Endothelial function monitoring system

Abstract

One example includes a computing system including: processing circuitry configured to: receive a first data set indicating changes in blood vessel diameter of a blood vessel of a patient over a time period; receiving a second data set indicating changes in blood vessel wall shear stress of the blood vessel over the time period; generate a transfer function based on the first data set and the second data set; determine a likelihood that the patient is experiencing endothelial dysfunction based on the transfer function; and output information indicative of the likelihood that the patient is experiencing endothelial dysfunction based on the determination.

Description

A0013002W001ENDOTHELIAL FUNCTION MONITORING SYSTEM

[0001] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 748,703, filed January 23, 2025, the entire content of which is incorporated herein by reference.TECHNICAL FIELD

[0002] The disclosure relates to devices and techniques for monitoring an endothelial function of a patient.BACKGROUND

[0003] Electrical stimulation of nerves, such as the vagus nerve, renal nerve, splenic nerve, etc., has been shown to be useful for a wide range of purposes. Some medical device systems include therapy delivery elements that may deliver neuromodulation therapy to target nerve(s) from within a blood vessel of the patient.SUMMARY

[0004] Endothelial dysfunction is a cardiac disease that affects cells along inner surface(s) of blood vessel(s) of the patient. When a patient experiences endothelial dysfunction, the blood vessel(s) of the patient may become restricted, which may increase the risk of the patient experiencing other cardiovascular conditions. A clinician may deliver neuromodulation therapy to target nerve(s) of the patient (e.g., to renal nerve(s) of the patient), which may improve vascular function of the patient and / or reduce endothelial dysfunction experienced by the patient. The clinician may need to first determine whether the patient is experiencing endothelial dysfunction prior to delivery of the neuromodulation therapy.

[0005] Some methods for determining endothelial dysfunction include assessing patient response to a pharmaceutical substances and / or to reactive hyperaemia. In both cases, a pharmaceutical substance may need to be ingested and / or a particular portion of the patient (e.g., a limb of the patient) may need to be cuffed, both of which increase patient discomfort. Additionally, the requirement to cuff a portion of the body of the patient to induce reactive hyperaemia may limit a number of possible monitoring locations on the body of the patient.A0013002W001

[0006] This disclosure is directed to devices, systems, and methods for assessing the endothelial function of the patient based on non-invasive techniques. Ultrasound and / or laser speckle flow measurement devices may obtain blood vessel wall shear rate changes and changes in blood vessel size, e.g., without requiring the application of pharmaceutical substances and / or ligatures to the patient. Thus, the techniques described herein may reduce patient discomfort and / or increase a range of possible monitoring locations on the body of the patient. That is, the example techniques may improve the technology of determining endothelial function by integrating techniques related to wall shear rate changes and blood vessel size changes into a practical application for determining endothelial function in a way that reduces patient discomfort and increases a range of possible monitoring locations.

[0007] The blood vessel wall shear rate changes and the blood vessel size changes may be spontaneous values and may be continuously monitored over a set period of time. The techniques described herein may allow for identification of changes in the blood vessel size due to endothelial dysfunction and isolate the identified changes from other factors (e.g., due to respiration by the patient, due to the cardiac cycle of the patient). Thus, the techniques described herein may provide for a more accurate indication of the endothelial function of the patient. The continuously monitoring the patient may allow the devices, systems, and methods described herein to produce real-time indications of patient endothelial function and / or trends in patient endothelial function, which may provide the clinician may a more extensive indication of the endothelial status of the patient, which in turn may indicate whether the patient is a candidate for other therapies such as delivering stimulation to renal nerves to address the endothelial dysfunction.

[0008] In some examples, this disclosure is directed to a computing system comprising: processing circuitry configured to: receive a first data set indicating changes in blood vessel diameter of a blood vessel of a patient over a time period; receive a second data set indicating changes in blood vessel wall shear stress of the blood vessel over the time period; generate a transfer function based on the first data set and the second data set; determine a likelihood that the patient is experiencing endothelial dysfunction based on the transfer function; and output information indicative of the likelihood that the patient is experiencing endothelial dysfunction based on the determination.

[0009] In some examples, this disclosure is directed to a method comprising: receiving, by processing circuitry of a computing system, a first data set indicating changes in blood vessel diameter of a blood vessel of a patient over a time period; receiving, by the processing circuitry, a second data set indicating changes in blood vessel wall shear stress of the bloodA0013002W001vessel over the time period; generating, by the processing circuitry, a transfer function based on the first data set and the second data set; determining, by the processing circuitry, a likelihood that the patient is experiencing endothelial dysfunction based on the transfer function; and outputting, by the processing circuitry, information indicative of the likelihood that the patient is experiencing endothelial dysfunction based on the determination.

[0010] In some examples, this disclosure is directed to a computer-readable medium comprising instructions that, when executed by processing circuitry of a computing system, causes the processing circuitry to: receive a first data set indicating changes in blood vessel diameter of a blood vessel of a patient over a time period; receive a second data set indicating changes in blood vessel wall shear stress of the blood vessel over the time period; generate a transfer function based on the first data set and the second data set; determine a likelihood that the patient is experiencing endothelial dysfunction based on the transfer function; and output information indicative of the likelihood that the patient is experiencing endothelial dysfunction based on the determination.

[0011] Further disclosed herein is a computing system including: processing circuitry configured to: receive a first data set indicating changes in blood vessel diameter of a blood vessel of a patient over a time period; receiving a second data set indicating changes in blood vessel wall shear stress of the blood vessel over the time period; generate a transfer function based on the first data set and the second data set; determine a likelihood that the patient is experiencing endothelial dysfunction based on the transfer function; and output information indicative of the likelihood that the patient is experiencing endothelial dysfunction based on the determination.

[0012] The details of one or more examples are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the disclosure will be apparent from the description and drawings, and from the claims.

[0013] The above summary is not intended to describe each illustrated example or every implementation of the present disclosure.BRIEF DESCRIPTION OF DRAWINGS

[0014] FIG. 1 is a conceptual diagram illustrating an example medical device system, in accordance with one or more techniques described herein.

[0015] FIG. 2 is a conceptual diagram illustrating an example target blood vessel of the patient of FIG. 1.A0013002W001

[0016] FIG. 3 A is a conceptual diagram illustrating example sensed values within the example target blood vessel of FIG. 2.

[0017] FIG. 3B is a conceptual diagram illustrating example stress acting on a target blood vessel.

[0018] FIG. 4 is a conceptual diagram illustrating sensing of the blood flow within the example target blood vessel by the medical device system of FIG. 1.

[0019] FIG. 5 is a plot diagram illustrating an example transfer function outputted by the medical device system of FIG. 1.

[0020] FIG. 6 is a flow chart illustrating an example process of determining an endothelial function status of the patient.DETAILED DESCRIPTION

[0021] A medical device system may deliver neuromodulation therapy to one or more target nerves within a patient. Target nerves may include, but are not limited to, vagus nerves, renal nerves, splenic nerves, pudendal nerves, nerve(s) of the sympathetic nervous system, nerve(s) of the parasympathetic nervous system, nerve(s) of the central nervous system, nerve(s) of the peripheral nervous system, nerve(s) within an intracranial region of the patient, or the like. The neuromodulation therapy may alleviate one or more medical conditions experienced by the patient. For example, delivery of neuromodulation therapy to renal nerves of the patient may reduce endothelial dysfunction experienced by the patient.

[0022] Endothelial function of a patient indicates a status of endothelial cells within blood vessels of the patient. Endothelial dysfunction is a pathological condition characterized mainly by an imbalance between substances with vasodilating, antimitogenic and antithrombogenic properties (endothelium-derived relaxing factors) and substances with vasoconstricting, prothrombotic and proliferative characteristics (endothelium derived contracting factors). Endothelial dysfunction occurs in many diseases such diabetes, hypertension, heart failure, metabolic syndrome, kidney disease and many more and accounts for both micro and macrovascular dysfunction.

[0023] Changes in endothelial function may effect changes in vasomotor tone and / or vascular remodeling, e.g., thereby leading to microvascular or macrovascular dysfunction in the patient’s body. Sympathetic nervous system activity may affect endothelial function within the patient by reducing nitric oxide (NO) production, by increasing vascular tone, by altering patterns in the shear stress in blood vessels, or the like. Delivery of neuromodulationA0013002W001therapy to target nerves may reduce sympathetic nervous system activity, e.g., thereby reducing and / or eliminating endothelial dysfunction.

[0024] For example, factors such as reduced NO production, increase in vascular tone, and / or altering pattern in the shear stress in blood vessels may result in rarefaction resulting in chronic hypoxia or the like, leading to function impairment of the kidney. Delivery of neuromodulation therapy, such as renal denervation, may stop the cycle of reduced NO production, increase in vascular tone, or altered pattern in the sheer stress in blood vessels.

[0025] FIG. 1 is a conceptual diagram illustrating an example medical device system 100 (alternative referred to herein as “system 100”), in accordance with one or more techniques described herein. System 100 may be used to determine a status of endothelial function of patient 102. System 100 may include one or more sensors 106A, 106B (collectively referred to herein as “sensors 106”) and computing system 108 in communication with sensors 106.

[0026] Sensors 106 may obtain signals from target blood vessel 104. Computing system 108 may, based on the sensed signals from sensors 106, determine the status of endothelial function of patient 102 (e.g., whether patient 102 is experiencing endothelial dysfunction). In some examples, as illustrated in FIG. 1, system 100 includes two sensors 106. In other examples, system 100 may include one sensor 106 or three or more sensors 106. Each of sensors 106 may include, but is not limited to, a laser Doppler flow measurement device, a laser speckle velocimeter, or the like. Sensors 106 may monitor blood flow through target blood vessel 104 and / or dimensions of target blood vessel 104 over time. Sensors 106 may output, e.g., to computing system 108, signals indicative of changes in blood flow and / or in one or more dimensions of target blood vessel 104 over time. For example, the sensed signals may be electrical signals indicative of changes in blood vessel diameter of target blood vessel 104 over time and / or changes in blood vessel wall shear stress in target blood vessel 104 over time.

[0027] In some examples, sensors 106 may be non-invasive sensors. For example, sensors 106 may be external to patient 102. Accordingly, sensors 106 may be referred to as non-invasive sensing devices. In some examples, sensors 106 may sense signals from patient 102 without causing patient 102 physical discomfort, without requiring introduction of a pharmaceutical substance into the body of patient 102, and / or without requiring restricting blood flow through a portion of the body of patient 102.

[0028] Computing system 108 may include a plurality of computing components including, but are not limited to, sensing circuitry 110, user interface (UI) 112, memory 114, and processing circuitry 116. The components of computing system 108 may be disposedA0013002W001within one or more computing devices, computing systems, and / or cloud computing environments.

[0029] Sensing circuitry 110 of computing system 108 may receive the sensed signals from sensors 106. Sensing circuitry 110 may be directly coupled to or be in wireless communication with sensors 106. Sensing circuitry 110 may include filters, amplifiers, analog-to-digital converters, or other circuitry configured determine changes in the diameter of target blood vessel 104 and / or in wall shear stress in target blood vessel 104 based at least in part on the sensed signals received from sensors 106.

[0030] Processing circuitry 116 may receive the sensed signals and / or information derived from the sensed signals (e.g., changes in the diameter of target blood vessel 104 and / or in wall shear stress in target blood vessel 104) from sensing circuitry 110. In some examples, processing circuitry 116 receives the information from another computing device and / or computing system in communication with computing system 108. Processing circuitry 116 may include one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), discrete logic circuitry, or any other processing circuitry configured to provide the functions attributed to processing circuitry 116 described herein. Processing circuitry 116 may be firmware, hardware, software, or any combination thereof.

[0031] Processing circuitry 116 may receive the sensed information indicating a plurality of metrics over a threshold time period. The plurality of metrics may include changes (e.g., spontaneous changes) in the diameter of target blood vessel 104 and changes (e.g., spontaneous changes) in the blood vessel wall shear stress on target blood vessel 104. The changes in the diameter of target blood vessel 104 and / or the changes in the blood vessel wall shear stress on target blood vessel 104 may be sensed directly by sensors 106, e.g., using laser speckle imaging and / or laser Doppler flow measurement techniques. In some examples, processing circuitry 116 may determine the changes in the blood vessel wall shear stress based on received changes in blood flow velocity within target blood vessel 104. Processing circuitry 116 may receive the changes in blood flow velocity from sensors 106 (e.g., via sensing circuitry 110) and / or from another computing device and / or computing system.

[0032] The threshold time period may be at least about two minutes (e.g., about two minutes to about ten minutes). The duration of the threshold time period may be sufficiently long to account for changes in the diameter of target blood vessel 104 due to one or more biological functions of patient 102. For example, the duration of threshold time period may be sufficiently long to encompass one or more complete cycles for each of the one or moreA0013002W001biological functions. The one or more biological functions may include, but are not limited to, a respiration cycle of patient 102 or a cardiac cycle of patient 102.

[0033] Processing circuitry 116 may generate a transfer function based on the received sensed signals and / or information. In some examples, processing circuitry 116 applies a Fourier transformation to the sensed signals and / or information to generate the transfer function. The transfer function may indicate the relative contributions of different waves in the sensed signals and / or information to the output of the transfer function. Each wave of the different waves may be at a different frequency. For example, the transfer function may illustrate the contributions of the respiration cycle of patient 102 and a cardiac cycle of patient 102 at different frequencies on the transfer function. Processing circuitry 116 may generate the transfer function using at least 600 datapoints from the sensed signals and / or information (e.g., based on obtaining 60 datapoints per minute over a threshold time period of 10 minutes). In some examples, processing circuitry 116 may continuously receive sensed signals and / or information (e.g., from sensors 106) and may continuously update the transfer function to reflect the received signals and / or information, e.g., in real time. For example, processing circuitry 116 may apply Fourier transformations to the updated signals and / or information to generate the transfer function, e.g., in real time or quasi-real time.

[0034] Processing circuitry 116 may determine an endothelial status of patient 102 based on the transfer function. As one example, processing circuitry 116 may isolate a portion of the transfer function (e.g., a range of frequencies on the transfer function) and compare the output in the isolated portion to a threshold condition to determine the endothelial status. The frequency range may be based on a timing of one or more biological functions associated with endothelial dysfunction. For example, processing circuitry 116 may analyze the portion of the transfer function in a frequency range of up to 0.05 Hz. In such examples, the frequency range of up to 0.05 Hz may correspond to the delay between an increase in blood flow through target blood vessel 104 and a release of NO by endothelial cells, which is about 23 seconds, and 0.05 Hz corresponds to 20 seconds. In other examples, the frequency range may be based on the timing of another biological function associated with endothelial dysfunction.

[0035] The threshold condition may include, but is not limited to, a threshold area under the curve within the selected frequency range. Processing circuitry 116 may determine that the selected output of the transfer function satisfies the threshold condition based on a determination that an area under the curve for the selected frequency range is greater than or equals to the threshold area. The threshold condition may correspond to an indication that patient 102 is experiencing endothelial dysfunction and / or has at least a specified probabilityA0013002W001of experiencing endothelial dysfunction. The value for the threshold condition may vary based on characteristics of patient 102 (e.g., age, gender, weight, presence of other medical conditions, etc.). Based on the determination, processing circuitry 116 may output information indicating that patient 102 is experiencing endothelial dysfunction and / or has at least a specific probability of experiencing endothelial dysfunction.

[0036] Processing circuitry 116 may output the determination to a user (e.g., patient 102, a clinician) via UI 112. UI 112 may output the determination in the form of a visual signal and / or an audio signal. UI 112 may output the determination as a Boolean (e.g., “ENDOTHELIAL DYSFUNCTION DETECTED” or “NO ENDOTHELIAL DYSFUNCTION DETECTED”), as a percentage probability, or as another indicator.Processing circuitry 116 may store the received signals and / or information, the generated transfer function(s), and / or the determinations made by processing circuitry 116 in memory 114. Processing circuitry 116 may identify trends in the endothelial function of patient 102 based on the stored information, e.g., based on changes in received signals, transfer functions, and / or determinations over time. Processing circuitry 116 may output the trends to the user viaUI 112.

[0037] The techniques performed by system 100 may not be performable by a clinician in their mind and without the aid of a computing device, system, or cloud computing environment. Processing circuitry 116 requires a significant amount of data points from the received signals over the threshold time period to generate a transfer function illustrating relative contributions of different waves to changes in the diameter of target blood vessel 104. The clinician may not be able to mentally generate the transfer function (e.g., applying a Fourier transformation to the data points) without aid of system 100. In some examples, processing circuitry 116 generates and analyzes the transfer functions in real time based on the received signals and / or information, which may not be feasibly accomplished by the clinician without aid of system 100.

[0038] The techniques performed by system 100 may provide several advantages over other techniques for determining endothelial status of the patient. The techniques described herein would not require ingestion of pharmaceutical substances by patient 102 or require cuffing or otherwise restricting blood flow to a limb of patient 102, which may reduce patient discomfort compared to other techniques. System 100 may perform the technique directly on the vessel of interest (i.e., target vessel 104), thereby increasing the accuracy of the evaluation of the endothelial function of patient 102 made by system 100. By comparison, other methods may not be able to directly monitor certain vessels of interest, e.g., due to the location of theA0013002W001vessels in body of patient 102 (e.g., deep within the body of patient 102, not in a limb of patient 102).

[0039] FIG. 2 is a conceptual diagram illustrating an example target blood vessel 104 of patient 102 of FIG. 1. Target blood vessel 104 may include a blood vessel wall 202, which may define blood vessel lumen 206. The flow of blood through blood vessel lumen 206 is illustrated by blood flow 208 in FIG. 2. An inner surface of blood vessel wall 202 is lined with endothelial cells 204. When patient 102 experiences endothelial dysfunction, endothelial cells 204 may constrict blood vessel lumen 206, thereby restricting blood flow 208. The restriction of blood flow 208 may lead to and / or contribute to microvascular and / or macrovascular dysfunction in the body of patient 102.

[0040] FIG. 3 A is a conceptual diagram illustrating example sensed values within example target blood vessel 104 of FIG. 2. The sensed values may include blood vessel diameter 302 and blood flow velocity, illustrated by velocity profile 304. The sensed values may be determined by sensors 106 and / or may be received by processing circuitry 112, e.g., from other sensing device(s). Blood flow velocity may be illustrated through velocity profile 304. As illustrated by velocity profile 304, the blood flow velocity may be higher towards a center of blood vessel lumen 206 than around inner surfaces 306 of blood vessel lumen 306. System 100 may determine the wall shear stress on blood vessel wall 202 (e.g., at or around inner surfaces 306) based on the blood flow velocity at or around inner surfaces 306. For example, system 100 may determine the wall shear stress at inner surface 306 by taking a derivative of velocity profile 304 at or around inner surface 306 and multiplying the derivative by a viscosity of the blood.

[0041] FIG. 3B is a conceptual diagram illustrating example stresses acting on target blood vessel 104. Blood may flow through target blood vessel 104 with velocity profile 304 and may exert blood pressure 310 on blood vessel wall 202. As blood flows along inner surface 306 of target blood vessel 104, frictional forces exerted by blood flow 108 on inner surface 306 may exert shear stress 308 on inner surface 306 (e.g., on endothelial cells 204). Blood pressure 310 may apply stresses on blood vessel wall 202. For example, blood pressure 310 may lead to radial wall stress 312, circumferential wall stress 314, and axial wall stress 316 on blood vessel wall 202.

[0042] FIG. 4 is a conceptual diagram illustrating sensing of blood flow 208 within example target blood vessel 104 by system 100 of FIG. 1. While FIG. 4 illustrating sensing of blood flow 208 via sensor 106 A of system 100, the technique may be performed by anotherA0013002W001sensor of system 100 (e.g., another of sensors 106) and / or an external sensor in communication with computing system 108.

[0043] Sensor 106 A may include a laser Doppler measurement device. Sensor 106 A may output an ultrasound signal 402 through target blood vessel 104 and receive a sensed ultrasound signal. Based on the sensed ultrasound signal, system 100 (e.g., processing circuitry 116) may determine blood vessel diameter 302 and / or wall shear stress 308 on inner surface 306 at the instance captured by the sensed ultrasound signal. Based on a plurality of sensed ultrasound signals over time, system 100 may determine changes in blood vessel diameter 302 and / or changes in blood vessel wall shear stress 308 over the duration of time.

[0044] Sensor 106A may output ultrasound signal 402 at angle 404. When ultrasound signal 402 travels through target blood vessel 104 at angle 404, sensor 106 A may measure the velocity of blood flow 108 at a plurality of locations within blood vessel lumen 206, e.g., due to the Doppler shift effect. Collectively, sensor 106 A may obtain velocity profile 304 of blood flow 108 at a specific instance. Using velocity profile 304, system 100 may determine wall shear stress 308 at the specific instance, e.g., based on a produce of the viscosity of the blood and a derivative of velocity profile 304 at or around inner surface 306. Angle 404 may be up to 70 degrees.

[0045] The technique illustrated in FIG. 4 may be performed while target blood vessel 104 is constricted and / or is dilated, e.g., thereby improving the accuracy of the sensed signals from sensor 106A. Parameters of ultrasound signal 402 (e.g., angle 404) may be adjusted based on a location of target blood vessel 104 within patient 102. In some examples, system 100 may perform a plurality of measurements using sensor 106 A with different angles 404 to determine an optimal angle 404 for target blood vessel 104, e.g., thereby improving the accuracy of the sensed signals.

[0046] System 100 may sense spontaneous changes in blood vessel diameter 302 and / or blood vessel wall shear stress 308 and may determine endothelial function of patient 102 based on the spontaneous changes. In such examples, the changes in blood vessel diameter 302 and / or blood vessel wall shear stress 308 may be in response to the respiratory and / or cardiac cycle of patient 102, as opposed to constriction, pharmaceutical substances, and / or exercise in the case of other techniques. Sensor 106A may be placed over the skin of patient 102 (e.g., as a patch, as a non-constricting wrap) to allow recordation of signals from patient 102 through the threshold time period (e.g., for about 2 minutes to 10 minutes). System 100 may present visual or auditory stimuli to patient 102 to elicit changes in blood vessel diameter 302 and / or blood vessel wall shear stress. For example, system 100 may present visual orA0013002W001auditory stimuli to patient 102 to increase the respiration rate and / or a heart rate of patient 102, which may shorten the duration of the threshold time period. In some examples, system 100 may sense signals from patient 102 while patient 102 raises a limb (e.g., above heart level) and / or while patient 102 experiences an orthostatic change.

[0047] In some examples, system 100 may measure signals at multiple locations on patient 102 simultaneously (e.g., at a central location on patient 102 and at a peripheral location on patient 102 simultaneously). System 100 may determine a value for a threshold condition indicative of endothelial dysfunction based on the sensed signals. The value for the threshold condition may be indicative of increase constriction in peripheral arteries of patient 102 relative to central arteries of patient 102.

[0048] FIG. 5 is a plot diagram 500 illustrating an example transfer function 506 generated by system 100 of FIG. 1. While transfer function 506 is primarily described herein as being generated by one technique, example transfer functions described herein may be generated using one or more other techniques.

[0049] System 100 may generate transfer function 506 based on signals indicating changes in blood vessel diameter 302 and changes in blood vessel wall shear stress 308 over a threshold time period. In some examples, system 100 applies a Fourier transformation to the signals to generate transfer function 506. Plot diagram 500 of transfer function 506 may represent frequency 502 (e.g., in Hz) along the x-axis and transfer function output 504 (e.g., gain of transfer function 506) along the y-axis. That is, transfer function output 504 may be indicative of the contribution of a wave at a particular frequency to the overall changes to blood vessel diameter 302 or wall shear stress 308. Transfer function 506 may be represented by Equation 1 :W) = sdsr( / ) / sdd( / ) (1)

[0050] In Equation 1, H(f) represents transfer function 506, Sdd(f) represents an autospectrum of blood vessel diameter 302, and Sdsr(f) represents a complex cross-spectrum between the changes in blood vessel diameter 302 and changes in blood vessel wall shear stress 308. System 100 may generate Sdd(f) and Sdsr(f) by applying a Fourier transformation to each of a first data set indicating changes in blood vessel diameter 302 and to a second data set indicating changes in blood vessel wall shear stress, respectively. System 100 may generate a first transfer function (e.g., Sdd(f)), a second transfer function (e.g., Sdsr(f)) basedA0013002W001on the received signals. System 100 may then generate transfer function 506 in accordance with Equation 1. Transfer function output 504 may be represented by equation 2:IW)I (W + (W ]°'5(2)

[0051] In equation 2, |H(f)| represents the gain of transfer function 506 (i.e., transfer function output 504), HR(f) represents the real portion of transfer function 506, and H,(f) represents the imaginary portion of transfer function 506.

[0052] System 100 may determine a threshold frequency 508 for transfer function 506. Threshold frequency 508 may corresponding to patient 102 experiencing endothelial dysfunction. Threshold frequency 508 may be selected to isolate the effects of endothelial dysfunction on blood vessel diameter 302 from the effects of one or more biological functions (e.g., of the respiration cycle, of the cardiac cycle) on blood vessel diameter 302. Threshold frequency 508 may correspond to a duration of one or more biological functions associated with endothelial dysfunction, such as, but is not limited to, release of NO in target blood vessel 104.

[0053] In some examples, as illustrated in FIG. 5, a target frequency range includes a range of frequencies up to threshold frequency 508. In some examples, the target frequency range includes a range of frequencies between two threshold frequencies 508.

[0054] System 100 may determine an area under transfer function 506 for the target frequency range. In the example illustrated in FIG. 5, system 100 may determine the area under transfer function 506 for the frequency range up to threshold frequency 508. System 100 may compare the determined area against a threshold value. The threshold value may correspond to a determination that patient 102 is experiencing or has at least a threshold probability of experiencing endothelial dysfunction. The threshold value may be determined based on the medical history of patient 102 and / or based on medical histories of one or more other individuals. The threshold value may vary between different individuals based on one or more characteristics of the individuals. The one or more characteristics may include, but are not limited to, age, gender, weight, disease state, medical history, medication(s) used by the individual (e.g., by patient 102) or the like. System 100 may determine that patient 102 is experiencing endothelial dysfunction or has at least a threshold probability of experiencing endothelial dysfunction based on a determination that the area under transfer function 506 is greater than or equal to the threshold value.A0013002W001

[0055] In some examples, system 100 compares a linearity of transfer function 506 for the target frequency range against a threshold linearity value. In the example illustrated in FIG. 5, system 100 may compare the linearity of the portion of transfer function in the frequency range up to threshold frequency 508 against the threshold linearity value. The threshold linearity value may be indicative that patient 102 is experiencing endothelial dysfunction or has at least a threshold probability of experiencing endothelial dysfunction. System 100 may determine that patient 102 is experiencing endothelial dysfunction or has at least a threshold probability of experiencing endothelial dysfunction based on a determination that the linearity of transfer function 506 in the target frequency range satisfies the threshold linearity value.

[0056] FIG. 6 is a flow chart illustrating an example process of determining an endothelial function status of patient 102. While the technique is primarily described with reference to system 100 of FIG. 1, the technique may be performed by any computing devices, computing systems, or cloud computing environments described herein.

[0057] System 100 may receive a first data set indicating changes in blood vessel diameter 302 of patient 102 over a time period (602). The changes in blood vessel diameter 302 may correspond to changes in blood vessel diameter 302 of target blood vessel 104. The time period may be a threshold time period, e.g., of about 2 minutes to about 10 minutes. The duration of threshold time period may be sufficient to encompass one or more complete cycles of one or more biological functions of patient 102 (e.g., respiration cycle of patient 102, cardiac cycle of patient 102).

[0058] System 100 may receive the first data set from an external computing device, computing system, cloud computing environment, and / or external sensors. In some examples, system 100 receives the first data set from sensors 106. Sensors 106 may include, but are not limited to, laser Doppler measurement devices and / or laser specklemeters. Sensors 106 may generate the first data set based on the signals sensed by sensors 106 during the time period. For example, the first data set may include each change in blood vessel diameter 302 sensed by sensors 106 during the time period, e.g., and the corresponding time stamps.

[0059] System 100 may receive a second data set indicating changes in blood vessel wall shear stress 308 over the time period (604). The first and second data sets may be over a same time period. In some examples, system 100 directly receives the changes in blood vessel wall shear stress 308. In some examples, system 100 receives changes in blood flow velocity over the time period (e.g., changes in velocity profile 304 over the time period). In such examples, computing system 108 may then determine the changes in blood vessel wall shear stress 308 based on the changes in blood flow velocity. For example, system 100 may determine, forA0013002W001each instance in the time period, wall shear stress 308 based on the velocity profile 304 corresponding to the instance. System 100 may then determine the change in wall shear stress 308 based on the changes in the determined wall shear stress 308 of a plurality of instances across the time period.

[0060] System 100 may receive the second data set from an external computing device, computing system, cloud computing environment, and / or external sensors. In some examples, system 100 receives the second data set from sensors 106. The same or difference sensors 106 may be used to generate the first and second data sets. Sensors 106 may include, but are not limited to, laser Doppler measurement devices and / or laser specklemeters. Sensors 106 may generate the second data set based on the signals sensed by sensors 106 during the time period. For example, the second data set may include each change in blood vessel wall shear stress 308 sensed by sensors 106 during the time period, e.g., and the corresponding time stamps.

[0061] System 100 may generate transfer function 506 based on the first and second data sets (606). Transfer function 506 may indicate the relative contributions of different waves in the sensed signals and / or information to transfer function output 504. System 100 may apply a Fourier transformation of the first and second data sets to generate transfer function 506.

[0062] System 100 may determine a likelihood that patient 102 is experiencing endothelial dysfunction based on transfer function 506 (608). System 100 may compare a portion of transfer function 506 across a specific frequency range and / or less than or equal to threshold frequency 508 against a threshold condition. Threshold frequency 508 and / or the specific frequency range may correspond to biological functions which affect endothelial function, such as release of NO. System 100 may select threshold frequency 508 and / or the specific frequency range to isolate the biological functions from one or more other biological functions (e.g., respiration cycle of patient 102, cardiac cycle of patient 102).

[0063] In some examples, system 100 determine an area under transfer function 506 across the specific frequency range and / or across a frequency range less than or equal to threshold frequency 508. System 100 may compare the determined area against a threshold area value. System 100 may determine that patient 102 is experiencing or will experience endothelial dysfunction based on a determination that determined area is greater than or equals to the threshold area value. The threshold area value may be based on characteristics of patient 102 (e.g., based on age, gender, weight, disease state, and / or medical history of patient 102).A0013002W001

[0064] In some examples, system 100 compares a linearity of transfer function 506 across the frequency range against a threshold linearity value. System 100 may determine that patient 102 is experiencing or will experience endothelial dysfunction based on a determination that determined linearity of transfer function 506 is greater than or equals to the threshold linearity value.

[0065] System 100 may output information indicative of the likelihood that patient 102 is experiencing endothelial dysfunction based on the determination (610). System 100 may output the information to a user (e.g., patient 102, the clinician). System 100 may output the information through UI 112 of computing system 108. The outputted information may be a Boolean, a percentage probability, or any other output indication.

[0066] While the techniques described herein primarily reference changes in blood vessel diameter 302, the techniques may use changes in one or more indicia of changes in the size of target blood vessel 104 to determine whether patient 102 is experiencing endothelial dysfunction. The one or more indicia may include, but are not limited to, changes in radius, diameter, or circumference of target blood vessel 104.

[0067] It should be noted that the techniques described herein, may not be limited to treatment or monitoring of a human patient. In alternative examples, the techniques of this disclosure may be applied to non-human patients, e.g., primates, canines, equines, pigs, and felines. These other animals may undergo clinical or research therapies that my benefit from the subject matter of this disclosure.

[0068] Various examples are discussed relative to one or more neurostimulation trial devices and systems. It is recognized that the stimulation devices and / or systems may include features and functionality in addition to electrical stimulation. Many of these additional features are expressly discussed herein. A few example features include, but are not limited to, different types of sensing capabilities and different types of wireless communication capabilities. For ease of discussion, the present disclosure does not expressly recite every conceivable combination of the additional features, such as by repeating every feature each time different examples and uses of the stimulation devices and / or systems are discussed.

[0069] The techniques of this disclosure may be implemented in a wide variety of computing devices, medical devices, or any combination thereof. Any of the described units, circuitry or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as circuitry or units is intended to highlight different functional aspects and does not necessarily imply that such circuitry or units must be realized by separate hardware or software components. Rather, functionalityA0013002W001associated with one or more circuitry or units may be performed by separate hardware or software components, or integrated within common or separate hardware or software components.

[0070] The disclosure contemplates computer-readable storage media comprising instructions to cause a processor to perform any of the functions and techniques described herein. The computer-readable storage media may take the example form of any volatile, non-volatile, magnetic, optical, or electrical media, such as a RAM, ROM, NVRAM, EEPROM, or flash memory that is tangible. The computer-readable storage media may be referred to as non-transitory. A server, client computing device, or any other computing device may also contain a more portable removable memory type to enable easy data transfer or offline data analysis.

[0071] The techniques described in this disclosure, including those attributed to various circuitry and various constituent components, may be implemented, at least in part, in hardware, software, firmware or any combination thereof. For example, various aspects of the techniques may be implemented within one or more processors, including one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated, discrete logic circuitry, or other processing circuitry, as well as any combinations of such components, remote servers, remote client devices, or other devices. The term “processing circuitry” or “processing circuitry” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry.

[0072] Such hardware, software, firmware may be implemented within the same device or within separate devices to support the various operations and functions described in this disclosure. In addition, any of the described units, circuitry or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as circuitry or units is intended to highlight different functional aspects and does not necessarily imply that such circuitry or units must be realized by separate hardware or software components. Rather, functionality associated with one or more circuitry or units may be performed by separate hardware or software components, or integrated within common or separate hardware or software components. For example, any circuitry described herein may include electrical circuitry configured to perform the features attributed to that particular circuitry, such as fixed function processing circuitry, programmable processing circuitry, or combinations thereof.

[0073] In some examples, a computer-readable storage medium comprises non-transitory medium. The term “non-transitory” may indicate that the storage medium is not embodied inA0013002W001a carrier wave or a propagated signal. In certain examples, a non-transitory storage medium may store data that may, over time, change (e.g., in RAM or cache).

[0074] This disclosure includes the following non-limiting examples.

[0075] Example 1: a computing system comprising: processing circuitry configured to: receive a first data set indicating changes in blood vessel diameter of a blood vessel of a patient over a time period; receive a second data set indicating changes in blood vessel wall shear stress of the blood vessel over the time period; generate a transfer function based on the first data set and the second data set; determine a likelihood that the patient is experiencing endothelial dysfunction based on the transfer function; and output information indicative of the likelihood that the patient is experiencing endothelial dysfunction based on the determination.

[0076] Example 2: the computing system of example 1, wherein a duration of the time period is about two to ten minutes.

[0077] Example 3: the computing system of any of examples 1 or 2, wherein the first data set indicates spontaneous changes in the blood vessel diameter of the blood vessel.

[0078] Example 4: the computing system of any of examples 1-3, wherein the second data set indicates spontaneous changes in blood vessel wall shear rate.

[0079] Example 5: the computing system of any of examples 1-4, further comprising one or more non-invasive sensing devices, wherein the processing circuitry is configured to receive the first data set and the second data set from the one or more non-invasive sensing devices.

[0080] Example 6: the computing system of example 5, wherein at least one sensing device of the one or more non-invasive sensing devices comprises: a laser Doppler flow measuring device; or a laser speckle velocimeter.

[0081] Example 7: the computing system of any of examples 1-6, wherein to generate the transfer function, the processing circuitry is configured to generate a Fourier transformation of the first and second data sets at a plurality of frequencies.

[0082] Example 8: the computing system of example 7, wherein at least one frequency of the plurality of frequencies corresponds to a frequency at which a diameter of the blood vessel changes in response to changes in wall shear stress on the blood vessel.

[0083] Example 9: the computing system of example 8, wherein the at least one frequency is less than or equal to 0.05 Hz.

[0084] Example 10: the computing system of any of examples 7-9, wherein the Fourier transformation indicates a relative contribution of each wave of a plurality of waves to theA0013002W001changes in blood vessel diameter, the plurality of waves comprising a first wave corresponding to changes in the blood vessel wall shear stress and one or more second waves corresponding to one or more biological functions of the patient.

[0085] Example 11 : the computing system of example 10, wherein the one or more biological functions comprises one or more of: a respiration cycle of the patient; or a cardiac cycle of the patient.

[0086] Example 12: the computing system of any of examples 10 or 11, wherein to determine the likelihood that the patient is experiencing the endothelial dysfunction based on the transfer function, the processing circuitry is configured to: isolate a first contribution of the first wave from one or more second contributions of the one or more second waves within the Fourier transformation; compare the first contribution against a threshold value; and based on a determination that the first contribution exceeds the threshold value, determine that the patient has at least a threshold likelihood of experiencing endothelial dysfunction.

[0087] Example 13: the computing system of example 12, wherein the threshold value is based at least in part on one or more of: a location of the blood vessel in the patient; an age of the patient; a gender of the patient; a medication in use by the patient; a weight of the patient; or a disease state of the patient.

[0088] Example 14: the computing system of any of examples 12 and 13, wherein the threshold value comprises a threshold area, and wherein to compare the first contribution against the threshold value, the processing circuitry is configured to: determine an area under a peak of the first contribution in the Fourier transformation; and compare the area against the threshold area.

[0089] Example 15: the computing system of any of examples 1-14, wherein the first data set comprises a continuous record of changes in the blood vessel diameter over the time period, and wherein the second data set comprises a continuous record of changes in the blood vessel wall shear stress over the time period.

[0090] Example 16: the computing system of any of examples 1-15, wherein the processing circuitry is further configured to update the likelihood that the patient is experiencing endothelial dysfunction in real time.

[0091] Example 17: a method comprising: receiving, by processing circuitry of a computing system, a first data set indicating changes in blood vessel diameter of a blood vessel of a patient over a time period; receiving, by the processing circuitry, a second data set indicating changes in blood vessel wall shear stress of the blood vessel over the time period; generating, by the processing circuitry, a transfer function based on the first data set and theA0013002W001second data set; determining, by the processing circuitry, a likelihood that the patient is experiencing endothelial dysfunction based on the transfer function; and outputting, by the processing circuitry, information indicative of the likelihood that the patient is experiencing endothelial dysfunction based on the determination.

[0092] Example 18: the method of example 17, wherein receiving the first data set comprises obtaining, by the processing circuitry and via one or more non-invasive sensing devices, the first data set from the patient, and wherein receiving the second data set comprises obtaining, by the processing circuitry and via the one or more non-invasive sensing devices, the second data set from the patient.

[0093] Example 19: the method of example 18, wherein at least one sensing device of the one or more non-invasive sensing devices comprises: a laser Doppler flow measuring device; or a laser speckle velocimeter.

[0094] Example 20: the method of any of examples 17-19, wherein generating the transfer function comprises generating, by the processing circuitry, a Fourier transformation of the first and second data sets at a plurality of frequencies.

[0095] Example 21 : the method of example 20, wherein at least one frequency of the plurality of frequencies corresponds to a frequency at which a diameter of the blood vessel changes in response to changes in wall shear stress on the blood vessel.

[0096] Example 22: the method of example 21, wherein the at least one frequency is less than or equal to 0.05 Hz.

[0097] Example 23: the method of any of examples 20-22, wherein the Fourier transformation indicates a relative contribution of each wave of a plurality of waves to the changes in blood vessel diameter, the plurality of waves comprising a first wave corresponding to changes in the blood vessel wall shear stress and one or more second waves corresponding to one or more biological functions of the patient.

[0098] Example 24: the method of example 23, wherein the one or more biological functions comprises one or more of: a respiration cycle of the patient; or a cardiac cycle of the patient.

[0099] Example 25: the method of any of examples 23 or 24, wherein determining the likelihood that the patient is experiencing the endothelial dysfunction based on the transfer function comprises: isolating, by the processing circuitry, a first contribution of the first wave from one or more second of the one or more second waves within the Fourier transformation; comparing, by the processing circuitry, the first contribution against a threshold value; and based on a determination that the first contribution exceeds the threshold value, determining,A0013002W001by the processing circuitry, that the patient has at least a threshold likelihood of experiencing endothelial dysfunction.

[0100] Example 26: the method of example 25, wherein the threshold value comprises a threshold area, and wherein comparing the first contribution against the threshold value comprises: determining, by the processing circuitry, an area under a peak of the first contribution in the Fourier transformation; and comparing, by the processing circuitry, the area against the threshold area.

[0101] Example 27: a computer-readable medium comprising instructions that, when executed by processing circuitry of a computing system, causes the processing circuitry to perform the operations of any of examples 1-16.

[0102] Various examples have been described herein. Any combination of the described operations or functions is contemplated. These and other examples are within the scope of the following claims. Based upon the above discussion and illustrations, it is recognized that various modifications and changes may be made to the disclosed examples in a manner that does not require strictly adherence to the examples and applications illustrated and described herein. Such modifications do not depart from the true spirit and scope of various aspects of the disclosure, including aspects set forth in the claims.

Claims

1. A0013002W001CLAIMS:

1. A computing system comprising:processing circuitry configured to:receive a first data set indicating changes in blood vessel diameter of a blood vessel of a patient over a time period;receive a second data set indicating changes in blood vessel wall shear stress of the blood vessel over the time period;generate a transfer function based on the first data set and the second data set; determine a likelihood that the patient is experiencing endothelial dysfunction based on the transfer function; andoutput information indicative of the likelihood that the patient is experiencing endothelial dysfunction based on the determination.

2. The computing system of claim 1, wherein a duration of the time period is about two to ten minutes.

3. The computing system of any of claims 1 or 2, wherein the first data set indicates spontaneous changes in the blood vessel diameter of the blood vessel.

4. The computing system of any of claims 1-3, wherein the second data set indicates spontaneous changes in blood vessel wall shear rate.

5. The computing system of any of claims 1-4, further comprising one or more non-invasive sensing devices, wherein the processing circuitry is configured to receive the first data set and the second data set from the one or more non-invasive sensing devices.

6. The computing system of claim 5, wherein at least one sensing device of the one or more non-invasive sensing devices comprises:a laser Doppler flow measuring device; ora laser speckle velocimeter.A0013002W0017. The computing system of any of claims 1-6, wherein to generate the transfer function, the processing circuitry is configured to generate a Fourier transformation of the first and second data sets at a plurality of frequencies.

8. The computing system of claim 7, wherein at least one frequency of the plurality of frequencies corresponds to a frequency at which a diameter of the blood vessel changes in response to changes in wall shear stress on the blood vessel.

9. The computing system of claim 8, wherein the at least one frequency is less than or equal to 0.05 Hz.

10. The computing system of any of claims 7-9, wherein the Fourier transformation indicates a relative contribution of each wave of a plurality of waves to the changes in blood vessel diameter, the plurality of waves comprising a first wave corresponding to changes in the blood vessel wall shear stress and one or more second waves corresponding to one or more biological functions of the patient.

11. The computing system of claim 10, wherein the one or more biological functions comprises one or more of:a respiration cycle of the patient; ora cardiac cycle of the patient.

12. The computing system of any of claims 10 or 11, wherein to determine the likelihood that the patient is experiencing the endothelial dysfunction based on the transfer function, the processing circuitry is configured to:isolate a first contribution of the first wave from one or more second contributions of the one or more second waves within the Fourier transformation;compare the first contribution against a threshold value; andbased on a determination that the first contribution exceeds the threshold value, determine that the patient has at least a threshold likelihood of experiencing endothelial dysfunction.

13. The computing system of claim 12, wherein the threshold value is based at least in part on one or more of:A0013002W001a location of the blood vessel in the patient;an age of the patient;a gender of the patient;a medication in use by the patient;a weight of the patient; ora disease state of the patient.

14. The computing system of any of claims 12 and 13, wherein the threshold value comprises a threshold area, and wherein to compare the first contribution against the threshold value, the processing circuitry is configured to:determine an area under a peak of the first contribution in the Fourier transformation; andcompare the area against the threshold area.

15. The computing system of any of claims 1-14,wherein the first data set comprises a continuous record of changes in the blood vessel diameter over the time period, andwherein the second data set comprises a continuous record of changes in the blood vessel wall shear stress over the time period.

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