Denervation therapy

12076,089

17/814757

July 25, 2022

Example systems and techniques for denervation, for example, renal denervation. In some examples, a processor determines one or more tissue characteristics of tissue proximate a target nerve and a blood vessel. The processor may generate, based on the one or more tissue characteristics, an estimated volume of influence of denervation therapy delivered by a therapy delivery device disposed within the blood vessel. The processor may generate a graphical user interface including a graphical representation of the tissue proximate the target nerve and the blood vessel and a graphical representation of the estimated volume of influence.

Medtronic Ireland Manufacturing Unlimited Company (Dublin, IE)

Medtronic Ireland Manufacturing Unlimited Company (Dublin, IE)

1. A method comprising: determining, by processing circuitry and based on one or more tissue characteristics of a region of a patient, the region comprising a target nerve and a blood vessel of a patient, a response state associated with each denervation stimulus of a plurality of denervation stimuli delivered to the region by a therapy delivery device disposed within the blood vessel; determining, by the processing circuitry and for each denervation stimulus of the plurality of denervation stimuli, whether a viability of the target nerve is below a threshold based on the respective response state, wherein the viability of the target nerve being below the threshold is indicative of a reduction in function of the target nerve; and selecting, by the processing circuitry, a denervation stimulus from the plurality of denervation stimuli based on the determined viability of the target nerve.

2. The method of claim 1 , wherein determining the response state associated with each denervation stimulation comprises: subjecting a computer model to digital representations of the plurality of denervation stimuli, wherein the computer model is generated based on a digital reconstruction of the region of the patient, and wherein the computer model defines a spatial representation of the one or more tissue characteristics in the region; and determining, based on the computer model, the response state associated with each denervation stimulus of the plurality of denervation stimuli.

3. The method of claim 2 , wherein subjecting the computer model to the digital representations of the plurality of denervation stimuli includes subjecting the computer model to digital representations of a delivery of the respective denervation stimulus by the therapy delivery device in a respective predetermined orientation and at a respective predetermined location along the blood vessel.

4. The method of claim 1 , wherein the response state associated with each denervation stimulus comprises a volume of influence of associated with the respective denervation stimulus.

5. The method of claim 1 , wherein the region comprises at least one non-target non-nerve tissue, wherein selecting the denervation stimulus further comprises: determining, by the processing circuitry, that a viability of the at least one non-target non-nerve tissue corresponding to the denervation stimulus is greater than the threshold.

6. The method of claim 1 , wherein selecting the denervation stimulus comprises selecting the denervation stimulus based on a determination that the determined viability of the target nerve is below the threshold.

7. The method of claim 1 , further comprising: determining, by the processing circuitry, a therapy program comprising the selected denervation stimulus; and causing, by the processing circuitry, a medical device to deliver the denervation therapy to the region of the patient according to the therapy program.

8. The method of claim 1 , wherein each denervation stimulus of the plurality of denervation stimuli comprises at least one of a radiofrequency (RF) stimulus, a thermal stimulus, a cryogenic stimulus, a microwave stimulus, an ultrasonic stimulus, an optical stimulus, or a chemical stimulus.

9. A system comprising: a memory configured to store one or more tissue characteristics of a region of a patient, the region comprising a target nerve and a blood vessel of a patient; and processing circuitry configured to: determine, based on the one or more tissue characteristics, a response state associated with each denervation stimulus of a plurality of denervation stimuli delivered to the region by a therapy delivery device disposed within the blood vessel; determine for each denervation stimulus of the plurality of denervation stimuli, whether a viability of the target nerve based on the respective response state is below a threshold, wherein the viability of the target nerve being below the threshold is indicative of a reduction in function of the target nerve; and select a denervation stimulus from the plurality of denervation stimuli based on the determined viability of the target nerve.

10. The system of claim 9 , wherein the memory stores a computer model generated based on a digital reconstruction of the region of a patient, wherein the computer model defines a spatial representation of the one or more tissue characteristics in the region, and wherein the processing circuitry is configured to determine the response state by at least: subjecting the computer model to digital representations of the plurality of denervation stimuli; and determining, based on the computer model, the response state associated with each denervation stimulus of the plurality of denervation stimuli.

11. The system of claim 10 , wherein to subject the computer model to the digital representations of the plurality of denervation stimuli, the processing circuitry is configured to: subject the computer model to digital representations of a delivery of the respective denervation stimulus by the therapy delivery device in a respective predetermined orientation and at a respective predetermined location along the blood vessel.

12. The system of claim 9 , wherein the response state associated with each denervation stimulus comprises a volume of influence of associated with the respective denervation stimulus.

13. The system of claim 9 , wherein the region comprises at least one non-target non-nerve tissue, and wherein to select the denervation stimulus, the processing circuitry is further configured to: determine that a viability of the at least one non-target non-nerve tissue corresponding to the respective denervation stimulus is greater than the threshold.

14. The system of claim 9 , wherein to select the denervation stimulus, the processing circuitry is configured to select the denervation stimulus based on a determination that the determined viability of the target nerve is below the threshold.

15. The system of claim 9 , wherein each denervation stimulus of the plurality of denervation stimuli comprises at least one of a radiofrequency (RF) stimulus, a thermal stimulus, a cryogenic stimulus, a microwave stimulus, an ultrasonic stimulus, an optical stimulus, or a chemical stimulus.

16. The system of claim 9 , further comprising a medical device, wherein the processing circuitry is further configured to: determine a therapy program comprising the selected denervation stimulus; and cause the medical device to deliver the denervation therapy to the region of the patient according to the therapy program.

17. A system comprising: a memory configured to store a computer model that defines a spatial representation of one or more tissue characteristics of a region of a patient, wherein the region comprises a target nerve and a blood vessel; and processing circuitry configured to: simulate, using the computer model, delivery of denervation therapy to the region of the patient according to a therapy program; determine, using the computer model, an effect of the simulated denervation therapy on the region; determine that a viability of the target nerve satisfies a threshold condition based on the determined effect of the simulated denervation therapy being below a threshold, wherein the viability of the target nerve being below the threshold is indicative of a reduction in function of the target nerve; and based on the determination that the viability of the target nerve satisfies the threshold condition, cause a medical device to deliver denervation therapy to the region in accordance with the therapy program.

18. The system of claim 17 , wherein the computer model simulates delivery of the denervation therapy by a therapy delivery device in a predetermined orientation and at a predetermined location along the blood vessel.

19. The system of claim 17 , wherein the region comprises at least one non-target non-nerve tissue, and wherein the processing circuitry is further configured to determine that a viability of the of the at least one non-target non-nerve tissue is greater than the threshold based on the determined effect of the simulated denervation therapy and cause the medical device to deliver the denervation therapy to the region in accordance with the therapy program based on the determination that the viability of the target nerve satisfies the threshold condition and determination that the viability of the of the at least one non-target non-nerve tissue is greater than the threshold.

20. The system of claim 17 , wherein the effect of the simulated denervation therapy comprises a volume of influence of associated with a denervation stimulus defined by the therapy program.

21. The system of claim 9 , wherein the plurality of denervation stimuli comprises a plurality of predetermined denervation stimuli, and wherein the system further comprises a memory configured to store the plurality of predetermined denervation stimuli.

8568399 October 2013 Azamian et al.
9066720 June 2015 Ballakur et al.
9675818 June 2017 Hirai et al.
9999461 June 2018 Azamian et al.
10342592 July 2019 Tunev et al.
10786306 September 2020 Coates
11419681 August 2022 Coates
20060142801 June 2006 Demarais et al.
20070129720 June 2007 Demarais et al.
20130178910 July 2013 Azamian
20140074076 March 2014 Gertner
20140276789 September 2014 Dandler
20140371774 December 2014 Hwang
20150088120 March 2015 Garcia
103313671 September 2013
104254366 December 2014
104254367 December 2014
104337529 February 2015
2001190587 July 2001
2015002983 January 2015
2015502820 January 2015
2012088482 June 2012
2013086461 June 2013

edspgr.12076089