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EP4622540A1 - Procédé de quantification de l'activité du système nerveux autonome et d'identification de répondeurs potentiels à une thérapie de modulation autonome - Google Patents

Procédé de quantification de l'activité du système nerveux autonome et d'identification de répondeurs potentiels à une thérapie de modulation autonome

Info

Publication number
EP4622540A1
EP4622540A1 EP23809166.4A EP23809166A EP4622540A1 EP 4622540 A1 EP4622540 A1 EP 4622540A1 EP 23809166 A EP23809166 A EP 23809166A EP 4622540 A1 EP4622540 A1 EP 4622540A1
Authority
EP
European Patent Office
Prior art keywords
blood flow
peripheral blood
period
computing device
generated
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP23809166.4A
Other languages
German (de)
English (en)
Inventor
Douglas A. Hettrick
Sean Michael White
Darion R. Peterson
Paul J. Coates
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Medtronic Ireland Manufacturing ULC
Original Assignee
Medtronic Ireland Manufacturing ULC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Medtronic Ireland Manufacturing ULC filed Critical Medtronic Ireland Manufacturing ULC
Publication of EP4622540A1 publication Critical patent/EP4622540A1/fr
Pending legal-status Critical Current

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4029—Detecting, measuring or recording for evaluating the nervous system for evaluating the peripheral nervous systems
    • A61B5/4035—Evaluating the autonomic nervous system
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/026—Measuring blood flow
    • A61B5/0261—Measuring blood flow using optical means, e.g. infrared light
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4029—Detecting, measuring or recording for evaluating the nervous system for evaluating the peripheral nervous systems
    • A61B5/4041—Evaluating nerves condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4884—Other medical applications inducing physiological or psychological stress, e.g. applications for stress testing

Definitions

  • the present disclosure relates generally to quantifying sympathetic nerve activity.
  • the disclosure is directed to diagnostic methods and systems for quantifying sympathetic nerve activity or changes in sympathetic nerve activity to identify diseases associated with autonomic nervous system function.
  • the sympathetic branch, or sympathetic nervous system (SNS), of the autonomic nervous system is critical to controlling multiple organs and physiologic systems, including the kidney.
  • the SNS is a primarily involuntary bodily control system typically associated with stress response.
  • Chronic over-activation of the SNS is a maladaptive response that can drive the progression of many disease states.
  • excessive activation of the renal SNS has been identified experimentally and in humans as a likely contributor to the complex pathophysiology of arrhythmias, hypertension, states of volume overload (e.g., heart failure), obstructive sleep apnea, and progressive renal disease, amongst others.
  • Quantifying the relative level of global sympathetic activation within the human body, or relative changes in sympathetic activity due to various stimuli have multiple useful clinical applications, including diagnosing and monitoring diseases associated with autonomic nervous system function.
  • a system for performing a diagnostic procedure includes a diagnostic device, the diagnostic device configured for placement proximate tissue, wherein a light emitter and a photodetector are disposed on the diagnostic device, a computing device including a processor and a memory storing instructions, which when executed by the processor, cause the computing device to deliver light from the light emitter into the tissue for a period of time, detect dynamic properties of light scattering particles within the tissue using the photodetector over the period of time, generate a peripheral blood flow waveform of a fluid flowing within the tissue using the detected dynamic properties of the light scattering particles over the period of time, calculate a power spectral density for the generated peripheral blood flow waveform over the period of time, quantify a relative level of global sympathetic nerve activity over the period of time using the calculated power spectral density for the generated peripheral blood flow waveform, identify relative changes in global sympathetic nerve activity within the quantified relative level of global sympathetic nerve activity over the period of time, and determine if the identified relative changes in global sympathetic nerve
  • combining the generated peripheral blood flow waveform and the generated arterial blood pressure waveform may include deriving a mean arterial blood pressure amplitude and a mean peripheral blood flow waveform from the generated peripheral blood flow waveform and the generated arterial blood pressure waveform over the period of time.
  • emitting light into tissue from a light emitted and detecting dynamic properties of light scattering particles within the tissue by a photodetector may include the light emitter and the photodetector being disposed on a diagnostic device.
  • the diagnostic device may be a portable, wearable device.
  • the diagnostic device may be disposed on a digit of a patient.
  • FIG. 3 is a perspective view of a therapeutic device of the system of FIG. 1;
  • FIG. 4 is a perspective view of a diagnostic device of the system of FIG. 1 shown disposed on a portion of a patient’s anatomy;
  • FIG. 6 is a graphical representation of the user interface of FIG. 5 illustrating photopl ethysmograpic (PPG) signals;
  • FIG. 7A is a pre-processing graphical representation of the flow waveform and the PPG signal of FIGS. 5 and 6;
  • FIG. 7C is a graphical representation of a power spectral analysis of arterial mechanical properties using an aortic input impedance spectrum
  • FIG. 8A is a schematic representation of an algorithm for performing the power spectral analysis of FIG. 7C;
  • FIG. 8B is another schematic representation of an algorithm for performing the power spectral analysis of FIG. 7C;
  • FIG. 9 is a flow chart illustrating a method of performing a diagnostic procedure in accordance with the present disclosure.
  • FIG. 10 is a flow chart illustrating another embodiment of a method of performing a diagnostic procedure in accordance with the present disclosure.
  • the devices, systems, and techniques described herein may be used in denervating nerves at a plurality of target locations within a patient, e.g., at two target locations accessible via different blood vessels.
  • the devices, systems, and techniques described herein may be used in denervating nerves that innervate the liver via an artery feeding the liver and denervating nerves that innervate a kidney via one or more renal arteries or renal vessels.
  • the diagnostic system conducts a power spectral analysis of arterial mechanical properties using an aortic input impedance spectrum.
  • the aortic input impedance spectrum quantifies frequency independent and dependent components of left ventricular afterload, such as peripheral arterial resistance and arterial compliance.
  • the aortic input impedance spectrum is calculated using the quantified arterial blood flow measurements and the arterial blood pressure waveform.
  • the arterial mechanical properties such as peripheral arteriolar dimensions (e.g., resistance), aortic wall stiffness (e.g., compliance), wave reflections (e.g., reflectance) can be derived from the magnitude or phase of the aortic input impedance spectrum using a mechanical or electrical model of the arterial circulation.
  • the aortic input impedance spectrum may be interpreted using a Windkessel model, such as the three-element Windkessel model.
  • the diagnostic system quantifies a relative level of global sympathetic nerve activity, as well as relative changes in activity, by analyzing components of the measured peripheral blood flow and PPG signals alone, or in combination, in the time or frequency domain.
  • the measured peripheral blood flow and the PPG signals can be analyzed in various combinations, such as individually in the time domain, individually in the frequency domain, combined in the time domain (e.g., the mean PPG signal amplitude and the mean measured peripheral blood flow amplitude), or combined in the frequency domain (e.g., resistance, compliance, amplitude, phase, etc.), amongst others.
  • Intentionally applied perturbations of the SNS may include a cold pressor, a hand rip exercise, mental stress (mental math, a stroop color test, etc.), a valsava or Muller maneuver, acute catecholamine injection (e.g., norepinephrine), orthostasis (e.g., rise from supine to standing), variable rate pacing (e.g., adjust the heat rate), amongst others.
  • a cold pressor e.g., a hand rip exercise, mental stress (mental math, a stroop color test, etc.), a valsava or Muller maneuver, acute catecholamine injection (e.g., norepinephrine), orthostasis (e.g., rise from supine to standing), variable rate pacing (e.g., adjust the heat rate), amongst others.
  • Naturally occurring perturbations of the SNS may include circadian variation (e.g., morning or evening surge), sleep apnea breathing, orthostasis (e.g., a rise from supine to standing that is detectable with a 3-D accelerometer), intense physical activity (e.g., a heart rate or activity increase), respiration, amongst others.
  • circadian variation e.g., morning or evening surge
  • sleep apnea breathing e.g., a rise from supine to standing that is detectable with a 3-D accelerometer
  • intense physical activity e.g., a heart rate or activity increase
  • respiration amongst others.
  • a normal range or normal pattern of variation may be defined as well as one or more thresholds for detecting a deviation from the defined normal range or pattern of variation.
  • the defined normal range or normal pattern of variation may be generated from data obtained from the patient or from clinical data obtained from an electronic medical records (EMR) system. It is envisioned that the defined normal range or normal pattern of variation may be expressed as either an absolute value or a proportional change without departing from the scope of the present disclosure.
  • the measurements described herein may be made acutely (e.g., over a short period of time) or chronically (e.g., over a long period of time) using the same signals obtained from a similar portable or wearable device.
  • the diagnostic system may be utilized to assess the efficacy of denervation therapy applied to target tissue.
  • the diagnostic device may once again provide parameters indicative of SNS activity in the basal steady state or following a perturbation of the SNS and provide an assessment of the efficacy of the applied denervation therapy. If the tracked peripheral blood flow or PPG signals deviate from the defined normal range or pattern of variation or otherwise exceed/fall below the predetermined thresholds, the application of denervation therapy has not been successful and further applications of denervation therapy may be needed.
  • FIG. 1 illustrates a guidance and therapy system provided in accordance with the disclosure and generally identified by reference numeral 10.
  • the guidance and therapy system 10 enables navigation of a therapeutic device 50 to a desired location within the patient’s anatomy (e.g., the patient’s renal artery), assessment of tissue within the renal artery for candidacy for denervation, and the application of denervation therapy to the tissue within the renal artery to denervate sympathetic nerves within the tissue.
  • the therapy system 10 includes a workstation 20, a therapeutic device 50 operably coupled to the workstation 20, and in embodiments, an imaging device 14, which may be operably coupled to the workstation 20.
  • the patient “P” is shown lying on an operating table 12 with the therapeutic device 50 inserted through a portion of the patient’s femoral artery, although it is contemplated that the therapeutic device 50 may be inserted into any suitable portion of the patient’s vascular network that is in fluid communication with a desired blood vessel for therapy (e.g., renal, hepatic, mesenteric, splanchnic, or other arteries enervated by the SNS).
  • a desired blood vessel for therapy e.g., renal, hepatic, mesenteric, splanchnic, or other arteries enervated by the SNS.
  • a desired blood vessel for therapy e.g., renal, hepatic, mesenteric, splanchnic, or other arteries enervated by the SNS.
  • the workstation includes a computer 22 and a therapy source 24 (e.g., an RF generator, a microwave generator, an ultrasound generator, a cryogenic medium source, a chemical source, etc.) operably coupled to the computer 22.
  • the computer 22 is coupled to a display 26 that is configured to display one or more user interfaces 28 (also illustrated in FIG. 5).
  • the computer 22 may be a desktop computer or a tower configuration with display 26 or may include a laptop computer or other computing device.
  • the computer 22 includes a processor 30 which executes software stored in a memory 32.
  • the memory 32 may store one or more applications 34 and/or algorithms 44 to be executed by the processor 30.
  • a network interface 36 enables the workstation 20 to communicate with a variety of other devices and systems via the Internet.
  • the network interface 36 may connect the workstation 20 to the Internet via a wired or wireless connection. Additionally, or alternatively, the communication may be via an ad hoc Bluetooth® or wireless network enabling communication with a wide-area network (WAN) and/or a local area network (LAN).
  • the network interface 36 may connect to the Internet via one or more gateways, routers, and network address translation (NAT) devices.
  • the network interface 36 may communicate with a cloud storage system 38, in which further data, image data, or videos may be stored.
  • the cloud storage system 38 may be remote from or on the premises of the hospital or clinic such as in a control or hospital information technology room.
  • the cloud storage system 38 could also serve as a host for more robust analysis of acquired images data or images (e.g., additional or reinforcement data for analysis and/or comparison, medical images (e.g., fluoroscopic, computed tomography (CT), magnetic resonance imaging (MRI), cone-beam computed tomography (CBCT), etc.)
  • An input module 40 receives inputs from an input device such as a keyboard, a mouse, voice commands, amongst others.
  • An output module 42 connects the processor 30 and the memory 32 to a variety of output devices such as the display 26.
  • the display 26 may be a touchscreen display.
  • the workstation 20 may also include a light source 24a, which is capable of generating one or more sources of light for transmission through a fiber-optic cable or other means to a diagnostic device 70 for use in the systems and methods described herein for quantification of sympathetic nerve activity or changes in sympathetic nerve activity.
  • the light source 24a may also be included within the diagnostic device 70 itself.
  • FIG. 3 depicts an embodiment of a therapeutic device 50 in accordance with the disclosure.
  • the therapeutic device 50 includes an elongated shaft 52 having a handle (not shown) disposed on a proximal end of the elongated shaft 52.
  • the elongated shaft 52 of the therapeutic device 50 is configured to be advanced within a portion of the patient’s vasculature, such as a femoral artery or other suitable portion of patient’ s vascular network that is in fluid communication with the patient’s renal artery, or any other suitable target vessel. As depicted in FIG.
  • the elongated shaft 52 may be configured to be received within a portion of a guide catheter or guide sheath (such as a 6F guide catheter) 62 that is utilized to navigate the therapeutic device 50 to a desired location at which point the guide catheter 62 is retracted to uncover the therapeutic portion 56 of the therapeutic device 50 which in the embodiment shown includes a plurality of monopolar electrodes 58.
  • the elongated shaft 52 of the therapeutic device 50 may further include an aperture (not shown) that is configured to slidably receive a guidewire 64 over which the therapeutic device 50, either alone or in combination with the guide catheter 62, are advanced. In this manner, the guidewire 64 is utilized to guide the therapeutic device 50 to the target tissue using over-the-wire (OTW) or rapid exchange (RX) techniques, at which point the guide wire may be partially or fully removed from the therapeutic device 50.
  • OW over-the-wire
  • RX rapid exchange
  • the photodetector 74 includes one or more light sensitive elements (not shown) and in embodiments, may be an image sensor.
  • the photodetector 74 may be a silicon-based camera sensor, such as a CMOS or CCD image sensor, amongst others.
  • the photodetector 74 detects light recovered from the light emitter 72 after interaction with the target tissue. It is contemplated that the photodetector 74 may generate one or more signals related to the detected light and transmit the generated signals to the computer 20.
  • the light emitter 72 emits light towards the target tissue for a predetermined period of time, at least a portion of the light is scattered internally within the target tissue and detected by the photodetector 74.
  • the predetermined amount of time during which the light is emitted from the light emitter 72 is long enough that the photodetector 74 can detect changes that occur within the target tissue. Changes in the target tissue during the emission of light alter the path of the emitted light or properties of the detected light. Dynamic properties of light scattering particles, such as rate of motion (e.g., flow rate) can be observed or measured and a peripheral blood flow waveform 76 can be generated and displayed on the user interface 28.
  • rate of motion e.g., flow rate
  • the computer 20 may record the detected signals from the photodetector 74 and store the detected signals within the memory 32.
  • the computer 20 analyzes the detected signals received from the photodetector 74 and determines information about the target tissue, such as a flow rate of blood flowing within the target tissue.
  • the photodetector 74 measures or detects changes in absorption of the light emitted from the light emitter 72.
  • the computer 20 analyses the measurements from the photodetector 74 and generates a photoplethymogram (PPG), which can be displayed on the user interface 28 (FIG. 6).
  • PPG photoplethymogram
  • the PPG and blood flow signals closely align with arterial blood pressure and therefore, the PPG signals can form an arterial blood pressure waveform 78 over a period of time.
  • the computer 20 determines the peripheral blood flow waveform 76 and the arterial blood pressure waveform 78 over a period of time (FIG. 7A).
  • the arterial mechanical properties can be derived from the magnitude or phase of the aortic input impedance spectrum 84, 86 using a mechanical or electrical model (e.g., an analogue model) of the arterial circulation (FIGS. 8A and 8B).
  • the computer 22 interprets the aortic input impedance spectrum 84, 86 using the Windkessel model, such as the three-element Windkessel model, although it is contemplated that suitable model capable of interpreting the aortic input impedance spectrum 84, 86 may be utilized without departing from the scope of the present disclosure.
  • a method of quantifying a relative level of global sympathetic nerve activity, as well as relative changes in activity, by analyzing components of the measured peripheral blood flow waveform 76 and the PPG signals (e.g., arterial blood pressure waveform 78) over a period of time alone, or in combination, in the time or frequency domain is illustrated and generally identified by reference numeral 200.
  • the measured peripheral blood flow 202 and the PPG signal 204 can be analyzed in various combinations, such as individually in the time domain 206, individually in the frequency domain (PSD) 208, combined in the time domain 210 (e.g., the mean PPG signal amplitude and the mean measured peripheral blood flow amplitude), combined in the frequency domain (PSD) 212 (e.g., resistance, compliance, amplitude, phase, etc.), amongst others.
  • time domain e.g., mean PPG signal amplitude and the mean measured peripheral blood flow amplitude
  • PSD frequency domain
  • various features of the signal can be derived, including both time domain (e.g., mean, maximum, minimum, etc.) or frequency domain (PSD) parameters (e.g., magnitude, phase, etc.).
  • the analysis may consist of low and high frequency bands, multiple bands, or any other frequency band of interest.
  • the very low frequency band is analyzed, which is within the range of SNS firing (e.g., vasomotion).
  • a normal range or normal pattern of variation is defined as well as one or more thresholds for detecting a deviation from the defined normal range or pattern of variation, which can be stored in the memory 32 or be uploaded or otherwise set in a memory (not shown) associated with a portable device, such as a wristwatch, etc. It is envisioned that the defined normal range or normal pattern of variation may be expressed as either an absolute value or a proportional change without departing from the scope of the present disclosure. If no change is detected or if the tracked peripheral blood flow or PPG signals do not deviate from the defined normal range or pattern of variation or otherwise exceed/fall below the predetermined thresholds 216, the process returns to monitoring the tracked peripheral blood flow and PPG signals 214.
  • the computer 20 may issue an alert (e.g., visual, auditory, haptic, etc.), display a clinical action associated with the deviation, and/or provide a recommendation regarding potential diagnostic decisions based upon the measured data 218.
  • an alert e.g., visual, auditory, haptic, etc.
  • a method of assessing a candidate for therapy is illustrated and generally identified by reference numeral 300.
  • step 302 light is emitted into target tissue from the light emitter 72 over a period of time.
  • the photodetector 74 detects dynamic properties of light scattering particles within the target tissue over the period of time in step 304.
  • step 306 a peripheral blood flow waveform 76 of a fluid flowing within the target tissue is generated using the detected dynamic properties of the light scattering particles over the period of time.
  • step 316 relative changes in global sympathetic nerve activity within the quantified relative level of global sympathetic nerve activity over the period of time is identified and in step 318, a determination is made regarding whether the identified relative changes in global sympathetic nerve activity fall outside of a predetermined range of global sympathetic nerve activity, where one or more identified relative changes in global sympathetic nerve activity falling outside of the predetermined rang is indicative of a candidate for therapy.
  • a method of assessing and performing a therapeutic procedure is illustrated and generally identified by reference numeral 400.
  • therapy is applied to the target tissue in step 402.
  • light is emitted into tissue from a light emitter in step 404.
  • dynamic properties of light scattering particles within the tissue are detected by a photodetector and in step 408, a peripheral blood flow waveform of a fluid flowing within the tissue is generated using the detected dynamic properties of the light scattering particles.
  • step 410 an amount of light received by the photodetector is calculated, and in step 412, an arterial blood pressure waveform of the fluid flowing within the tissue is calculated using the calculated amount of light received by the photodetector.
  • step 414 a power spectral density for each of the generated peripheral blood flow waveform and the generated arterial blood pressure waveform is calculated.
  • step 416 a relative level of global sympathetic nerve activity is quantified using the calculated power spectral density for each of the generated peripheral blood flow waveform and the generated arterial blood pressure waveform.
  • step 418 relative changes in global sympathetic nerve activity within the quantified relative level of global sympathetic nerve activity is identified and in step 420, it is determined whether the identified relative changes in global sympathetic nerve activity falls outside of a predetermined range of global sympathetic nerve activity.
  • step 404 the method returns to step 404 to continue emitting light into the tissue. If the identified relative changes in global sympathetic nerve activity falls outside of the predetermined range of global sympathetic nerve activity, in step 422, the application of therapy to the target tissue is terminated.
  • the disclosure is not so limited.
  • the method 300 may be undertaken to ensure that the patient is a candidate for denervation. Denervation to a desired blood vessel of the patient may be undertaken, and then method 300 may be undertaken a second time to assess the efficacy of the denervation. If sufficient change is detected (e.g., as in step 424) then the therapy is terminated. Otherwise, denervation can be continued for a time, or the parameters of the denervation (e.g., power, duration, location) may be altered and denervation again undertaken. This process may be repeated until a denervation has been achieved or therapy limits are reached without achieving the desired denervation.
  • the parameters of the denervation e.g., power, duration, location
  • the therapeutic portion 56 includes one or more electrodes 58 disposed on the shaft 52 that are configured to apply denervation therapy to the target tissue. It is envisioned that the one or more electrodes 58 may be disposed in spaced relation to each other and configured to contact the blood vessel walls suitable configuration, such as a helical, expanded configuration or by manipulating the therapeutic portion 56 to contact tissue walls (e.g., in the case of a linear arrangement).
  • the therapeutic assembly 56 may be capable of being placed in any suitable numbers of configurations depending upon the design needs of the therapeutic device 50 or the type of therapeutic procedure being performed.
  • the therapeutic device 50 includes four electrodes 58.
  • the present disclosure is not so limited and the therapeutic device 50 may have more or fewer electrodes 58 without departing from the scope of the present disclosure.
  • the electrodes 58 may be replaced with ultrasound transducers, microwave antennae, ports for delivery of cryoablation medium or chemical medium and other implements and/or ablation and denervation modalities without departing from the scope of the present disclosure
  • the electrodes 58 are disposed in spaced relation to one another along a length of the therapeutic device 50 forming the therapeutic portion 56. As will be appreciated, these electrodes 58 are in communication with the therapy source 24 which produces, for example, monopolar RF energy to denervate the sympathetic nerves of the relevant blood vessel. Additionally, or alternatively, the electrodes 58 may deliver RF energy independently of one another (e.g., monopolar), simultaneously, selectively, sequentially, and/or between any desired combination of the electrodes 58 (e.g., bipolar).
  • the therapeutic device 50 may be a cryotherapy device where the therapeutic portion 56 may include one therapy delivery element, such as an occlusive balloon, a non-occlusive balloon, or other balloon permitting the flow of blood, etc.
  • the therapy source 24 may include a cryogen or coolant source or means to generate a cryogen.
  • the therapeutic device 50 may be a microwave energy device where the therapeutic portion 56 may include one or more therapy delivery elements, such as a microwave antenna.
  • the therapy source 24 may be a microwave energy generator that is operably coupled to the microwave antenna.
  • the therapeutic device may be an ultrasound device where the therapeutic portion 56 may include one or more therapy delivery elements, such as an ultrasound transducer, etc.
  • the memory 32 may include any non-transitory computer-readable storage media for storing data and/or software including instructions that are executable by the processor 30 and which control the operation of the workstation 20 and, in some embodiments, may also control the operation of the therapeutic device 50, and/or imaging device 70.
  • memory 32 may include one or more storage devices such as solid-state storage devices, e.g., flash memory chips.
  • the memory 32 may include one or more mass storage devices connected to the processor 30 through a mass storage controller (not shown) and a communications bus (not shown).
  • computer-readable media can be any available media that can be accessed by the processor 30. That is, computer readable storage media may include non-transitory, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data.
  • computer-readable storage media may include RAM, ROM, EPROM, EEPROM, flash memory or other solid-state memory technology, CD-ROM, DVD, Blu-Ray or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which may be used to store the desired information, and which may be accessed by the therapy source 24.
  • Example 1 A system for performing a diagnostic procedure, comprising: a diagnostic device, the diagnostic configured for placement proximate tissue, wherein a light emitter and a photodetector are disposed on the diagnostic device; a computing device including a processor and a memory storing instructions, which when executed by the processor, cause the computing device to: deliver light from the light emitter into the tissue for a period of time; detect dynamic properties of light scattering particles within the tissue using the photodetector over the period of time; generate a peripheral blood flow waveform of a fluid flowing within the tissue using the detected dynamic properties of the light scattering particles over the period of time; calculate a power spectral density for the generated peripheral blood flow waveform over the period of time; quantify a relative level of global sympathetic nerve activity over the period of time using the calculated power spectral density for the generated peripheral blood flow waveform; identify relative changes in global sympathetic nerve activity within the quantified relative level of global sympathetic nerve activity over the period of time; and determine if the identified relative changes in global sympathetic nerve activity fall outside of
  • Example 2 The system according to Example 1, wherein the instructions, when executed by the processor, cause the computing device to calculate the power spectral density the generated peripheral blood flow waveform over the period of time using the fast Fourier transform.
  • Example 3 The system according to Example 2, wherein calculating the power spectral density includes calculating the power spectral density for the generated peripheral blood flow waveform over the period of time using the fast Fourier transform.
  • Example 4 The system according to Example 1, wherein the instructions, when executed by the processor, cause the computing device to calculate an aortic input impedance spectrum for the generated peripheral blood flow waveform over the period of time using the calculated power spectral density for the generated peripheral blood flow waveform.
  • Example 5 The system according to Example 4, wherein the instructions, when executed by the processor, cause the computing device to quantify the relative level of global sympathetic nerve activity over the period of time using one of the calculated power spectral density or the calculated aortic impedance spectrum.
  • Example 6 The system according to Example 4, wherein the instructions, when executed by the processor, cause the computing device to calculate the aortic input impedance spectrum for the generated peripheral blood flow waveform over the period of time using a Windkessel model.
  • Example 7 The system according to Example 5, wherein the instructions, when executed by the processor, cause the computing device to calculate the aortic input impedance spectrum for the generated peripheral blood flow waveform over the period of time using the three-element Windkessel model.
  • Example 8 The system according to Example 5, wherein the instructions, when executed by the processor, cause the computing device to calculate an amount of light received by the photodetector over the period of time.
  • Example 9 The system according to Example 8, wherein the instructions, when executed by the processor, cause the computing device to generate an arterial blood pressure waveform of the fluid flowing within the target tissue using the calculated amount of light received by the photodetector over the period of time.
  • Example 10 The system according to Example 9, wherein the instructions, when executed by the processor, cause the computing device to calculate the aortic input impedance spectrum of a combined generated peripheral blood flow waveform and generated arterial blood pressure waveform.
  • Example 11 The system according to Example 10, wherein the instructions, when executed by the processor, cause the computing device to combine the generated peripheral blood flow waveform and the generated arterial blood pressure waveform using a derived one or more of a determined resistance, compliance, amplitude, or phase from the generated peripheral blood flow waveform and the generated arterial blood pressure waveform.
  • Example 12 The system according to Example 9, wherein the instructions, when executed by the processor, cause the computing device to calculate a power spectral density of a combined generated peripheral blood flow waveform and generated arterial blood pressure waveform.
  • Example 13 The system according to Example 12, wherein the instructions, when executed by the processor, cause the computing device to combine the generated peripheral blood flow waveform and the generated arterial blood pressure waveform using a derived mean arterial blood pressure amplitude and a derived mean peripheral blood flow waveform from the generated peripheral blood flow waveform and the generated arterial blood pressure waveform over the period of time.
  • Example 14 The system according to Example 1, further comprising intentionally applying a sympathetic stimulus to the candidate for therapy, wherein identifying relative changes in global sympathetic nerve activity includes identifying relative changes in global sympathetic nerve activity during the intentionally applied sympathetic stimulus.
  • Example 15 The system according to Example 14, wherein the intentionally applied sympathetic stimulus is selected from the group consisting of a cold pressor, a hand rip exercise, mental stress, a Valsalva or Mueller maneuver, an acute catecholamine injection, orthostasis, and variable rate pacing.
  • the intentionally applied sympathetic stimulus is selected from the group consisting of a cold pressor, a hand rip exercise, mental stress, a Valsalva or Mueller maneuver, an acute catecholamine injection, orthostasis, and variable rate pacing.
  • Example 16 The system according to Example 1, wherein the instructions, when executed by the processor, cause the computing device to identify relative changes in global sympathetic nerve activity due to naturally occurring sympathetic stimulus.
  • Example 17 The system according to Example 16, wherein the naturally occurring sympathetic stimulus is selected from the group consisting of circadian variation, sleep apnea breathing, orthostasis, intense physical activity, and respiration.
  • Example 19 The system according to Example 1, wherein the diagnostic device is operably coupled to the computing device using a wired connection.
  • Example 20 The system according to Example 1, wherein the instructions, when executed by the processor, cause the computing device to issue one or more of a clinical action, an alert, or a recommendation based upon whether the identified relative changes in global sympathetic nerve activity fall outside of the predetermined range.
  • Example 22 The method according to Example 21, wherein calculating the power spectral density includes calculating the power spectral density for the generated peripheral blood flow waveform over the period of time using a Fourier transform.
  • Example 23 The method according to Example 22, wherein calculating the power spectral density includes calculating the power spectral density for the generated peripheral blood flow waveform over the period of time using the fast Fourier transform.
  • Example 24 The method according to Example 21, further comprising calculating, by the computing device, an aortic input impedance spectrum for the generated peripheral blood flow waveform over the period of time using the calculated power spectral density for the generated peripheral blood flow waveform.
  • Example 25 The method according to Example 24, wherein quantifying the relative level of global sympathetic nerve activity includes quantifying the relative level of global sympathetic nerve activity over the period of time using one of the calculated power spectral density or the calculated aortic impedance spectrum.
  • Example 27 The method according to Example 25, wherein calculating the aortic input impedance spectrum includes calculating the aortic input impedance spectrum for the generated peripheral blood flow waveform over the period of time using the three-element Windkessel model.
  • Example 28 The method according to Example 25, further comprising calculating, by the computing device, an amount of light received by the photodetector over the period of time.
  • Example 29 The method according to Example 28, further comprising generating, by the computing device, an arterial blood pressure waveform of the fluid flowing within the target tissue using the calculated amount of light received by the photodetector over the period of time
  • Example 30 The method according to Example 29, wherein calculating the aortic input impedance spectrum includes calculating the aortic input impedance spectrum of a combined generated peripheral blood flow waveform and generated arterial blood pressure waveform.
  • Example 31 The method according to Example 30, wherein combining the generated peripheral blood flow waveform and the generated arterial blood pressure waveform includes deriving one or more of a determined resistance, compliance, amplitude, or phase from the generated peripheral blood flow waveform and the generated arterial blood pressure waveform.
  • Example 32 The method according to Example 29, wherein calculating the power spectral density includes calculating a power spectral density of a combined generated peripheral blood flow waveform and generated arterial blood pressure waveform.
  • Example 33 The method according to Example 32, wherein combining the generated peripheral blood flow waveform and the generated arterial blood pressure waveform includes deriving a mean arterial blood pressure amplitude and a mean peripheral blood flow waveform amplitude from the generated peripheral blood flow waveform and the generated arterial blood pressure waveform over the period of time.
  • Example 34 The method according to Example 21, further comprising intentionally applying a sympathetic stimulus to the candidate for therapy, wherein identifying relative changes in global sympathetic nerve activity includes identifying relative changes in global sympathetic nerve activity during the intentionally applied sympathetic stimulus.
  • Example 35 The method according to Example 34, wherein the intentionally applied sympathetic stimulus is selected from the group consisting of a cold pressor, a hand rip exercise, mental stress, a Valsalva or Mueller maneuver, an acute catecholamine injection, orthostasis, and variable rate pacing.
  • the intentionally applied sympathetic stimulus is selected from the group consisting of a cold pressor, a hand rip exercise, mental stress, a Valsalva or Mueller maneuver, an acute catecholamine injection, orthostasis, and variable rate pacing.
  • Example 36 The method according to Example 21, wherein identifying relative changes in global sympathetic nerve activity includes identifying relative changes in global sympathetic nerve activity due to naturally occurring sympathetic stimulus.
  • Example 37 The method according to Example 36, wherein the naturally occurring sympathetic stimulus is selected from the group consisting of circadian variation, sleep apnea breathing, orthostasis, intense physical activity, and respiration.
  • Example 38 The method according to Example 21, further comprising issuing one or more of a clinical action, an alert, or a recommendation based upon whether the identified relative changes in global sympathetic nerve activity fall outside of the predetermined range.
  • Example 39 A method of assessing and performing a therapeutic procedure, comprising: navigating a therapeutic device to target tissue, the therapeutic device configured to apply therapy to the target tissue; applying therapy, by the therapeutic device, to the target tissue;
  • monitoring, by a computing device, global sympathetic nerve activity includes: emitting light, from a light emitter, into tissue over a period of time; detecting, by the computing device, dynamic properties of light scattering particles within the tissue by a photodetector over the period of time; generating, by the computing device, a peripheral blood flow waveform of a fluid flowing within the tissue using the detected dynamic properties of the light scattering particles over the period of time; calculating, by the computing device, a power spectral density for the generated peripheral blood flow waveform over the period of time; quantifying, by the computing device, a relative level of global sympathetic nerve activity using the calculated power spectral density for the generated peripheral blood flow waveform; identifying, by the computing device, relative changes in global sympathetic nerve activity within the quantified relative level of global sympathetic nerve activity over the period of time; and determining, by the computing device, if the identified relative changes in global sympathetic nerve activity falls outside of a predetermined range of global sympathetic nerve
  • Example 41 The method according to Example 39, further comprising, after the application of therapy to the target tissue, monitoring, by the computing device, global sympathetic nerve activity a second time to determine, by the computing device, an efficacy of the application of therapy to the target tissue.
  • Example 42 The method according to Example 39, wherein calculating a power spectral density includes calculating the power spectral density for the generated peripheral blood flow waveform over the period of time using a Fourier transform.
  • Example 43 The method according to Example 42, wherein calculating the power spectral density includes calculating the power spectral density for the generated peripheral blood flow waveform over the period of time using the fast Fourier transform.
  • Example 44 The method according to Example 39, further comprising calculating, by the computing device, an aortic input impedance spectrum for the generated peripheral blood flow waveform over the period of time using the calculated power spectral density for the generated peripheral blood flow waveform.
  • Example 45 The method according to Example 44, wherein quantifying the relative level of global sympathetic nerve activity includes quantifying the relative level of global sympathetic nerve activity over the period of time using one of the calculated power spectral density or the calculated aortic input impedance spectrum.
  • Example 48 The method according to Example 46, further comprising calculating, by the computing device, an amount of light received by the photodetector over the period of time.
  • Example 52 The method according to Example 39, wherein calculating the power spectral density includes calculating a power spectral density of a combined generated peripheral blood flow waveform and generated arterial blood pressure waveform.

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Abstract

Un système pour effectuer une procédure de diagnostic comprend un dispositif de diagnostic configuré pour placer un tissu à proximité ayant un émetteur de lumière et un photodétecteur, un dispositif informatique qui délivre de la lumière provenant de l'émetteur de lumière dans le tissu pendant une période de temps, détecte des propriétés dynamiques de particules de diffusion de lumière à l'intérieur du tissu à l'aide du photodétecteur, génère une forme d'onde de flux sanguin périphérique d'un fluide s'écoulant à l'intérieur du tissu à l'aide des propriétés dynamiques détectées, calcule une densité spectrale de puissance pour la forme d'onde de flux sanguin périphérique générée, quantifie un niveau relatif d'activité nerveuse sympathique globale à l'aide de la densité spectrale de puissance calculée, identifie des changements relatifs dans l'activité nerveuse sympathique globale à l'intérieur du niveau relatif quantifié d'activité nerveuse sympathique globale, et détermine si les changements relatifs identifiés dans l'activité nerveuse sympathique globale se situent en dehors d'une plage prédéterminée d'activité nerveuse sympathique globale, qui indique un candidat à une thérapie.
EP23809166.4A 2022-11-23 2023-11-16 Procédé de quantification de l'activité du système nerveux autonome et d'identification de répondeurs potentiels à une thérapie de modulation autonome Pending EP4622540A1 (fr)

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EP1359843A2 (fr) * 2000-11-14 2003-11-12 Yale University Detection et caracterisation de la commande oscillatoire cholinergique dans la microvasculature peripherique
JP2009226167A (ja) * 2008-03-25 2009-10-08 Toshiba Corp 脈波計測装置及びこれを用いた自律神経解析システム
US9610444B2 (en) * 2013-03-15 2017-04-04 Pacesetter, Inc. Erythropoeitin production by electrical stimulation
US20150335288A1 (en) * 2013-06-06 2015-11-26 Tricord Holdings, Llc Modular physiologic monitoring systems, kits, and methods
US12233265B2 (en) * 2016-08-25 2025-02-25 Cala Health, Inc. Systems and methods for treating cardiac dysfunction through peripheral nerve stimulation

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