations," or any combination thereof. In some examples, the methods of detecting, registering, and / or displaying objects may further include cardiac cycle data from an external electrocardiogram (ECG) signal, intravascular data, extravascular data, or any combination thereof. The cardiac cycle data may be used to improve the accuracy of registration of locations within the intravascular data and locations within the extravascular data to real-time extravascular data by at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99% compared to not measuring the cardiac cycle data. In some cases, the cardiac cycle data may be used to time the acquisition of any data source (e.g., to improve image quality). In some cases, the method of displaying an object may further include displaying an indicator, the indicator including a metric of distance between the object and a target location in the real-time extravascular data. In some cases, the target location may be determined by at least the intravascular data, at least the extravascular data, or any combination thereof. In some cases, the method of displaying an object may further include processing vascular geometry of the extravascular data as described elsewhere herein and displaying the processed vascular geometry in a view of the one or more data views.

[0054] In some cases, the method of displaying an object may further include determining a location to guide the location of a foreign object. The foreign object may comprise an intravascular stent that can be delivered to a region of a blood vessel via a minimally invasive catheter. In some examples, the method of displaying an object may further include guiding a catheter to the object through a coronary artery to treat coronary artery disease. In some cases, the catheter may comprise an atherectomy catheter. In some examples, the catheter may comprise an imaging probe as described elsewhere herein. In some examples, the catheter includes a catheter for measuring fractional flow reserve of a coronary artery. In some examples, the registered location of intravascular data, registered location of extravascular data, or location to guide the location of a foreign object may include the location of a blood vessel, any representation of a vascular network, a side branch of a blood vessel, a region for stent deployment, coronary plaque, a guidewire, a guide catheter, a stent, a distal or proximal location of an intravascular imaging pullback, a balloon, a valve, a clip, an atherectomy device, an intravascular data device, or any combination thereof. In some examples, the method of displaying an object may further include measuring a distance from the catheter to the object. In some cases, the measured distance from the catheter to the object may be displayed in real time. In some cases, the measured distance from the catheter may be displayed in real time using a visual representation. In some cases, the measured distance from a first detected foreign object to a second detected foreign object may be displayed in real time. In some examples, the measured distance from a first detected foreign object to a second detected foreign object may be displayed in real time using a visual representation. In some cases, the measured distance from a foreign object to an anatomical landmark may be displayed in real time. In some examples, the measured distance from a foreign object to an anatomical landmark may be displayed in real time using a visual representation.

[0055] In some cases, the intravascular data may include data from optical coherence tomography (OCT), intravascular ultrasound (IVUS), photoacoustics (PA), near-infrared spectroscopy (NIRS), reflectance, Raman spectroscopy, fluorescence, fluorescence lifetime imaging (FLIM), or any combination thereof. In some cases, the intravascular data may be detected by a multimodal imaging system (e.g., an OCT-IVUS or OCT-IVUS-NIRS imaging system). In some examples, the intravascular data may be detected by a one-dimensional sensing system. The one-dimensional sensing system may include a pressure sensing system. In some examples, the intravascular data may include measurements of flow rate within the blood vessel.

[0056] In some cases, the reference location of the extravascular data may include features not shown in the intravascular data. The reference location may include radiopaque markers of a catheter or imaging probe as described elsewhere herein. In some examples, the reference location may include a known correlation to the intravascular data. In some cases, the known correlation may include a distance.

[0057] In some cases, real-time extravascular data may be streamed from the x-ray system without transferring the real-time extravascular data over a network to a processor described elsewhere herein configured to display objects superimposed on a display of the real-time extravascular data.

[0058] In some examples, the first object and / or the second object may be displayed overlaid on the real-time extravascular data in one or more data views, as shown in Figures 7A-10. A first view of the one or more data views may include a display of the real-time extravascular data without a display of the first object or the second object. In some cases, a second view of the one or more data views may include a display of the real-time extravascular data with a display of the first object or the second object. In some examples, a view of the one or more data views may include a zoomed view, where the zoom may include a zoom of at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 100%.

[0059] In some cases, the display of the first object or the second object relative to the registered location of the intravascular data or the registered location of the extravascular data may include a first state in which the display of the first object or the second object is visible or a second state in which the display of the first object or the second object is not visible. In some cases, the display of the first or second object superimposed on the real-time extravascular data may be displayed on one or more monitors. The one or more monitors may include an internal monitor facing an operator of the medical device, an external monitor positioned to face a medical professional using the medical device, or any combination thereof. The operator may include a physician, surgeon, attending physician, resident, nurse, clinical nurse, surgical staff, or any combination thereof. In some cases, the internal monitor and the external monitor may include different user interfaces, as described elsewhere herein. In some examples, the one or more monitors include at least two external monitors positioned to face a medical professional using the medical device, and the at least two external monitors include different user interfaces. In some cases, the present disclosure describes a method that includes displaying an object relative to features of an endovascular dataset or features of an extravascular dataset, where the features of the endovascular dataset and the features of the extravascular dataset are registered to the real-time extravascular dataset, and the object is overlaid on a display of the real-time extravascular data.

[0060] In some examples, the disclosure herein describes a method 400 for tracking the position of an intravascular device 412 relative to registered intravascular (404, 408, 410) and / or extravascular data sets 402, as seen in FIGS. 4A-4D . In some cases, the method may include acquiring intravascular data 404 and extravascular data 402, registering the intravascular and extravascular data, guiding a medical device 412 to objects (408, 410) registered in the intravascular data, and providing a visual indicator when the medical device is adjacent to the object ( FIG. 4D ). In some examples, the objects include a first object 410 and a second object 408. In some cases, the visual indicator may be provided when the medical device is positioned between the first object 410 and the second object 408. In some cases, the indicator may include a colored indicator, as shown in FIG. 4D . For example, a green visual indicator may be provided when the medical device 412 is within a spatial location defined by the first object 410 and the second object 408. In some examples, the indicator may include a red visual indicator that may be provided when the medical device 412 is outside of the area defined by the first object 410 and the second object 408. In some cases, the first object 410 and the second object 408 may be set by a user or automatically by the system, as described elsewhere herein. In some cases, the medical device may comprise a catheter, as described elsewhere herein, and / or a catheter that delivers a medical device (e.g., a stent).

[0061] 5 , the indicator may include a percentage indicator 512 of the position of the medical device 506 relative to the first object 508 and / or the second object 510. For example, the percentage indicator 512 may describe the percentage of the medical device within a spatial position range between the first object 508 and the second object 510. In some instances, a representation of a cross section of the blood vessel 502 from the extravascular data 504 may be overlaid with the medical device intravascular tracking position 506, the first object 508, and the second object 510. In some examples, the registered first object 508 and second object 510 can be registered to a real-time display of the extravascular data to facilitate real-time guidance and / or placement of the medical device within the blood vessel.

[0062] In some cases, the disclosure provided herein describes a method 600 for processing registered intravascular and extravascular data, as seen in FIG. 6. In some examples, the method may include obtaining intravascular data 606 and / or extravascular data 604 of a vascular structure 602, determining a nonlinear structure of the vessel from the intravascular data and / or extravascular data, and processing the nonlinear structure of the vessel into a linear structure 608. In some cases, processing the nonlinear structure of the vessel into a linear structure may provide one or more features, determined by one or more predictive models and / or machine learning algorithms, that increase the accuracy of characterizing various tissue types and / or categories, for example, as described elsewhere herein. In some cases, the accuracy can be increased by at least about 5%, at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0063] In some cases, the method and / or system for correlating and / or registering intravascular and extravascular data in real time may operate and / or be implemented without contrast or with variable use of contrast, as described elsewhere herein. In some cases, variable use of contrast (as shown in FIG. 13E, F, and G) may include providing and / or injecting contrast (i.e., a puff of contrast) for less than about 1 second or less than about 2 seconds. In some cases, variable use of contrast may include providing and / or injecting contrast for up to about two events of providing and / or injecting contrast into the subject's vascular network during real-time extravascular and / or intravascular data acquisition. In some cases, variable use of contrast may provide real-time updates to the registration and / or correlation of previously registered intravascular and extravascular data, as shown in FIG. 13A. In some cases, as shown in FIG. 12 , a method 1200 for correlating and / or registering intravascular data and extravascular data without or with variable use of contrast may include step 1202 acquiring, detecting, and / or collecting extravascular and intravascular data in real time without or with variable contrast; step 1204 identifying, determining, detecting, and / or segmenting one or more locations in the real-time extravascular data (1300, 1302, 1304, 1308, 1310, as shown in FIGS. 13B-C, D, and F); step 1206 identifying, determining, detecting, and / or segmenting intravascular data (e.g., intravascular probe image data generated during probe pullback) that corresponds to, correlates with, and / or matches the one or more locations in the extravascular data; and step 1208 registering and / or correlating the one or more locations in the extravascular and intravascular data in real time.In some cases, one or more locations of the real-time extravascular data may be identified, determined, detected, and / or segmented using a contrast agent, without a contrast agent, or with a contrast agent provided and / or injected into the subject's vascular network for less than about 1 second or less than about 2 seconds during the collection of the real-time extravascular data and / or intravascular data. In some cases, a contrast agent may be provided and / or injected into the subject's vascular network for up to about two events of providing and / or injecting a contrast agent into the subject's vascular network during the collection of the real-time extravascular data and / or intravascular data. In some cases, the identification, determination, and / or segmentation of the intravascular data may be performed without a contrast agent being provided and / or injected into the subject's vascular network during the collection of the real-time intravascular data. The one or more locations of the extravascular data set may include the location and / or spatial location of the guide catheter tip 1300, the primary guidewire tip 1306, the secondary guidewire tip 1302, the imaging catheter position marker 1304, the distal imaging catheter marker 1306, the guidewire path, the guidewire position, any other location of the extravascular data described elsewhere herein, or any combination thereof. In some cases, the imaging catheter position marker may include a radiopaque catheter marker that is visualized and / or detected as shown in the extravascular data. In some cases, the variable use of contrast agents may segment one or more vascular geometries 1312, as shown in FIG. 13G. In some examples, the identification, determination, detection, collection, and / or segmentation of one or more locations of the extravascular data may be performed automatically, for example, by one or more processors of a system described elsewhere herein. In some cases, the methods and / or systems described elsewhere herein for guiding, delivering, and / or implanting an object (e.g., a stent) at one or more locations within extravascular data and / or intravascular data may be performed and / or operated with or without the use of contrast agents.

[0064] In some cases, method 1600 may include collecting, acquiring, and / or detecting intravascular and extravascular data without injecting and / or providing contrast agent into the vascular network of the subject, while providing and / or injecting contrast agent when guiding, implanting, and / or providing an object to one or more locations that include extravascular and / or intravascular data, as shown in FIG. 16 . In some cases, method 1600 may include step 1602 acquiring, detecting, and / or collecting extravascular data without a contrast agent, step 1604 identifying, determining, detecting, and / or segmenting one or more locations of the real-time extravascular data, step 1606 acquiring, detecting, and / or collecting intravascular data without a contrast agent that corresponds to, correlates with, and / or matches the one or more locations of the extravascular data, step 1608 registering and / or correlating the one or more locations of the extravascular data with corresponding one or more locations of the intravascular data, and step 1610 providing and / or guiding an object to an indicator of one or more locations of the registered extravascular data and / or intravascular data overlaid on the real-time extravascular data acquired and / or collected with a contrast agent (e.g., a variable contrast agent). In some cases, the real-time extravascular data acquired and / or collected with a contrast agent may be registered to one or more locations of the registered extravascular and intravascular data acquired and / or collected without a contrast agent. In some cases, the acquisition, detection, and / or collection of intravascular and extravascular data may occur simultaneously. In some cases, the intravascular and / or extravascular data acquired without contrast may be acquired in real time, as described elsewhere herein. In some cases, the one or more locations of the intravascular and / or extravascular data may include one or more regions, one or more segments, or a combination thereof, of the intravascular and / or extravascular data. In some cases, the intravascular data may be collected and / or detected using an intravascular imaging probe, as described elsewhere herein. In some cases, the object may include a stent, as described elsewhere herein.In some examples, providing and / or injecting the contrast agent into the subject's vascular network may include injecting and / or providing the contrast agent for less than about 1 second or less than about 2 seconds. In some examples, the contrast agent may be provided in up to about 2 events of providing and / or injecting the contrast agent into the subject's vascular network during the collection of real-time intravascular and / or extravascular data.

[0065] In some cases, method 1700 may include injecting and / or providing a contrast agent into the vascular network of the subject while directing, implanting, and / or providing an object to one or more locations of extravascular data and / or intravascular data, as shown in FIG. 17, and then collecting, acquiring, and / or detecting the intravascular and extravascular data while collecting, acquiring, and / or detecting real-time contrast-free extravascular data. In some cases, method 1700 may include step 1702 acquiring, detecting, and / or collecting extravascular data using a contrast agent, step 1704 identifying, determining, detecting, and / or segmenting one or more locations of the extravascular data, step 1706 acquiring, detecting, and / or collecting intravascular data while providing and / or injecting a contrast agent into the vascular network of the subject that corresponds to, correlates with, and / or matches the one or more locations of the extravascular data, step 1708 registering and / or correlating the one or more locations of the extravascular data with corresponding one or more locations of the intravascular data, and step 1710 providing and / or guiding an object to an indicator of the one or more locations of the registered extravascular data and / or endovascular data overlaid on the real-time extravascular data collected and / or acquired without the contrast agent. In some cases, the real-time extravascular data collected and / or acquired without the contrast agent may be registered to one or more locations of the registered extravascular and endovascular data collected and / or acquired with the contrast agent. In some cases, the acquisition, detection, and / or collection of intravascular and extravascular data may occur simultaneously. In some cases, the intravascular and / or extravascular data acquired using contrast may be acquired in real time, as described elsewhere herein. In some cases, the one or more locations of the intravascular and / or extravascular data may include one or more regions, one or more segments, or a combination thereof, of the intravascular and / or extravascular data. In some cases, the intravascular data may be collected and / or detected using an intravascular imaging probe, as described elsewhere herein. In some cases, the object may include a stent, as described elsewhere herein.In some examples, providing and / or injecting the contrast agent into the subject's vascular network may include injecting and / or providing the contrast agent for less than about 1 second or less than about 2 seconds. In some examples, the contrast agent may be provided in up to about 2 events of providing and / or injecting the contrast agent into the subject's vascular network during the collection of real-time intravascular and / or extravascular data.

[0066] 18, method 1800 may include steps of acquiring, obtaining, and / or detecting intravascular data and / or extravascular data without a contrast agent, and guiding, embedding, and / or providing an object to one or more locations of the extravascular data and / or intravascular data without a contrast agent. In some cases, method 1800 may include step 1802 of acquiring, detecting, and / or collecting extravascular data without a contrast agent, step 1804 of identifying, determining, detecting, and / or segmenting one or more locations of the extravascular data, step 1806 of acquiring, detecting, and / or collecting intravascular data without a contrast agent that corresponds to, correlates with, and / or matches the one or more locations of the extravascular data, step 1808 of registering and / or correlating the one or more locations of the extravascular data with corresponding one or more locations of the intravascular data, and step 1810 of providing and / or guiding an object to an indicator of the one or more locations of the registered extravascular data and / or intravascular data overlaid on the real-time extravascular data without a contrast agent. In some cases, real-time extravascular data without contrast may be registered and / or correlated with registered extravascular and intravascular data acquired without contrast. In some cases, the acquisition, detection, and / or collection of intravascular and extravascular data may occur simultaneously. In some cases, the intravascular and / or extravascular data acquired without contrast may be acquired in real time, as described elsewhere herein. In some cases, the one or more locations of the intravascular and / or extravascular data may include one or more regions, one or more segments, or a combination thereof, of the intravascular and / or extravascular data. In some cases, the intravascular data may be collected and / or detected using an intravascular imaging probe, as described elsewhere herein. In some cases, the object may include a stent, as described elsewhere herein.

[0067] In some cases, as shown in Figure 15A, previously registered locations of endovascular data registered to extravascular data may change or vary in location and / or spatial position over time (e.g., during real-time extravascular or intravascular data collection) as one or more locations of the extravascular data move spatially as a result of the subject's heartbeat, inspiration and expiration, or subject motion. In some cases, method 1400 (e.g., as shown in Figure 14) performed using a system described elsewhere herein can correct and / or adjust the location and / or position of registered endovascular data in real time, as shown in Figures 15B-D. In some cases, the method and system may adjust the position of the registered endovascular data in real time by determining 1402 an interpolated value between one or more positions of the extravascular data registered to the endovascular data from a first extravascular data set acquired at a first time point and a second extravascular data set acquired at a second time point, where the first time point precedes the second time point (e.g., between consecutive and / or subsequent extravascular data acquired in real time), and adjusting and / or modifying 1404 the location and / or position of the endovascular data by the interpolated value. In some cases, the adjustment and / or modification of the location and / or position of the endovascular data by the interpolated value may be performed in real time. In some cases, the interpolated value may include a translation of one or more positions of the extravascular data in at least one dimension, at least two dimensions, or at least three dimensions. In some cases, the translation value may include a value that modifies the position of the endovascular data by the first dimension and the second dimension. In some examples, the first dimension, the second dimension, and the third dimension may be orthogonal to one another. In some cases, a first extravascular data set (e.g., an extravascular image) acquired at a first time point may include a first interpolated value, and a second extravascular data set acquired at a second time point later after the first time point may include a different interpolated value. In some cases, the interpolated value may include a modified distance for one or more locations of the extravascular data.In some cases, the one or more locations of the extravascular data may include the location and / or spatial location of the guide catheter tip 1300, the primary guidewire tip 1306, the secondary guidewire tip 1302, the imaging catheter position marker 1304, the distal imaging catheter marker 1306, the guidewire path, the guidewire position, any other location of the extravascular data described elsewhere herein, or any combination thereof. In some cases, the one or more locations of the extravascular data may be determined automatically, for example, using one or more algorithms or predictive models, as described elsewhere herein. In some cases, the one or more locations of the extravascular data may be determined in real time.

[0068] User Interface Aspects of the systems of the present disclosure provided herein may include one or more view configurations (i.e., interface (UI)) 1116 that display on one or more monitors (102, 104) as shown in FIG. 1A, for example, one or more data views 300, including an extravascular data view (302), an intravascular data view (320, 304), as shown in FIGS. 3A-3C. The UI 1116 may be displayed on a flat screen panel or touchscreen display 1114. In some embodiments, the user interface 1116 may comprise a touchscreen interface that allows a user to tap the screen to select actions and / or interact with data. In some examples, the user interface 1116 may be operated or interacted with with a keyboard and / or mouse. In some examples, the user interface 1116 may be operated using separate hardware located near the end user and the patient.

[0069] The UI 1116 can display intravascular data, extravascular data, registered intravascular and extravascular data, or any combination thereof. The user interface can provide actionable information to guide medical personnel in diagnosing coronary artery disease. In some cases, the user interface may include a data view showing measured parameters of the distance between the imaging probe and an object superimposed on the registered intravascular and extravascular images. In some embodiments, the user interface 1116 may include one or more buttons (330, 306, 318), switches, editable dialog boxes, sliders, wireless communication buttons, or any combination thereof. In some examples, the user interface may include menus that allow a user to configure device parameters, such as scan speed, resolution, or any combination thereof, of the imaging system. The user interface may include function buttons that allow a user to switch between various views of the extravascular data with or without an overlay of objects and / or registered endovascular data. In some cases, the user interface may include function buttons that allow a user to scan, stop a scan, emergency stop a scan, pause a scan, resume a scan, or any combination thereof.

[0070] In some cases, the intravascular (320, 304) view may include a sagittal and / or circular cross-sectional view 320 and a longitudinal vessel cross-section 304. The circular cross-sectional view 320 may display the circular cross-sectional endovascular data and one or more annotations, for example, a user and / or machine determining a segment of the tissue region of interest 321, a center of the imaging probe, an overlaid biochemical signature indicator 332, or any combination thereof. In some examples, the circular cross-sectional view 320 may also display a measurement tool 322 configured to generate one or more measurement parameters. In some cases, when a user interacts (e.g., clicks, touches, and / or presses) with the measurement tool 322, the cursor or pointer can change to a measurement cursor or pointer, allowing the user to interact with the circular cross-sectional view 320 to measure one or more parameters 319 described elsewhere herein. In some cases, when a user interacts (e.g., clicks, touches, and / or presses) with the measurement tool 322, the system and one or more algorithms described elsewhere herein can automatically generate one or more measured parameters 319. The circular cross-sectional view 320 may display one or more measured parameters 319 of the blood vessel, such as the external elastic membrane (EEM) 321, lumen, stenosis, lumen area, or any combination thereof.

[0071] The longitudinal vessel cross-section view 304 can display the lumen contour of the vessel 308 as a function of vessel length. In some cases, the longitudinal vessel cross-section view may display a scale 323 of the intravascular data displayed within the data view. The longitudinal vessel cross-section view 304 may also include corresponding indicators of regions along the vessel length where one or more biochemical spectroscopic signals (310, 314), e.g., calcium, lipids, etc., have been detected. In some examples, a user can interact with the longitudinal vessel cross-section view 304 by scrubbing or scrolling with a cursor 315 along the length of the longitudinal cross-section view to display a circular or cross-sectional image corresponding to the cursor's position on the longitudinal cross-section view 320.

[0072] In some cases, one or more objects (312, 316, 325, 309) described elsewhere herein may be added and / or overlaid on the longitudinal vessel cross-section (304), as seen in Figures 3A-3C. In some examples, one or more objects (312, 316, 325, 309) may be added and / or overlaid by a user and / or a predictive model (e.g., a machine learning model and / or algorithm). The one or more objects may include a first object 312, a second object 316, a third object 325, a fourth object 309, or any combination thereof, as described elsewhere herein. A user can place one or more objects (312, 316, 325, 309) by clicking or tapping on an area of ​​the displayed imaged outline of the vessel 308 to display an object set dialog. By tapping and / or clicking one or more buttons of a view and / or view configuration, the user can then confirm the placement of one or more objects (312, 316, 325, 309). Annotations and / or markups of the circular cross-section 320 may be displayed on the longitudinal vessel cross-section 304. For example, line annotations of the cross-section 321 may be displayed as similar line annotations 309 in the longitudinal vessel cross-section 304, as shown in Figures 3B-3C. In some examples, the fourth object 309 may include an indicator of the location and / or area of ​​the vessel's external elastic membrane.

[0073] In some instances, the first object 312 may include a first visual indicator 328, and the second object 316 may include a second visual indicator 329. In some examples, the first visual indicator 328 and / or the second visual indicator 329 may display one or more measured parameters. The one or more measured parameters may include an external elastic membrane diameter, a lumen diameter, a lumen area, or any combination thereof. In some examples, the one or more measured parameters may be measured by a user and / or by one or more algorithms and / or predictive models of a system described elsewhere herein. In some examples, a minimum lumen area 331 may be determined and / or displayed along the longitudinal vessel cross-section 304. In some instances, the minimum lumen area 331 may be determined and / or set by a user, one or more algorithms and / or one or more predictive models of a system described elsewhere herein. In some cases, the distance between the first object 312 and the second object 316 may be determined by the user and / or the system (i.e., one or more algorithms and / or predictive models described elsewhere herein) and displayed on the longitudinal vessel cross-section 304. In some cases, the third object 325 may include a marker or indicia (e.g., a square or circle) superimposed on the longitudinal vessel cross-section 304. In some examples, the marker or indicia 325 may indicate a branching of the vessel.

[0074] In some cases, the extravascular data view 302 may display an overlay of one or more registered objects (324, 326, 327, 328, 333), as seen in FIGS. 3B-3C. In some cases, the registered one or more objects (324, 326, 327, 328, 333) may be configured by a user and / or a predictive model from the endovascular data and / or corresponding endovascular data views (304, 320). In some examples, the registered one or more objects may include a scan path traversed by an imaging probe, as described elsewhere herein, which may be displayed at a corresponding registered location of a blood vessel in the extravascular data view 302. In some examples, the registered one or more objects may be registered to the extravascular data and displayed in the extravascular data view 302 to track the movement of the subject as real-time extravascular data is displayed in the extravascular data view 302. In some cases, the registered one or more objects (327, 328) may include objects corresponding to the position of one or more biochemical spectroscopic signals (310, 314), e.g., calcium, lipids, etc., detected as shown in the longitudinal vessel cross-section 304. In some cases, the registered one or more objects (327, 328, 314, 310) may include different colored indicators, e.g., yellow corresponding to lipids and blue corresponding to calcium, as shown in FIGS. 3A-3C. In some examples, an object 326 of the registered one or more objects may include a corresponding marker or indicator 326 that corresponds to and / or correlates with a marker or indicator 325 displayed on the longitudinal vessel cross-section 304 described elsewhere herein. In some cases, the registered one or more objects may include an object 333 that corresponds to and / or is registered with the position and / or location of the first object 312 displayed on the longitudinal vessel cross-section 304. In some examples, the registered one or more objects may include an object 324 that corresponds to and / or is registered with the position and / or location of the second object 316 displayed in the longitudinal vessel cross-section 304.

[0075] In some cases, the user interface may comprise one or more view configurations (i.e., user interfaces), as shown in FIGS. 7A-10. In some cases, the one or more view configurations (700, 716, 724) may include one or more data views (710, 712, 714, 726), e.g., extravascular data views and / or endovascular data views, with one or more user interface elements (702, 704, 706, 708) (e.g., buttons or tabs) that, upon activation, switch between, e.g., the first view configuration 700, the second view configuration 716, or the third view configuration 724. In some cases, the one or more user interface elements may correspond to one or more view configurations of one or more subjects and / or patients imaged using the systems and methods described elsewhere herein. In some examples, the one or more view configurations may comprise the same number, arrangement, size, or any combination thereof, of data views, as seen in FIGS. 7A-7B. In some cases, one or more view configurations may include a different number, arrangement, size, or any combination thereof, of data views 726, as seen in FIG. 7C, compared to the data views (710, 712, 714) shown in FIG. 7A.

[0076] In some examples, the user interface may include one or more data views capable of displaying data, e.g., extravascular data, endovascular data, or a combination thereof, as described elsewhere herein. In some cases, the user interface 800 may include one or more data views (802, 804, 806, 808) that display a single type of data (812, 814, 820), as shown in FIGS. 8A-8B. In some examples, one or more data views may display a single type of data, e.g., extravascular data from one or more imaging perspectives. For example, a first data view (802, 812) of the one or more data views may display macroscopic extravascular data collected, e.g., by x-ray angiography. A second data view (804, 814) of the one or more data views may display a zoomed-in portion of the first data view (802, 812). In some cases, a user and / or a predictive model and / or machine learning model implemented by a system described elsewhere herein may select a region of interest 826 in the first data view (802, 812), which may be displayed in the second data view (804, 814). In some examples, the region of interest 826 may be dynamically adjusted and / or moved across the first data view (802, 812), and the corresponding display of the second data view (804, 814) may be updated accordingly based on the adjusted region of interest 826. In some cases, one or more data views may comprise a third data view (820, 806). The third data view (820, 806) may display a cross-sectional imaging perspective of the first and / or second data views (802, 812 and 804, 814). In some examples, the region of interest 826 in the first data view (802, 812) may be displayed in the third data view (824, 816). In some cases, adjusting the region of interest 826 in the first data view (802, 812) may adjust the corresponding data displayed in the third data view (824, 816) according to the adjusted area covered by the region of interest.In some cases, the fourth data view 808 may display intravascular data, extravascular data, measurements, or any combination thereof, as described elsewhere herein, in the form of a graphical representation (e.g., to reduce display overlay on other data views).

[0077] In some examples, for example, the second data view 1004 of one or more data views (1002, 1104, 1012, 1020) may include one or more objects and / or annotations of the registered intravascular and extravascular data (1006, 1108, 1010), as seen in view configuration 1000 of FIG. 10 . In some cases, the one or more objects and / or annotations of the registered intravascular and extravascular data may include the path of the imaging probe and / or medical device 1006, the first object 1008, the second object 1010, or any combination thereof. In some cases, the third data view 1012 of the extravascular and / or endovascular data may include one or more objects and / or annotations (1014, 1018) that correspond to the one or more objects and / or annotations (1006, 1008, 1010) of the second data view 1004. In some cases, one or more objects and / or annotations in the second data view 1004 may be adjusted by a user and / or a predictive model and / or algorithm described elsewhere herein, and the corresponding adjusted one or more objects and / or annotations displayed in the second data view may be updated in a corresponding manner as shown in the third data view 1012. In some cases, one or more objects and / or annotations (1014, 1018) displayed in the third data view may be adjusted and / or moved by a user and / or a predictive model and / or algorithm (e.g., a machine learning algorithm), where after adjusting one or more objects and / or annotations, the corresponding positions of one or more objects and / or annotations (1006, 1008, 1010) may be adjusted as displayed in the second data view 1004. In some cases, the fourth data view 1020 may display endovascular data, extravascular data, measurements, or any combination thereof, as described elsewhere herein, in the form of a graphical representation (e.g., to reduce overlay of displays on other data views).

[0078] In some cases, one or more monitors of a system described elsewhere herein can display one or more view configurations (900, 916), as seen in FIGS. 9A-9B. In some cases, the one or more monitors can include a first monitor 900 having a first view configuration comprised of one or more data views (910, 912, 914) and a second monitor 916 having a second view configuration comprised of one or more data views (918, 920). In some cases, the first view configuration and the second view configuration can be the same. In some examples, the first view configuration and the second view configuration can be different. In some examples, the first data view configuration can include one or more user interface elements (902, 904, 906, 908) described elsewhere herein, while the second data view configuration 916 does not. In some examples, the first monitor and first view configuration may be utilized by a device operator, nurse, scrub technician, and / or other medical personnel not performing the medical procedure, i.e., not the attending physician and / or doctor guiding the imaging probe and / or medical device through the blood vessel as described elsewhere herein. In some cases, the second monitor display may be a guide for the attending physician and / or doctor when performing the imaging procedure. In some examples, the second view configuration 916 may include one or more views of extravascular data, endovascular data, or a combination thereof. In some cases, one or more data views (918, 920) may include the same type of data. In some examples, one or more data views may include different types of data. In some cases, one or more data views may display data with registered endovascular data (922, 924, 926) and extravascular data 920, as shown in FIG. 9B. In some cases, the registered intravascular data (922, 924, 926) may include the scan path of the imaging probe 922 and / or one or more objects (924, 926) described elsewhere herein.

[0079] definition Unless otherwise defined, all terminology, notations, and other technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the claimed subject matter belongs. In some cases, terms having commonly understood meanings are defined herein for clarity and / or ready reference, and the inclusion of such definitions herein should not necessarily be construed as representing a substantial departure from what is commonly understood in the art.

[0080] Throughout this application, various embodiments may be presented in a range format. It should be understood that the range format is for convenience and brevity only and should not be construed as an inflexible limitation on the scope of the present disclosure. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges and individual numerical values ​​within that range. For example, the description of a range such as 1 to 6 should be considered to have specifically disclosed subranges such as 1 to 3, 1 to 4, 1 to 5, 2 to 4, 2 to 6, and 3 to 6, as well as individual numerical values ​​within that range, such as 1, 2, 3, 4, 5, and 6. This applies regardless of the broadness of the range.

[0081] As used in this specification and claims, "a," "an," and "the" include plural references unless the content clearly dictates otherwise. For example, the term "sample" includes multiple samples, including mixtures thereof.

[0082] "Determining," "measuring," "evaluating," "assessing," "assaying," and "analyzing" are often used interchangeably herein to refer to forms of measurement. The terms include determining whether an element is present (e.g., detecting). These terms can include quantitative, qualitative, or quantitative and qualitative determinations. Evaluating can be relative or absolute. "Detecting the presence of" can include determining the amount of something present, in addition to determining whether something is present or absent, depending on the context.

[0083] The terms "subject," "individual," "patient," or "subject" are often used interchangeably herein. A "subject" can be a biological entity containing expressed genetic material. The biological entity can be, for example, a plant, an animal, or a microorganism, including bacteria, viruses, fungi, and protozoa. A subject can be tissues, cells, and their progeny of a biological entity obtained in vivo or cultured in vitro. A subject can be a mammal. A mammal can be a human. A subject can also be diagnosed or suspected of being at high risk for a disease. In some cases, a subject is not necessarily diagnosed or suspected of being at high risk for a disease.

[0084] The term "in vivo" is used to describe events that occur in a subject's body. "Ex vivo" is used to describe events that occur outside of a subject's body. An ex vivo assay is not performed on a subject. Rather, it is performed on a sample separate from the subject. An example of an ex vivo assay performed on a sample is an "in vitro" assay. The term "in vitro" is used to describe events that occur in a container that holds laboratory reagents such that the reagents are separate from the biological source from which the material was obtained. In vitro assays can include cell-based assays in which live or dead cells are utilized. In vitro assays can also include cell-free assays in which intact cells are not utilized.

[0085] As used herein, a number followed by the term "about" refers to a number that is plus or minus 10% of that number. A range followed by the term "about" refers to a range of minus 10% of the minimum value and plus 10% of the maximum value.

[0086] The use of absolute or sequential terms, such as "will," "will not," "shall," "shall not," "must," "must not," "first," "initially," "next," "sequently," "before," "after," "lastly," and "finally," is intended to be illustrative and not limiting of the scope of the embodiments disclosed herein.

[0087] Any systems, methods, software, compositions, and platforms described herein are modular and not limited to sequential processes, and therefore terms such as "first" and "second" do not necessarily imply a priority, order of importance, or sequence of actions.

[0088] As used herein, the terms "treatment" or "treating" are used in reference to a pharmaceutical or other interventional regimen to obtain a beneficial or desired result in a recipient. Beneficial or desired results include, but are not limited to, therapeutic benefit and / or prophylactic benefit. A therapeutic benefit may also refer to the eradication or amelioration of the condition or underlying disease being treated. Similarly, a therapeutic benefit may be achieved by the eradication or amelioration of one or more physiological symptoms associated with an underlying disease, such that an improvement in the subject is observed, even though the subject may still be suffering from the underlying disease. A prophylactic effect includes delaying, preventing, or eliminating the appearance of a disease or condition, delaying or eliminating the onset of symptoms of a disease or condition, slowing, halting, or reversing the progression of a disease or condition, or any combination thereof. With regard to prophylactic benefit, subjects at risk of developing a particular disease or reporting one or more physiological symptoms of a disease can receive treatment even if a diagnosis of the disease has not been made. The section headings used herein are for organizational purposes only and should not be construed as limiting the subject matter described. [Example]

[0089] Example 1: Registration between extravascular data without contrast and intravascular data with variable use of contrast during cardiovascular stent placement

[0090] The methods and systems of the present disclosure, as described elsewhere herein, can register extravascular and intravascular data without or with variable use of contrast agent when acquiring real-time extravascular and intravascular data. Variable use of contrast agent includes providing and / or injecting contrast agent (i.e., one puff of contrast agent) for less than about 1 second or less than about 2 seconds between up to about two events of providing and / or injecting contrast agent into the subject's vascular network during collection of real-time extravascular data, as described elsewhere herein.

[0091] Injecting and / or providing a variable amount of contrast agent can be used during registration of extravascular and intravascular data during a cardiovascular stent placement procedure in a subject. An example of such a procedure includes acquiring, collecting, and / or detecting real-time extravascular data (e.g., angiographic fluoroscopy data) of one or more locations of the extravascular data (e.g., the location of a non-contrast object, such as a guidewire tip, as described elsewhere herein) without the use of contrast agent, and acquiring, collecting, and / or detecting real-time intravascular data (e.g., intravascular OCT and / or near-infrared spectroscopy data) by rotating and translating an integrated intravascular OCT and near-infrared spectroscopy probe, where the location and / or position of the probe can be determined without the use of contrast agent. The method includes determining and / or detecting in the extravascular data based on at least imaging markers of the probe visualized in the extravascular data, registering and / or correlating one or more locations in the extravascular data with corresponding one or more locations in the intravascular data, and guiding and placing an object (e.g., a cardiovascular stent) at the one or more location indicators in the registered intravascular and / or extravascular data overlaid on real-time extravascular data collected and / or acquired while providing or injecting a variable amount of contrast agent into the subject's vascular network to visualize vascular morphology and stent placement. Such exemplary use of a variable contrast agent reduces overall contrast agent usage and potential side effects of using a typical amount of contrast agent on a subject undergoing guided angiography using fluoroscopy.

[0092] Example 2: Registration between contrast-filled extravascular data and contrast-free intravascular data during cardiovascular stent placement

[0093] The disclosed methods and / or systems described elsewhere herein can register extravascular and intravascular data without or with variable use of contrast agent when acquiring real-time extravascular data. Variable use of contrast agent includes providing and / or injecting contrast agent (i.e., one puff of contrast agent) for less than about 1 second or less than about 2 seconds between up to about two events of providing and / or injecting contrast agent into the subject's vascular network during collection of real-time extravascular data, as described elsewhere herein.

[0094] Injecting and / or providing variable amounts of contrast agent can be used during registration of extravascular and intravascular data during a cardiovascular stent placement procedure in a subject. Examples of such procedures include acquiring, collecting, and / or detecting extravascular data (e.g., angiographic fluoroscopy data) of one or more locations in the extravascular data (e.g., locations of non-contrast objects such as the tip of a guidewire, as described elsewhere herein) using a contrast agent; acquiring, collecting, and / or detecting intravascular data (e.g., intravascular OCT and / or near-infrared spectroscopy data) by rotating and translating an integrated intravascular OCT and near-infrared spectroscopy probe, wherein the location and / or position of the probe is determined and / or detected in the extravascular data based on at least imaging markers of the probe visualized in the extravascular data using a contrast agent; registering and / or correlating the one or more locations in the extravascular data with corresponding one or more locations in the intravascular data; and using the real-time extravascular data without a contrast agent to guide the procedure and / or place an object (e.g., a cardiovascular stent) relative to an indication of the one or more locations in the registered extravascular and / or intravascular data overlaid on the real-time extravascular data. Such exemplary use of a variable contrast agent during the real-time portion of the procedure reduces the overall use of contrast agent and the potential side effects of using a typical amount of contrast agent for a subject undergoing fluoroscopically guided angiography.

[0095] Example 3: Registration between extravascular data without contrast and intravascular data without contrast during cardiovascular stent placement

[0096] The disclosed methods and / or systems described elsewhere herein can acquire and / or register extravascular and intravascular data without the use of contrast agents, which can then be used to guide the placement of an object (e.g., a cardiovascular stent) without the need for contrast agents (e.g., during real-time acquisition of the extravascular data).

[0097] An example of such a procedure includes acquiring, collecting, and / or detecting extravascular data (e.g., angiographic fluoroscopy data) of one or more locations of the extravascular data (e.g., the location of an object, such as a guidewire tip, as described elsewhere herein) without the use of contrast; and acquiring, collecting, and / or detecting intravascular data (e.g., intravascular OCT and / or near-infrared spectroscopy data) by rotating and translating an integrated intravascular OCT and near-infrared spectroscopy probe, where the location and / or position of the probe is at least one image of the probe visualized in the extravascular data without the use of contrast. and determining and / or detecting in the extravascular data based on the image markers, acquiring the real-time extravascular data without the use of contrast, registering and / or correlating one or more locations in the extravascular data with corresponding one or more locations in the endovascular data collected and / or acquired without the use of contrast, and guiding the procedure and / or placing an object (e.g., a cardiovascular stent) at one or more location indicators of the registered one or more locations in the extravascular and / or endovascular data overlaid on the real-time extravascular data collected and / or acquired without the use of contrast. Such contrast-free use examples are provided elsewhere herein to illustrate the methods of the present disclosure, whereby any potential side effects from the use of contrast are not noted in a subject undergoing fluoroscopically guided angiography.

[0098] Although the steps of the methods described elsewhere herein are described in sequential order as described elsewhere herein, those skilled in the art will recognize many variations based on the teachings set forth herein. Steps may be completed in a different order. Steps may be added or omitted. Some of the steps may include substeps. Many of the steps may be repeated as frequently as is useful. One or more of the steps of the methods described elsewhere herein may be acted upon or completed simultaneously. One or more of the steps of the methods may be performed using one or more circuitry as described herein, e.g., a processor or logic circuitry of a computer system or processing architecture.

[0099] While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. It is not intended that the present invention be limited by the specific examples provided within the specification. While the present invention has been described with reference to the foregoing specification, the description and illustration of the embodiments herein are not meant to be construed in a limiting sense. Numerous variations, changes, and substitutions will occur to those skilled in the art without departing from the invention. Furthermore, it will be understood that all aspects of the present invention are not limited to the specific depictions, configurations, or relative proportions set forth herein, which depend upon a variety of conditions and variables. It will be appreciated that various alternatives to the embodiments of the present invention described herein may be utilized in practicing the invention. It is therefore contemplated that the present invention also encompasses such alternatives, modifications, variations, or equivalents. The following claims define the scope of the invention, and it is intended that methods and structures within the scope of these claims and their equivalents be covered thereby.

Claims

1. 1. A method for displaying an object, said method comprising: acquiring intravascular and extravascular data; determining features in the endovascular data and features in the extravascular data; registering the features in the endovascular data and the features in the extravascular data; and displaying the object relative to the registered features in the intravascular data or the registered features in the extravascular data, wherein the object is overlaid on a display of real-time extravascular data.

2. The method of claim 1 , wherein the features in the endovascular data or the features in the extravascular data are manually selected.

3. The method of claim 1 , wherein the features in the intravascular data include locations within the intravascular data and the features in the extravascular data include locations within the extravascular data.

4. The method of claim 3 , wherein the location within the endovascular data and the location within the extravascular data are selected automatically.

5. 2. The method of claim 1, wherein the objects comprise a first object and a second object, the first object and the second object being displayed relative to a registered location in the intravascular data or a registered location in the extravascular data.

6. The method of claim 1 further comprising determining a location to guide the location of the foreign body.

7. The method of claim 1 , wherein the intravascular data includes at least one image.

8. The method of claim 1 , wherein the extravascular data includes at least one image.

9. The method of claim 1 , wherein the locations within the intravascular data, the locations within the extravascular data, the locations that guide the location of the foreign body, or any combination thereof, are determined by a predictive model.

10. The method of claim 9 , wherein the predictive model comprises a machine learning model.

11. The method of claim 10 , wherein the machine learning model comprises a neural network algorithm.

12. The method of claim 1 , further comprising guiding a catheter through a coronary artery to the object to treat coronary artery disease.

13. The method of claim 12 , wherein the catheter comprises an atherectomy catheter.

14. The method of claim 1 , further comprising guiding a catheter through a coronary artery to the object to diagnose coronary artery disease.

15. The method of claim 14 , wherein the catheter comprises a catheter for measuring fractional flow reserve of the coronary artery.

16. 10. The method of claim 1, wherein the intravascular data comprises optical coherence tomography (OCT), intravascular ultrasound (IVUS), photoacoustics (PA), near-infrared spectroscopy (NIRS), fluorescence, autofluorescence (AF), or any combination of such data.

17. The method of claim 1 , wherein the intravascular data is detected by a multimodal imaging system.

18. The method of claim 17 , wherein the multi-modal imaging system comprises an integrated OCT and NIRS imaging system.

19. The method of claim 1 , wherein the intravascular data is detected by a one-dimensional sensing system.

20. The method of claim 19 , wherein the one-dimensional sensing system comprises a pressure sensing system.

21. The method of claim 1 , wherein the intravascular data includes a measurement of flow rate.

22. 10. The method of claim 1, wherein the real-time extravascular data is streamed directly from the x-ray system without transfer over a network to a processing unit configured to display the object superimposed on a display of the real-time extravascular data.

23. 4. The method of claim 3, wherein the location within the intravascular data, the location within the extravascular data, or the location for guiding the location of a foreign body comprises the location of a blood vessel, any representation of a vascular network, a side branch of a blood vessel, an area for deploying a stent, coronary plaque, a guidewire, a guide catheter, a stent, a distal or proximal location of an intravascular imaging pullback, a balloon, a valve, a clip, an atherectomy device, an intravascular data device, or any combination thereof.

24. The method of claim 1 , wherein the extravascular data comprises x-ray, CT, magnetic resonance, ultrasound, fluoroscopy, or any combination of these data.

25. 4. The method of claim 3, further comprising measuring cardiac cycle data from an external ECG signal, intravascular data, extravascular data, or any combination thereof, wherein the cardiac cycle data is used to improve accuracy of registration of the location in the intravascular data and the location in the extravascular data to the real-time extravascular data.

26. The method of claim 3 , wherein the locations within the extravascular data are derived from a priori selection, annotations, or any combination thereof from previous patient records.

27. The method of claim 1 , wherein the object includes a fiducial marker, the spatial position of the fiducial marker being adjusted to account for motion artifacts when the real-time extravascular data is displayed.

28. 28. The method of claim 27, further comprising removing the motion artifact from the extravascular data.

29. The method of claim 1 , further comprising measuring a distance from the catheter to the object.

30. 30. The method of claim 29, wherein the measured distance from the catheter to the object is displayed in real time using a visual representation.

31. The method of claim 1 , wherein the reference location in the extravascular data is a feature not represented in the intravascular data.

32. 32. The method of claim 31, wherein the reference location comprises a radiopaque marker on a catheter.

33. 32. The method of claim 31, wherein the reference location comprises a known correlation to the intravascular data.

34. 34. The method of claim 33, wherein the known correlation comprises a distance.

35. The method of claim 5 , wherein the first object or the second object is overlaid on the real-time extravascular data in one or more data views.

36. 36. The method of claim 35, wherein a first view of the one or more data views includes a display of the real-time extravascular data without a display of the first object or the second object, and a second view of the one or more data views includes a display of the real-time extravascular data with a display of the first object or the second object.

37. 36. The method of claim 35, wherein the one or more views of data include a zoom view.

38. 6. The method of claim 5, wherein the display of the first object or the second object relative to the registered location in the intravascular data or the registered location in the extravascular data includes a first state in which the display of the first object or the second object is visible, or a second state in which the display of the first object or the second object is not visible.

39. 36. The method of claim 35, wherein a representation of the first object or the second object superimposed on the real-time extravascular data is displayed on one or more monitors.

40. 40. The method of claim 39, wherein the one or more monitors include an internal monitor positioned to face an operator of a medical device, an external monitor positioned to face a medical professional using the medical device, or any combination of these monitor configurations.

41. 41. The method of claim 40, wherein the internal monitor and the external monitor include different view configurations.

42. 40. The method of claim 39, wherein the one or more monitors include at least two external monitors positioned to face a medical professional using a medical device, the at least two external monitors including different view configurations.

43. The method of claim 1 , further comprising displaying an indicator, the indicator comprising a metric representing a distance between the object and a target location within the real-time extravascular data.

44. 44. The method of claim 43, wherein the target location is determined by at least one intravascular image or at least one extravascular image.

45. 36. The method of claim 35, further comprising processing vascular geometry of the extravascular data and displaying the processed vascular geometry within a view of the one or more data views.

46. The method of claim 1 , wherein the extravascular data or the intravascular data is acquired without or with variable use of contrast agents.

47. 10. The method of claim 1, further comprising: displaying an object relative to a feature of an endovascular data set or a feature of extravascular data, wherein the feature of the endovascular data set and the feature of the extravascular data are registered to real-time extravascular data, and the object is overlaid on a display of the real-time extravascular data.

48. 48. The method of claim 47, wherein the features in the endovascular data include locations within the endovascular data set and the features of the extravascular data include locations within the extravascular data.

49. 49. The method of claim 48, wherein the location within the intravascular data and the location within the extravascular data are selected automatically.

50. 49. The method of claim 48, wherein the objects comprise a first object and a second object, the first object and the second object being displayed relative to a registered location in the intravascular data or a registered location in the extravascular data.

51. 51. The method of claim 50, further comprising determining a position between the first object and the second object to guide stent placement.

52. 48. The method of claim 47, wherein the intravascular data includes at least one image.

53. 48. The method of claim 47, wherein the extravascular data includes at least one image.

54. 51. The method of claim 50, wherein the location within the intravascular data, the location within the extravascular data, the location between the first object and the second object, or any combination thereof, is determined by a predictive model.

55. 55. The method of claim 54, wherein the predictive model comprises a machine learning model.

56. 56. The method of claim 55, wherein the machine learning model comprises a neural network algorithm.

57. 48. The method of claim 47, further comprising guiding a catheter through a coronary artery to the object to treat coronary artery disease.

58. 58. The method of claim 57, wherein the catheter comprises an atherectomy catheter.

59. 48. The method of claim 47, further comprising guiding a catheter through a coronary artery to the object to diagnose coronary artery disease.

60. 60. The method of claim 59, wherein the catheter comprises a catheter for measuring fractional flow reserve of the coronary artery.

61. 48. The method of claim 47, wherein the intravascular data comprises optical coherence tomography (OCT), intravascular ultrasound (IVUS), photoacoustics (PA), near-infrared spectroscopy (NIRS), or any combination of such data.

62. 48. The method of claim 47, wherein the intravascular data is detected by a multimodal imaging system.

63. 63. The method of claim 62, wherein the multi-modal imaging system comprises an integrated OCT and NIRS imaging system.

64. 48. The method of claim 47, wherein the intravascular data is detected by a one-dimensional sensing system.

65. 65. The method of claim 64, wherein the one-dimensional sensing system comprises a pressure sensing system.

66. 48. The method of claim 47, wherein the intravascular data includes a measurement of flow rate.

67. 48. The method of claim 47, wherein the real-time extravascular data is streamed directly from the x-ray system without transfer over a network to a processing unit configured to display the object superimposed on a display of the real-time extravascular data.

68. 55. The method of claim 54, wherein the location within the intravascular data, the location within the extravascular data, or the location between the first object and the second object comprises the location of a side branch of a blood vessel, an area for deploying a stent, coronary plaque, a guidewire, a guide catheter, a stent, a distal or proximal location of an intravascular imaging pullback, a balloon, a valve, a clip, an atherectomy device, an intravascular data device, or any combination thereof.

69. 48. The method of claim 47, wherein the extravascular data comprises x-ray, CT, magnetic resonance, ultrasound, fluoroscopy, or any combination thereof image data.

70. 49. The method of claim 48, further comprising measuring cardiac cycle data from an external ECG signal, intravascular data, extravascular data, or any combination thereof, wherein the cardiac cycle data is used to improve accuracy of registration of the location in the intravascular data and the location in the extravascular data to the real-time extravascular data.

71. 49. The method of claim 48, wherein the locations within the extravascular data are derived from a priori selection, annotations, or any combination thereof from previous patient records.

72. 48. The method of claim 47, wherein the object includes a fiducial marker, the spatial position of the fiducial marker being adjusted to account for motion artifacts when the real-time extravascular data is displayed.

73. 28. The method of claim 27, further comprising removing the motion artifact from the extravascular data.

74. 48. The method of claim 47, further comprising measuring the distance from the catheter to the object.

75. 75. The method of claim 74, wherein the distance from the catheter to the object is displayed in real time using a visual representation.

76. 48. The method of claim 47, wherein the reference location in the extravascular data is a feature not represented in the intravascular data.

77. 77. The method of claim 76, wherein the reference location comprises a radiopaque marker on a catheter.

78. 77. The method of claim 76, wherein the reference location comprises a known correlation to the intravascular data.

79. 79. The method of claim 78, wherein the known correlation comprises a distance.

80. 51. The method of claim 50, wherein the first object or the second object is displayed overlaid on the real-time extravascular data in one or more data views.

81. 81. The method of claim 80, wherein a first view of the one or more data views includes a display of the real-time extravascular data without a display of the first object or the second object, and a second view of the one or more data views includes a display of the real-time extravascular data with a display of the first object or the second object.

82. 81. The method of claim 80, wherein the one or more views of data include a zoom view.

83. 51. The method of claim 50, wherein the display of the first object or the second object relative to the location in the intravascular data or the location in the extravascular data includes a first state in which the display of the first object or the second object is visible, or a second state in which the display of the first object or the second object is not visible.

84. 51. The method of claim 50, wherein a representation of the first object or the second object superimposed on the real-time extravascular data is displayed on one or more monitors.

85. 85. The method of claim 84, wherein the one or more monitors include an internal monitor positioned to face an operator of a medical device, an external monitor positioned to face a medical professional using the medical device, or any combination of these configurations.

86. 86. The method of claim 85, wherein the internal monitor and the external monitor include different view configurations.

87. 85. The method of claim 84, wherein the one or more monitors include at least two external monitors positioned to face a medical professional using a medical device, the at least two external monitors including different view configurations.

88. 48. The method of claim 47, further comprising displaying an indicator, the indicator comprising a metric representing a distance between the object and a target location within the real-time extravascular data.

89. 90. The method of claim 88, wherein the target location is determined by at least one intravascular image or at least one extravascular image.

90. 81. The method of claim 80, further comprising processing vascular geometry of the extravascular data and displaying the processed vascular geometry within a view of the one or more data views.

91. 48. The method of claim 47, wherein the extravascular or intravascular data is acquired without contrast or with a variable contrast agent.

Images