IP Library › Granted Patent US 12,279,879
Granted Patent B1
US 12,279,879 · App. 18/799,987 · Granted Apr 22, 2025

System and method for empirical assessment of nerve health during a spinal decompression procedure

Inventors: David S. Nay (Novi, MI); Christopher Wybo (Brighton, MI)
Assignee: NEURALYTIX, LLC
A61B5/4041A61B5/1107A61B5/294A61B5/388A61B5/7246A61B5/7267A61B5/7275A61B5/742A61B2505/05
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Quick Facts
Patent No.
US 12,279,879
App. No.
18/799,987
Filed
Aug 9, 2024
Granted
Apr 22, 2025
Kind
B1
Art Unit
3791
USPC
600/595
Abstract

A method for assessing nerve health during a spinal decompression procedure includes: accessing a database containing historical patient data; receiving patient data of a target patient; identifying a subset of historical patients with similar pre-operative characteristics; generating an individualized target range for at least one nerve function parameter based on the subset; measuring an actual nerve function parameter of the target patient during the procedure; and displaying a graphical representation of the measured parameter relative to the individualized target range.

Claims (54)

1. A method for empirically assessing nerve health during a spinal decompression procedure performed on a target patient, the method comprising:

accessing, by a processor, a database containing historical patient data, the historical patient data including at least one of: pre-operative patient characteristics; intraoperative nerve function parameters obtained during spinal decompression procedures; or post-operative outcomes following spinal decompression procedures;

receiving, by the processor, patient data of the target patient, the patient data including pre-operative characteristics;

identifying, by the processor, a subset of historical patients with pre-operative characteristics similar to the pre-operative characteristics of the target patient;

generating, by the processor, an individualized target range for at least one nerve function parameter based on the subset of historical patients;

measuring, during the spinal decompression procedure, at least one actual nerve function parameter of the target patient, wherein the measuring includes:

generating, by the processor, one or more electrical stimuli;

transmitting the one or more electrical stimuli to an electrode in contact with a nerve of the target patient;

detecting, by a sensor in communication with the processor, muscle responses evoked by the electrical stimuli; and

analyzing, by the processor, the detected muscle responses to determine the at least one actual nerve function parameter; and

displaying, on a display device, a graphical representation of the measured nerve function parameter relative to the individualized target range.

2. The method of claim 1 , wherein the pre-operative characteristics include at least one of: age, gender, body mass index (BMI), and pre-operative neurological function assessment.

3. The method of claim 1 , further comprising:

generating, by the processor, a statistical risk profile correlating nerve function measurements with probabilities of surgical complications based on the subset of historical patients; and

comparing, by the processor, the measured nerve function parameter to the statistical risk profile.

4. The method of claim 3 , further comprising:

displaying, on the display device, a graphical representation of the measured nerve function parameter relative to the statistical risk profile.

5. The method of claim 4 , wherein the graphical representation includes:

a graph showing the individualized target range for the at least one nerve function parameter;

a curve representing the statistical risk profile;

an indicator showing the position of the measured nerve function parameter relative to the graph and the curve;

a probability of successful outcome based on the measured nerve function parameter; and

a risk of complications based on the measured nerve function parameter.

6. The method of claim 1 , wherein the at least one nerve function parameter includes at least one of: minimum stimulation threshold, maximal stimulation threshold, and magnitude of maximal muscle response.

7. The method of claim 1 , wherein identifying the subset of historical patients comprises applying a machine learning algorithm to the historical patient data to cluster patients based on similarity of pre-operative characteristics.

8. The method of claim 1 , further comprising calculating a nerve function index based on multiple nerve function measurements, wherein the individualized target range is generated for the nerve function index.

9. The method of claim 3 , wherein the statistical risk profile includes probabilities of specific surgical complications, including at least one of: a destabilization of the spine, a dural tear, a blood clot, a cerebrospinal fluid (CSF) leak, or an infection.

10. The method of claim 1 , wherein the sensor is a mechanomyography (MMG) sensor configured to detect mechanical muscle responses.

11. The method of claim 1 , further comprising:

receiving post-operative outcome data for the target patient;

updating the database with the target patient's pre-operative characteristics, intraoperative nerve function measurements, and post-operative outcome data; and

refining the process of generating individualized target ranges based on the updated database.

12. The method of claim 11 , wherein refining the process of generating individualized target ranges comprises using a machine learning algorithm to analyze patterns and associations between patient characteristics, nerve function parameters, and surgical outcomes.

13. A system for assessing nerve health during a spinal decompression procedure performed on a target patient, the system comprising:

a database containing historical patient data;

a stimulator configured to deliver electrical stimuli to a nerve of the target patient;

a mechanical sensor configured to detect muscle responses evoked by the electrical stimuli;

a display device; and

a processor in communication with the database, the stimulator, and the sensor, the processor configured to:

access the historical patient data;

identify a subset of historical patients similar to the target patient;

generate an individualized target range for at least one nerve function parameter based on the subset of historical patients;

control the stimulator to deliver the electrical stimuli;

analyze signals from the sensor to determine at least one actual nerve function parameter;

display a graphical representation of the actual nerve function parameter relative to the individualized target range on the display device.

14. The system of claim 13 , wherein the processor is further configured to:

generate a statistical risk profile correlating nerve function measurements with probabilities of surgical complications based on the subset of historical patients; and

compare the actual nerve function parameter to the statistical risk profile.

15. The system of claim 14 , wherein the processor is further configured to display a graphical representation of the actual nerve function parameter relative to the statistical risk profile.

16. The system of claim 13 , wherein the processor is further configured to generate an alert when the actual nerve function parameter enters the individualized target range.

17. The system of claim 13 , wherein the processor is further configured to:

receive post-operative outcome data for the target patient;

update the database with the target patient's pre-operative characteristics, intraoperative nerve function measurements, and post-operative outcome data; and

refine the process of generating individualized target ranges using a machine learning algorithm to analyze patterns and associations between patient characteristics, nerve function parameters, and surgical outcomes.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 12, 2024
From: NAY, DAVID S.; CHRISTOPHER, CHRISTOPHER
To: NEURALYTIX, LLC
Reel/Frame 068249/0057 →
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