Assessment of coronary blood flow and microvasculature using pressure wire and pressure dilution curves

Abstract

The present disclosure provides a system and method for determining the mean transit time of blood through a blood vessel using pressure measurements collected by an intravascular tool, without relying on temperature measurements. The intravascular tool can collect multiple pressure measurements distal to an area of ​​interest within the blood vessel as a bolus passes through the blood vessel and past the tool. The multiple pressure measurements can be plotted on a pressure dilution curve. The pressure dilution curve and a function of time are used to determine the mean transit time of blood through the blood vessel.

Description

[Technical Field]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application claims the benefit of the filing date of U.S. Provisional Patent Application No. 63 / 477,878, filed December 30, 2022, entitled "Methodology for Assessing Coronary Flow and Microvascular System Through Pressurewires -- Pressure Dilution Curve," the disclosure of which is incorporated herein by reference. [Background technology]

[0002] To identify a patient's microvascular resistance, one or more data acquisition systems may be required. For example, physicians can use pressure wire, angiography, intravascular imaging, etc. to collect data to identify microvascular disease. Angiography can provide insight into what is happening within the entire heart, while pressure wire can provide certain data measurements within the blood vessels.

[0003] The mean transit time, which corresponds to the flow rate of blood through a vessel, is calculated by passing a bolus of chilled saline through the vessel. The temperature of the bolus is measured as it passes proximal and distal temperature sensors on a pressure wire. This pressure wire is inserted separately from an optical coherence tomography (OCT) catheter. A thermodilution curve is then plotted based on the temperature of the bolus as it passes the temperature sensors, providing an indication of the flow rate, or mean transit time. However, this requires additional steps and equipment that can be cumbersome and dangerous in practice. Summary of the Invention

[0004] The present disclosure generally relates to systems and methods for determining mean transit time using a pressure dilution curve. The pressure dilution curve can be derived from pressure measurements obtained using an intravascular device. For example, the intravascular device can be a pressure wire, a catheter, or an intravascular imaging probe with pressure sensing capabilities. According to some examples, the intravascular imaging probe can be an OCT probe, a micro-OCT probe, a near-infrared spectroscopy ("NIRS") sensor, or an intravascular ultrasound ("IVUS") probe. The mean transit time can be a flow rate in a blood vessel.

[0005] The intravascular device can be inserted into the blood vessel at a location distal to the area of ​​interest. The intravascular device can have a distal opening that connects to an external pressure transducer. The intravascular device can have an incompressible fluid column, such as contrast agent, saline, or any suitable blood-compatible fluid. The intravascular device can take multiple pressure readings at the distal opening as it advances through the blood vessel to the area of ​​interest. The system can use these pressure readings to determine and / or create a pressure dilution curve. The pressure dilution curve can be used to determine the mean transit time through the blood vessel. In some examples, the pressure dilution curve can yield other downstream flow indices, such as coronary flow reserve ("CFR"), index of microcirculatory resistance ("IMR"), etc.

[0006] One aspect of the present disclosure includes a method including the steps of: one or more processors receiving intravascular data of a blood vessel, the intravascular data including a plurality of pressure measurements at a location within the blood vessel collected by an intravascular device; and the one or more processors determining a mean transit time of blood through the blood vessel based on the plurality of pressure measurements, the determining step being independent of a temperature measurement of the blood vessel.

[0007] The method may further include the step of the one or more processors determining the mean transit time by determining the ratio of the integral of a given average pressure measurement multiplied by the time for the given average pressure measurement to the integral of the given average pressure measurement.

[0008] The method may further include the one or more processors determining an average pressure measurement based on the plurality of pressure measurements, and the one or more processors creating a distribution curve based on the determined average pressure measurement.

[0009] The method may further include providing for display one or more indicators of blood flow based on the determined mean transit time, The indicators of blood flow may include at least one of a numerical value, a color, a graphic, and an animation.

[0010] The method may further include determining a mean transit time of blood through a vessel based on the distribution curve.

[0011] The method may further include the one or more processors determining the mean transit time by using a ratio of the integral of a given average pressure measurement multiplied by the time for the given average pressure measurement to the integral of the given average pressure measurement.

[0012] The method may further include the one or more processors being configured to determine at least one of a coronary flow reserve (CFR) value or an index of microvascular resistance (IMR) value based on the determined mean transit time.

[0013] In the method, when determining the average pressure measurement, the one or more processors are further configured to use multiple intravascular data over multiple periods including pressure readings before, during, and after the intravascular device reaches a location within the blood vessel.

[0014] The method may further include one or more processors determining an averaged pressure waveform by identifying an initial pressure measurement of the plurality of pressure measurements as the intravascular device advances into the area of ​​interest.

[0015] The method may further include the intravascular device being one of a pressure wire, an intravascular imaging tool, and a catheter. The intravascular imaging tool may be an optical coherence tomography (OCT) probe or an intravascular ultrasound (IVUS) probe.

[0016] The intravascular device may have pressure sensing capabilities with a pressure transducer connected to the pressure assessment port.

[0017] Another aspect of the present disclosure includes a system including one or more processors that accept a plurality of pressure measurements at a location within a blood vessel, wherein the one or more processors are capable of determining a mean transit time of blood through the blood vessel based on the plurality of pressure measurements, the determination being independent of a temperature measurement of the blood vessel.

[0018] The system may further include an intravascular device in communication with the one or more processors and configured to collect a plurality of pressure measurements.

[0019] The one or more processors may be further configured to determine at least one of a CFR value or an IMR value based on the mean transit time.

[0020] The one or more processors may be further configured to determine an average pressure measurement and to generate a distribution curve based on the determined average pressure measurement. Additionally, the one or more processors may determine a mean transit time of blood through the vessel based on the distribution curve.

[0021] The system may further comprise one or more of the one or more processors determining the mean transit time by determining the ratio of the integral of a given average pressure measurement multiplied by the time for the given average pressure measurement to the integral of the given average pressure measurement.

[0022] The one or more processors can be configured to use multiple intravascular data over multiple periods including pressure readings before, during, and after the intravascular device reaches a location within the blood vessel. The one or more processors can be configured to integrate the distribution curve when determining the mean transit time.

[0023] The intravascular device can be either a pressure wire with pressure sensing capabilities, a catheter, or an intravascular imaging tool, which can be an OCT probe or an IVUS probe with a purge port.

[0024] The system may further comprise an intravascular device that collects a plurality of pressure measurements distal to the area of ​​interest within the blood vessel.

[0025] The system may further comprise a column of fluid within the intravascular device, the fluid being either saline, contrast medium, or a blood-compatible fluid.

[0026] Another aspect of the present disclosure relates to a pressure sensing catheter comprising: a hypotube for delivering a blood-compatible fluid to a target area of ​​a blood vessel; an outer member having a proximal end and a distal end, the proximal end of the outer member being secured to the hypotube; an inner member having a proximal end and a distal end, the proximal end of the inner tube being secured to the outer member; and at least one opening at the distal end of the outer member that allows for measurement of pressure at a location within the blood vessel.

[0027] The pressure sensing catheter may further comprise one or more processors connected to the pressure sensing catheter, the one or more processors performing the steps of accepting pressure measurements and determining a mean transit time of blood through the blood vessel based on the plurality of pressure measurements, the determining step being independent of the temperature measurements.

[0028] The pressure sensing catheter can be connected to a pressure transducer in fluid communication with at least one opening in the distal end of the outer member.

[0029] The pressure sensing catheter may further be connected to one or more processors that determine at least one of a CFR value or an IMR value based on the determined mean transit time.

[0030] The pressure sensing catheter can be further connected to one or more processors that determine average pressure measurements and generate a distribution curve based on the determined average pressure measurements, and the one or more processors can determine a mean transit time of blood through the vessel based on the distribution curve.

[0031] The pressure sensing catheter may further be connected to one or more processors that determine the ratio of the integral of a given average pressure measurement multiplied by the time of the given average pressure measurement to the integral of the given average pressure measurement.

[0032] The pressure sensing catheter can be connected to one or more processors further configured to determine an average pressure measurement by using multiple intravascular data over multiple periods, including pressure readings before, during, and after the intravascular device reaches a location within the blood vessel.

[0033] The pressure sensing catheter may be connected to one or more processors further configured to integrate the distribution curve when determining the mean transit time.

[0034] The pressure sensing catheter is capable of collecting multiple pressure measurements distal to the area of ​​interest.

[0035] The method may further include the one or more processors determining the mean transit time using a value of the area subtended by the minimum points of the distribution curve. [Brief explanation of the drawings]

[0036] [Figure 1] FIG. 1 illustrates an exemplary system having a pressure wire according to aspects of the present disclosure. [Figure 2] FIG. 1 is an illustration of an experimental setup according to aspects of the present disclosure. [Figure 3] FIG. 1 illustrates an exemplary system having an intravascular imaging probe according to aspects of the present disclosure. [Figure 4] FIG. 1 is an illustration of an experimental setup according to aspects of the present disclosure. [Figure 5] FIG. 1 illustrates an exemplary system having a pressure-sensing catheter according to aspects of the present disclosure. [Figure 6A] FIG. 2 is a cross-sectional view of the distal end of a pressure-sensing catheter. [Figure 6B] FIG. 2 is a cross-sectional view of the distal end of a pressure-sensing catheter. [Figure 7] FIG. 1 illustrates an exemplary system having an OCT catheter according to an embodiment of the present disclosure. [Figure 8] FIG. 1 illustrates an exemplary system having a delivery catheter according to aspects of the present disclosure. [Figure 9] FIG. 10 illustrates an example averaged pressure waveform from raw pressure sensor measurements. [Figure 10A] 1 illustrates an example pressure dilution curve according to an aspect of the present disclosure and an example functional representation of mean transit time according to an aspect of the present disclosure. [Figure 10B] FIG. 10 illustrates another example of a pressure dilution curve according to an aspect of the present disclosure and an example of a functional representation of mean transit time according to an aspect of the present disclosure. [Figure 11A] FIG. 10 illustrates another example of a pressure dilution curve according to aspects of the present disclosure. [Figure 11B] FIG. 10 illustrates an example of a functional representation of mean transit time according to aspects of the present disclosure. [Figure 12A] FIG. 10 is a scatter plot of experimental results for determining mean transit time from thermodilution and true flow rates. [Figure 12B] FIG. 1 is a scatter plot of experimental results for determining mean transit time from the thermodilution method and the area under the curve method. [Figure 12C] FIG. 10 is a scatter plot of experimental results for determining mean transit time from the area under the curve method and true flow rate. [Figure 13A] FIG. 1 is a flow diagram illustrating a method for determining the mean transit time of blood in a blood vessel according to aspects of the present disclosure. [Figure 13B] FIG. 10 is a flow diagram illustrating an alternative method for determining the mean transit time of blood in a blood vessel according to aspects of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0037] The present technology provides for the use of a single intravascular instrument to identify and / or diagnose one or more aspects of microvascular disease within a blood vessel. For example, blood flow can be determined using only pressure measurements, without accompanying temperature measurements as required by existing systems. The use of a single intravascular instrument reduces risk to the patient during the procedure because fewer incisions are made, fewer instruments are inserted into the patient, and time in the procedure room or operating room is reduced. In some instances, the use of a single intravascular instrument allows physicians to collect more data at once, thereby more efficiently diagnosing a patient's microvascular disease.

[0038] According to some examples, an intravascular device can be used to collect intravascular data of a blood vessel. The intravascular data can be, for example, pressure measurements. The intravascular data can be used to determine the mean transit time of blood through the blood vessel. In some examples, the mean transit time can be determined at rest and / or during hyperemia. The mean transit time determined from the pressure measurements can be used to determine coronary flow reserve ("CFR"), index of microcirculatory resistance ("IMR"), or other diagnostic indices. The CFR and / or IMR values ​​can be used to diagnose microvascular disease. According to some examples, the pressure measurements and / or any values ​​determined using the pressure measurements can be used to evaluate lesions in the blood vessel, evaluate potential stent placement, diagnose microvascular disease, etc.

[0039] According to some examples, additional factors in combination with the determined CFR and / or IMR can be used to identify one or more aspects of microvascular disease in a blood vessel. Additional factors can include, for example, a patient's age, sex, body mass index ("BMI"), medical history, vessel type, vessel condition, prior treatment, etc. Medical history can include, for example, known heart failure, a previous diagnosis of diabetes, hypertension, etc. Vessel types can include, for example, left anterior descending ("LAD") artery, left circumflex ("LCX") artery, right coronary artery ("RCA"), left marginal artery, diagonal artery, right marginal artery, etc. Prior treatments can include, for example, previous percutaneous coronary intervention ("PCI"), coronary artery bypass graft ("CABG"), etc.

[0040] By using pressure measurements instead of temperature measurements, the system and software used to calculate mean transit time can operate without strict adherence to parameters related to the bolus injection methodology. This reduces errors that could otherwise result from injecting a bolus at an imperfect time or temperature. Additionally, the intravascular device does not require temperature sensing, thereby reducing the cost and complexity of the required device. For example, mean transit time can be determined by collecting pressure measurements using a pressure transducer connected to the purge port of an OCT catheter. These pressure measurements can be used to determine mean transit time, eliminating the need for inserting pressure wires. This reduces the risk of complications during the procedure. Additionally or alternatively, determining mean transit time using a catheter can allow for real-time reading and calculation of mean transit time. In some examples, mean transit time determined using a pressure dilution curve can be used to determine CFR data and / or IMR data. In this manner, pressure dilution curves can be used to determine anatomical information in addition to physiological information.

[0041] FIG. 1 illustrates a data acquisition system 100 used to collect intravascular data. The system can include an intravascular device that can be used to collect data within a blood vessel 102. The intravascular device can be a pressure wire, a pressure-sensing catheter, an OCT probe, a micro-OCT probe, a NIRS sensor, or an IVUS catheter. While FIG. 1 illustrates the use of a pressure wire, the system is not limited to the use of a pressure wire. IVUS catheters, NIRS sensors, OCT probes, and the like can also be used in conjunction with or in place of the pressure wire, as described in more detail below. A guide catheter, not shown, can be used to introduce the pressure wire 104 into the blood vessel 102. The pressure wire 104 can be introduced and positioned distal to an area of ​​interest within the blood vessel 104. In some examples, the area of ​​interest can be a location within the blood vessel where there is high calcium or plaque buildup restricting blood flow or a potential location for a stent.

[0042] According to some examples, the pressure wire 104 can be introduced and held stationary to obtain multiple intravascular measurements. The pressure wire 104 can be held stationary distal to the area of ​​interest to obtain distal pressure measurements. A bolus can be injected into the blood vessel 102 through a purge port positioned so that the bolus will flow along the pressure wire 104. The pressure wire 104 can capture intravascular measurements as the bolus passes. According to some examples, the saline bolus can be at room temperature or matched to the patient's body temperature. The intravascular measurements obtained by the pressure wire 104 can be used to identify characteristics of the blood vessel 102.

[0043] The pressure wire 104 may be communicatively connected to a subsystem 108 via a wired or wireless connection. The subsystem 108 may have a receiver 110 that sends signals to a computing device 112. The computing device 112 may have one or more processors 113, memory 114, instructions 115, data 116, and one or more modules 117.

[0044] The one or more processors 113 may be any conventional processor, such as a commercially available microprocessor. Alternatively, the one or more processors may be dedicated devices, such as an application-specific integrated circuit (ASIC) or other hardware-based processor. While FIG. 1 functionally depicts the processor, memory, and other elements of device 110 as being within the same block, those skilled in the art will understand that a processor, computing device, or memory may actually include multiple processors, computing devices, or memories that may or may not be housed within the same physical housing. Similarly, memory may be a hard drive or other storage medium located in a different housing than that of device 112. Thus, reference to a processor or computing device will be understood to include reference to a collection of processors or computing devices or memories that may or may not operate in parallel. By way of example, a processor within computing device 112 may be communicatively connected to a remote processor, such as over a wired or wireless network, such as the Internet. The remote processor may perform some or all of the calculations and may coordinate with computing device 112.

[0045] The memory 114 may store information accessible by the processor 113, including instructions 115 that may be executed by the processor 113, and data 116. The memory 114 may be any type of memory that operates to store information accessible by the processor 113, including a non-transitory computer-readable medium or other medium that stores data that is readable by an electronic device, such as a hard drive, a memory card, a read-only memory ("ROM"), a random access memory ("RAM"), an optical disk, and other writable and read-only memory. The subject matter disclosed herein may include different combinations of the above, where different portions of the instructions 115 and data 116 are stored on different types of media.

[0046] Memory 114 may be retrieved, stored, or modified by processor 113 in accordance with instructions 115. For example, although this disclosure is not limited by a particular data structure, data 116 may be stored in a computer register, in a relational database as a table with multiple different fields and records, an XML document, or a flat file. Data 116 may also be formatted in a computer-readable format, such as, but not limited to, binary values, ASCII, or Unicode. Further by way of example only, data 116 may be stored as a bitmap composed of pixels stored in compressed or uncompressed format, or as computer instructions for drawing a graphic. Furthermore, data 116 may include associated information, such as numbers, descriptive text, proprietary codes, pointers, references to data stored in other memory (including other network locations), or sufficient information to identify information used by a function that computes the associated data.

[0047] The instructions 115 may be any set of instructions executed by the processor 113 directly, e.g., in machine code, or indirectly, e.g., in script. In that regard, the terms "instructions," "application," "steps," and "program" are used interchangeably herein. The instructions may be stored in object code format for direct processing by the processor, or in any other computing device language, including a script or collection of independent source code modules that are interpreted on demand or pre-compiled. The functions, methods, and routines of the instructions are described in more detail below.

[0048] Modules 117 may include a plaque detection module, such as calcium plaque, a display module, a flow or mean transit time module, a pressure change module, a temperature change module, a stent detection or other detection and display module, etc. For example, computing device 112 may have access to a flow module for detecting the mean transit time of blood through a blood vessel.

[0049] The subsystem 108 may include a display 118 for outputting content to an operator. As shown, the display 118 is separate from the computing device 112. However, according to some examples, the display 118 may be part of the computing device 112. The display 118 may output pressure data associated with one or more features detected within the blood vessel. For example, the output may include, but is not limited to, pressure data, thermodilution data, aortic and distal pressures, a pressure-based risk indication for stent expansion, flow rate, etc. The display 118 may identify features using numerical values, text, arrows, color coding, highlighting, outlines, animations, or other suitable human-readable or machine-readable indications. For example, the display may output a green color when the pressure of the blood within the blood vessel is within a given range of pressure measurements and a red color when the pressure is outside that range. The range may be programmed by the operator, preset in the processor, or configured in the processor by artificial intelligence. The display may output graphics, which may be icons, pictures, curves, or other visual images. The display may output an animation that may depict the patient's blood vessels with an animation of blood flowing at a velocity corresponding to the determined mean transit time.

[0050] According to some examples, the display 118 may include a graphic user interface ("GUI"). One or more steps for navigating an image, entering information, selecting and / or interacting with an input, etc. may be performed automatically, i.e., without user input. The display 118, alone or in combination with the computing device 112, may enable switching between one or more view modes in response to user input. For example, a user may be able to switch between different side branches on the display 118, e.g., by selecting a particular side branch and / or by selecting a view associated with a particular side branch.

[0051] In some examples, the display 118, alone or in combination with the computing device 112, can include a menu. The menu allows the user to show or hide various features. There can be more than one menu. For example, there can be a menu for selecting vascular features to display. Additionally or alternatively, a menu can be provided for selecting target areas of the vessel from which pressure measurements can be collected.

[0052] 2 shows a system for data collection system 100. System 100 includes pressure wire 104, subsystem 108, physiology phantom 120, and guide catheter 121. Subsystem 108 includes receiver 110, computing device 112, and display 118. The illustrated system can simulate a clinical scenario in which pressure measurements are collected using an intravascular device.

[0053] The physiological phantom 120 can simulate vascular physiology and represent the human vascular system. The physiological phantom 120 is a combination of hardware and software used to mimic the flow of a patient's heart in benchtop experiments. The hardware in the physiological phantom represents the coronary artery branches. The software in the physiological phantom 120 controls the internal hardware that generates conditions found in the coronary arteries, such as waveforms similar to the heartbeat.

[0054] The guide catheter 121 can be used to introduce the pressure wire 104 into the blood vessel 102. The guide catheter 121 can be any tubular delivery device, such as any catheter, guide sheath, trocar, or tubular instrument, that can be used in a percutaneous intracoronary (PCI) procedure. Additionally, the guide catheter 121 can measure the aortic pressure of the blood vessel. The guide catheter 121 can be inserted into the blood vessel, hyperemia can be pharmacologically induced using adenosine, and the aortic pressure at the opening of the blood vessel can be measured. In some examples, the guide catheter 121 can be connected to a separate receiver via a wired or wireless connection. This receiver can collect aortic pressure readings and send them to the subsystem 108 for use in intravascular calculations.

[0055] According to some examples, the pressure wire 104 can be inserted into the physiological phantom 120 through a guide catheter 121. The guide catheter 121 can be inserted into the physiological phantom 120. The pressure wire 104 can be inserted into the guide catheter 121 and into the blood vessel 102 and advanced to the area of ​​interest. The pressure wire 104 can communicate with the receiver 110 via a wired or wireless connection. In examples where the connection is wireless, the pressure wire 104 and receiver 110 can communicate via Bluetooth, near-field communication ("NFC"), Wi-Fi, or other short-range communication interface.

[0056] According to some examples, subsystem 108 can have components within a single housing, outside a housing, or within multiple housings. As shown, receiver 110 is in a separate housing and is wirelessly connected to the single housing that houses computing device 112 and display 118, as described above.

[0057] FIG. 3 illustrates another data acquisition system 200 for collecting intravascular pressure data. System 200 can perform the same or substantially the same operations as system 100. The components of system 200 can be similar to system 100, except that the intravascular device of system 200 is a pressure-sensing catheter 221 instead of pressure wire 104. The system can be interfaced with an intravascular imaging probe, such as an OCT probe, micro-OCT, NIRS sensor, or intravascular ultrasound ("IVUS") probe. Catheter 221 can have a distal opening 203. In some examples, distal opening 203 can be provided within the catheter and can be connected to an external pressure transducer. In some examples, the pressure transducer can be connected to a pressure assessment port on catheter 221.

[0058] Although only one distal opening 203 is shown, this is not intended to limit the number of distal openings 203 in the catheter 221. In one example, the distal opening 203 can be located at the distal end of the catheter. Additionally or alternatively, one or more openings can be located near the central portion of the catheter. Additionally or alternatively, one or more openings can be located near the proximal end of the catheter. In yet another example, one or more openings can be located anywhere in the body of the catheter, such as one or more openings at the distal end of the catheter and one or more openings in the central portion of the catheter.

[0059] Figure 4 shows a benchtop arrangement of a data acquisition system with an intravascular imaging tool similar to the system described in Figure 3. The system 200 has a pressure assessment port 220 of the imaging tool connected to a pressure transducer 222. The pressure transducer 222 is connected to a subsystem 208 having a receiver 210, a computing device 212, and a display 218, and to a distal opening 203 (not shown). A catheter 221 is inserted into a physiological phantom 120. The illustrated system can simulate a clinical scenario in which pressure measurements are collected using an intravascular device.

[0060] The distal opening may be in fluid communication with a pressure transducer 222. The pressure transducer 222 may be connected to a pressure assessment port 220 at the end of the catheter 221. The pressure transducer 222 may be communicatively connected to a receiver 210 via a wired or wireless connection to collect multiple pressure measurements. The catheter 221 may be filled with an incompressible fluid before being inserted into a blood vessel. The incompressible fluid may comprise a contrast agent, saline, a blood-compatible fluid, or another medium. The pressure transducer 222 may measure the pressure of the hydraulic column of the catheter 221 while the catheter 221 is inserted into the blood vessel.

[0061] For example, the distal opening can be positioned distal to the area of ​​interest. The catheter fluid column pressure can change based on the physiology of the blood vessel in which the distal opening is located, specifically, the increase or decrease in blood pressure at the point where the blood vessel narrows or widens. The pressure transducer 222 can receive blood vessel pressure readings at the distal opening as the catheter is inserted into the blood vessel. The user can select the area of ​​interest for the system to use in calculations.

[0062] The series of pressure measurements can represent the blood vessel before, during, and after the distal opening reaches the area of ​​interest. The series of pressure measurements can be used to determine the flow rate of blood within the blood vessel. For example, each pressure measurement can include a timestamp indicating when the pressure measurement was taken at the distal opening 203. In some examples, the pressure measurements can be taken at predetermined time intervals and marked as such. For example, the system can record pressure measurements every 0.01 seconds as the catheter advances to the area of ​​interest. The pressure within the blood vessel 202 can be determined. The determined pressure measurements of the blood vessel at the location of the distal opening 203 can be used along with the timestamps or time intervals to determine the flow of blood within the blood vessel and, consequently, the mean transit time of blood within the blood vessel. As described more fully below with reference to FIG. 12 , the mean transit time can be determined based on the ratio of the integral of the average pressure measurement at a given time multiplied by that time to the integral of the average pressure measurement at that time.

[0063] In this example, the pressure transducer 222 may be communicatively connected to the subsystem 208 by a wireless or wired connection 206. The subsystem 208 may include a receiver 110 that sends the pressure signal to the computing device 212.

[0064] An example of a system employing a catheter to measure pressure variations within a blood vessel is shown in Figure 5. Catheter 321 can be any catheter that can be connected to a pressure transducer.

[0065] The catheter 321 can have a proximal end with a side arm and a hypotube 341. The side arm and hypotube 341 can facilitate the delivery of contrast, saline, or a hemocompatible fluid to a target area of ​​a blood vessel. The catheter 321 can further have a distal end with two polymeric members. These two polymeric members can be an outer member 342 and an inner member 343. The outer member 342 can be secured to the hypotube 341, such as by being directly bonded thereto. The inner member 343 can be bonded to the outer member 342 to form a rapid exchange (RX) notch. In some embodiments, the catheter can be configured as an over-the-wire catheter with a side arm. The inner member 343 can provide a means for delivering the catheter 321 over a guidewire 344. The space between the outer member 342 and the inner member 343 can provide a space for an incompressible fluid column, such as contrast agent, saline, or a blood-compatible fluid, in the target vessel. The fluid column can allow for direct pressure measurement within the vessel at the distal opening 303 of the catheter 321.

[0066] In some examples, catheter 321 can include a distal opening, such as distal opening 303, at the distal end of the catheter. Distal opening 303 can be located at the distal end of catheter 321. At the location of distal opening 303, the fluid column is subjected to vascular fluctuations, such as fluctuations in blood pressure. In some embodiments, distal opening 303 can capture the intravascular fluctuations as vascular data and transmit the vascular data through catheter 321 to a pressure transducer. Once the vascular data at distal opening 303 is received, the pressure transducer can collect direct pressure measurements.

[0067] In some examples, the distal opening 303 can be located at the distal end of the catheter 321. The distal opening 303 can be positioned perpendicular to the flow of blood within the blood vessel. Alternatively, the distal opening 303 can be located on the outer surface of the outer member 342, parallel to the flow path.

[0068] Although only one distal opening 303 is shown, this is not intended to limit the number of distal openings connected to and / or integrated with catheter 321. In some instances, multiple openings are distributed circumferentially around the outer member. In other instances, openings can be distributed laterally along one or more portions of the outer member.

[0069] The openings can be formed in the outer member 342 by heat machining. The openings can be formed by special contouring around the edges of the openings. The contouring can prevent turbulence of the fluid as blood passes through the openings.

[0070] The opening is 0.01 mm 2 ~4mm 2 In some examples, the openings can have a variety of sizes ranging from 0.025 mm 2 ~2mm 2 The openings can be of various shapes such as circular, square, triangular, or any polygonal shape.

[0071] Figure 6A shows a cross-sectional view of the distal end of the catheter 321 shown in Figure 5. The distal end of the catheter 321 can include an outer member 342 and an inner member 343. The outer member 342 can feature a distal opening 303. The inner member can provide a path for a guidewire 344 to pass through in order to properly position the catheter 321 within a blood vessel.

[0072] 6B shows another cross-sectional view of the distal end of the catheter, showing two distal openings. The distal end of catheter 321 can include an outer member 342 and an inner member 343. Outer member 342 can feature two distal openings 303 and 303'. Multiple distal openings can provide more accurate vascular pressure measurements. The inner member can provide a path for a guidewire 344 to properly position catheter 321 within the blood vessel.

[0073] 7 shows a catheter similar to that shown in FIG. 5 but with an imaging tool. The catheter 421 can have at least one distal opening 403, a liquid seal 422, and a purge port 423. The catheter 421 can also have a guidewire entry point 441 and a guidewire exit point 442. In this example, the catheter 421 has an imaging tool 404 that is an OCT probe, and therefore the catheter 421 can have a fiber optic connector 431, an OCT lens 432, and a radiopaque marker 433. In other examples, the imaging tool 404 can be an IVUS probe, a NIRS probe, a micro-OCT probe, etc.

[0074] In this example, purge port 423 takes the place of the pressure assessment port shown in Figure 4. The distal opening can be connected to purge port 423 via a pressure transducer. The pressure transducer can be communicatively connected to a receiver via a wired or wireless connection to collect multiple pressure measurements. According to methods known in the art, pressure proximal to the area of ​​interest, also known as aortic pressure, can be measured by a guide catheter.

[0075] The catheter can hold a column of incompressible fluid to facilitate pressure measurements at the distal opening 403. In this example, the incompressible fluid can be any blood-compatible fluid, such as saline or another suitable medium, that does not interfere with the imaging tool. The column of fluid is held in place by a liquid seal 422, which prevents the bolus from exiting the distal end of the catheter 421. The column of fluid is held around the imaging tool 404. A purge port 423 can be used to push the fluid bolus into the area of ​​interest to properly image the area of ​​interest. The purge port 423 can be used to fill the catheter 421 with a column of fluid to take pressure measurements.

[0076] The distal opening 403 can be positioned distal to the area of ​​interest such that a pressure transducer measures the pressure distal to the area of ​​interest at the distal opening 403. Measurements begin when the distal opening reaches the area of ​​interest. As the distal opening 403 approaches the area of ​​interest, the pressure transducer can collect multiple distal pressure measurements of the area of ​​interest continuously or at a high acquisition rate. Pressure measurements can be taken by the pressure transducer at the distal opening within the blood vessel before, during, and after the distal opening reaches the area of ​​interest. The pressure measurements can be expressed as a function of time to provide a profile of pressure across the area of ​​interest. This function can be used to determine the mean transit time of blood, as described in more detail below with respect to FIGS. 8-10. The pressure measurements can be used to determine the flow rate of blood within the blood vessel. For example, each pressure measurement can be assigned a corresponding timestamp based on where the distal opening 403 was located when the pressure measurement was taken, such as before, during, and after the distal opening reaches the area of ​​interest. In some examples, pressure measurements can be taken at predetermined time intervals and marked as such. For example, the system can record pressure measurements every 0.01 seconds as the catheter is advanced to the area of ​​interest. Pressure measurements of the blood vessel at the distal opening 403 can be used to determine blood flow within the blood vessel and, consequently, the mean transit time of blood through the blood vessel. Additionally, the raw pressure waveform can be used to derive coronary indices such as the resting full-cycle ratio (RFR) and the instantaneous wave-free ratio (iFR).

[0077] FIG. 8 illustrates a catheter similar to that shown in FIG. 5 but with a delivery device. Catheter 521 can have at least one distal opening 503 and a pressure assessment port 520. The pressure assessment port can be connected to an external pressure transducer. In this example, catheter 521 has a delivery device, which is a delivery catheter 551 with a balloon 553 at its distal end. The delivery catheter can have a port 552 at its proximal end. This port can be used to facilitate a delivery device to inflate and deflate balloon 553, etc.

[0078] The catheter 521 and delivery catheter 551 can be simultaneously advanced through the blood vessel toward the area of ​​interest. The catheter can be configured to hold a column of fluid to measure pressure at the distal opening 503 as the catheter is advanced through the blood vessel, as described in FIGS. 4 and 5 . A pressure transducer can collect pressure measurements at the distal opening 503. The combined pressure assessment catheter and delivery device can provide real-time pressure measurements immediately before or after an interventional device is deployed. For example, a stent can be placed over the balloon 553 and catheter 521, and the delivery catheter 551 can be advanced to the stent deployment site. Once the stent deployment site is reached, the distal opening 503 can be positioned beyond the site, with the balloon 553 and stent in place. The pressure transducer can collect pre-deployment pressure readings at the distal opening 503. A user can inflate the balloon 553 by injecting a solution, such as saline, into the port 552 and toward the balloon 553. The balloon 553 can be inflated to deploy a stent at the stent deployment site within the blood vessel. The user can deflate balloon 553 by removing the solution through port 552. Once normal flow through the newly stented site resumes, the pressure transducer can begin collecting post-deployment pressure measurements at distal opening 503. This allows the user to verify proper placement of the interventional device in real time. Using these instantaneous pressure measurements, the operator can determine whether to readjust the interventional device. This shortens the procedure time and therefore reduces potential health risks to the patient.

[0079] 9 shows raw pressure measurements and averaged pressure waveforms. Distal pressure measurements collected by the intravascular device are processed within the subsystem. Pressure measurements from the intravascular device can be displayed on a chart as shown at 610. The pressure measurements are plotted on the chart 610 in sequential order based on their timestamp or time interval. Raw pressure data 611 can be plotted along with cardiac cycle waveform 612. A representation of the raw pressure measurements 611 is used to create an averaged waveform 613.

[0080] The one or more processors can determine the first time the distal opening reaches an area of ​​interest ("ROI"), such as a stenotic area, by identifying the first spike in pressure readings from multiple pressure measurements collected as the intravascular device moves through the area of ​​interest. When the spike begins to drop off, the distal opening has passed the stenotic area. An averaged waveform 613 is calculated using measurements of a specific number of cycles in the ROI. These cycles may include measurements just before and just after the intravascular device reaches the ROI. For example, the eight cycles used to calculate the averaged waveform include the peak from the ROI, four cycles before the peak, and four cycles after the peak.

[0081] The system can use raw pressure measurements of periods of the same length used for the averaged waveform 613 from either before or after the section with the ROI as a template sequence for comparison. For example, eight periods including the ROI (the "ROI sequence") can be used to calculate the averaged waveform 613, and eight periods following the ROI sequence can be used as a template to calculate the averaged waveform 613. Once the averaged waveform 613 is determined, it can be plotted as shown at 620 along with the raw pressure measurements 611 of the particular periods used to obtain the averaged waveform 613.

[0082] An example of a pressure dilution curve is shown in FIG. 10A. The pressure dilution curve 710 shows the pressure measurements at the intravascular device at a given time as the distal opening advances through the blood vessel and passes the ROI. For example, the pressure dilution curve 710 can be charted as pressure measurements in inches of mercury (inHg) based on the time the measurement was taken. Using the initial time and a log normal fit applied, the mean transit time can be determined. The x-axis of the pressure dilution curve is time.

[0083] The pressure dilution curve 710 can be used to determine the mean transit time Tmn, which can be the flow rate of blood in a blood vessel.

[0084] Pressure dilution curve 710 can have a pressure measurement p. In some examples, pressure measurement p of curve 710 can be determined by any of multiple pressure measurements between the first and last pressure readings collected by the intravascular device as the pressure-sensing catheter is advanced through the blood vessel. Pressure measurement p is shown in the area marked by the ROI in FIG. 10A .

[0085] The integral of curve 710 can be used to calculate the mean transit time Tmn through the blood vessel. The mean transit time Tmn is calculated using the pressure dilution curve 710 to calculate the mean transit time t O and the starting point of the pressure measurement p. For example, the mean transit time can be determined using a ratio of a function of the average pressure at the distal opening in the vessel at a given time multiplied by time to the average pressure at the distal opening in the vessel. According to some examples, the mean transit time Tmn can be determined using the following equation:

number

[0086] In this equation, t can correspond to time, which can be the time time stamped corresponding to any given pressure measurement, and c in this equation can correspond to the average pressure at the distal opening at time t.

[0087] Another example of a pressure dilution curve is shown in FIG. 10B. Pressure dilution curve 710 shows pressure measurements collected by an intravascular device at a given time as the distal opening advances through a blood vessel and passes an ROI. For example, pressure dilution curve 710 can be a chart of pressure measurements in inches of mercury (inHg) based on the time the measurements were taken. Using the initial time and an applied log-normal approximation, the mean transit time can be determined. The x-axis of the pressure dilution curve is time.

[0088] The pressure dilution curve 710 can be used to determine the mean transit time Tmn, which can be the flow rate of blood in a blood vessel.

[0089] The pressure dilution curve 710 can have a pressure measurement p. In some examples, the pressure measurement p of the curve 710 can be determined by any of multiple pressure measurements between the first pressure measurement at which the distal opening reaches the ROI and the point at which the pressure reading begins to drop rapidly. The pressure measurement p is shown in the area marked by the ROI in FIG. 10B.

[0090] The integral of curve 710 can be used to calculate the mean transit time Tmn through the blood vessel. The mean transit time Tmn is calculated using the pressure dilution curve 710 to calculate the mean transit time t O and the drop point of the pressure measurement p. For example, the mean transit time can be calculated using the initial time t O The mean transit time Tmn can be calculated by subtracting the time at which the pressure reading begins to drop from the time at which the pressure reading begins to drop.

number

[0091] The mean transit time can be determined at rest and during hyperemia. Determining the mean transit time at rest can include collecting one or more pressure measurements while the distal opening is held distal to the area of ​​interest in a blood vessel that is in a natural state. For example, the natural state can be a state in a blood vessel that is not receiving any treatment or medication. Determining the mean transit time during hyperemia can include collecting one or more pressure measurements while the distal opening is distal to the area of ​​interest in a blood vessel that has been pharmacologically induced to become hyperemic to cause full dilation of the blood vessel.

[0092] Conventionally, users use pressure wire temperature readings to determine mean transit time. Specifically, the pressure wire temperature sensor captures a thermodilution curve to determine mean transit time. The thermodilution curve is defined by points of temperature increase and decrease as the cooled bolus passes through the stenotic area or ROI.

[0093] CFR is calculated by the mean transit time T at rest as shown in the following formula: mn at rest and mean transit time T during hyperemia mn at hyperemia It can be found using

number

[0094] According to some examples, the mean transit time during hyperemia, T mn at hyperemia For example, the IMR can be calculated using the following formula:

number

[0095] In this equation, P d at hyperemiacan correspond to the distal pressure during pharmacologically induced hyperemia. This distal pressure can be determined based on intravascular data collected by an intravascular device. For example, P can be defined as a pressure measurement collected by an intravascular device while positioned distal to the area of ​​interest. d at hyperemia The pressure gradient (ΔP) can be calculated based on Ohm's law as flow rate (Q) multiplied by vascular resistance (R) as shown in the following equation:

number

[0096] Flow can be calculated from theoretical aortic and venous pressures through a resistance model.

[0097] 11A and 11B illustrate another method for calculating the mean transit time of a blood vessel. FIG. 11A shows pressure measurements from an intravascular device plotted in chart 810, similar to chart 610 in FIG. 9. The pressure measurements are measured in millimeters of mercury (mmHg) with time in milliseconds (ms). The pressure measurements are plotted in chart 810 in consecutive order based on their timestamps or time intervals. In some examples, a moving average filter can be applied to the intravascular device pressure measurements shown as raw pressure waveform 811. In some examples, the window length of chart 810 can be equivalent to one cardiac cycle. A filtered waveform 812 can be generated and overlaid on the raw pressure waveform 811 in chart 810, similar to chart 610 in FIG. 9.

[0098] 11B illustrates further processing of the filtered waveform 912. The filtered waveform 912 may be processed by a subsystem, which may be similar to subsystem 108 described in FIG. 1. The subsystem may be communicatively connected to an intravascular tool having pressure sensing capabilities, such as a pressure wire or catheter. Pressure readings from the intravascular device having pressure sensing capabilities may be sent to the subsystem.

[0099] In some examples, the subsystem may extract various landmarks along the filtered waveform 912 to aid in data processing, analysis, and determination of vascular characteristics, such as mean transit time. The various landmarks may be extracted based on manual settings or filters built into the subsystem. In some examples, the various landmarks may be extracted automatically based on prior data stored by the system or subsystem. The various landmarks in the filtered waveform 912 may include a zero reference point 961, an ascent point 962, a maximum point 963, a plateau point 964, a descent point 965, a decline point 966, and a minimum point 967. The filtered waveform 912 is aligned with 0 on the y-axis based on the reference point 961.

[0100] The filtered waveform 912 can be used to calculate the mean transit time of the blood vessel. In some examples, a minimum point 967 falls below zero on the y-axis, resulting in a defined area 969 under the curve. In FIG. 11B, the defined area 969 is shown as the shaded area below zero on the y-axis. Additionally, the time between the maximum point 963 and the minimum point 967 is shown as a change in time 968. The mean transit time can be calculated by multiplying the area of ​​the defined area 969 by the change in time 968. By including the change in time 968, the calculated mean transit time is adjusted for the patient's heart rate. According to some examples, the mean transit time Tmn can be calculated using the following equation:

number

[0101] In this equation, a may correspond to the area under the curve below 0 on the y-axis, as described above as defined area 969. b in this equation may correspond to the time between the highest peak 963 and the most negative peak 967, as described above as change in time 968.

[0102] Figures 12A-12C show a comparison of mean transit time using thermodilution and area-under-the-curve (AUC) methods. Figure 12A shows true flow rate with thermodilution mean transit time. True flow rate and thermodilution mean transit time were measured and collected by utilizing an in-line flow meter and pressure wires as appropriate to serve as study controls representing the industry standard for calculating mean transit time. The data presented in Figure 12A are from 122 samples with various combinations of different pressures, flow rates, and heart rates.

[0103] Figure 12B shows the correlation between AUC mean transit time and true flow rate. The correlation coefficient between AUC mean transit time and true flow rate is -0.77. Figure 12C shows the correlation between AUC mean transit time and thermodilution mean transit time. The correlation coefficient between AUC mean transit time and thermodilution mean transit time is 0.7. The correlation coefficient can be a statistical measure that quantifies the strength and direction of the linear relationship between two variables, and a correlation coefficient greater than 0.7 or less than -0.7 can be considered a strong correlation.

[0104] 13A illustrates an example method 1000 for determining the mean transit time of blood through a blood vessel. The following operations do not have to be performed in the exact order described below. Rather, various operations may be processed in a different order or simultaneously, and certain operations may be added or omitted.

[0105] At block 1001, multiple pressure measurements can be received. For example, a data collection system such as system 100 can collect the multiple pressure measurements using an intravascular device. The pressure measurements can be collected by a pressure wire, probe, or catheter having one or more distal openings. The pressure measurements can be sent to a subsystem through a receiver. The pressure measurements are stored in memory 114. One or more of the processors can determine an average pressure measurement based on the multiple pressure measurements. Additionally, one or more of the processors can generate a distribution curve based on the average pressure measurements.

[0106] At block 1002, a mean transit time of blood through a blood vessel may be determined without using a temperature reading. Using the distribution curve, one or more of the processors may determine the mean transit time of blood through the blood vessel. The one or more of the processors may integrate the distribution curve in determining the mean transit time of blood through the blood vessel. The one or more of the processors may use the determined mean transit time to determine at least one of a CFR value or an IMR value.

[0107] The mean transit time may also be determined in block 1003 using the ratio of the integral of a given average pressure measurement multiplied by the time for that given average pressure measurement to the integral of that given average pressure measurement.

[0108] 13B illustrates an example method 1100 for determining the mean transit time of blood through a blood vessel. The following actions do not have to be performed in the exact order listed below. Rather, various actions may be performed in a different order or simultaneously, and certain actions may be added or omitted. Method 1100 may include many of the same features as method 1000 illustrated in FIG. 13A.

[0109] Similar to method 1000, method 1100 can determine the mean transit time of blood through a blood vessel using a distribution curve of pressure readings, which is independent of temperature measurements. At block 1103, the mean transit time can further be determined using the value of the area subtended by the minimum points of the distribution curve of the mean pressure measurements. The distribution curve can be based on pressure measurements collected by an intravascular device inserted into a patient's blood vessel. In some examples, the distribution curve can be derived from raw pressure measurements plotted in sequential order based on timestamps. The raw pressure measurements can be processed using a moving average filter to form a distribution curve. The distribution curve can be the same as that shown in filtered waveform 912 in FIGS. 11A and 11B and can be similarly processed.

[0110] In some examples, the mean transit time can be determined using the area bounded by the minimum point of the distribution curve and 0 on the y-axis. The mean transit time can also be determined using the change in time between the maximum and minimum points of the distribution curve.

[0111] The disclosed method and apparatus enable a simpler procedure that can provide more consistent results and require less time to obtain results. Methods of obtaining mean transit time using temperature measurements require the bolus to be cooled to a specific temperature before being injected into the blood vessel. These methods require a highly skilled operator and require the cooled material to be processed quickly before the temperature drops. These methods are prone to error and potentially require multiple attempts to gather an accurate reading. The disclosed method avoids these problems by allowing the mean transit time to be determined without using temperature, thus reducing the procedure time and resulting in improved patient safety. Furthermore, by determining the mean transit time without using temperature measurements, the process of determining the mean transit time is more cost-effective than other methods that require the use of electrical sensors within the blood vessel to enable temperature measurement.

[0112] According to some examples, at least one of a CFR value and an IMR value can be determined based on the determined mean transit time. For example, the CFR value can be determined by dividing the determined mean transit time at rest by the mean transit time during hyperemia. The IMR value can be determined by multiplying the mean transit time during hyperemia by the distal pressure during hyperemia.

[0113] The determined CFR and / or IMR values ​​can be used in conjunction with one or more patient factors when determining microvascular disease and possible treatments. For example, a physician can consider the patient's age, sex, BMI, medical history, vascular type, vascular status, previous treatments, etc., in conjunction with the determined CFR and / or IMR values ​​to determine whether any microvascular disease and / or possible treatments are present.

[0114] In one example, microvascular resistance can be determined based on the determined mean transit time, CFR value, and / or IMR value and the patient's age. For example, the patient's age can be input and processed along with the CFR value and / or IMR value to determine the microvascular resistance of the blood vessel. According to some examples, one or more age-specific parameters can be introduced based on training data. In some examples, the age-specific parameter can be an age range for classifying the patient. The training data can be collected and used as input to a machine learning model. Based on the one or more age-specific parameters and the mean transit time, CFR value, and / or IMR value, the machine learning model can determine the microvascular resistance of the blood vessel.

[0115] In one example, the microvascular resistance can be determined based on the determined mean transit time, CFR value, and / or IMR value and the patient's gender. For example, the patient's gender can be input and processed along with the CFR value and / or IMR value to determine the microvascular resistance of the blood vessel. In some examples, the mean transit time, CFR value, and / or IMR value may differ based on the patient's gender. The patient's gender can be introduced based on training data. The training data can be collected and used as input to a machine learning model. The machine learning model can determine the microvascular resistance of the blood vessel based on the patient's gender and the mean transit time, CFR value, and / or IMR value.

[0116] In one example, microvascular resistance can be determined based on the determined mean transit time, CFR value, and / or IMR value and the patient's BMI. For example, the patient's BMI can be input and processed together with the CFR value and / or IMR value to determine the microvascular resistance of the blood vessel. According to some examples, one or more BMI parameters can be introduced based on training data. In some examples, the BMI parameter can be an age range for categorizing the patient. The training data can be collected and used as input to a machine learning model. Based on the one or more BMI parameters and the mean transit time, CFR value, and / or IMR value, the machine learning model can determine the microvascular resistance of the blood vessel.

[0117] In one example, the microvascular resistance can be determined based on the determined mean transit time, CFR value, and / or IMR value and the patient's medical history. For example, the patient's medical history, such as known heart failure, can be input and processed along with the CFR value and / or IMR value to determine the microvascular resistance of the blood vessel. According to some examples, one or more condition-specific parameters can be introduced based on training data. In some examples, the condition-specific parameters can be based on the patient's medical history. For example, the patient's medical history can indicate a history of heart failure. The training data can be collected and used as input to a machine learning model. Based on the one or more condition-specific parameters and the mean transit time, CFR value, and / or IMR value, the machine learning model can determine the microvascular resistance of the blood vessel.

[0118] As another example, a patient's medical history, such as a previous diagnosis of diabetes, can be input and processed in conjunction with the CFR and / or IMR values ​​to determine the microvascular resistance of the blood vessel. According to some examples, one or more condition-specific parameters can be introduced based on training data. In some examples, the condition-specific parameters can be based on the patient's medical history. For example, the patient's medical history can indicate a history of diabetes. The training data can be collected and used as input to a machine learning model. Based on the one or more condition-specific parameters and the mean transit time, the CFR, and / or the IMR, the machine learning model can determine the microvascular resistance of the blood vessel.

[0119] As another example, a patient's medical history, such as a previous diagnosis of hypertension, can be input and processed in conjunction with the CFR and / or IMR values ​​to determine the microvascular resistance of the blood vessel. According to some examples, one or more condition-specific parameters can be derived based on training data. In some examples, the condition-specific parameters can be based on the patient's medical history. For example, the patient's medical history can indicate a history of hypertension. The training data can be collected and used as input to a machine learning model. Based on the one or more condition-specific parameters and the mean transit time, the CFR, and / or the IMR, the machine learning model can determine the microvascular resistance of the blood vessel.

[0120] In one example, microvascular resistance can be determined based on the determined mean transit time, CFR value, and / or IMR value and the diagnosed vessel type. For example, a vessel type, such as a patient's left anterior descending artery ("LAD"), along with the CFR value and / or IMR value can be input and processed to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be derived based on training data. In some examples, the vessel-specific parameters can be based on the vessel type. For example, the type can be LAD. The training data can be collected and used as input to a machine learning model. Based on the one or more vessel-specific parameters and the mean transit time, CFR value, and / or IMR value, the machine learning model can determine the microvascular resistance of the vessel.

[0121] As another example, a vessel type, such as a patient's left circumflex artery ("LCX"), can be input and processed along with a CFR value and / or an IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be derived based on training data. In some examples, the vessel-specific parameter can be based on the vessel type. For example, the type can be LCX. The training data can be collected and used as input to a machine learning model. Based on the one or more vessel-specific parameters and the mean transit time, the CFR value, and / or the IMR value, the machine learning model can determine the microvascular resistance of the vessel.

[0122] As another example, a vessel type, such as a patient's right coronary artery ("RCA"), along with a CFR value and / or an IMR value, can be input and processed to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be derived based on training data. In some examples, the vessel-specific parameters can be based on the vessel type. For example, the type can be RCA. The training data can be collected and used as input to a machine learning model. Based on the one or more vessel-specific parameters and the mean transit time, the CFR value, and / or the IMR value, the machine learning model can determine the microvascular resistance of the vessel.

[0123] As another example, a patient's vessel type, such as a left marginal branch, can be input and processed along with a CFR value and / or an IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be derived based on training data. In some examples, the vessel-specific parameter can be based on the vessel type. For example, the type can be a left marginal branch. The training data can be collected and used as input to a machine learning model. Based on the one or more vessel-specific parameters and the mean transit time, the CFR value, and / or the IMR value, the machine learning model can determine the microvascular resistance of the vessel.

[0124] As another example, a patient's vessel type, such as a diagonal artery, can be input and processed along with a CFR value and / or an IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be derived based on training data. In some examples, the vessel-specific parameters can be based on the vessel type. For example, the type can be a diagonal artery. The training data can be collected and used as input to a machine learning model. Based on the one or more vessel-specific parameters and the mean transit time, the CFR value, and / or the IMR value, the machine learning model can determine the microvascular resistance of the vessel.

[0125] As another example, a patient's vessel type, such as a right marginal branch, can be input and processed along with a CFR value and / or an IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be derived based on training data. In some examples, the vessel-specific parameter can be based on the vessel type. For example, the type can be a right marginal branch. The training data can be collected and used as input to a machine learning model. Based on the one or more vessel-specific parameters and the mean transit time, the CFR value, and / or the IMR value, the machine learning model can determine the microvascular resistance of the vessel.

[0126] In one example, microvascular resistance can be determined based on the determined mean transit time, CFR value, and / or IMR value and a patient treatment history. For example, a patient treatment history, such as a previous percutaneous coronary intervention (“PCI”), can be input and processed along with a CFR value and / or IMR value to determine the microvascular resistance of the blood vessel. According to some examples, one or more treatment parameters can be introduced based on training data. In some examples, the treatment parameters can be based on the patient's treatment history. For example, the patient may have undergone a previous PCI. A previous PCI may cause microvascular injury and, therefore, can be taken into account when determining the microvascular resistance of the blood vessel. The training data can be collected and used as input to a machine learning model. Based on one or more vessel-specific parameters and the mean transit time, CFR value, and / or IMR value, the machine learning model can determine the microvascular resistance of the blood vessel.

[0127] As another example, a patient's medical history, such as a coronary artery bypass graft ("CABG"), can be input and processed along with the CFR and / or IMR values ​​to determine the microvascular resistance of a blood vessel. According to some examples, one or more treatment parameters can be implemented based on training data. In some examples, the treatment parameters can be based on the patient's medical history. For example, the patient may have undergone a previous CABG. CABG may alter cardiac physiology and / or may result in microvascular changes that can be taken into account when determining the microvascular resistance of a blood vessel. The training data can be collected and used as input to a machine learning model. Based on one or more vessel-specific parameters and the mean transit time, CFR, and / or IMR values, the machine learning model can determine the microvascular resistance of a blood vessel.

[0128] The aspects, examples, features, and examples of the present disclosure are to be considered in all respects illustrative and are not intended to limit the disclosure, the scope of which is defined solely by the claims. Other examples, modifications, and uses will be apparent to those skilled in the art without departing from the spirit and scope of the claimed invention.

[0129] Throughout this application, when a composition is described as having, including, or comprising particular components, or a process is described as having, including, or comprising particular process steps, it is intended that the compositions of the present teachings also consist essentially of, or consist of, the recited components, and that the processes of the present teachings also consist essentially of, or consist of, the recited process steps.

[0130] When an element or component is referred to herein as being included in and / or selected from a list of described elements or components, it should be understood that the element or component can be any one of the described elements or components, or can be selected from a group consisting of two or more of the described elements or components. Furthermore, it should be understood that the elements and / or features of the compositions, devices, or methods described herein, whether expressly or implied herein, can be combined in various ways without departing from the spirit and scope of the present teachings.

[0131] The use of the words "include," "including," "have," "has," or "having" should generally be understood to be open-ended and non-limiting, unless specifically stated otherwise.

[0132] The use of the singular herein includes the plural (and vice versa) unless specifically stated otherwise. Furthermore, the singular forms "a," "an," and "the" include the plural unless the context clearly dictates otherwise. Furthermore, when the word "about" is used before a quantitative value, the present teachings also include that specific quantitative value itself unless specifically stated otherwise. As used herein, the word "about" refers to a ±10% variation from the nominal value. All numerical values ​​and numerical ranges disclosed herein are considered to include "about" before each value.

[0133] It should be understood that the order of steps or order for performing certain actions is immaterial so long as the present teachings remain operable. Moreover, two or more steps or actions may be conducted simultaneously.

[0134] When a range or list of values ​​is provided, each intervening value between the upper and lower limits of the range or list of values ​​is considered individually and is encompassed by the invention as if each value were specifically recited herein. Additionally, smaller ranges between (and including) the upper and lower limits of a given range are also contemplated and encompassed by the invention. The listing of exemplary values ​​or ranges does not waive any other values ​​or ranges between (and including) the upper and lower limits of a given range.

[0135] While the present disclosure has been described with reference to particular examples, it is to be understood that these examples are merely illustrative of exemplary applications and embodiments. It is therefore to be understood that numerous modifications can be made to the illustrated examples and other arrangements can be devised without departing from the spirit and scope of the appended claims.

Claims

1. receiving, by one or more processors, intravascular data for a blood vessel, the intravascular data including a plurality of pressure measurements at a location in the blood vessel collected by an intravascular device; determining, by the one or more processors, a mean transit time of blood through the blood vessel based on the plurality of pressure measurements independent of temperature measurements; A method comprising:

2. 2. The method of claim 1, wherein determining the mean transit time includes the one or more processors determining a ratio of the integral of a given average pressure measurement multiplied by the time for the given average pressure measurement to the integral of the given average pressure measurement.

3. determining an average pressure measurement based on the plurality of pressure measurements by the one or more processors; generating a distribution curve based on the determined average pressure measurements; The method of claim 2 further comprising:

4. The method of claim 1 , further comprising providing for display one or more indicators of blood flow based on the determined mean transit time.

5. The method of claim 4 , wherein the one or more indicators of blood flow include at least one of a number, a color, a graphic, and an animation.

6. The method of claim 3, wherein the step of determining the mean blood flow time of the blood vessel is further based on the distribution curve.

7. 4. The method of claim 3, wherein determining the mean transit time further comprises the one or more processors determining a ratio of the integral of a given average pressure measurement multiplied by the time for the given average pressure measurement to the integral of the given average pressure measurement.

8. 7. The method of claim 6, wherein the one or more processors further determine at least one of a coronary flow reserve (CFR) value and an index of microcirculatory resistance (IMR) value based on the determined mean transit time.

9. 4. The method of claim 3, wherein in determining the average pressure measurement, the one or more processors further use the plurality of intravascular data over a plurality of periods including pressure readings before, during, and after the intravascular device reaches a location in the blood vessel.

10. The method of claim 1 , wherein the intravascular device is a pressure wire or an intravascular imaging tool.

11. The method of claim 10 , wherein the intravascular imaging tool is an optical coherence tomography probe or an IVUS probe.

12. The method of claim 10 , wherein the intravascular imaging tool has pressure sensing capability with a pressure transducer connected to a pressure assessment port.

13. 4. The method of claim 3, further comprising determining an averaged pressure waveform by identifying an initial pressure measurement of the plurality of pressure measurements as the intravascular device is advanced into an area of ​​interest.

14. receiving intravascular data for a blood vessel, the intravascular data including a plurality of pressure measurements at a location within the blood vessel; determining, by one or more processors, a mean transit time of blood through the blood vessel based on the plurality of pressure measurements independent of temperature measurements; A system comprising one or more processors that perform the steps of:

15. The system of claim 14 , further comprising an intravascular device in communication with the one or more processors and configured to collect the plurality of pressure measurements.

16. 15. The system of claim 14, wherein the one or more processors further determine at least one of a coronary flow reserve (CFR) value and an index of microcirculatory resistance (IMR) value based on the determined mean transit time.

17. The one or more processors: determining an average pressure measurement; creating a distribution curve based on the determined average pressure measurements; The system of claim 14 further comprising:

18. 18. The system of claim 17, wherein determining the mean transit time of blood through the blood vessel is further based on the distribution curve.

19. 20. The system of claim 18, wherein determining the mean transit time further comprises the one or more processors determining a ratio of the integral of a given average pressure measurement multiplied by the time for the given average pressure measurement to the integral of the given average pressure measurement.

20. 15. The system of claim 14, wherein determining the average pressure measurement further includes the one or more processors using the plurality of intravascular data over a plurality of periods including pressure readings before, during, and after the intravascular device reaches a location in the blood vessel.

21. The system of claim 14 , wherein the one or more processors further integrate the distribution curve when determining the mean transit time.

22. The system of claim 15 , wherein the intravascular device is a pressure wire or an intravascular imaging probe with pressure sensing capabilities.

23. 23. The system of claim 22, wherein the intravascular imaging probe with pressure sensing capability is an optical coherence tomography probe with a purge port or an IVUS.

24. The system of claim 14 , wherein the plurality of pressure measurements are collected distal to an area of ​​interest in the blood vessel.

25. a hypotube for delivering a blood compatible fluid to a location in a blood vessel; an outer member having a proximal end and a distal end, the proximal end being secured to the hypotube; an inner member having a proximal end and a distal end, the proximal end of the inner member being secured to the outer member; at least one opening at a distal end of the outer member that allows measurement of pressure at a location in the blood vessel; A pressure sensing catheter comprising:

26. one or more processors coupled to the pressure sensing catheter; the one or more processors: accepting a pressure measurement; determining, by the one or more processors, a mean transit time of blood through the blood vessel based on the plurality of pressure measurements independent of temperature measurements; To do 26. The pressure sensing catheter of claim 25.

27. 27. The pressure sensing catheter of claim 26, further comprising a pressure transducer in fluid communication with the at least one opening in the distal end of the outer member.

28. 26. The pressure sensing catheter of claim 25, wherein the one or more processors are further configured to determine at least one of a CFR value and an IMR value based on the determined mean transit time.

29. The one or more processors further include: determining an average pressure measurement; creating a distribution curve based on the determined average pressure measurements; 26. The pressure sensing catheter of claim 25,

30. 30. The pressure sensing catheter of claim 29, wherein determining the mean transit time of blood through the blood vessel is further based on the distribution curve.

31. 27. The pressure sensing catheter of claim 26, wherein determining the mean transit time further comprises the one or more processors determining a ratio of the integral of a given average pressure measurement multiplied by the time for the given average pressure measurement to the integral of the given average pressure measurement.

32. 27. The pressure sensing catheter of claim 26, wherein determining the average pressure measurement further includes the one or more processors using multiple intravascular data over multiple periods including pressure readings before, during, and after the intravascular device reaches a location in the blood vessel.

33. 27. The pressure sensing catheter of claim 26, wherein the one or more processors further integrate the distribution curve when determining the mean transit time.

34. 26. The pressure sensing catheter of claim 25, wherein the plurality of pressure measurements are collected distal to an area of ​​interest in the blood vessel.

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