Method for assessing coronary blood flow and microvascular system-pressure dilution curve by means of pressure line

Abstract

The present disclosure provides systems and methods for determining an average transit time of blood within a blood vessel using pressure measurements acquired by an intravascular tool and independent of temperature measurements. The intravascular instrument may acquire a plurality of pressure measurements distal to a region of interest within the vessel as the medicament passes through the vessel and is positioned over the instrument. The plurality of pressure measurements may be plotted on a pressure dilution curve. A function of the pressure dilution curve and the time is used to determine an average transport time of the blood within the blood vessel.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. Provisional Application No. 63 / 477,878, filed on December 30, 2022, entitled “Methodology for Assessing Coronary Flow and Microvascular System Through Pressurewires--Pressure Dilution Curve,” the entire disclosure of which is incorporated herein by reference. Background Art

[0003] Identifying a patient's microvascular resistance may require one or more data acquisition systems. For example, doctors can use pressure tracing, angiography, intravascular imaging, and other methods to acquire data to identify microvascular disease. Angiography provides a visual understanding of the entire heart, while pressure tracing provides certain measurements within the blood vessels.

[0004] The average transit time, corresponding to the blood flow rate in a blood vessel, is calculated by passing a bolus of cold saline through the blood vessel. The temperature of the bolus of saline is measured as it passes through a proximal temperature sensor and a distal temperature sensor on a pressure line inserted separately from an optical coherence tomography ("OCT") catheter. A thermodilution curve is then plotted based on the temperature of the bolus of saline as it passes the temperature sensors, which provides an indication of the flow rate and the average transit time. However, this requires additional steps and instrumentation, which can be cumbersome and dangerous in practice. Summary of the Invention

[0005] 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 instrument. For example, the intravascular instrument 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 velocity within a blood vessel.

[0006] An intravascular instrument can be inserted into a blood vessel at a location distal to the area of ​​interest. The intravascular instrument can have a distal port that is connected to an external pressure transducer. The intravascular instrument can have a column of an incompressible fluid (e.g., contrast agent, saline, or any suitable blood-compatible fluid). As the intravascular instrument advances through the blood vessel to the area of ​​interest, the intravascular instrument can collect multiple pressure readings at the distal port. The system can use the pressure readings to determine and / or create a pressure-dilution curve. The pressure-dilution curve can be used to determine the average transit time within the vessel. In some examples, the pressure-dilution curve can allow for other downstream flow indicators, such as coronary flow reserve ("CFR"), index of microcirculatory resistance ("IMR"), etc.

[0007] One aspect of the present disclosure includes a method comprising receiving, at one to multiple processors, intravascular data for a blood vessel, the intravascular data comprising a plurality of pressure measurements acquired by an intravascular instrument at locations within the vessel, and determining, by the one or more processors, an average transit time of blood within the vessel based on the plurality of pressure measurements, wherein the determination is independent of a vessel temperature measurement.

[0008] The method may further include determining, by one or more of the processors, the average transit time by determining a ratio of an integral of a product of a given average pressure measurement and a time for the given average pressure measurement to an integral of the given average pressure measurement.

[0009] The method may further include determining, by the one or more processors, an average pressure measurement based on the plurality of pressure measurements, and creating, by the one or more processors, a profile based on the determined average pressure measurement.

[0010] The method may further include providing for display one or more indicators of blood flow based on the determined mean transit time, wherein the indicator of blood flow may include at least one of a value, a color, a graphic, or an animation.

[0011] The method may further include determining an average transit time of the blood within the blood vessel based on the distribution curve.

[0012] The method may further include determining, by the one or more processors, the average transit time using a ratio of an integral of a product of a given average pressure measurement and a time for the given average pressure measurement to an integral of the given average pressure measurement.

[0013] The method may further include the one or more processors 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.

[0014] The method wherein when determining the mean pressure measurement, the one or more processors are further configured to use multiple cycles from a plurality of intravascular data including pressure readings before, during, and after the intravascular instrument reaches a position in the blood vessel.

[0015] The method may further include determining, by the one or more processors, a mean pressure waveform by identifying a first pressure measurement of the plurality of pressure measurements as the intravascular instrument is advanced to the region of interest.

[0016] The method may further include: the intravascular instrument is one of a pressure wire or an intravascular imaging tool or a catheter. The intravascular imaging tool may be an optical coherence tomography ("OCT") probe or an intravascular ultrasound ("IVUS") probe.

[0017] The intravascular instrument may have pressure sensing capabilities, with a pressure transducer coupled to the pressure assessment port.

[0018] Another aspect of the present disclosure includes a system comprising one or more processors configured to receive a plurality of pressure measurements at a location within a blood vessel. The one or more processors can determine an average transit time of blood within the blood vessel based on the plurality of pressure measurements, wherein the determination is independent of a blood vessel temperature measurement.

[0019] The system may further include an intravascular instrument in communication with one or more processors configured to acquire the plurality of pressure measurements.

[0020] 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 average transit time.

[0021] The one or more processors may be further configured to determine a mean pressure measurement and create a distribution curve based on the determined mean pressure measurement.In addition, the one or more processors may determine an average transit time of blood within the vessel based on the distribution curve.

[0022] The system may further include one or more of the processors that determine the average transit time by determining a ratio of an integral of a given average pressure measurement multiplied by a time measured at the given pressure to an integral of the given average pressure measurement.

[0023] The one or more processors can be configured to use multiple cycles of multiple intravascular data including pressure readings before, during, and after the intravascular instrument reaches a position in the blood vessel. The one or more processors can be configured to integrate the distribution curve in determining the average transit time.

[0024] The intravascular instrument can be one of a pressure wire with pressure sensing capability, a catheter, or an intravascular imaging tool. The intravascular imaging tool can be an OCT probe or an IVUS probe with a cleaning port.

[0025] The system may further include an intravascular instrument that acquires a plurality of pressure measurements distal to the region of interest in the blood vessel.

[0026] The system may further include a column of fluid within the intravascular device, wherein the fluid may be saline, a contrast agent, or a hemocompatible fluid.

[0027] Another aspect of the present disclosure relates to a pressure sensing catheter comprising: a hypotube configured to deliver a blood-compatible fluid to a target area of ​​a blood vessel; an outer member having a proximal end and a distal end, wherein the proximal end is secured to the hypotube; an inner member having a proximal end and a distal end, wherein the proximal end of the inner tube is secured to the outer member; and at least one aperture located on the distal end of the outer member, the aperture permitting measurement of pressure at a location within the blood vessel.

[0028] The pressure sensing catheter may further include one or more processors coupled to the pressure sensing catheter, the pressure sensing catheter configured to receive the pressure measurements, and to determine, by the one or more processors, an average transit time of blood within the vessel based on the plurality of pressure measurements, wherein the determination is independent of the temperature measurement.

[0029] The pressure sensing catheter may be coupled to a pressure transducer in fluid communication with the at least one aperture on the distal end of the outer member.

[0030] The pressure sensing catheter may be further coupled to one or more processors configured to determine at least one of a CFR value or an IMR value based on the determined average transit time.

[0031] The pressure sensing catheter can be further coupled to one or more processors configured to determine an average pressure measurement and create a profile based on the determined average pressure measurement. The one or more processors can determine an average transit time of blood within the vessel based on the profile.

[0032] The pressure sensing catheter may be further coupled to one or more processors configured to determine a ratio of an integral of a product of a given mean pressure measurement and a time for the given mean pressure measurement to an integral of the given mean pressure measurement.

[0033] The pressure sensing catheter can be coupled to one or more processors that are further configured to determine an average pressure measurement using multiple cycles of intravascular data including pressure readings before, during, and after the intravascular instrument reaches position in the blood vessel.

[0034] The pressure sensing catheter may be coupled to one or more processors further configured to integrate the profile when averaging the transit times.

[0035] The pressure sensing catheter can acquire multiple pressure measurements distal to the region of interest.

[0036] The method may further include determining, by the one or more processors, the average transit time using the value of the area defined by the lowest point of the distribution curve. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is an exemplary system including a pressure line according to aspects of the present disclosure.

[0038] Figure 2 is a diagram of an experimental setup according to aspects of the present disclosure.

[0039] Figure 3 is an exemplary system including an intravascular imaging probe according to aspects of the present disclosure.

[0040] Figure 4 is a diagram of an experimental setup according to aspects of the present disclosure.

[0041] Figure 5 is an exemplary system with a pressure sensing catheter according to aspects of the present disclosure.

[0042] Figure 6A and Figure 6B is a cross-sectional view of the distal end of the pressure sensing catheter.

[0043] Figure 7 is an exemplary system with an OCT catheter according to aspects of the present disclosure.

[0044] Figure 8 is an exemplary system having a delivery catheter according to aspects of the present disclosure.

[0045] Figure 9 is an exemplary average pressure waveform from a raw pressure sensor measurement.

[0046] Figure 10A are examples of pressure dilution curves according to aspects of the present disclosure and examples of functional representations of average transit time according to aspects of the present disclosure.

[0047] Figure 10B is another example of a pressure dilution curve according to aspects of the present disclosure and an example of a functional representation of average transit time according to aspects of the present disclosure.

[0048] Figure 11A is another example of a pressure-dilution curve according to aspects of the present disclosure, and

[0049] Figure 11B is an example of a functional representation of average transit time according to aspects of the present disclosure.

[0050] Figure 12A is a scatter plot of the experimental results for determining the mean transit time based on the thermodilution method and the true flow rate.

[0051] Figure 12B It is a scatter plot of the experimental results of determining the mean transit time based on the thermodilution method and the area under the curve method.

[0052] Figure 12C It is a scatter plot of the experimental results of determining the average transit time based on the area under the curve method and the true flow rate.

[0053] Figure 13A is a flow chart of a method of determining the average transit time of blood within a blood vessel according to aspects of the present disclosure.

[0054] Figure 13B is a flow chart of an alternative method of determining the mean transit time of blood within a blood vessel in accordance with aspects of the present disclosure. DETAILED DESCRIPTION

[0055] The present technology provides one or more aspects of identifying and / or diagnosing microvascular disease within a blood vessel using a single intravascular instrument. For example, blood flow can be determined using only pressure measurements, without the need for temperature measurements required by existing systems. By using a single intravascular instrument, patient risk during surgery is reduced because fewer incisions may be made, fewer instruments may be inserted into the patient's body, and the time spent in the surgery / operating room may be reduced. In some examples, by using a single intravascular instrument, microvascular disease in a patient can be diagnosed more efficiently because the physician is able to collect more data at once.

[0056] According to some examples, an intravascular instrument can be used to collect intravascular data of a blood vessel. The intravascular data can be, for example, a pressure measurement. The intravascular data can be used to determine the average transit time of blood within the blood vessel. In some examples, the average transit time can be determined at rest and / or during hyperemia. The average transit time determined based on the pressure measurement can be used to determine the coronary flow reserve ("CFR"), the microcirculatory resistance index ("IMR"), or other diagnostic indices. The CFR and / or IMR values ​​can be used to diagnose microvascular disease. According to some examples, the pressure measurement and / or any value determined using the pressure measurement can be used to assess lesions within the blood vessel, assess potential stent implantation, diagnose microvascular disease, etc.

[0057] According to some examples, additional factors can be used in combination with the determined CFR and / or IMR to identify one or more aspects of microvascular disease within a vessel. The additional factors can include, for example, the patient's age, sex, body mass index ("BMI"), medical history, vessel type, vessel condition, treatment history, etc. The medical history can include, for example, known heart failure, previously diagnosed diabetes, hypertension, etc. The vessel type can include the left anterior descending ("LAD") artery, the left circumflex artery ("LCX"), the right coronary artery ("RCA"), the left marginal artery, the diagonal artery, the right marginal artery, etc. The treatment history can include, for example, previous percutaneous coronary intervention ("PCI"), coronary artery bypass grafting ("CABG"), etc.

[0058] By using pressure measurements as an alternative to temperature measurements, the systems and software used to calculate average transit time can operate without strictly adhering to parameters regarding the method of injecting the medication. Thus, errors that might otherwise result from injecting the medication at an imperfect time or temperature can be reduced. Additionally, the intravascular instrument would not require temperature sensing capabilities, thereby reducing the cost and complexity of the required instrumentation. For example, average transit time can be determined by using a pressure transducer connected to the wash port of an OCT catheter to acquire pressure measurements, and using pressure measurements to determine the average transit time can eliminate the need to insert a pressure line. This can reduce the risk of complications during the procedure. Additionally, or alternatively, using a catheter to determine the average transit time can allow the average transit time to be read and calculated in real time. In some examples, the average transit time determined using a pressure-dilution curve can be used to determine CFR data and / or to determine IMR data. Thus, the pressure-dilution curve can be used to determine physiological information as well as anatomical information.

[0059] Figure 1A data acquisition system 100 for acquiring intravascular data is described. The system may include an intravascular instrument that can be used to acquire data within a blood vessel 102. The intravascular instrument may be a pressure line, a pressure sensing catheter, an OCT probe, a micro-OCT probe, a near-NIRS sensor, or an IVUS catheter. Figure 1 The use of a pressure wire is illustrated, but the use of a pressure wire is not limiting. An IVUS catheter, NIRS sensor, OCT probe, etc. can be used in combination with or in place of a pressure wire, as described in 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 in the blood vessel where there is high calcium or plaque accumulation that has restricted blood flow or a location where a stent may be needed.

[0060] According to some examples, pressure line 104 can be introduced and held stationary so that multiple intravascular measurements can be captured. Pressure line 104 can be held stationary distal to the region of interest so that distal pressure measurements can be captured. A medication can be injected into vessel 102 through the purge port at a location such that the medication flows through pressure line 104. Pressure line 104 can capture intravascular measurements as the medication passes through. According to some examples, the saline solution can be room temperature or at the patient's body temperature. The intravascular measurements captured by pressure line 104 can be used to identify characteristics of vessel 102.

[0061] Pressure line 104 may be communicatively connected to subsystem 108 via a wired or wireless connection. Subsystem 108 may include a receiver 110 that transmits signals to a computing device 112. Computing device 112 may include one or more processors 113, memory 114, instructions 115, data 116, and one or more modules 117.

[0062] 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 a dedicated device, such as an application specific integrated circuit (ASIC), or other hardware-based processor. Figure 1The processor, memory and other elements of device 110 are functionally illustrated within the same box, but one of ordinary skill in the art will understand that the processor, computing device or memory may actually include multiple processors, computing devices or memories that may or may not be stored in the same physical housing. Similarly, the memory may be a hard disk or other storage medium located in a housing that is different from the housing of device 112. Therefore, references to a processor or computing device will be understood to include references to a collection of processors, 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 via a wired network or a wireless network (such as the Internet). The remote processor may perform some or all of the calculations and coordinate with computing device 112.

[0063] Memory 114 can store information accessible by the processor, including instructions 115 executable by the processor 113, and data 116. Memory 114 can be a type of memory operable to store information accessible by the processor 113 (including non-transitory computer-readable media), or other media that stores data readable by electronic means, such as a hard disk, a memory card, a read-only memory ("ROM"), a random access memory ("RAM"), an optical disk, and other writable and read-only memories. The subject matter disclosed herein can include different combinations of the foregoing, whereby different portions of the instructions 115 and data 116 are stored on different types of media.

[0064] Memory 114 can be retrieved, stored, or modified by processor 113 according to instructions 115. For example, although the present disclosure is not limited to a particular data structure, data 116 can be stored in a computer register, stored in a relational database as a table with multiple different fields and records, stored in an XML document, or a flat file. Data 116 can also be formatted in a computer-readable format, such as, but not limited to, binary values, ASCII code, or Unicode. By way of further example only, data 116 can be stored as a compressed or uncompressed bitmap composed of pixels, or computer instructions for drawing graphics. In addition, data 116 can include information sufficient to identify the relevant information, such as numbers, descriptive text, proprietary codes, pointers, references to data stored in other memories (including other network locations), or information used by functions to calculate related data.

[0065] Instructions 115 may be any set of instructions that are directly executed (e.g., machine code) or indirectly executed (e.g., scripts) by processor 113. In this regard, the terms "instructions," "application," "steps," and "program" may be used interchangeably herein. Instructions may be stored in object code format for direct processing by a processor, or in any other computing device language, including scripts or collections of independent source code modules that are interpreted on demand or compiled in advance. The functions, methods, and routines of the instructions are explained in detail below.

[0066] Modules 117 may include a plaque (e.g., calcium plaque), a detection module, a display module, a flow rate or average transit time module, a pressure change module, a temperature change module, a stent detection module, or other detection and display modules. For example, computing device 112 may access a flow rate module for detecting the average transit time of blood in a blood vessel.

[0067] Subsystem 108 may include a display 118 for outputting information to the operator. As shown, display 118 is separate from computing device 112. However, according to some examples, display 118 may be part of computing device 112. Display 118 may output pressure data related to one or more features detected in the blood vessel. For example, the output may include, but is not limited to, pressure data, thermodilution data, aortic and distal pressures, pressure-based risk markers for stent expansion, flow rate, etc. Display 118 may identify features using values, text, arrows, color coding, highlighting, outlines, animations, or other suitable human- or machine-readable indicia. For example, if the pressure of blood within the vessel is within a given range of pressure measurements, the display may display green, and if the pressure is outside this range, the display may display red. This range may be programmed by the operator, preset within the processor, or configured by artificial intelligence within the processor. The display may output graphics such as icons, pictures, graphs, or other visual images. The display may also output an animation depicting a patient's blood vessel with blood flowing through it at a rate corresponding to the determined mean transit time.

[0068] According to some examples, the display 118 may include a graphical user interface ("GUI"). One or more steps may be performed automatically or without user input to navigate images, enter information, select input, and / or interact with input, etc. The display 118, alone or in combination with the computing device 112, may allow switching between one or more viewing modes in response to user input. For example, a user may be able to switch between different side branches on the display 118, for example, by selecting a particular side branch and / or by selecting a view associated with a particular side branch.

[0069] In some examples, display 118, either alone or in combination with computing device 112, may include a menu. This menu may allow a user to display or hide various features. There may be more than one menu. For example, a menu may be provided for selecting vessel features to display. Additionally or alternatively, a menu may be provided for selecting a target region of a vessel where pressure measurements may be acquired.

[0070] Figure 2 Illustrated is a system for data acquisition system 100. System 100 includes pressure line 104, subsystem 108 (including receiver 110), computing device 112 and display 118, physiological phantom 120, and guide catheter 121. The system as depicted can simulate a clinical scenario for acquiring pressure measurements using intravascular instrumentation.

[0071] The physiological phantom 120 simulates vascular physiology and represents the human vascular system. It is a combination of hardware and software used to simulate blood flow through a patient's heart for benchtop experiments. The phantom's hardware represents the branches of the coronary arteries. The phantom's software controls the internal hardware, generating conditions found within the coronary arteries (e.g., waveforms similar to a beating heart).

[0072] The guide catheter 121 can be used to introduce the pressure line 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 or the like) that can be used for percutaneous coronary intervention (PCI) surgery. 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, adenosine can be used to pharmacologically induce hyperemia, 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 connection or a wireless connection. The receiver can collect aortic pressure readings and transmit them to the subsystem 108 for intravascular calculation.

[0073] According to some examples, the pressure wire 104 can be inserted into the physiological phantom 120 via 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 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 connection or a wireless connection. In an example where the connection is a wireless connection, the pressure wire 104 and the receiver 110 can communicate via Bluetooth, near field communication ("NFC"), Wi-Fi, or other short-range communication interfaces.

[0074] According to some examples, subsystem 108 can include components within a single housing, external to a housing, or in multiple housings. As shown, receiver 110 is located in a separate housing and is wirelessly connected to a single housing containing computing device 112 and display 118, as described above.

[0075] Figure 3 Another data acquisition system 200 for acquiring intravascular pressure data is illustrated. System 200 can operate the same or substantially the same as system 100. The components of system 200 can be similar to system 100, except that the intravascular instrument of system 200 is a pressure sensing catheter 221 instead of pressure line 104. The system can be coupled to an intravascular imaging probe, such as an OCT probe, a micro-OCT, a NIRS sensor, or an intravascular ultrasound ("IVUS") probe. Catheter 221 can be equipped with a distal port 203. In some examples, distal port 203 can be located within the catheter and coupled to an external pressure transducer. In some examples, the pressure transducer can be coupled to a pressure assessment port of catheter 221.

[0076] Although only one distal hole 203 is depicted, this is not intended to limit the number of distal holes 203 on the catheter 221. In one example, the distal hole 203 can be positioned at the distal end of the catheter. Additionally or alternatively, one or more holes can be positioned near the middle section of the catheter. Additionally or alternatively, one or more holes can be positioned near the proximal end of the catheter. In yet another example, one or more holes can be present anywhere on the body of the catheter, for example, one or more holes at the distal end of the catheter and one or more holes at the middle section of the catheter.

[0077] Figure 4 Illustration of a benchtop setup of a data acquisition system with intravascular imaging tools, similar to Figure 3 . System 200 includes a pressure assessment port 220 of an imaging tool connected to a pressure transducer 222, which is connected to a subsystem 208, which includes a receiver 210, a computing device 212, and a display 218, and is connected to a distal port 203 (not shown). A catheter 221 is inserted into a physiological phantom 120. The system as depicted can simulate a clinical scenario for acquiring pressure measurements using intravascular instruments.

[0078] The distal hole 394 can be in fluid communication with the pressure transducer 222. The pressure transducer 222 can be coupled to the pressure assessment port 220 at the end of the catheter 221. The pressure transducer 222 can be communicatively connected to the receiver 210 via a wired connection or a wireless connection to collect multiple pressure measurements. The catheter 221 can be filled with an incompressible fluid before being inserted into the blood vessel. The incompressible fluid can be composed of a contrast agent, saline, a fluid compatible with blood, or other media. The pressure transducer 222 can measure the hydraulic column pressure of the catheter 221 when the catheter 221 is inserted into the blood vessel.

[0079] For example, the distal port can be positioned distal to the region of interest. The hydraulic pressure of the catheter can be varied based on the physiological conditions of the vessel in which the distal port is located. Specifically, narrowing or widening of the vessel can increase or decrease blood pressure. When inserted into the vessel, the pressure transducer 222 can receive a pressure reading of the vessel at the distal port. The user can select a region of interest for the system to use in calculations.

[0080] The sequence of pressure measurements can show the condition of the blood vessel before, during, and after the distal orifice reaches the region of interest. The sequence of pressure measurements can be used to determine the flow rate of blood within the vessel. For example, each pressure measurement can include a timestamp indicating when the pressure measurement was taken at distal orifice 203. In some examples, pressure measurements can be taken at predetermined time intervals and marked as such. For example, as the catheter advances to the region of interest, the system can record pressure measurements every 0.01 seconds. The pressure within vessel 202 can be determined. The determined pressure measurements within the vessel where distal orifice 203 is located can be used, along with the timestamps or time intervals, to determine the flow rate and, therefore, the average transit time of blood within the vessel. As described more fully below with respect to FIG. 12 , the average transit time can be determined based on the ratio of the integral of the average pressure measurement at a given time multiplied by the time to the integral of the average pressure measurement at that time.

[0081] In this example, pressure transducer 222 can be communicatively connected to subsystem 208 via wireless or wired connection 206. Subsystem 208 can include receiver 110 that transmits the pressure signal to computing device 212.

[0082] Figure 5 An exemplary system is illustrated that employs a catheter configured to measure pressure changes within a blood vessel. Catheter 321 can be any catheter that can be connected to a pressure transducer.

[0083] The catheter 321 may include a proximal end having a side arm and a hypotube 341. The side arm and hypotube 341 may help deliver contrast media, saline, or a blood-compatible fluid to a target area of ​​a blood vessel. The catheter 321 may further include a distal end having two polymer components. The two polymer components may be an outer member 342 and an inner member 343. The outer member 342 may be fixed to the hypotube 341, for example, by being directly coupled to the hypotube 341. The inner member 343 may be coupled to the outer member 342 to form a rapid exchange (RX) notch. In some embodiments, the catheter may be configured as an on-line catheter with side arms. The inner member 343 may provide a device for delivering the catheter 321 on a guide wire 344. The space between the outer member 342 and the inner member 343 may provide space for an incompressible fluid column (such as a contrast medium, saline, or a blood-compatible fluid) to the target blood vessel. This fluid column enables measurement of direct pressure in the blood vessel at the distal hole 303 of the catheter 321 .

[0084] In some examples, catheter 321 can include a distal hole (e.g., distal hole 303) on the distal end of the catheter. Distal hole 303 can be positioned at the distal end of catheter 321. At the location of distal hole 303, the fluid column is subjected to changes in the blood vessel (such as changes in blood pressure). In some embodiments, distal hole 303 can capture changes in the blood vessel as vascular data and transmit the vascular data to the pressure transducer via catheter 321. Once the vascular data is received at distal hole 303, the pressure transducer can acquire direct pressure measurements.

[0085] In some examples, distal hole 303 can be positioned at the distal end of catheter 321. Distal hole 303 can be positioned perpendicular to the flow of blood in the blood vessel. Alternatively, distal hole 303 can be located on the outer surface of outer member 342 and parallel to the flow path.

[0086] Although only one distal hole 303 is depicted, this is not intended to limit the number of distal holes that can be coupled to and / or integrated with the catheter 321. In some examples, multiple holes are distributed circumferentially around the outer member. In another example, the holes can be distributed laterally along one or more portions of the outer member.

[0087] A heat treatment can be used to form the holes in the outer member 342. The holes can be formed with a special contour around the edge of the hole. When blood passes through the hole, the contour can prevent fluid turbulence.

[0088] The hole can have a diameter of 0.01 mm. 2 Up to 4mm 2 In some examples, the holes have a size of 0.025 mm. 2 Up to 2mm 2The shapes of the holes can vary, such as circular, square, triangular or any polygonal shape.

[0089] Figure 6A Pictured Figure 5 FIG3 is a cross-sectional view of the distal end of the catheter 321 described in FIG3. The distal end of the catheter 321 may include an outer member 342 and an inner member 343. The outer member 342 may be provided with a distal hole 303. The inner member may provide a path for a guide wire 344 to pass through to properly place the catheter 321 in the blood vessel.

[0090] Figure 6B Another cross-sectional view of the distal end of the catheter is shown, showing two distal apertures. The distal end of catheter 321 may include an outer member 342 and an inner member 343. Outer member 342 may have two distal apertures 303 and 303'. Multiple distal apertures can provide more accurate vascular pressure measurements. The inner member may provide a path for a guidewire 344 to pass through, ensuring proper placement of catheter 321 within a blood vessel.

[0091] Figure 7 The diagram is similar to Figure 5 , but equipped with an imaging tool. Catheter 421 can have at least one distal port 403, a liquid seal 422, and a wash port 423. Catheter 421 can also have a guidewire entry point 441 and a guidewire exit point 442. In this example, catheter 421 has imaging tool 404, which is an OCT probe and thus can have a fiber optic connector 431, an OCT lens 432, and radiopaque markers 433. In other examples, imaging tool 404 can be an IVUS probe, a NIRS probe, a micro OCT probe, etc.

[0092] In this example, the cleaning port 423 replaces the Figure 4 The distal port can be connected to the purge port 423 via a pressure transducer. The pressure transducer can be communicatively connected to a receiver via a wired or wireless connection to acquire multiple pressure measurements. The pressure proximal to the region of interest, also known as aortic pressure, can be measured by a guide catheter according to methods known in the art.

[0093] The catheter can hold a column of incompressible fluid to facilitate pressure measurement at the location of the distal hole 403. In this example, the incompressible fluid can be any blood-compatible fluid (e.g., saline or other suitable medium) that does not interfere with the imaging tool. The fluid column is held in place by a liquid seal 422. The liquid seal 422 prevents the agent from moving away from the distal end of the catheter 421. The fluid column is maintained around the imaging tool 404. The cleaning port 423 can be used to push the fluid agent to the area of ​​interest to properly image the area. The cleaning port 423 can be used to fill the catheter 421 with a fluid column for pressure measurement.

[0094] The distal port 403 can be positioned distal to the region of interest such that the pressure transducer measures the pressure distal to the region of interest at the distal port 403. Measurements are initiated when the distal port reaches the region of interest. As the distal port 403 approaches the region of interest, the pressure transducer can acquire multiple distal pressure measurements of the region of interest continuously or at a high acquisition rate. Pressure measurements can be taken by the pressure transducer at the distal port within the blood vessel before, during, and after the distal port reaches the region of interest. The pressure measurements can be expressed as a function of time and provide a curve of pressure across the region of interest. As described below with respect to Figure 8 to Figure 1 0 explained in more detail, this function is used to determine the average transit time of blood. Pressure measurements can be used to determine the flow rate of blood within a vessel. For example, each pressure measurement can be assigned a corresponding timestamp based on the location of the distal orifice 403 when the pressure measurement was taken (e.g., before, during, and after the distal orifice reaches the area of ​​interest). In some examples, pressure measurements can be taken at predetermined time intervals and marked as such. For example, as the catheter advances to the area of ​​interest, the system can record pressure measurements every 0.01 seconds. Pressure measurements of the vessel at the distal orifice 403 can be used to determine the flow rate, and therefore the average transit time of blood within the 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)).

[0095] Figure 8 The diagram is similar to Figure 5 , but equipped with a delivery device. Catheter 521 may have at least one distal port 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 having a balloon 553 at its distal end. The delivery catheter may have a port 552 at its proximal end. This port can be used to facilitate delivery of the device, such as by inflating and deflating balloon 553.

[0096] The catheter 521 and the delivery catheter 551 can be simultaneously advanced into the blood vessel to reach the area of ​​interest. Figure 4 and Figure 5 As described in

[15] , the catheter can be configured to maintain a fluid column to measure the pressure at distal port 503 as the catheter is advanced through the vessel. A pressure transducer can collect pressure measurements at distal port 503. The combined pressure assessment catheter and delivery device can provide real-time pressure measurements immediately before and after placement of an interventional device. For example, a stent can be placed on balloon 553 and catheter 521, and delivery catheter 551 can be advanced to the stent deployment site. Once the stent deployment site is reached, distal port 503 can be located outside the site, with balloon 553 and stent located within the site. A pressure transducer can collect pre-implantation pressure readings at distal port 503. The user can inflate balloon 553 by injecting a solution, such as saline, into port 552 and into balloon 553. Balloon 553 can be inflated to deploy the stent at the stent deployment site within the vessel. The user can deflate balloon 553 by removing the solution from port 552. Once normal flow is restored through the now stented area, the pressure transducer can begin collecting post-implantation pressure measurements at the distal port 503. This allows the user to verify the correct implantation of the interventional device in real time. Using these instantaneous pressure measurements, the operator can make decisions about whether to readjust the interventional device. This reduces the duration of the procedure, thereby reducing potential health risks to the patient.

[0097] Figure 9 The diagram illustrates raw pressure measurements and an averaged pressure waveform. Distal pressure measurements acquired by an intravascular instrument are processed within the subsystem. Pressure measurements from the intravascular instrument can be plotted on a graph as depicted in 610. Pressure measurements are plotted sequentially on graph 610 based on their timestamps or time intervals. Raw pressure data 611 can be plotted with a cardiac cycle waveform 612. A representation of raw pressure measurements 611 is used to create an averaged waveform 613.

[0098] The one or more processors can determine the initial time that the distal orifice reaches a region or interval of interest ("ROI") (e.g., a stenotic region) by identifying the first spike in the pressure readings of a plurality of pressure measurements collected as the intravascular instrument moves through the region of interest. Where the spike begins to decrease, the distal orifice has passed the stenotic region. An average waveform 613 is calculated using a specific number of measurement cycles at the ROI. These cycles may include measurements taken just before and just after the intravascular instrument reaches the ROI. For example, the eight cycles used to calculate the average waveform include the peak from the ROI as well as four cycles before and four cycles after the peak.

[0099] The system can use raw pressure measurements of the same cycle length for average waveform 613 from before or after the segment with the ROI as a template sequence for comparison. For example, eight cycles including the ROI ("ROI sequence") can be used to calculate average waveform 613, and eight cycles after the ROI sequence can be used as a template to calculate average waveform 613. Once average waveform 613 is determined, it can be plotted as depicted in 620, where a specific cycle of raw pressure measurements 611 was used to obtain average waveform 613.

[0100] Figure 10A An exemplary pressure-dilution curve is illustrated. Pressure-dilution curve 710 illustrates pressure measurements at an intravascular instrument at a given time as a distal port is advanced through a vessel past an ROI. For example, pressure-dilution curve 710 can plot pressure measurements in inches of mercury (inHg) based on the time at which the measurements were taken. An initial time and an applied lognormal fit can be used to determine the average transit time. Time is on the x-axis of the pressure-dilution curve.

[0101] The pressure dilution curve 710 can be used to determine the average transit time "T mn ". The average transit time can be the blood flow rate within the blood vessels.

[0102] The pressure dilution curve 710 may have a pressure measurement "p". In some examples, the pressure measurement "p" of the curve 710 may be defined by any one of a plurality of pressure measurements between a first pressure measurement and a last pressure measurement in a plurality of pressure readings acquired by the intravascular instrument as the pressure sensing catheter is advanced through the blood vessel. The pressure measurement "p" may be defined by any one of a plurality of pressure measurements between a first pressure measurement and a last pressure measurement in a plurality of pressure readings acquired by the intravascular instrument as the pressure sensing catheter is advanced through the blood vessel. Figure 10A The image is depicted at the region marked by the ROI.

[0103] The integral of curve 710 can be used to calculate the average vascular transit time "T mn The average transport time "T" can be determined using the initial time "t0". mn The initial time t0 is determined using the pressure dilution curve 710 and the starting point of the pressure measurement "p". For example, the average transit time can be determined using a ratio that is a function of the ratio of the product of time and the average pressure at the distal orifice within the blood vessel at a given time to the average pressure at the distal orifice within the blood vessel. According to some examples, the average transit time "T mn ” can be determined using the following equation:

[0104]

[0105] In this equation, "t" may correspond to time. This time may be the time corresponding to the timestamp of any given pressure measurement. "c" in the equation may correspond to the average pressure at the distal orifice at that time "t."

[0106] Figure 10B Another exemplary pressure-dilution curve is illustrated. Pressure-dilution curve 710 illustrates pressure measurements acquired by an intravascular instrument at a given time as a distal port is advanced through a vessel past an ROI. For example, pressure-dilution curve 710 can plot pressure measurements in inches of mercury (inHg) based on the time at which the measurements were taken. An initial time and an applied lognormal fit can be used to determine the average transit time. Time is on the x-axis of the pressure-dilution curve.

[0107] The pressure dilution curve 710 can be used to determine the average transit time "T mn ". The average transit time can be the blood flow rate within the blood vessels.

[0108] The pressure dilution curve 710 may have a pressure measurement "p". In some examples, the pressure measurement "p" of the curve 710 may be defined by any one of a plurality of pressure measurements between the first pressure measurement at the distal aperture reaching the ROI and the point at which the pressure reading begins to rapidly decrease. The pressure measurement "p" may be defined by any one of a plurality of pressure measurements between the first pressure measurement at the distal aperture reaching the ROI and the point at which the pressure reading begins to rapidly decrease. Figure 10B The image is depicted in the region marked by the ROI.

[0109] The integral of curve 710 can be used to calculate the average vascular transit time "T mn The average transport time "T" can be determined using the initial time "t0". mn The initial time t0 is determined using the pressure dilution curve 710 and the point at which the pressure measurement "p" begins to decrease. For example, the average transit time "T" may be determined by subtracting the initial time "t0" from the time at which the pressure reading begins to decrease. According to some examples, the average transit time "T" may be determined by subtracting the initial time "t0" from the time at which the pressure reading begins to decrease. mn ” can be determined using the following equation:

[0110] T mn =t1-t0

[0111] The average transit time can be determined at rest and during hyperemia. Determining the average transit time at rest can include acquiring one or more pressure measurements while the distal aperture is positioned distal to the region of interest in the vessel in a natural state. For example, the natural state can be a state in which the vessel is not undergoing any therapy or medication. Determining the average transit time during hyperemia can include acquiring one or more pressure measurements while the distal aperture is positioned distal to the region of interest in the vessel, which has been pharmacologically induced to undergo hyperemia to produce full dilation of the vessel.

[0112] Under current standards, users use temperature readings from a pressure line to determine average transit time. Specifically, the pressure line's temperature sensor is used to capture a thermodilution curve to determine average transit time. The thermodilution curve is defined by the points at which the temperature rises and falls as the cooled medication passes through a confined area, or ROI.

[0113] CFR can use the determined average transit time "T mn at rest ” and the average transit time during hyperemia “T mn at hyperemia " is determined as shown in the following equation:

[0114]

[0115] According to some examples, the average transit time "T mn at hyperemia " can be used to determine the IMR. For example, the IMR can be determined using the following equation:

[0116] IMR=P d at hyperemia ×T mn at h yperemia

[0117] In the equation, “P d at hyperemia " may correspond to the distal pressure during pharmacologically induced hyperemia. The distal pressure may be determined based on intravascular data acquired by the intravascular instrument. For example, a pressure measurement acquired by the intravascular instrument when located distal to the region of interest may be used as "P d at hypermia Based on Ohm's law, the pressure gradient (ΔP) can be equal to the flow rate (Q) multiplied by the resistance of the blood vessel (R), as shown in the following equation:

[0118] ΔP=QR

[0119] Flow rate can be calculated from the theoretical aortic and venous pressures through the resistance model.

[0120] Figures 11A to 11B An alternative method for calculating mean transit time in blood vessels is shown. Figure 9 Chart 610, Figure 11A810 . The pressure measurements are plotted in millimeters of mercury (mmHg) and in milliseconds (ms). The pressure measurements are plotted in sequence on the graph 810 based on their timestamps or time intervals. In some examples, there may be a moving average filter applied to the pressure measurements from the intravascular instrument, as shown in the raw pressure waveform 811. In some examples, the window length of the graph 810 may be equivalent to one cardiac cycle. Similar to Figure 9 Referring to the graph 610 in FIG. 8 , a filtered waveform 812 may be generated and overlaid on the raw pressure waveform 811 in the graph 810 .

[0121] Figure 11B Further processing of the filtered waveform 912 is depicted. The filtered waveform 912 may be processed by a subsystem. The subsystem may be similar to Figure 1 The subsystem 108 described in . The subsystem can be communicatively coupled to an intravascular tool (eg, a pressure line or catheter) having pressure sensing capabilities. Pressure readings from the intravascular instrument having pressure sensing capabilities can be transmitted to the subsystem.

[0122] In some examples, the subsystem can extract various landmarks along the filtered waveform 912 to aid in processing, analyzing the data, and determining characteristics of the vessel (e.g., mean transit time). The various landmarks can be extracted based on filters that are manually set or built into the subsystem. In some examples, the various landmarks can be automatically extracted based on previous data stored by the system or subsystem. The various landmarks in the filtered waveform 912 can include a zero anchor point 961, a rising point 962, a highest peak 963, a plateau point 964, a falling point 965, a falling point 966, and a negative peak 967. Based on the anchor point 961, the filtered waveform 912 is aligned with zero on the y-axis.

[0123] The filtered waveform 912 can be used to calculate the average transit time of the blood vessel. In some examples, the negative peak 967 falls below zero on the y-axis, resulting in a defined area 969 under the curve. Figure 11B In FIG. 1 , a defined area 969 is depicted as the shaded area below zero on the y-axis. Additionally, the time between the highest peak 963 and the negative peak 967 is depicted as time variation 968. The average transit time 968 can be calculated by multiplying the area of ​​the defined area 969 by the time variation 968. By including the time variation 968, the calculated average transit time is adjusted for the patient's heart rate. According to some examples, the average transit time "T mn ” can be calculated using the following equation:

[0124] T mn =a×b

[0125] In the equation, "a" may correspond to the area under the curve below the zero point of the y-axis, as described above as defined area 969. "b" in the equation may correspond to the amount of time between the highest peak 963 and the negative peak 967, described above as time variation 968.

[0126] 12A to 12C A comparison of results using thermodilution and area under the curve ("AUC") methods to determine mean transit time is shown. Figure 12A The true flow rate is shown as the thermodilution mean transit time. Therefore, the true flow rate and thermodilution mean transit time were measured and collected using an inline flow meter and pressure line as study controls and represent the industry standard for calculating mean transit time. Figure 12A The data represented in come from 122 samples with various combinations of pressure, flow rate, and heart rate.

[0127] Figure 12B The correlation between AUC mean transit time and the true flow rate is shown. The correlation coefficient between AUC mean transit time and the true flow rate is -0.77. Figure 12C The correlation between AUC mean transit time and thermodilution mean transit time is shown. 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, where values ​​above 0.7 or below -0.7 can be considered a strong correlation.

[0128] Figure 13A An exemplary method 1000 for determining the average transit time of blood within a blood vessel is illustrated. The following operations do not have to be performed in the exact order described below. Instead, various operations may be processed in a different order or simultaneously, and operations may be added or omitted.

[0129] In block 1001, multiple pressure measurements can be received. For example, a data acquisition system (e.g., system 100) can acquire multiple pressure measurements using an intravascular instrument. The pressure measurements can be acquired via a pressure line, a probe, or a catheter having one or more distal holes. The pressure measurements can be transmitted to the subsystem via 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 create a distribution curve based on the average pressure measurement.

[0130] In block 1002, an average transit time of blood within a blood vessel can be determined without a temperature reading. Using a distribution curve, one or more processors can determine the average transit time of blood within the blood vessel. When determining the average transit time of blood within the blood vessel, one or more processors can integrate the distribution curve. One or more processors can be configured to use the determined average transit time to determine at least one of a CFR value or an IMR value.

[0131] In block 1003 , the average transit time may be further determined using a ratio of the integral of the product of the given average pressure measurement and the time of the given average pressure measurement to the integral of the given average pressure measurement.

[0132] Figure 13B An exemplary method 1100 for determining the average transit time of blood within a blood vessel is illustrated. The following operations do not have to be performed in the exact order described below. Instead, various operations can be processed in a different order or simultaneously, and operations can be added or omitted. The method 1100 may include many steps related to Figure 13A The same features as described in method 1000.

[0133] Similar to method 1000, method 1100 may use a distribution curve of pressure readings to determine an average transit time of blood within a vessel, wherein the determination is independent of temperature measurements. In block 1103, the average transit time may be further determined using the value of the area defined by the lowest point of the distribution curve of the average pressure measurements. The distribution curve may be based on pressure measurements acquired by an intravascular instrument inserted into a patient's vessel. In some examples, the distribution curve may be derived from raw pressure measurements that are plotted sequentially based on their timestamps. The raw pressure measurements may be processed into the distribution curve using a moving average filter. The distribution curve may be compared to Figures 11A to 11B The filtered waveform 912 in is the same as described and undergoes similar processing.

[0134] In some examples, the average transit time can be determined using the area bounded by the lowest point of the distribution curve and the zero point of the y-axis. The average transit time can be further determined using the time variation between the highest and lowest points of the distribution curve.

[0135] The methods and devices disclosed herein will allow for simpler procedures, more consistent results, and take less time to obtain results. Methods that use temperature measurements to obtain average transit time require cooling the agent to a certain temperature before injecting it into the blood vessel. These methods require the operator to be highly skilled and to quickly handle the cooled material before the temperature drops. These methods are prone to error and may require multiple attempts to obtain an accurate reading. The methods disclosed herein avoid these problems by allowing the average transit time to be determined without the use of temperature, thereby reducing surgical time and therefore increasing patient safety. In addition, by determining the average transit time without the use of temperature measurements, the process of determining the average transit time is more cost-effective than other methods that require the use of electrical sensors in the blood vessel to achieve temperature measurement.

[0136] According to some examples, at least one of a CFR value or an IMR value may be determined based on a determined average transit time. For example, a CFR value may be determined by dividing a determined average transit time during rest by an average transit time during hyperemia. An IMR value may be determined by multiplying the average transit time during hyperemia by the distal pressure during hyperemia.

[0137] The determined CFR value and / or IMR can be used in conjunction with one or more patient factors to determine the presence of microvascular disease and potential treatment. For example, a physician can consider the patient's age, sex, BMI, medical history, vascular type, vascular condition, previous treatments, etc., in conjunction with the determined CFR and / or IMR value to determine the presence of any microvascular disease and / or potential treatment.

[0138] 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 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 age-specific parameters can be introduced based on training data. In some examples, the age-specific parameter can be a range of age to classify patients. The training data can be collected and used as input to a machine learning model. Based on 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.

[0139] In one example, microvascular resistance can be determined based on the determined average transit time, CFR value and / or IMR value, and the patient's gender. For example, the patient's gender can be input and processed together with the CFR value and / or IMR value to determine the microvascular resistance of the blood vessel. In some examples, the average transit time, CFR value and / or IMR value can be different 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. Based on the patient's gender and the average transit time, CFR value and / or IMR value, the machine learning model can determine the microvascular resistance of the blood vessel.

[0140] 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 vessels. According to some examples, one or more BMI parameters can be introduced based on training data. In some examples, the BMI parameter can be a range of age to classify patients. The training data can be collected and used as input to a machine learning model. Based on 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 vessels.

[0141] 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 medical history. For example, the patient's medical history (e.g., known heart failure) 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 state-specific parameters can be introduced based on training data. In some examples, the state-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 one or more state-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.

[0142] As another example, a patient's medical history (e.g., a known previous diagnosis of diabetes) can be input and processed along with CFR values ​​and / or IMR values ​​to determine the microvascular resistance of a blood vessel. According to some examples, one or more state-specific parameters can be introduced based on training data. In some examples, the state-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 one or more state-specific parameters and the mean transit time, CFR values, and / or IMR values, the machine learning model can determine the microvascular resistance of a blood vessel.

[0143] As another example, a patient's medical history (e.g., a known previous diagnosis of hypertension) can be input and processed along with CFR values ​​and / or IMR values ​​to determine the microvascular resistance of a blood vessel. According to some examples, one or more state-specific parameters can be introduced based on training data. In some examples, the state-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 one or more state-specific parameters and mean transit time, CFR values, and / or IMR values, the machine learning model can determine the microvascular resistance of a blood vessel.

[0144] In one example, microvascular resistance can be determined based on the determined mean transit time, CFR value and / or IMR value, and the diagnosed blood vessel type. For example, the patient's blood vessel type (e.g., the left anterior descending ("LAD") artery) 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 blood vessel-specific parameters can be introduced based on training data. In some examples, the blood vessel-specific parameters can be based on the blood vessel type. For example, the type can be LAD. Training data can be collected and used as input to a machine learning model. Based on one or more blood 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.

[0145] As another example, the patient's vessel type (e.g., the left circumflex artery ("LCX")) can be input and processed along with the CFR value and / or the IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be introduced based on the training data. In some examples, the vessel-specific parameters 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 the 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.

[0146] As another example, the patient's vessel type (e.g., right coronary artery ("RCA")) can be input and processed along with the CFR value and / or IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be introduced based on the 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 the 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.

[0147] As another example, the patient's vessel type (e.g., left marginal artery) can be input and processed along with the CFR value and / or IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be introduced based on the training data. In some examples, the vessel-specific parameters can be based on the vessel type. For example, the type can be the left marginal artery. The training data can be collected and used as input to the 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.

[0148] As another example, the patient's vessel type (e.g., diagonal artery) can be input and processed along with the CFR value and / or IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be introduced based on the training data. In some examples, the vessel-specific parameters can be based on the vessel type. For example, the type can be diagonal artery. The training data can be collected and used as input to the 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.

[0149] As another example, the patient's vessel type (e.g., right marginal artery) can be input and processed along with the CFR value and / or IMR value to determine the microvascular resistance of the vessel. According to some examples, one or more vessel-specific parameters can be introduced based on training data. In some examples, the vessel-specific parameters can be based on the vessel type. For example, the type can be the right marginal artery. The training data can be collected and used as input to the 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.

[0150] 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 treatment history. For example, the patient's treatment history (e.g., previous percutaneous coronary intervention ("PCI")) 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 treatment parameters can be introduced based on the training data. In some examples, the treatment parameters can be based on the patient's treatment history. For example, the patient may have previously undergone PCI. The previous PCI may have caused microvascular damage, which may need to be taken into account when determining the microvascular resistance of the blood vessel. The training data can be collected and used as input to the 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.

[0151] As another example, a patient's treatment history, such as coronary artery bypass grafting ("CABG"), can be input and processed along with CFR values ​​and / or IMR values ​​to determine the microvascular resistance of a blood vessel. According to some examples, one or more treatment parameters can be introduced based on the training data. In some examples, the treatment parameters can be based on the patient's treatment history. For example, the patient may have previously undergone CABG. CABG may change the physiological structure of the heart and / or may cause changes in the microvasculature, and therefore may need to 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 as well as the mean transit time, CFR values, and / or IMR values, the machine learning model can determine the microvascular resistance of a blood vessel.

[0152] The various aspects, examples, features and examples of the present disclosure should be considered as illustrative in all respects and are not intended to limit the present disclosure, the scope of which is limited only by the claims. For those skilled in the art, other examples, modifications and uses will be apparent without departing from the spirit and scope of the present invention.

[0153] Throughout this application, when a composition is described as having, including, or comprising specific components, or when a method is described as having, including, or comprising specific method steps, it is considered that the compositions of the present teachings also consist essentially of (or consist of) the described components, and that the methods of the present teachings also consist essentially of (or consist of) the recited method steps.

[0154] In this application, when an element or component is said to be included in and / or selected from a list of recited elements or components, it should be understood that the element or component can be any one of the recited elements or components and can be selected from a group consisting of two or more recited elements or components. In addition, it should be understood that the elements and / or features of the compositions, apparatuses, or methods described herein can be combined in various ways without departing from the spirit and scope of the invention, whether explicitly or implicitly stated herein.

[0155] The use of the terms "including," "comprising," or "having" should be generally understood as open and non-limiting unless specifically stated otherwise.

[0156] Unless otherwise specifically stated, singular forms used herein include plural forms (and vice versa). In addition, the singular forms "a," "an," and "the" include plural forms unless the context clearly dictates otherwise. In addition, when the term "approximately" is used before a quantitative value, the present teachings also include the specific quantitative value itself unless otherwise specifically stated. As used herein, the term "approximately" refers to a variation of ±10% of the nominal value. All numerical values ​​and ranges disclosed herein are deemed to include "approximately" before each numerical value.

[0157] Should be understood that, as long as the present invention remains operable, the order of steps or the order in which certain actions are performed is not important.In addition, two or more steps or actions can be performed simultaneously.

[0158] Where a range of values ​​or a list of values ​​is provided, each interval between the upper and lower limits of the range or list of values ​​is individually contemplated and included in the present invention, just as if each value were specifically enumerated herein. In addition, smaller ranges between and including the upper and lower limits of a given range are also contemplated and encompassed in the present invention. The enumeration of exemplary values ​​or ranges does not necessarily disclaim other values ​​or ranges between and including the upper and lower limits of the given range.

[0159] Although the present disclosure has been described with reference to specific examples, it should be understood that these examples are only intended to illustrate exemplary applications and implementations. It should be understood that various modifications can be made to the illustrative examples and that other arrangements can be designed without departing from the spirit and scope of the appended claims.

Claims

1. A method comprising: receiving, at one or more processors, intravascular data for a blood vessel, the intravascular data comprising a plurality of pressure measurements at locations within the blood vessel acquired by an intravascular instrument; and An average transit time of blood within the blood vessel is determined by the one or more processors based on the plurality of pressure measurements, wherein the determination is independent of temperature measurements.

2. The method of claim 1 , wherein determining the average transit time comprises: A ratio of an integral of a given mean pressure measurement multiplied by a time of the given mean pressure measurement to an integral of the given mean pressure measurement is determined by the one or more processors.

3. The method according to claim 2, further comprising: determining, by the one or more processors, an average pressure measurement based on the plurality of pressure measurements; A profile is created by the one or more processors based on the determined average pressure measurement. 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 comprise at least one of a value, a color, a graphic, or an animation. The method of claim 3 , wherein determining the average transit time of the blood within the blood vessel is further based on the distribution curve.

7. The method of claim 3, wherein determining the average transit time further comprises: A ratio of an integral of a product of a given average pressure measurement and a time for the given average pressure measurement to an integral of the given average pressure measurement is determined by the one or more processors.

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

9. The method of claim 3, wherein when determining the mean pressure measurement, the one or more processors are further configured to use multiple cycles of intravascular data including pressure readings before, during, and after the intravascular instrument reaches its position in the blood vessel.

10. The method of claim 1, wherein the intravascular instrument is one of 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 capabilities, wherein a pressure transducer is connected to a pressure assessment port.

13. The method according to claim 3, further comprising: The average pressure waveform is determined by identifying a first pressure measurement of the plurality of pressure measurements when the intravascular instrument is advanced to the region of interest.

14. A system comprising: One or more processors configured to: receiving intravascular data for a blood vessel, the intravascular data comprising a plurality of pressure measurements at locations within the blood vessel; and An average transit time of blood within the blood vessel is determined by the one or more processors based on the plurality of pressure measurements, wherein the determination is independent of temperature measurements.

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

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

17. The system of claim 14, wherein the one or more processors are further configured to: Determine the mean pressure measurement; and A profile curve is created based on the determined average pressure measurements.

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

19. The system of claim 18, wherein determining the average transit time further comprises: A ratio of an integral of a product of a given average pressure measurement and a time for the given average pressure measurement to an integral of the given average pressure measurement is determined by the one or more processors.

20. The system of claim 14, wherein determining the average pressure measurement further comprises: A plurality of cycles of intravascular data from a plurality of pressure readings including before, during, and after the intravascular instrument reaches a position in the blood vessel are used by the one or more processors.

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

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

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

24. The system of claim 14, wherein the plurality of pressure measurements are acquired distal to a region of interest in the blood vessel.

25. A pressure sensing catheter comprising: a hypotube configured to deliver a blood-compatible fluid to a vascular location; an outer member having a proximal end and a distal end, wherein the proximal end is secured to the hypotube; an inner member having a proximal end and a distal end, wherein the proximal end of the inner member is secured to the outer member; as well as At least one aperture is located on the distal end of the outer member, the aperture permitting pressure measurement at a location within the blood vessel.

26. The pressure sensing catheter of claim 25, wherein: One or more processors are coupled to the pressure sensing catheter, the pressure sensing catheter being configured to: receiving pressure measurements; as well as An average transit time of blood within the blood vessel is determined by the one or more processors based on the plurality of pressure measurements, wherein the determination is independent of temperature measurements.

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

28. 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 or an IMR value based on the determined average transit time.

29. The system of claim 25, wherein the one or more processors are further configured to: Determine the mean pressure measurement; and A profile curve is created based on the determined average pressure measurements.

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

31. The pressure sensing catheter of claim 26, wherein determining the average transit time further comprises: A ratio of an integral of a product of a given average pressure measurement and a time for the given average pressure measurement to an integral of the given average pressure measurement is determined by the one or more processors.

32. The pressure sensing catheter of claim 26, wherein determining the average pressure measurement further comprises using, by the one or more processors, multiple cycles of intravascular data from a plurality of pressure readings including before, during, and after the intravascular instrument reaches a position in the blood vessel.

33. The pressure sensing catheter of claim 26, wherein when determining the average transit time, the one or more processors are further configured to integrate the profile.

34. The pressure sensing catheter of claim 25, wherein the plurality of pressure measurements are acquired distal to a region of interest in the blood vessel.

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