ROBOTIC SYSTEMS FOR NAVIGATION OF LUMINAL NETWORKS THAT COMPENSATE FOR PHYSIOLOGICAL NOISE

• US 20180279852A1
• Filed: 03/29/2018
• Published: 10/04/2018
• Est. Priority Date: 03/31/2017
• Status: Active Grant

• Current Assignee: Auris Health, Inc. (Johnson & Johnson)
• Original Assignee: Auris Health, Inc. (Johnson & Johnson)
• Inventors: Rafii-Tari, Hedyeh, Ummalaneni, Ritwik, Graetzel, Chauncey F.
• Granted Patent: US 11,490,782 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 1/00006 of control signals
• CPC Class Codes: A61B 1/2676 Bronchoscopes
• CPC Class Codes: A61B 10/04 Endoscopic instruments
• CPC Class Codes: A61B 2017/00699 correcting for movement caused by respiration, e.g. by triggering
• CPC Class Codes: A61B 2017/00809 Lung operations
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/2048 using an accelerometer or inertia sensor
• CPC Class Codes: A61B 2034/2051 Electromagnetic tracking systems
• CPC Class Codes: A61B 2034/2063 Acoustic tracking systems, e.g. using ultrasound
• CPC Class Codes: A61B 2034/301 for introducing or steering flexible instruments inserted into the body, e.g. catheters or endoscopes
• CPC Class Codes: A61B 2034/303 specifically adapted for manipulations within body lumens, e.g. within lumen of gut, spine, or blood vessels
• CPC Class Codes: A61B 2090/3614 using optical fibre
• CPC Class Codes: A61B 2090/371 with simultaneous use of two cameras
• CPC Class Codes: A61B 34/20 Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• CPC Class Codes: A61B 34/30 Surgical robots
• CPC Class Codes: A61B 34/32 operating autonomously
• CPC Class Codes: A61B 34/35 for telesurgery
• CPC Class Codes: A61B 34/76 Manipulators having means for providing feel, e.g. force or tactile feedback
• CPC Class Codes: A61B 5/062 using magnetic field
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0816 : Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/6867 : specially adapted to be attached or implanted in a specific body part A61B5/6847 takes precedence
• CPC Class Codes: A61B 5/7207 : of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7275 : Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7289 : Retrospective gating, i.e. associating measured signals or images with a physiological event after the actual measurement or image acquisition, e.g. by simultaneously recording an additional physiological signal during the measurement or image acquisition
• CPC Class Codes: G06T 19/003 : Navigation within 3D models or images
• CPC Class Codes: G06T 2200/24 : involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 2210/41 : Medical
• CPC Class Codes: G16H 20/40 : relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders

Abstract

Certain aspects relate to systems and techniques for luminal network navigation. Some aspects relate to incorporating respiratory frequency and/or magnitude into a navigation system to implement patient safety measures. Some aspects relate to identifying, and compensating for, motion caused by patient respiration in order to provide a more accurate identification of the position of an instrument within a luminal network.

Claims

1. A system configured to navigate a luminal network of a patient, the system comprising:

a field generator configured to generate an electromagnetic (EM) field;

a set of one or more EM sensors at a distal end of a steerable instrument;

a set of one or more respiration sensors;

at least one computer-readable memory having stored thereon executable instructions; and

one or more processors in communication with the at least one computer-readable memory and configured to execute the instructions to cause the system to at least;

access a preoperative model representative of the luminal network;

access a mapping between a coordinate frame of the EM field and a coordinate frame of the preoperative model;

calculate at least one position of the set of EM sensors within the EM field based on a data signal from the set of EM sensors;

calculate a frequency of respiration of the patient based on a data signal from the set of respiration sensors; and

determine a position of the distal end of the steerable instrument relative to the preoperative model based on the registration mapping, the frequency of the respiration, and the at least one position of the set of EM sensors within the EM field.

2. The system of claim 1, wherein the one or more processors are configured to execute the instructions to cause the system to at least:

transform one or more data signals from the set of respiration sensors into a frequency domain representation of the one or more data signals; and

identify the frequency of respiration from the frequency domain representation of the one or more data signals.

3. The system of claim 2, wherein the one or more processors are configured to execute the instructions to cause the system to at least:

apply a predictive filter to one or more data signals from the set of EM sensors, the predictive filter configured to predict respiration motion due to the respiration; and

remove components of the one or more data signals attributable to the predicted respiration motion to determine the position of the distal end of the steerable instrument relative to the preoperative model.

4. The system of claim 1, wherein the one or more processors are configured to execute the instructions to cause the system to at least calculate at least one magnitude of displacement of the set of respiration sensors between inspiration and expiration phases of the respiration of the patient.

5. The system of claim 4, wherein the one or more processors are configured to execute the instructions to at least:

determine at least one position of the set of EM sensors relative to the set of respiration sensors;

calculate at least one positional displacement of the set of EM sensors between the inspiration and the expiration phases based on (i) the determined at least one position of the set of EM sensors relative to the set of respiration sensors and (ii) the at least one magnitude of displacement of the set of respiration sensors between inspiration and expiration phases; and

determine the position of the distal end of the steerable instrument relative to the preoperative model based on the calculated at least one positional displacement of the set of EM sensors between the inspiration and the expiration phases.

6. The system of claim 5, wherein the set of respiration sensors comprises a first additional EM sensor positioned, in use, at a first position on the body surface and a second additional EM sensor positioned, in use, at a second position of the body surface, wherein the second position is spaced apart from the first position such that a first magnitude of displacement of the first additional EM sensor is greater than a second magnitude of displacement of the second additional EM sensor between the inspiration and the expiration phases.

7. The system of claim 6, wherein the one or more processors are configured to execute the instructions to cause the system to at least:

determine a relative positioning of the set of EM sensors with respect to the first and second additional EM sensors; and

interpolate between the first and second magnitudes of displacement based on the determined relative positioning of the set of EM sensors, wherein the calculation of the positional displacement of the set of EM sensors between the inspiration and the expiration phases is based on the interpolated magnitude.

8. The system of claim 6, wherein the one or more processors are configured to execute the instructions cause the system to at least:

estimate a movement vector for at least a portion of the preoperative model based on the calculated at least one magnitude of displacement;

translate the preoperative model within the coordinate frame of the EM field based on the estimated movement vector; and

determine the position of the distal end of the steerable instrument based on the translated preoperative model.

9. The system of claim 8, wherein, to translate the preoperative model within the coordinate frame of the EM field, the one or more processors are configured to execute the instructions cause the system to at least:

move a first portion of the model to first new coordinates based on the first magnitude of displacement; and

move a second portion of the model to second new coordinates based on the second magnitude of displacement.

10. The system of claim 1, further comprising a display, wherein the one or more processors are configured to execute the instructions to cause the system to at least:

generate a graphical representation of the position of the distal end of the steerable instrument relative to the preoperative model; and

render the generated graphical representation on the display.

11. An apparatus configured to determine navigation of a luminal network of a patient, the apparatus comprising:

at least one computer-readable memory having stored thereon executable instructions; and

one or more processors in communication with the at least one computer-readable memory and configured to execute the instructions to cause the apparatus to at least;

access a model representative of the luminal network;

access a mapping between a coordinate frame of the model and a coordinate frame of an electromagnetic (EM) field generated around the luminal network;

receive data from an EM sensor on a distal end of a steerable instrument inserted, in use, into the luminal network;

calculate, based on data from the EM sensor, a position of the EM sensor within the EM field based on data from the EM sensor;

receive data from at least one additional sensor configured to detect movement of the luminal network;

calculate, based on data from the at least one additional sensor, a frequency of cyclic movement of the luminal network; and

determine a position of the distal end of the steerable instrument relative to the model based on the mapping, the frequency, and the position of the EM sensor within the EM field.

12. The apparatus of claim 11, wherein the at least one additional sensor comprises an acoustic respiratory sensor, and wherein the acoustic respiratory sensor detects the cyclic movement during patient respiration.

13. The apparatus of claim 11, wherein the luminal network comprises respiratory airways, wherein the one or more processors are configured to execute the instructions to cause the apparatus to guide the steerable instrument through the luminal network.

14. The apparatus of claim 11, wherein the one or more processors are configured to execute the instructions to cause the system to at least:

transform one or more data signals from the at least one additional sensor into a frequency domain representation of the one or more data signals; and

identify the frequency of cyclic movement from the frequency domain representation of the one or more data signals.

15. The apparatus of claim 14, wherein the one or more processors are configured to execute the instructions to cause the system to at least:

apply a filter to one or more data signals from the EM sensor, the filter configured to attenuate a portion of the one or more data signals with the identified frequency; and

determine the position of the distal end of the steerable instrument relative to the model based on the filtered one or more data signals from the EM sensor.

16. The apparatus of claim 11, wherein the luminal network comprises respiratory airways, and wherein the one or more processors are configured to execute the instructions to cause the system to at least calculate at least one magnitude of displacement of the at least one additional sensor between inspiration and expiration phases of the respiration of the patient.

17. The apparatus of claim 16, wherein the one or more processors are configured to execute the instructions to at least:

determine a position of the EM sensor relative to the at least one additional sensor;

calculate a positional displacement of the EM sensor between the inspiration and the expiration phases based on (i) the determined position of the EM sensor relative to the at least one additional sensor and (ii) the at least one magnitude of displacement of the at least one additional sensor between inspiration and expiration phases; and

determine the position of the distal end of the steerable instrument relative to the preoperative model based on the calculated positional displacement of EM sensor between the inspiration and the expiration phases.

18. The apparatus of claim 17, wherein the at least one additional sensor comprises a first additional EM sensor positioned, in use, at a first position on the body surface and a second additional EM sensor positioned, in use, at a second position of the body surface, wherein the second position is spaced apart from the first position such that a first magnitude of displacement of the first additional EM sensor is greater than a second magnitude of displacement of the second additional EM sensor between the inspiration and the expiration phases.

19. The apparatus of claim 18, wherein the one or more processors are configured to execute the instructions to cause the system to at least:

determine a position of the EM sensor relative to the first and second additional EM sensors; and

interpolate between the first and second magnitudes of displacement based on the determined position of the EM sensor relative to the first and second additional EM sensors, wherein the calculation of the positional displacement of the EM sensor between the inspiration and the expiration phases is based on the interpolated magnitude.

20. The apparatus of claim 18, wherein the one or more processors are configured to execute the instructions cause the system to at least:

estimate a movement vector for at least a portion of the model based on the calculated at least one magnitude of displacement;

translate the model within the coordinate frame of the EM field based on the estimated movement vector; and

determine the position of the distal end of the steerable instrument based on the translated model.

21. The apparatus of claim 20, wherein, to translate the preoperative model within the coordinate frame of the EM field, the one or more processors are configured to execute the instructions cause the system to at least:

move a first portion of the model to first new coordinates based on the first magnitude of displacement; and

move a second portion of the model to second new coordinates based on the second magnitude of displacement.

22. A non-transitory computer readable storage medium having stored thereon instructions that, when executed, cause at least one computing device to at least:

receive first data from an electromagnetic (EM) sensor on an instrument inserted, in use, in a tissue site of a patient and second data from at least one additional sensor configured to detect movement of the tissue site;

calculate, based on the first data, a position of the EM sensor within an EM field disposed around the tissue site;

calculate, based on second data, a frequency of cyclic movement of the tissue site; and

determine a position of the instrument relative to the tissue site based on (i) the frequency of cyclic movement of the tissue site and (ii) the position of the EM sensor within the field.

23. The non-transitory computer readable storage medium of claim 22, wherein the instructions, when executed, cause the at least one computing device to:

transform the second data into a frequency domain representation; and

identify the frequency of the cyclic movement from the frequency domain representation.

24. The non-transitory computer readable storage medium of claim 23, wherein the instructions, when executed, cause the at least one computing device to:

apply a filter to the first data, the filter configured to attenuate a portion of the first data with the identified frequency; and

determine the position of the instrument based on the filtered first data.

25. The non-transitory computer readable storage medium of claim 22, wherein the tissue site comprises respiratory airways, and wherein the instructions, when executed, cause the at least one computing device to calculate at least one magnitude of displacement of the at least one additional sensor between inspiration and expiration phases of the respiration of the patient.

26. The non-transitory computer readable storage medium of claim 25, wherein the instructions, when executed, cause the at least one computing device to:

determine a position of the EM sensor relative to the at least one additional sensor;

calculate a positional displacement of the EM sensor between the inspiration and the expiration phases based on (i) the determined position of the EM sensor relative to the at least one additional sensor and (ii) the at least one magnitude of displacement of the at least one additional sensor between inspiration and expiration phases; and

determine the position of the distal end of the steerable instrument relative to the preoperative model based on the calculated positional displacement of EM sensor between the inspiration and the expiration phases.

27. The non-transitory computer readable storage medium of claim 25, wherein the at least one additional sensor comprises a first additional EM sensor positioned, in use, at a first position on the patient and a second additional EM sensor positioned, in use, at a second position of the patient, wherein the second position is spaced apart from the first position such that a first magnitude of displacement of the first additional EM sensor is greater than a second magnitude of displacement of the second additional EM sensor between the inspiration and the expiration phases, and wherein the instructions, when executed, cause the at least one computing device to:

determine a position of the EM sensor relative to the first and second additional EM sensors; and

interpolate between the first and second magnitudes of displacement based on the determined position of the EM sensor relative to the first and second additional EM sensors, wherein the calculation of the positional displacement of the EM sensor between the inspiration and the expiration phases is based on the interpolated magnitude.

28. The non-transitory computer readable storage medium of claim 22, wherein the instructions, when executed, cause the at least one computing device to access data representing:

a model representing a topography of the tissue site; and

a mapping between coordinate frames of the field and the model,

wherein determining the position of the instrument is based on the mapping, the frequency, and the position of the EM sensor within the field.

29. The non-transitory computer readable storage medium of claim 28, wherein the tissue site comprises respiratory airways, and wherein the instructions, when executed, cause the at least one computing device to:

calculate at least one magnitude of displacement of the at least one additional sensor between inspiration and expiration phases of the respiration of the patient;

estimate a movement vector for at least a portion of the model based on the calculated at least one magnitude of displacement;

translate the model within a coordinate frame based on the estimated movement vector; and

determine the position of the instrument based on the translated model.

30. The non-transitory computer readable storage medium of claim 29, wherein, to translate the model within the coordinate frame, the instructions, when executed, cause the at least one computing device to:

move a first portion of the model to first new coordinates based on the first magnitude of displacement; and

move a second portion of the model to second new coordinates based on the second magnitude of displacement.