WO2025175171A1

WO2025175171A1 - Improved path planning and alignment for lung navigation

Info

Publication number: WO2025175171A1
Application number: PCT/US2025/016034
Authority: WO
Inventors: Nathan J. Knutson; Steven J. LEVINE; Badr Elmaanaoui; Ofer Barasofsky; Ariel Birenbaum; Guy Alexandroni; Paul M. Loschak; Jing Zhao; Scott E.M. Frushour; Sahar SARAGE; Maria MINDLIN; Ilana KOREH; Batel SONSINO
Original assignee: Covidien LP
Current assignee: Covidien LP
Priority date: 2024-02-16
Filing date: 2025-02-14
Publication date: 2025-08-21
Anticipated expiration: 2026-08-16

Abstract

A system for performing a surgical procedure includes a catheter navigable within a luminal network of a patient and a workstation operably coupled to the catheter and including a memory and a processor, the memory storing instructions thereon, which when executed by the processor cause the processor to generate a 3D model of the luminal network of the patient's lungs, identify target tissue in the generated 3D model, receive catheter information, generate a plurality of proposed pathways through the luminal network to the identified target tissue, determine weighting factors based on the generated plurality of potential airways, modify the determined weighting factors based on the received catheter information, apply the modified weighting factors to the generated plurality of proposed pathways, rank the generated proposed pathways after applying the modifying weighting factors to the generated plurality of proposed pathways, and display the ranked proposed pathways to the target tissue.

Description

IMPROVED PATH PLANNING AND ALIGNMENT FOR LUNG NAVIGATION

BACKGROUND

Technical Field

[0001] The present disclosure relates to the field of navigating medical devices within a patient, and in particular, planning a pathway though a luminal network of a patient and navigating medical devices to a target.

Description of Related Art

[0002] There are several commonly applied medical methods, such as endoscopic procedures or minimally invasive procedures, for treating various maladies affecting organs including the liver, brain, heart, lungs, gall bladder, kidneys, and bones. Often, one or more imaging modalities, such as magnetic resonance imaging (MRI), ultrasound imaging, computed tomography (CT), cone-beam computed tomography (CBCT) or fluoroscopy (including 3D fluoroscopy) are employed by clinicians to identify and navigate to areas of interest within a patient and ultimately a target for biopsy or treatment. In some procedures, pre-operative scans may be utilized for target identification and intraoperative guidance. However, real-time imaging may be required to obtain a more accurate and current image of the target area. Furthermore, real-time image data displaying the current location of a medical device with respect to the target and its surroundings may be needed to navigate the medical device to the target in a safe and accurate manner (e.g., without causing damage to other organs or tissue).

[0003] For example, an endoscopic approach has proven useful in navigating to areas of interest within a patient. To enable the endoscopic approach endoscopic navigation systems have been developed that use previously acquired MRI data or CT image data to generate a three-dimensional (3D) rendering, model, or volume of the particular body part such as the lungs.

[0004] In some applications, the acquired MRI data or CT Image data may be acquired during the procedure (perioperatively). The resulting volume generated from the MRI scan or CT scan is then utilized to create a navigation plan to facilitate the advancement of the endoscope (or other suitable medical device) within the patient anatomy to an area of interest. In some cases, the volume generated may be used to update a previously created navigation plan. A locating or tracking system, such as an electromagnetic (EM) tracking system, or fiberoptic shape sensing system may be utilized in conjunction with, for example, CT data, to facilitate guidance of the endoscope to the area of interest. [0005] However, larger access devices may have difficulty navigating to the area of interest if the area of interest is located adjacent to small or narrow airways. As can be appreciated, the difficulty of navigating larger access devices, such as those having a camera, within narrow airways can lead to increased surgical times to navigate to the proper position relative to the area of interest which can lead to navigational inaccuracies or the use of fluoroscopy that leads to additional set-up time and radiation exposure.

SUMMARY

[0006] A system for performing a surgical procedure includes a catheter navigable within a luminal network of a patient’s lungs and a workstation operably coupled to the catheter, the workstation including a memory and a processor, the memory storing instructions thereon, which when executed by the processor cause the processor to generate a 3D model of the luminal network of the patient’s lungs, identify target tissue in the generated 3D model, receive catheter information, generate a plurality of proposed pathways through the luminal network to the identified target tissue, determine weighting factors based on the generated plurality of potential pathways, modify the determined weighting factors based on the received catheter information, apply the modified weighting factors to the generated plurality of proposed pathways, rank the generated proposed pathways after applying the modified weighting factors to the generated plurality proposed pathways, and display the ranked proposed pathways to the target tissue.

[0007] In aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to receive patient information and modify the determined weighting factors based on the received medical device information and the received patient information.

[0008] In other aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to receive the weighting factors, the weighting factors including at least one of a distance to a selected portion of the target tissue from a distal end portion of the catheter, or an alignment of candidate airways of the luminal network with a selected portion of the target tissue, or a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter, or crossing of pleura or segmental boundaries of the patient’s lungs, or a volumetric overlap of expected trajectories of a surgical tool received within the catheter, or airways within the luminal network having an inner dimension that is less than a predetermined threshold. [0009] In certain aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to determine the distance to the selected portion of the target tissue from the distal end portion of the catheter at a terminus of the plurality of generated proposed pathways.

[0010] In other aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to determine the alignment of candidate airways with the selected portion of the target tissue by determining an angle between an alignment vector of a working channel of the catheter and a vector from a position of the distal end portion of the catheter to the selected portion of the target tissue.

[0011] In aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to determine the predetermined threshold inner dimension based on a percentage of an outer dimension of the catheter.

[0012] In certain aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to determine the predetermined threshold inner dimension based on a percentage increase of the outer dimension of the catheter.

[0013] In aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to identify pleura or segmental boundaries between a distal end portion of the catheter and the target tissue that if crossed, may result in pneumothorax.

[0014] In other aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to determine a volumetric overlap between the proposed surgical tool path in the plurality of generated proposed pathways and a coverage of the volume of the target tissue.

[0015] In certain aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to receive catheter information on the type of catheter used to navigate to the target tissue, receive catheter information on the type of surgical tool used to treat the target tissue, and receive catheter information on the outer dimension of the catheter.

[0016] In accordance with another aspect of the present disclosure, a method for performing a surgical procedure includes generating a 3D model of the luminal network of a patient’s lungs, identifying target tissue in the generated 3D model, receiving catheter information, generating a plurality of proposed pathways through the luminal network to the identified target tissue, determining weighting factors based on the generated plurality of potential pathways, modifying the determined weighting factors based on the received catheter information, applying the modified weighting factors to the generated plurality of proposed pathways, ranking the generated proposed pathways after applying the modified weighting factors to the generated plurality of proposed pathways, and displaying the ranked proposed pathways to the target tissue.

[0017] In aspects, the determined weighting factors may include at least one of a distance to a volumetric center of the target tissue from a distal end portion of the catheter, or a distance to a center of malignancy of the target tissue from a distal end portion of the catheter; or an alignment of candidate airways of the luminal network with a volumetric center of the target tissue, or an alignment of candidate airways of the luminal network with a center of malignancy of the target tissue; or a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter, or crossing of pleural or segmental boundaries of the patient’s lungs, or a volumetric overlap of expected trajectories of a surgical tool received within the catheter, or airways within the luminal network having an inner dimension that is less than a predetermined threshold.

[0018] In other aspects, the predetermined threshold inner dimension may be based on a percentage of an outer dimension of the catheter.

[0019] In certain aspects, the predetermined threshold inner dimension may be based on a percentage increase of the outer dimension of the catheter.

[0020] In aspects, the alignment of candidate airways with the volumetric center of the target tissue may be determined using an angle between an alignment vector of a working channel of the catheter and a vector from a position of the distal end portion of the catheter to the volumetric center of the target tissue.

[0021] In accordance with another aspect of the present disclosure, a system for performing a surgical procedure includes a catheter navigable within a luminal network of a patient’s lungs, a workstation operably coupled to the catheter, the workstation including a memory and a processor, the memory storing instructions thereon, which when executed by the processor cause the processor to generate a 3D model of the luminal network of a patient’ s lungs, identify target tissue in the generated 3D model, generate a plurality of proposed pathways through the luminal network to the identified target tissue, determine weighting factors based on the generated plurality of potential pathways, the weighting factors including at least one of a distance to a selected portion of the target tissue from a distal end portion of the catheter, and an alignment of candidate airways of the luminal network with a selected portion of the target tissue, and a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter, and crossing of pleural or segmental boundaries of the patient’s lungs, and a volumetric overlap of expected trajectories of a surgical tool received within the catheter, and airways within the luminal network having an inner dimension that is less than a predetermined threshold, apply the weighting factors to the generated plurality of proposed pathways, rank the generated proposed pathways, and display the ranked proposed pathways to the target tissue.

[0022] In aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to determine the predetermined threshold inner dimension based on a percentage of an outer dimension of the catheter.

[0023] In other aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to determine the predetermined threshold inner dimension based on a percentage increase of an outer dimension of the catheter.

[0024] In certain aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to identify pleural or segmental boundaries between a distal end portion of the catheter and the target tissue that if crossed, may result in pneumothorax.

[0025] In aspects, the memory may store thereon further instructions, which when executed by the processor cause the processor to determine a volumetric overlap between the proposed surgical tool path in the plurality of generated proposed pathways and a coverage of the volume of the target tissue.

BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Various aspects and embodiments of the disclosure are described hereinbelow with references to the drawings, wherein:

[0027] FIG. 1 is a schematic view of a surgical system provided in accordance with the disclosure;

[0028] FIG. 2 is a perspective view of a distal portion of a catheter of the surgical system of FIG. 1;

[0029] FIG. 3 is a schematic view of a workstation of the surgical system of FIG. 1;

[0030] FIG. 4 is a depiction of a graphical user interface of the surgical system of FIG. 1 illustrating a 3D representation of a patient’s airways and a generated pathway to an area of interest within the patient’s lungs;

[0031] FIG. 5 is an enlarged view of the area of detail indicated in FIG. 4; [0032] FIG. 6 is a schematic view of a medical device of the surgical system of FIG. 1 disposed within an airway of the patient’s lungs illustrating a distal end of the medical device being unaligned with a center of the area of interest;

[0033] FIG. 7 is a schematic view of the medical device of FIG. 1 illustrating the distal end of the medical device being aligned with a center of the area of interest;

[0034] FIG. 8 is a schematic view of the medical device of FIG. 1 illustrating a surgical tool of the surgical system of FIG. 1 advanced through the medical device and treating the area of interest;

[0035] FIG. 9 is an enlarged view of the area of detail indicated in FIG. 8;

[0036] FIG. 10 is a schematic view of the medical device of FIG. 1 illustrating a bend radius of the medical device;

[0037] FIG. 11 is a schematic view of the medical device of FIG. 1 illustrating a difference between a desired pose and the actual pose of the medical device;

[0038] FIG. 12 is a schematic view of the medical device of FIG. 1 illustrating a length of the medical device that is stiffened within the patient’s airways;

[0039] FIG. 13 is a graphical representation of malignancy within a volumetric boundary of a lesion within the patient’s lungs;

[0040] FIG. 14A is a flow diagram of a method of navigating a medical device to an area of interest within a patient’s luminal network;

[0041] FIG. 14B is a continuation of the flow diagram of FIG. 14A;

[0042] FIG. 15 is a perspective view of a robotic surgical system of the surgical system of

FIG. 1;

[0043] FIG. 16 is an exploded view of a drive mechanism of an extended working channel of the surgical system of FIG. 1; and

[0044] FIG. 17 is a flow diagram of a method of navigating a medical device to an area of interest within a patient’s luminal network.

DETAILED DESCRIPTION

[0045] The disclosure is directed to a surgical system configured to enable navigation of a medical device through a luminal network of a patient, for example, the airways of the lungs. The surgical system generates a 3 -dimensional (3D) representation of the airways of the patient using pre-procedure images, such as for example, CT, CBCT, or MRI images and identifies anatomical landmarks or target tissue (e.g., for example, bifurcations or lesions) within the 3D representation. The system generates a plurality of pathways to the target tissue through the luminal network of the patient’s lungs. Weighting factors are applied to each of the pathways of the plurality of pathways to the target tissue to prioritize or de-rate pathways for consideration. The weighting factors may include distance to a selected portion of the target tissue (e.g., for example, distance to a surface of the target tissue and distance to a volumetric center, center of mass, and/or center of malignancy of the target tissue), an alignment of candidate airways with a selected portion of the target tissue (e.g., for example, a surface, a volumetric center, a center of mass, and/or a center of malignancy) of the target tissue, a distance to a bifurcation nearest to the distal end portion of the catheter, crossing of pleural or segmental boundaries, a volumetric overlap of expected tool pass trajectories, and combinations thereof. It is envisioned that the selected portion of the target tissue may be selected automatically, semi-automatically, or manually. Although generally described as being related to a catheter, it is envisioned that the weighting factors may be related to any suitable medical device without departing from the scope of the disclosure.

[0046] The distance between the distal end portion of the catheter and a desired portion the target tissue (e.g., for example, a surface, a volumetric center, a center of mass, and/or a center of malignancy) is determined at the terminus of the pathway being analyzed. The distance is a linear distance, determined regardless of any structure or tissue between the distal end portion of the catheter and the selected portion of the target tissue. The alignment of candidate airways with the selected portion of the target tissue is determined using an angle between an alignment vector of a working channel of the catheter and a vector from the position of the distal end portion of the catheter to the selected portion of the target tissue. It is contemplated that the system may store a predetermined maximum angle from the alignment vector of the working channel in 3D space (e.g., for example, a cone shaped boundary line) in which the target tissue must be located in order to be considered a proposed pathway. The distance to a bifurcation nearest to the distal end portion of the catheter is determined by identifying a position of the nearest bifurcation proximal of the distal end portion of the catheter. As can be appreciated, if the distal end portion of the catheter is close to a bifurcation, the distal end portion of the catheter is not adequately supported and there is a higher likelihood that the distal end portion of the catheter may move relative to the target tissue as the catheter is pushed away from the target tissue during alignment of a surgical tool advanced within the catheter, sampling of the target tissue, or delivering therapy to the target tissue. In embodiments, the distance to the nearest bifurcation from the distal end portion of the catheter may be compared to a predetermined threshold (e.g., for example, 2mm), within which there would be a higher likelihood that small disturbances could cause a loss of navigational position of the distal end portion of the catheter as the catheter is pushed or otherwise urged away from the area of interest or target tissue. The system identifies pleural or segmental boundaries between the distal end portion of the catheter and the target tissue. As can be appreciated, puncturing sub- segmental boundaries or pleura may result in pneumothorax. Therefore, potential pathways that may result in a higher likelihood of pneumothorax are de-rated or scored lower. In embodiments, the system may identify a volumetric overlap of expected tool pass trajectories and the system prioritizes proposed pathways to the target tissue that enable increased volumetric overlap of possible tool paths and coverage of the volume of the target tissue.

[0047] As can be appreciated, the weighting factors may differ based upon various factors, such as for example the type of procedure being performed, the type of medical device used to navigate to the target tissue, the type of surgical tool used to treat or sample the target tissue, the size of the medical device used to navigate to the target tissue, a range of motion of the catheter (e.g., a minimum bend radius), accuracy of the pose control of the catheter, a stiffness of the catheter, the volume of the target tissue, and patient history. Some weighting factors may be modified by giving greater or lesser weight depending upon one or more of the factors described hereinabove. For example, the system may identify the medical device being used, and therefore, the outer dimension of the medical device, a range of motion of the medical device, accuracy of the pose control of the medical device, a stiffness of the medical device, and combinations thereof. The system may assign a predetermined threshold value to the inner dimensions of the airways, such as a maximum inner dimension through which the medical device is able to be navigated within. The threshold value of the inner dimension of the airways may be equal to or greater than the outer dimension of the medical device or may be calculated as a percentage of the outer dimension of the medical device, which in embodiments, may be a percentage increase of the outer dimension of the medical device. Potential pathways that include airways that are equal to or greater than the threshold value of the inner dimension are de-rated.

[0048] Turns and bends along the pathway to the target tissue are constrained by the range of motion (e.g., a minimum bend radius) of the medical device. In this manner, the system may assign a predetermined threshold value to the radius of bends or curves along the pathway to the target tissue, such as a minimum bend radius the medical device is capable of achieving. The threshold value of the radius of bends or curves may be equal to or greater than the minimum bend radius of the medical device, and in embodiments, may be a percentage increase of the bend radius of the medical device to accommodate tolerances and fluctuations of the calculated pathway to the target tissue. Potential pathways that include bends or curves that are equal to or less than the threshold value of the radius of bends or curves of the medical device are de-rated.

[0049] As can be appreciated, a pose control of the medical device may be more accurate in one region of the airways of the patient than others. In this manner, a medical device may achieve a less accurate poses in one direction than others, which may encumber navigation of the medical device or treatment of the area of interest by the medical device. The accuracy of the pose control of the medical device may be automatically determined or manually determined using both past and present data. In embodiments, the system may update the weighting of the pose accuracy in real-time during the procedure based upon performance of the pose control of the medical device in other portions of the airways of the patient (e.g., for example, the medical device was unable to achieve an accurate pose). Potential pathways that include manipulations of the medical device to poses that fall below a predetermined threshold value for the pose accuracy are de-rated.

[0050] During navigation to the target tissue and treatment of the target tissue, one or more portions along the length of the medical device may require stiffening of the medical device to accomplish the desired diagnostic or therapeutic task. As can be appreciated, stiffening of one or more portions along the length of the medical device requires space within the airways of the patient to accommodate stiffening. For example, the system may require a portion of the medical device adjacent to the distal end portion of the medical device to stiffen, which may abut or otherwise contact walls of the airways of the patient. The system may determine a minimum threshold value for the length of the medical device that is required to be stiffened, which may take into account an outer dimension of the medical device, an inner dimension of the airways of the patient, and bends or bifurcations within the airways of the patient. Potential pathways that include portions of the airways of the patient equal to or less than the predetermined threshold value of length are de-rated.

[0051] The modified weighting factors are applied to each proposed pathway of the plurality of proposed pathways and the weighted plurality of proposed pathways are ranked. The system displays one or more of the weighted proposed pathways for consideration, and a proposed pathway is chosen, either automatically, semi-automatically, or manually. As can be appreciated, these and other aspects of the present disclosure enable selection of a pathway for lung navigation that considers metrics beyond proximity. Inclusion of these other metrics in pathway planning systems and processes allows for optimization of the user experience, patient safety, and procedural time efficiency as compared to relying on proximity alone. These and other aspects of the disclosure will be described in further detail hereinbelow. Although generally described with reference to the lung, it is contemplated that the systems and methods described herein may be used with any structure within the patient’s body, such as the liver, kidney, prostate, gynecological, amongst others.

[0052] Turning now to the drawings, FIG. 1 illustrates a system 10 in accordance with the disclosure facilitating navigation of a medical device through a luminal network and to an area of interest. As will be described in further detail hereinbelow, the surgical system 10 is generally configured to identify target tissue, automatically register real-time images captured by a surgical instrument to a generated 3 -dimensional (3D) model, and navigate the surgical instrument to the target tissue.

[0053] The system 10 includes a catheter guide assembly 12 including an extended working channel (EWC) 14, which may be a smart extended working channel (sEWC) including an electromagnetic (EM) sensor. In one embodiment, the sEWC 14 is inserted into a bronchoscope 16 for access to a luminal network of the patient P. In this manner, the sEWC 14 may be inserted into a working channel of the bronchoscope 16 for navigation through a patient P’s luminal network, such as for example, the lungs. It is envisioned that the sEWC 14 may itself include imaging capabilities via an integrated camera or optics component (not shown) and therefore, a separate bronchoscope 16 is not strictly required. In embodiments, the sEWC 14 may be selectively locked to the bronchoscope 16 using a bronchoscope adapter 16a. In this manner, the bronchoscope adapter 16a is configured to permit motion of the sEWC 14 relative to the bronchoscope 16 (which may be referred to as an unlocked state of the bronchoscope adapter 16a) or inhibit motion of the sEWC 14 relative to the bronchoscope 16 (which may be referred to as a locked state of the bronchoscope adapter 16a). Bronchoscope adapters 16a are currently marketed and sold by Medtronic PLC under the brand names EDGE® Bronchoscope Adapter or the ILLUMISITE® Bronchoscope Adapter, and are contemplated as being usable with the disclosure.

[0054] As compared to an EWC, the sEWC 14 may include one or more EM sensors 14a disposed in or on the sEWC 14 at a predetermined distance from the distal end 14b of the sEWC 14. It is contemplated that the EM sensor 14a may be a five degree-of-freedom sensor or a six degree-of-freedom sensor. As can be appreciated, the position and orientation of the EM sensor 14a of the sEWC relative to a reference coordinate system, and thus a distal portion of the sEWC 14 within an electromagnetic field can be derived. Catheter guide assemblies 12 are currently marketed and sold by Medtronic PLC under the brand names SUPERDIMENSION® Procedure Kits, ILLUMISITE™ Endobronchial Procedure Kit, ILLUMISITE™ Navigation Catheters, or EDGE® Procedure Kits, and are contemplated as being usable with the disclosure.

[0055] With reference to FIG. 2, a catheter 70, including one or more EM sensors 72, is inserted into the sEWC and selectively locked into position relative to the sEWC 14 such that the sensor 72 extends a predetermined distance beyond a distal tip of the sEWC 14. As can be appreciated, the EM sensor 72 disposed on the catheter 70 is separate from the EM sensor 14a disposed on the sEWC. The EM sensor 72 is disposed on or in the catheter 70 a predetermined distance from a distal end portion 76 of the catheter 70. In this manner, the system 10 is able to determine a position of a distal portion of the catheter 70 within the luminal network of the patient P. It is envisioned that the catheter 70 may be selectively locked relative to the sEWC 14 at any time, regardless of the position of the distal end portion 76 of the catheter 70 relative to the sEWC 14. It is contemplated that the catheter 70 may be selectively locked to a handle 12a of the catheter guide assembly 12 using any suitable means, such as for example, a snap fit, a press fit, a friction fit, a cam, one or more detents, threadable engagement, or a chuck clamp. It is envisioned that the EM sensor 72 may be a five degree-of-freedom sensor or a six degree-of-freedom sensor. As will be described in further detail hereinbelow, the position and orientation of the EM sensor 72 of the catheter 70 relative to a reference coordinate system, and thus a distal portion of the catheter 70, within an electromagnetic field can be derived.

[0056] At least one camera 74 is disposed on or adjacent a distal end surface 76a of the catheter 70 and is configured to capture, for example, still images, real-time images, or realtime video. Although generally described as being disposed on the distal end surface 76a of the catheter 70, it is envisioned that the camera 74 may be disposed on any suitable location on the camera 70, such as for example, a sidewall. In embodiments, the catheter 70 may include one or more light sources 80 disposed on or adjacent to the distal end surface 76a of the catheter 70 or any other suitable location (e.g., for example, a side surface or a protuberance). The light source 80 may be or may include, for example, a light emitting diode (LED), an optical fiber connected to a light source that is located external to the patient P, or combinations thereof, and may emit one or more of white, IR, or near infrared (NIR) light. In this manner, the camera 74 may be, for example, a white light camera, IR camera, or NIR camera, a camera that is capable of capturing white light and NIR light, or combinations thereof. In one non-limiting embodiment, the camera 74 is a white light mini complementary metal-oxide semiconductor (CMOS) camera, although it is contemplated that the camera 74 may be any suitable camera, such as for example, a charge-coupled device (CCD), a complementary metal-oxide- semiconductor (CMOS), a N-type metal-oxide-semiconductor (NMOS), and in embodiments, may be an infrared (IR) camera, depending upon the design needs of the system 10. As can be appreciated, the camera 74 captures images of the patient P’s anatomy from a perspective of looking out from the distal end portion 76 of the catheter 70. In embodiments, the camera 74 may be a dual lens camera or a Red Blue Green and Depth (RGB-D) camera configured to identify a distance between the camera 74 and anatomical features within the patient P’s anatomy without departing from the scope of the disclosure. As described hereinabove, it is envisioned that the camera 74 may be disposed on the catheter 70, the sEWC 14, or the bronchoscope 16.

[0057] Continuing with FIG. 2, in embodiments, the catheter 70 may include a working channel 82 defined through a proximal portion (not shown) and the distal end surface 76a, although in embodiments, it is contemplated that the working channel 82 may extend through a sidewall of the catheter 70 depending upon the design needs of the catheter 70. As can be appreciated, the working channel 82 is configured to receive a locatable guide (not shown) or a surgical tool 90, such as for example, a biopsy tool. The catheter 70 includes an inertial measurement unit (IMU) 84 disposed within or adjacent to the distal end portion 76. As can be appreciated, the IMU 84 detects an orientation of the distal end portion 76 of the catheter 70 relative to a reference coordinate frame and detects movement and speed of the distal end portion 76 of the catheter 70 as the catheter 70 is navigated within the patient P’s luminal network. Using the data received from the IMU 84, the system 10 is able to determine alignment and trajectory information of the distal end portion 76 of the catheter 70. In embodiments, the system 10 may utilize the data received from the IMU 84 to determine a gravity vector, which may be used to determine the orientation of the distal end portion 76 of the catheter 70 within the airways of the patient P. Although generally described as using the IMU 84 to detect an orientation and/or movement of the distal end portion 76 of the catheter 70, the instant disclosure is not so limited and may be used in conjunction with flexible sensors, such as for example, fiber-bragg grating sensors, ultrasonic sensors, without sensors, or combinations thereof. As will be described in further detail hereinbelow, it is contemplated that the devices and systems described herein may be used in conjunction with robotic systems such that robotic actuators drive the sEWC 14 or bronchoscope 16 proximate the target. [0058] Referring again to FIG. 1, the system 10 generally includes an operating table 52 configured to support a patient P and monitoring equipment 24 coupled to the sEWC 14, the bronchoscope 16, or the catheter 70 (e.g., for example, a video display for displaying the video images received from the video imaging system of the bronchoscope 12 or the camera 74 of the catheter 70), a locating or tracking system 46 including a tracking module 48, a plurality of reference sensors 50 and a transmitter mat 54 including a plurality of incorporated markers, and a workstation 20 having a computing device 22 including software and/or hardware used to facilitate identification of a target, pathway planning to the target, navigation of a medical device to the target, and/or confirmation and or determination of placement of, for example, the sEWC 14, the bronchoscope 16, the catheter 70, or a surgical tool (e.g., for example, the surgical tool 90), relative to the target.

[0059] The tracking system 46 is, for example, a six degrees-of-freedom electromagnetic locating or tracking system, or other suitable system for determining position and orientation of, for example, a distal portion the sEWC 14, the bronchoscope 16, the catheter 70, or a surgical tool, for performing registration of a detected position of one or more of the EM sensors 14a or 72 and a three-dimensional (3D) model generated from a CT, CBCT, or MRI image scan. The tracking system 46 is configured for use with the sEWC 14 and the catheter 70, and particularly with the EM sensors 14a and 72.

[0060] Continuing with FIG. 1, the transmitter mat 54 is positioned beneath the patient P. The transmitter mat 54 generates an electromagnetic field around at least a portion of the patient P within which the position of the plurality of reference sensors 50 and the EM sensors 14a and 74 can be determined with the use of the tracking module 48. In one non-limiting embodiment, the transmitter mat 54 generates three or more electromagnetic fields. One or more of the reference sensors 50 are attached to the chest of the patient P. In embodiments, coordinates of the reference sensors 50 within the electromagnetic field generated by the transmitter mat 54 are sent to the computing device 22 where they are used to calculate a patient P coordinate frame of reference (e.g., for example, a reference coordinate frame). As will be described in further detail hereinbelow, registration is generally performed using coordinate locations of the 3D model and 2D images from the planning phase, with the patient P’s airways as observed through the bronchoscope 12 or catheter 70 and allow for the navigation phase to be undertaken with knowledge of the location of the EM sensors 14a and 72. It is envisioned that any one of the EM sensors 14a and 72 may be a single coil sensor that enables the system 10 to identify the position of the sEWC 14 or the catheter 70 within the EM field generated by the transmitter mat 54, although it is contemplated that the EM sensors 14a and 72 may be any suitable sensor and may be a sensor capable of enabling the system 10 to identify the position, orientation, and/or pose of the sEWC 14 or the catheter 70 within the EM field.

[0061] Although generally described with respect to EMN systems using EM sensors, the instant disclosure is not so limited and may be used in conjunction with flexible sensors, such as for example, fiber-bragg grating sensors, inertial measurement units (IMU), ultrasonic sensors, optical sensors, pose sensors (e.g., for example, ultra- wide band, global positioning system, fiber-bragg, radio-opaque markers), without sensors, or combinations thereof. It is contemplated that the devices and systems described herein may be used in conjunction with robotic systems such that robotic actuators drive the sEWC 14 or bronchoscope 16 proximate the target.

[0062] In accordance with aspects of the disclosure, the visualization of intra-body navigation of a medical device (e.g., for example a biopsy tool or a therapy tool), towards a target (e.g. , for example, a lesion) may be a portion of a larger workflow of a navigation system. An imaging device 56 (e.g, for example, a CT imaging device, such as for example, a conebeam computed tomography (CBCT) device, including but not limited to Medtronic pic’s O- arm™ system) capable of acquiring 2D and 3D images or video of the patient P is also included in the particular aspect of system 10. The images, sequence of images, or video captured by the imaging device 56 may be stored within the imaging device 56 or transmitted to the computing device 22 for storage, processing, and display. In embodiments, the imaging device 56 may move relative to the patient P so that images may be acquired from different angles or perspectives relative to the patient P to create a sequence of images, such as for example, a fluoroscopic video. The pose of the imaging device 56 relative to the patient P while capturing the images may be estimated via markers incorporated with the transmitter mat 54. The markers are positioned under the patient P, between the patient P and the operating table 52, and between the patient P and a radiation source or a sensing unit of the imaging device 56. The markers incorporated with the transmitter mat 54 may be two separate elements which may be coupled in a fixed manner or alternatively may be manufactured as a single unit. It is contemplated that the imaging device 56 may include a single imaging device or more than one imaging device.

[0063] Continuing with FIG. 1 and with additional reference to FIG. 3, the workstation 20 includes a computer 22 and a display 24 that is configured to display one or more user interfaces 26 and/or 28. The workstation 20 may be a desktop computer or a tower configuration with the display 24 or may be a laptop computer or other computing device. The workstation 20 includes a processor 30 which executes software stored in a memory 32. The memory 32 may store video or other imaging data captured by the bronchoscope 16 or catheter 70 or preprocedure images from, for example, a computer -tomography (CT) scan, Positron Emission Tomography (PET), Magnetic Resonance Imaging (MRI), Cone-beam CT, amongst others. In addition, the memory 32 may store one or more software applications 34 to be executed on the processor 30. Though not explicitly illustrated, the display 24 may be incorporated into a head mounted display such as an augmented reality (AR) headset such as the HoloLens offered by Microsoft Corp.

[0064] 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 image data and videos may be stored. The cloud storage system 38 may be remote from or on the premises of the hospital such as in a control or hospital information technology room. 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 24. In embodiments, the workstation 20 may include its own display 44, which may be a touchscreen display.

[0065] In a planning or pre-procedure phase, the software application utilizes preprocedure CT image data, either stored in the memory 32 or retrieved via the network interface 36, for generating and viewing a 3D model of the patient P’s anatomy, enabling the identification of target tissue TT on the 3D model (automatically, semi-automatically, or manually), and in embodiments, allowing for the selection of a pathway PW through the patient P’s anatomy to the target tissue, as will be described in further detail hereinbelow. Examples of such an application is the ILOGIC® planning and navigation suites and the ILLUMISITE® planning and navigation suites currently marketed by Medtronic PLC. The 3D model may be displayed on the display 24 or another suitable display associated with the workstation 20, such as for example, the display 44, or in any other suitable fashion. Using the workstation 20, various views of the 3D model may be provided and/or the 3D model may be manipulated to facilitate identification of target tissue TT on the 3D model and/or selection of a suitable pathway PW to the target tissue.

[0066] It is envisioned that the 3D model may be generated by segmenting and reconstructing the airways of the patient P’s lungs to generate a 3D airway tree 100. The reconstructed 3D airway tree 100 includes various branches and bifurcations which, in embodiments, may be labeled using, for example, well accepted nomenclature such as RBI (right branch 1), LB1 (left branch 1, or Bl (bifurcation one). In embodiments, the segmentation and labeling of the airways of the patient P’s lungs is performed to a resolution that includes terminal bronchioles having a diameter of approximately less than 1 mm. As can be appreciated, segmenting the airways of the patient P’s lungs to terminal bronchioles improves the accuracy registration between the position of the sEWC 14 and catheter 70 and the 3D model, improves the accuracy of the pathway to the target, and improves the ability of the software application to identify the location of the sEWC 14 and catheter 70 within the airways and navigate the sEWC 14 and catheter 70 to the target tissue. Those of skill in the art will recognize that a variety of different algorithms may be employed to segment the CT image data set, including, for example, connected component, region growing, thresholding, clustering, watershed segmentation, or edge detection. It is envisioned that the entire reconstructed 3D airway tree may be labeled, or only branches or branch points within the reconstructed 3D airway tree that are located adjacent to the pathway to the target tissue.

[0067] In embodiments, the software stored in the memory 32 may identify and segment out a targeted critical structure (e.g., for example, blood vessels, lymphatic vessels, lesions, and/or other intrathoracic structures) within the 3D model. It is envisioned that the segmentation process may be performed automatically, manually, or a combination of both. The segmentation process isolates the targeted critical structure from the surrounding tissue in the 3D model and identifies its position within the 3D model. In embodiments, the software application segments the CT images to terminal bronchioles that are less than 1 mm in diameter such that branches and/or bifurcations are identified and labeled deep into the patient P’s luminal network. It is envisioned that this position can be updated depending upon the view selected on the display 24 such that the view of the segmented targeted critical structure may approximate a view captured by the camera 74 of the catheter 70.

[0068] With reference to FIGS. 4-8, using the 3D model tree 100, or in embodiments, the 3D model or combinations thereof, the software stored in the memory 32 generates a plurality of proposed pathways PW through the luminal network of the patient P to the target tissue TT. In this manner, the software stored in the memory 32 identifies the location of the target tissue TT within the patient P’s lungs and identifies a proposed pathway PW starting with airways that are the smallest and nearest to the target tissue TT. The software stored in the memory 32 propagates the pathway PW contiguously through subsequently larger airways until a proposed pathway PW reaches the trachea of the patient P. This process is repeated until a predetermined number of pathways PW have been generated or all possible pathways PW have been identified.

[0069] The software stored in the memory 32 utilizes weighting factors to assign a ranking to each of the proposed pathways PW, from which a preferred pathway PW to the target tissue TT can be selected, either manually via the user interface 26, semiautomatically, or automatically by the software stored in the memory 32. As can be appreciated any number or type of weighting factors may be utilized to assign a ranking to each of the proposed pathways PW without departing from the scope of the disclosure, and any or all of the weighting factors may be applied to the proposed pathways PW without departing from the scope of the disclosure. In one non-limiting embodiment, the weighting factors include a distance to a selected portion (e.g., for example, a surface, a volumetric center, a center of mass, and/or a center of malignancy) of the target tissue TT from the distal end portion 76 of the catheter 70, an alignment of candidate airways with the selected portion (e.g., for example, a surface, a volumetric center, a center of mass, and/or a center of malignancy) of the target tissue TT, a distance to a bifurcation nearest to the distal end portion 76 of the catheter 70, crossing of pleural or segmental boundaries, a volumetric overlap of expected tool pass trajectories and combinations thereof. It is envisioned that the selected portion of the target tissue TT may be selected automatically, semi-automatically, or manually. Although generally described as being related to the catheter 70, it is envisioned that the weighting factors may be related to any suitable medical device without departing from the scope of the disclosure.

[0070] The distance d between the distal end portion 76 of the catheter 70 and the selected portion of the target tissue TT is determined by the software stored in the memory 32 at the terminus of the pathway PW (FIGS. 8 and 9). The distance d is a linear distance, determined regardless of any structure or tissue between the distal end portion 76 and the selected portion of the target tissue TT, although it is contemplated that the distance d may be determined using any suitable method or pathway PW without departing from the scope of the disclosure. The software stored in the memory 32 may identify a center of malignancy of the target tissue TT and determine the distance d from the distal end portion 76 of the catheter 70 to the identified center of malignancy. In this manner, the software stored in the memory 32 analyzes the 3D model and identifies volumetric parameters, such as for example, boundaries, of the target tissue TT. A voxel map is generated based on the identified volumetric boundaries of the target tissue TT by assigning an attenuation value (e.g., for example, Hounsfield units) to each voxel of the target tissue TT. It is envisioned that the software stored on the memory 32 may identify a maximum attenuation value, a minimum attenuation value, a local maximum attenuation value, a local minimum attenuation value, an average or mean attenuation value within and/or outside of the target tissue, sand/or combinations thereof. The software stored on the memory 32 applies differential calculus to the 3D space of the voxel map to develop a volumetric vector map of the partial differential equation from the voxel with the highest Hounsfield unit to the margin or target tissue TT boundary and a volume of the target tissue TT is formed. In this manner, a gradient or gradient curve 110 may be calculated from the voxel with the maximum attenuation value to the voxel with the minimum attenuation value (or local maximum and local minimum) (FIG. 13). As can be appreciated, large or stronger gradients 112 represent malignant tissue whereas low or weaker gradients 114 represent benign tissue. The software stored on the memory 32 analyzes the volumetric vector map and identifies a location, such as for example, a center of malignancy, within the volumetric boundaries of the target tissue TT. [0071] As can be appreciated, the center of malignancy of the target tissue TT may be at the same or different location as the volumetric center or the center of mass of the target tissue. Therefore, a pathway PW through the patient P’s luminal network that is optimal to treat the volumetric center or center of mass of the target tissue TT may not be optimal to treat the center of malignancy of the target tissue TT. It is envisioned that the distance between the center of malignancy of the target tissue TT and the distal end portion 76 of the catheter 70 may be determined by registering the position of the distal end portion 76 of the catheter 70 within the reference coordinate frame to the 3D model, as described in further detail herein. In this manner, the center of malignancy of the target tissue TT can be identified within the reference coordinate frame, and likewise, the position of the distal end portion 76 of the catheter 70 can be determined.

[0072] The alignment of candidate airways with the selected portion (e.g., for example, a surface, a volumetric center, a center of mass, and/or a center of malignancy) of the target tissue TT is determined by the software stored in the memory 32 using an angle P between an alignment vector AV of the working channel 82 of the catheter 70 and a vector TV from the position of the distal end portion 76 of the catheter 70 to the selected portion of the target tissue TT (FIGS. 8 and 9). In embodiments, the software stored in the memory 32 may store or otherwise define a predetermined maximum angle from the alignment vector of the working channel 82 in 3D space (e.g., for example, a cone shaped boundary line) in which the target tissue TT must be located in order to be considered a proposed pathway PW.

[0073] The distance to a bifurcation nearest to the distal end portion 76 of the catheter 70 is determined by the software stored in the memory 32 by identifying a position of the nearest bifurcation proximal of the distal end portion 76 of the catheter 70. As can be appreciated, if the distal end portion 76 of the catheter 70 is close to a bifurcation, the distal end portion 76 of the catheter 70 is not adequately supported. In this manner, there is a higher likelihood that the distal end portion 76 of the catheter 70 may move relative to the target tissue TT as the catheter 70 is pushed away from the target tissue TT during alignment of the surgical tool 90, sampling of the target tissue TT, or delivering therapy to the target tissue TT. It is envisioned that a predetermined distance or threshold (e.g., for example 2 mm) may be defined within which there is a higher likelihood that the distal end portion 76 of the catheter 70 may move relative to the area of interest of target tissue TT as the catheter 70 is pushed away from the area of interest or target tissue TT. In embodiments, the system 10 may issue an alert or warning (e.g. , for example, lights, messages, and/or haptic feedback) to the user that the distal end portion 76 of the catheter 70 is approaching or is within the predetermined threshold distance from the nearest bifurcation. As can be appreciated, the system 10 may automatically inhibit movement of the distal end portion 76 of the catheter 70 to or within the predetermined threshold distance using any suitable means, such as for example, a robotic surgical system.

[0074] The software stored in the memory 32 identifies pleural or segmental boundaries SB between the distal end portion 76 of the catheter and the target tissue TT (FIGS. 8 and 9). As can be appreciated, puncturing sub-segmental boundaries or pleura may result in pneumothorax. Therefore, proposed pathways PW that may result in a higher likelihood of pneumothorax are de-rated or scored lower.

[0075] In addition to the above-described weighting factors, the software stored in the memory 32 identifies a volumetric overlap of expected tool pass trajectories. The software stored in the memory 32 prioritizes proposed pathways PW to the target tissue TT that enable increased volumetric overlap of possible tool paths (e.g., for example, the path of the surgical tool 90) and coverage of the volume of the target tissue TT. [0076] As can be appreciated, the weighting factors may differ based upon the various factors, such as for example, the type of procedure being performed, the type of medical device used to navigate to the target tissue TT, the type of surgical tool used to treat or sample the target tissue TT, the size of the medical device used to navigate to the target tissue TT, a range of motion of the catheter (e.g., for example, a minimum bend radius), accuracy of the pose control of the catheter, a stiffness of the catheter, the volume of the target tissue TT, and patient P history. In this manner, some weighting factors may be given greater or lesser weight depending upon one or more of the factors described hereinabove. In one non-limiting embodiment, for medical devices having a relatively large outer dimension or diameter (e.g., for example, greater than or equal to 3.5 mm), the proximity and orientation of the distal end portion of the medical device relative to the target tissue TT is more important than being in the same airway as the target tissue TT (FIGS. 8 and 9). As can be appreciated, small or narrow airways within the patient P’s lungs are unable to receive large access devices or medical devices, such as for example, those having an outer dimension or diameter larger than 3.5 mm. Although generally described as having a diameter of 3.5 mm, those having skill in the art would recognize that access devices or other medical devices having any diameter become unable to navigate within small airways approximating the outer dimension of the medical device. In this manner, the inner dimensions of unnavigable airways vary depending upon the size of the medical device being used. In one non-limiting embodiment, the medical device may have an outer dimension of about between 3.5 mm to 4.2 mm. It is contemplated that the software stored in the memory 32 may automatically identify the medical device being used, and therefore, the outer dimension of the medical device, or the type and dimensions of the medical device may be manually entered. The software stored in the memory 32 may assign a predetermined threshold value to the inner dimensions of the airways, such as a maximum inner dimension through which the medical device is able to be navigated within. The predetermined threshold value may be an inner dimension that is about equal to or less than the outer dimension of the medical device. In embodiments, the software stored in the memory 32 may apply an offset to the identified maximum inner dimension, such as for example, an inner dimension that is a percentage of the maximum inner dimension, which may be a percentage increase of the maximum inner dimension. In this manner, the software stored in the memory 32 may increase the maximum inner dimension of the airways by a predetermined amount to ensure that airways adjacent to navigable airways are segmented and rendered. In one nonlimiting embodiment, the software stored in the memory 32 may reduce the inner dimension of the airways from about equal to a medical device having an outer dimension of 3.5 mm to an inner dimension of about 2 mm.

[0077] It is envisioned that the system stored in the memory 32 may automatically or manually identify a range of motion or minimum bend radius R of the medical device (FIG. 9). As can be appreciated, the range of motion or minimum bend radius R of the medical device limits or otherwise inhibits the medical device from traversing pathways through the airways of the patient P requiring bends or curves tighter or otherwise smaller than the minimum bend radius R. The software stored in the memory 32 may assign a predetermined threshold value to the bends or curves within the airways of the patient P, such as a minimum bend radius R achievable by the medical device. In embodiments, the software stored in the memory 32 may apply an offset to the predetermined threshold value of the bend radius R, such as for example, a bend radius R that is a percentage of the minimum bend radius R, which may be a percentage increase of the minimum bend radius R. In this manner, the software stored in the memory 32 may increase the minimum bend radius R by a predetermined amount to ensure that the medical device is capable of being navigated through airways of the patient P to the target tissue TT. [0078] In embodiments, the system stored in the memory 32 may determine an accuracy of the pose of the medical device within one or more portions of the airways of the patient P. As can be appreciated, navigation of the medical device through the airways of the patient P and diagnostic and/or therapeutic tasks requires the medical device to be placed in particular poses with respect to the airways of the patient P or the target tissue TT. The software stored in the memory 32 may automatically or manually identify whether the medical device has achieved the desired pose at one or more locations within the airways of the patient P and determine directional movements and/or poses where the medical device is able to be accurately or inaccurately placed. As can be appreciated, movements or poses that the medical device is less likely to achieve may encumber navigation of the medical device through the airways of the patient P and accurate treatment of the target tissue TT. In embodiments, the software stored in the memory 32 may analyze pose information obtained from prior procedures or in real-time and determine a difference A between the desired pose and the achieved pose (FIG. 10). The software stored in the memory may assign a predetermined threshold value for accuracy of the actual pose as compared to the desired pose. In one nonlimiting embodiment, the predetermined threshold value may be a maximum percentage of deviation from the desired pose in one or more axes (e.g., for example, roll, pitch, yaw, and combinations thereof). Potential pathways that include manipulations of the medical device to poses having an accuracy less than or equal to the predetermined threshold value for accuracy of the pose are de-rated. It is envisioned that the software stored in the memory 32 may update the weighting of the accuracy of the pose of the medical device in real-time as the medical device is navigated within the airways of the patient P.

[0079] As can be appreciated, during navigation of the medical device through the patient P’s airways to the target tissue TT and treatment of the target tissue, one or more portions along the length of the medical device may require stiffening to accomplish the desired diagnostic or therapeutic task. Stiffening of one or more portions along the length of the medical device requires space within the airways of the patient P to accommodate the stiffening of the medical device (e.g., for example, a linear length). In this manner, the software stored in the memory 32 may require a portion of the medical device adjacent to the distal end portion of the medical device to stiffen, which may abut or otherwise contact walls of the airways of the patient P. It is envisioned that the software stored in the memory 32 may determine a minimum threshold value for the length L_s of the medical device that is required to be stiffened (FIG. 11), which may take into account an outer dimension of the medical device, an inner dimension of the airways of the patient, and bends or bifurcations within the airways of the patient. Potential pathways that include portions of the airways of the patient P equal to or less than the predetermined threshold value of length are de-rated.

[0080] Registration of the patient P’s location on the transmitter mat 54 may be performed by moving the EM sensors 14a and/or 72 through the airways of the patient P. In this manner, the software stored on the memory 32 periodically determines the location of the EM sensors 14a or 72 within the coordinate system as the sEWC 14 of the catheter 70 is moving through the airways using the transmitter mat 54, the reference sensors 50, and the tracking system 46. The location data may be represented on the user interface 26 as a marker or other suitable visual indicator, a plurality of which develop a point cloud having a shape that may approximate the interior geometry of the 3D model. The shape resulting from this location data is compared to an interior geometry of passages of a 3D model, and a location correlation between the shape and the 3D model based on the comparison is determined. In addition, the software identifies non-tissue space (e.g., for example, air filled cavities) in the 3D model. The software aligns, or registers, an image representing a location of the EM sensors 14a or 72 with the 3D model and/or 2D images generated from the 3D model, which are based on the recorded location data and an assumption that the sEWC 14 or the catheter 70 remains located in nontissue space in a patient P’s airways. In embodiments, a manual registration technique may be employed by navigating the sEWC 14 or catheter 70 with the EM sensors 14a and 72 to prespecified locations in the lungs of the patient P, and manually correlating the images from the bronchoscope 16 or the catheter 70 to the model data of the 3D model. Although generally described herein as utilizing a point cloud (e.g., for example, a plurality of location data points), it is envisioned that registration can be completed utilizing any number of location data points, and in one non-limiting embodiment, may utilize only a single location data point.

[0081] With reference to FIGS. 14A and 14B, a method of generating a pathway to target tissue within a luminal network of a patient P is described and generally identified by reference numeral 200. Initially, at step 202, the patient P is imaged and the captured images are stored in the memory 32. In step 204, the software stored in the memory 32 generated a 3D representation of the patient P’s airways. In step 206, target tissue TT is identified in the generated 3D representation of the patient P’s airways. Optionally, in step 208, patient P information, such as for example, the type of procedure being performed, patient P history, and the volume of the target tissue is received. Optionally, in parallel, in step 210, medical device information, such as the type of medical device used to navigate to the target tissue TT, the type of surgical tool used to treat or sample the target tissue TT, and the size of the medical device used to navigate to the target tissue TT is received. In step 212, the software stored in the memory 32 generates proposed pathways to the target tissue TT through the luminal network of the patient P. In step 214, the software stored in the memory 32 analyzes the generated proposed pathways PW to calculate the weighting factors, such as for example, a distance to a selected portion (e.g. , for example, a surface, a volumetric center, a center of mass, and/or a center of malignancy) of the target tissue TT from the distal end of the medical device, an alignment of candidate airways with a selected portion (e.g, for example, a surface, a volumetric center, a center of mass, and/or a center of malignancy) of the target tissue TT, a distance to a bifurcation nearest to the distal end of the medical device, crossing of pleural or segmental boundaries, a volumetric overlap of expected tool pass trajectories, and combinations thereof. Optionally, in step 216, the software stored in the memory modifies the calculated weighting factors based on the medical device information received in step 210. Optionally, in step 218 the software stored in the memory 32 may modify the calculated weighting factors based on the patient P information received in step 208 in addition to, or in lieu of, using the medical device information. In step 220, at least one of the weighting factors are applied to the generated proposed pathways PW to the target tissue TT and in step 222, the software stored in the memory 32 ranks the generated proposed pathways PW to the target tissue TT based on the results of applying the modified weighting factors. In step 224, the ranked proposed pathways PW to the target tissue TT are displayed on the user interface 26, where the desired pathway PW may be automatically or manually selected, and the method ends in step 224. As can be appreciated, the above described method may be repeated as many times as necessary depending upon the needs of the user or the procedure being performed.

[0082] Turning to FIGS. 15 and 16, it is envisioned that the system 10 may include a robotic surgical system 600 having a drive mechanism 602 including a robotic arm 604 operably coupled to a base or cart 606, which may, in embodiments, be the workstation 20. The robotic arm 604 includes a cradle 608 that is configured to receive a portion of the sEWC 14. The sEWC 14 is coupled to the cradle 608 using any suitable means (e.g., for example, straps, mechanical fasteners, and/or couplings). It is envisioned that the robotic surgical system 600 may communicate with the sEWC 14 via electrical connection (e.g., for example, contacts and/or plugs) or may be in wireless communication with the sEWC 14 to control or otherwise effectuate movement of one or more motors (FIG. 16) disposed within the sEWC 14 and in embodiments, may receive images captured by a camera (not shown) associated with the sEWC 14. In this manner, it is contemplated that the robotic surgical system 600 may include a wireless communication system 610 operably coupled thereto such that the sEWC 14 may wirelessly communicate with the robotic surgical system 600 and/or the workstation 20 via WiFi, Bluetooth®, for example. As can be appreciated, the robotic surgical system 600 may omit the electrical contacts altogether and may communicate with the sEWC 14 wirelessly or may utilize both electrical contacts and wireless communication. The wireless communication system 610 is substantially similar to the network interface 36 (FIG. 3) described hereinabove, and therefore, will not be described in detail herein in the interest of brevity. As indicated hereinabove, the robotic surgical system 600 and the workstation 20 may be one in the same, or in embodiments, may be widely distributed over multiple locations within the operating room. It is contemplated that the workstation 20 may be disposed in a separate location and the display 44 (FIGS. 1 and 3) may be an overhead monitor disposed within the operating room. [0083] As indicated hereinabove, it is envisioned that the sEWC 14 may be manually actuated via cables or push wires, or for example, may be electronically operated via one or more buttonsjoysticks, toggles, actuators (not shown) operably coupled to a drive mechanism 614 disposed within an interior portion of the sEWC 14 that is operably coupled to a proximal portion of the sEWC 14, although it is envisioned that the drive mechanism 614 may be operably coupled to any portion of the sEWC 14. The drive mechanism 614 effectuates manipulation or articulation of the distal end of the sEWC 14 in four degrees of freedom or two planes of articulation (e.g., for example, left, right, up, or down), which is controlled by two push-pull wires, although it is contemplated that the drive mechanism 614 may include any suitable number of wires to effectuate movement or articulation of the distal end of the sEWC 14 in greater or fewer degrees of freedom without departing from the scope of the disclosure. It is contemplated that the distal end of the sEWC 14 may be manipulated in more than two planes of articulation, such as for example, in polar coordinates, or may maintain an angle of the distal end relative to the longitudinal axis of the sEWC 14 while altering the azimuth of the distal end of the sEWC 14 or vice versa. In one non-limiting embodiment, the system 10 may define a vector or trajectory of the distal end of the sEWC 14 in relation to the two planes of articulation.

[0084] It is envisioned that the drive mechanism 614 may be cable actuated using artificial tendons or pull wires 616 (e.g., for example, metallic, non-metallic, and/or composite) or may be a nitinol wire mechanism. In embodiments, the drive mechanism 614 may include motors 618 or other suitable devices capable of effectuating movement of the pull wires 616. In this manner, the motors 618 are disposed within the sEWC 14 such that rotation of an output shaft the motors 618 effectuates a corresponding articulation of the distal end of the sEWC 14.

[0085] Although generally described as having the motors 618 disposed within the sEWC 14, it is contemplated that the sEWC 14 may not include motors 618 disposed therein. Rather, the drive mechanism 614 disposed within the sEWC 14 may interface with motors 622 disposed within the cradle 608 of the robotic surgical system 600. In embodiments, the sEWC 14 may include a motor or motors 618 for controlling articulation of the distal end 14b of the sEWC 14 in one plane (e.g., for example, left/null or right/null) and the drive mechanism 624 of the robotic surgical system 600 may include at least one motor 622 to effectuate the second axis of rotation and for axial motion. In this manner, the motor 618 of the sEWC 14 and the motors 622 of the robotic surgical system 600 cooperate to effectuate four-way articulation of the distal end of the sEWC 14 and effectuate rotation of the sEWC 14. As can be appreciated, by removing the motors 618 from the sEWC 14, the sEWC 14 becomes increasingly cheaper to manufacture and may be a disposable unit. In embodiments, the sEWC 14 may be integrated into the robotic surgical system 600 (e.g., for example, one piece) and may not be a separate component. [0086] From the foregoing and with reference to the various figures, those skilled in the art will appreciate that certain modifications can be made to the disclosure without departing from the scope of the disclosure.

[0087] Although the description of computer-readable media contained herein refers to solid-state storage, it should be appreciated by those skilled in the art that computer-readable storage 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 for example, computer-readable instructions, data structures, program modules or other data. For example, 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 workstation 20.

[0088] A further aspect of the disclosure is directed to a method of providing assistance to a clinician during a luminal network navigation. As noted above, and similar to method 200 captured images of a luminal network (e.g., the airways of the lungs) are received and stored in memory at step 302. At step 304 the images are reviewed (either manually or automatically) to identify one or more targets (e.g., tumors) within the images. As will be appreciated artificial intelligence and neural networks may be employed as part of the automatic target identification step. At step 306, with the targets identified a closest lumen (e.g., airway) to the target is identified. Again, this closest lumen may be manually or automatically identified. At step 308 an initial pathway to the target is generated. In accordance with one aspect of the disclosure, the initial pathway is a pathway to a closest point of approach to the target or the nearest point in the luminal network to the target. However, as noted above and for a variety of reasons, the closest point of approach is not the best pathway to navigate a catheter 70 to the target to perform a procedure (e.g., a biopsy or therapy procedure). At step 310 an input may be optionally received by an application 34 (e.g., via user interface 26) indicating the type of catheter 70 or the type of medical device to be navigated to the identified target(s).

[0089] At step 312 the application 34 analyzes the initial pathway to determine whether a better pathway can be identified for navigation of the selected catheter 70 or medical device to the identified target(s). A variety of factors can be analyzed by the application including the mechanical limitations and features of the catheter 70 and medical device (e.g., bending radii, bending stiffness, column stiffness, etc.), the eccentricity of the target to the initial planned pathway (e.g., is the tumor within the luminal network or outside of the luminal network), closest point of approach for alternative pathways, proximity of and angle to critical structures (e.g., blood vessels, pleura boundary, segmental boundaries), the size of the lumens of the luminal network to navigate (e.g., larger airways vs smaller airways), ability to cannulate along alternative pathway (e.g., stability), align-ability of catheter 70 to target, distance from the target to which the catheter 70 can be navigated, expected tissue properties, for navigation within the lungs the lobe the target is located in, pushability limits of the catheter 70 and medical device, number of curves or turns required to reach the target, and others without departing from the scope of the disclosure. A further aspect that may be considered is the potential for decoupling of motion. As will be understood by those of skill in the art, where the organ being navigated is elastic and flexible (e.g., the lungs) application of force on the catheter 70 can cause the target to move. This is particularly true with the airway size is close to or even smaller than the diameter of the catheter 70. Where the initial pathway follows a lumen with a diameter close to or smaller than the diameter of the catheter, following this pathway may result in the movement of the location of the target making the procedure more difficult to successfully perform, thus a pathway navigating lumen that are of greater diameter can reduce the coupled motion of the target as the catheter 70 is being navigated towards it.

[0090] At step 314 a proposed alternative pathway(s) is presented in the user interface 26 associated with the application 34. The presentation of the alternative pathway on the user interface 26 may include additional data including likelihood of success following the pathway, benefits of the alternative pathway (e.g., improved cannulation, improved alignment), airway size, improved safety, critical structure avoidance, risks on the pathway, decoupling of motion, and any of the factors described in connection with step 312 as well as others without departing from the scope of the disclosure. As described above, these factors may be weighted by an algorithm incorporated into the application 34 (or incorporated in a costing function), and the potential alternative pathways may be optionally presented in a ranked order based on likelihood of success or another criteria selected by the clinician. Step 314 enables the clinician to assess whether an identified alternative pathway, having a closest point of approach to the target that is greater than the initial pathway, nonetheless provides clinical or mechanical advantages for navigation of a catheter 70 to a location from which to launch a medical device (e.g., biopsy or therapy device) to perform a procedure. [0091] At step 316, the pathway for navigation (either the initial pathway or an alternative pathway) may be selected via the user interface 26 and at step 318 navigation of the catheter 70 and medical device commences. If there are multiple targets, each target may undergo the process above to define a pathway for navigation to each target. During navigation, the application 34 is configured to receive localization data of the catheter 70 indicating a location and orientation of at least a distal portion of the catheter 70 within the luminal network and present an indication of the location of the catheter in the 3D model. Despite the prior selection of the pathway for navigation, challenges (e.g., bleeding or blockages) may nonetheless be experienced during navigation. In the case of navigation of the lungs the challenges may be due to the imaging and modeling being performed on lungs at full breath hold, where navigation occurs with the lugs substantially deflated. Challenges may include a lack of cannulation at a location, a lack of progress in the navigation, an excessive number of tool passes, and other criteria without departing from the scope of the disclosure. Where difficulties are detected by the application 34, at step 320, the application 34 may present on the user interface 26 re-routing data (e.g., a further alternative pathway) to arrive at the target from the current location of the catheter 70 at step 322. The further alternative pathway may be analyzed and identified using the same or similar factors as the alternative pathways identified and presented in steps 312 and 314 (above). If the further alternative pathway is accepted at step 324, the further alternate pathway is presented in the user interface 26 on the 3D model at step 326 and the method returns to step 318 for navigation along the further alternative pathway. If the further alternative pathway is not accepted, the method also returns to step 318 for further navigation, but along the originally selected pathway for navigation. At step 328 a determination is made whether the catheter 70 or medical device has reached the target. If no at step 328 the method returns to step 318 for continued navigation, if yes at step 328 the procedure (e.g., biopsy or therapy) can be performed. Following performance of the procedure a determination is made whether there are additional targets to navigate to at step 330, if yes at step 330 to user interface 26 is updated to display the pathway for navigation to a next target and the method returns to step 318. If no at step 330 the method ends. As will be appreciated, one or more of the method steps may be eliminated or performed in an alternative order without departing from the scope of the disclosure.

[0092] As described above, the method 300 provides in at least one aspect an intraprocedural re-routing capability to arrive at a target when the navigation of a catheter 70 or medical device along initial pathway for navigation experiences challenges. This real-time update of potential pathway offers clinicians intra-operative updated guidance for navigation within the luminal network. As a result, the application 34 and method 300 enable guidance to achieve a successful navigation, even when challenges are encountered along the original planned pathway to the target.

[0093] While method 300 is described with reference to FIG. 17 as being an application starting with initial pathway planning (e.g., steps 302-316) the disclosure is not so limited. Indeed, the methods and applications described herein include a variety of subroutines which are performed during the navigation of the catheter towards the targets. These subroutines may be employed as part of method 300 or as separate applications 34. For example, steps 318-326 may be embodied in an application separate from method 300.

[0094] Thus, at any point following the initiation of navigation (e.g., step 318) of the catheter towards the target, difficulties or challenges may be experienced by the surgeon. As noted in method 300 these challenges or difficulties may be automatically detected or may be detected by the surgeon. In the event they are automatically detected the user interface 26 may present an indicator of the detection of challenges or difficulties and offer one or more alternative paths for navigation of the catheter 70 to the target from the current location of the catheter 70 (e.g., step 322). Alternatively, the user interface 26 may include a button or other feature where during the navigation of the catheter 70 towards the target the surgeon may request alternative routing of the catheter 70 to the target from the current location of the catheter 70. Following presentation of alternative pathways to the target from the current location of the catheter 70, the surgeon is able to select one of the pathways (e.g., step 324) and the user interface 26 is updated to display the new pathway from the current location of the catheter 70 to the target (e.g., step 3276) and the method returns to step 318 for continued navigation of the catheter 70 to the target following the intraprocedurally updated pathway. As will be appreciated, the new pathway may present an alternative closest point of approach for the target as well as lead to a location where a different portion of the target may be sampled by a biopsy tool, of where a therapy tool will be placed.

[0095] As an alternative to step 320, where difficulties or challenges are detected, the application 34 may simply detect that the surgeon has deviated from the planned pathway (e.g., as defined at step 316), and navigated the catheter 70 into an unplanned airway. Detecting that the catheter has deviated to an unplanned airway, t the application 34 may skip directly to, for example, step 322 and present re-routing data following the newly entered airway to the target. The surgeon then may confirm the re-routing data and accept the alternative pathway (e.g., step 324) which the surgeon initiated by their navigation decision to enter an unplanned pathway. Again, with the confirmation, the user interface 26 displays the updated pathway (e.g., step 326) and the surgeon can continue navigation of the catheter 70 to the target (e.g., step 318).

[0096] A further aspect of the disclosure is directed lumen selection intraprocedurally. In accordance with this aspect of the disclosure, at any time during navigation of the catheter 70 the surgeon may select (e.g., in the user interface 26) an airway in the 3D model other than one that is part of the pathway currently being navigated. Once selected (e.g., via a touch screen, mouse, or other input device) the application 34 generates an alternative pathway through the selected airway to the target (e.g., step 322). The surgeon may adopt the alternative pathway (e.g., step 324) and with the alternative pathway displayed in the user interface (e.g., step 326) for continued navigation (e.g., step 318). Alternatively, the alternative pathway may be stored in the memory and accessed by the application 34 at a different point in the procedure.

[0097] Additional features of the application 34 may include both manual and automatic target identification and pathway generation. In some instances, for example when the images being acquired at step 302 are cone-beam computed tomography (CBCT) images, those images may be acquired during the initial navigation of the catheter 70. As such, steps 302-316 may be performed after some initial navigation of the catheter 70 into the patient’s airways (e.g., step 318). This reordering of the steps of method 300 can beneficially streamline the procedure. As with other, applications 34, targets may be manually or automatically identified in the captured CBCT images (e.g., step 304). In instances where the target is within the airways, the application can automatically generate an initial pathway (e.g., step 308) and no identification of a closest lumen (e.g., step 306) can be eliminated or skipped. Alternatively, where the target is outside of an airway, the surgeon or another clinician utilizing the application 34 identifies the closest airway to the target (e.g., step 306) and the application 34 automatically generates the initial pathway (e.g., step 308). Steps 310-316 may be undertaken or the method can advance directly to navigation of the catheter towards the target (e.g., step 318).

[0098] Utilizing the steps outlined in method 300, whether as outlined herein above or in alternative order and with or without one or more of the steps being omitted a variety of routines and subroutines can be formulated to generate initial pathways and alternative pathways for the navigation of the catheter 70 to the targets. The routines and subroutines utilizing some portion of the steps of method 300 can be stored as part of one or more applications 34. The alternative pathways generated by the routines and subroutines provide greater ability to navigate the catheter 70 to the target and launch one or more biopsy or therapy tools to successfully sample and treat the target tissues.

[0099] The invention may be further described by reference to the following numbered paragraphs:

[00100] 1. A surgical system, comprising: a catheter; a workstation operably coupled to the catheter, the workstation including processing means configured to: generate a 3D model of the luminal network of the patient’s lungs; identify target tissue in the generated 3D model; receive catheter information; generate a plurality of proposed pathways through the luminal network to the identified target tissue; determine weighting factors based on the generated plurality of potential pathways; modify the determined weighting factors based on the received catheter information; apply the modified weighting factors to the generated plurality of proposed pathways; rank the generated proposed pathways after applying the modified weighting factors to the generated plurality of proposed pathways; and display the ranked proposed pathways to the target tissue.

2. The system according to paragraph 1, wherein the processing means is configured to receive patient information and modify the determined weighting factors based on the received medical device information and the received patient information.

3. The system according to paragraph 1, wherein the processing means is configured to receive the weighting factors, the weighting factors including at least one of: a distance to a selected portion of the target tissue from a distal end portion of the catheter; or an alignment of candidate airways of the luminal network with a selected portion of the target tissue; or a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter; or crossing of pleural or segmental boundaries of the patient’s lungs; or a volumetric overlap of expected trajectories of a surgical tool received within the catheter; or airways within the luminal network having an inner dimension that is less than a predetermined threshold.

4. The system according to paragraph 3, wherein the processing means is configured to determine the distance to the selected portion of the target tissue from the distal end portion of the catheter at a terminus of the plurality of generated proposed pathways.

5. The system according to paragraph 3, wherein the processing means is configured to determine the alignment of candidate airways with the selected portion of the target tissue by determining an angle between an alignment vector of a working channel of the catheter and a vector from a position of the distal end portion of the catheter to the selected portion of the target tissue.

6. The system according to paragraph 3, wherein the processing means is configured to: determine the predetermined threshold inner dimension based on a percentage of an outer dimension of the catheter; or determine the predetermined threshold inner dimension based on a percentage increase of the outer dimension of the catheter.

7. The system according to paragraph 3, wherein the processing means is configured to: identify pleural or segmental boundaries between a distal end portion of the catheter and the target tissue that if crossed, may result in pneumothorax; or determine a volumetric overlap between the proposed surgical tool path in the plurality of generated proposed pathways and a coverage of the volume of the target tissue.

8. The system according to paragraph 1, wherein the processing means is configured to: receive catheter information on the type of catheter used to navigate to the target tissue; receive catheter information on the type of surgical tool used to treat the target tissue; and receive catheter information of the outer dimension of the catheter.

9. A method of operating a surgical system, the method comprising: generating a 3D model of a luminal network of a patient’s lungs; identifying target tissue in the generated 3D model; receiving catheter information; generating a plurality of proposed pathways through the luminal network to the identified target tissue; determining weighting factors based on the generated plurality of potential pathways; modifying the determined weighting factors based on the received catheter information; applying the modified weighting factors to the generated plurality of proposed pathways; ranking the generated proposed pathways after applying the modified weighting factors to the generated plurality of proposed pathways; and displaying the ranked proposed pathways to the target tissue.

10. The method according to paragraph 9, wherein the determined weighting factors include at least one of: a distance to a volumetric center of the target tissue from a distal end portion of the catheter; or a distance to a center of malignancy of the target tissue from a distal end portion of the catheter; or an alignment of candidate airways of the luminal network with a volumetric center of the target tissue; or an alignment of candidate airways of the luminal network with a center of malignancy of the target tissue; or a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter; or crossing of pleural or segmental boundaries of the patient’s lungs; or a volumetric overlap of expected trajectories of a surgical tool received within the catheter; or airways within the luminal network having an inner dimension that is less than a predetermined threshold.

11. The method according to paragraph 10, further comprising: determining the predetermined threshold inner dimension based on a percentage of an outer dimension of the catheter; or determining the predetermined threshold inner dimension based on a percentage increase of the outer dimension of the catheter.

12. The method according to paragraph 10, further comprising determining the alignment of candidate airways with the volumetric center of the target tissue using an angle between an alignment vector of a working channel of the catheter and a vector from a position of the distal end portion of the catheter to a volumetric center of the target tissue.

13. A system, comprising: a catheter; and a workstation operably coupled to the catheter, the workstation including processing means configured to: generate a 3D model of the luminal network of a patient’s lungs; identify target tissue in the generated 3D model; generate a plurality of proposed pathways through the luminal network to the identified target tissue; determine weighting factors based on the generated plurality of potential pathways, the weighting factors including at least one of: a distance to a selected portion of the target tissue from a distal end portion of the catheter; and an alignment of candidate airways of the luminal network with a selected portion of the target tissue; and a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter; and crossing of pleural or segmental boundaries of the patient’s lungs; and a volumetric overlap of expected trajectories of a surgical tool received within the catheter; and airways within the luminal network having an inner dimension that is less than a predetermined threshold; apply the weighting factors to the generated plurality of proposed pathways; rank the generated proposed pathways; and display the ranked proposed pathways to the target tissue.

14. The method according to paragraph 13, wherein the processing meansgured to: determine the predetermined threshold inner dimension based on a percentage of an outer dimension of the catheter; or determine the predetermined threshold inner dimension based on a percentage increase of the outer dimension of the catheter.

15. The method according to paragraph 13, wherein the processing meansgured to: identify pleural or segmental boundaries between a distal end portion of the catheter and the target tissue that if crossed, may result in pneumothorax; or determine a volumetric overlap between the proposed surgical tool path in the plurality of generated proposed pathways and a coverage of the volume of the target tissue.

Claims

CLAIMS What is claimed is:

1. A system for performing a surgical procedure, comprising: a catheter navigable within a luminal network of a patient’s lungs; and a workstation operably coupled to the catheter, the workstation including a memory and a processor, the memory storing instructions thereon, which when executed by the processor cause the processor to: generate a 3D model of the luminal network of the patient’s lungs; identify target tissue in the generated 3D model; receive catheter information; generate a plurality of proposed pathways through the luminal network to the identified target tissue; determine weighting factors based on the generated plurality of potential pathways; modify the determined weighting factors based on the received catheter information; apply the modified weighting factors to the generated plurality of proposed pathways; rank the generated proposed pathways after applying the modified weighting factors to the generated plurality of proposed pathways; and display the ranked proposed pathways to the target tissue.

2. The system according to claim 1, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to receive patient information and modify the determined weighting factors based on the received medical device information and the received patient information.

3. The system according to claim 1, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to receive the weighting factors, the weighting factors including at least one of: a distance to a selected portion of the target tissue from a distal end portion of the catheter; or an alignment of candidate airways of the luminal network with a selected portion of the target tissue; or a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter; or crossing of pleural or segmental boundaries of the patient’s lungs; or a volumetric overlap of expected trajectories of a surgical tool received within the catheter; or airways within the luminal network having an inner dimension that is less than a predetermined threshold.

4. The system according to claim 3, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to determine the distance to the selected portion of the target tissue from the distal end portion of the catheter at a terminus of the plurality of generated proposed pathways.

5. The system according to claim 3, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to determine the alignment of candidate airways with the selected portion of the target tissue by determining an angle between an alignment vector of a working channel of the catheter and a vector from a position of the distal end portion of the catheter to the selected portion of the target tissue.

6. The system according to claim 3, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to determine the predetermined threshold inner dimension based on a percentage of an outer dimension of the catheter.

7. The system according to claim 6, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to determine the predetermined threshold inner dimension based on a percentage increase of the outer dimension of the catheter.

8. The system according to claim 3, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to identify pleural or segmental boundaries between a distal end portion of the catheter and the target tissue that, if crossed, may result in pneumothorax.

9. The system according to claim 3, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to determine a volumetric overlap between the proposed surgical tool path in the plurality of generated proposed pathways and a coverage of the volume of the target tissue.

10. The system according to claim 1, wherein the memory stores thereon further instructions, which when executed by the processor, cause the processor to: receive catheter information on the type of catheter used to navigate to the target tissue; receive catheter information on the type of surgical tool used to treat the target tissue; and receive catheter information on the outer dimension of the catheter.

11. A method for performing a surgical procedure, the method comprising: generating a 3D model of the luminal network of a patient’s lungs; identifying target tissue in the generated 3D model; receiving catheter information; generating a plurality of proposed pathways through the luminal network to the identified target tissue; determining weighting factors based on the generated plurality of potential pathways; modifying the determined weighting factors based on the received catheter information; applying the modified weighting factors to the generated plurality of proposed pathways; ranking the generated proposed pathways after applying the modified weighting factors to the generated plurality of proposed pathways; and displaying the ranked proposed pathways to the target tissue.

12. The method according to claim 11, wherein determining the weighting factors includes determining at least one of: a distance to a volumetric center of the target tissue from a distal end portion of the catheter; or a distance to a center of malignancy of the target tissue from a distal end portion of the catheter; or an alignment of candidate airways of the luminal network with a volumetric center of the target tissue; or an alignment of candidate airways of the luminal network with a center of malignancy of the target tissue; or a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter; or crossing of pleural or segmental boundaries of the patient’s lungs; or a volumetric overlap of expected trajectories of a surgical tool received within the catheter; or airways within the luminal network having an inner dimension that is less than a predetermined threshold.

13. The method according to claim 12, further comprising determining the predetermined threshold inner dimension based on a percentage of an outer diameter of the catheter.

14. The method according to claim 13, further comprising determining the predetermined threshold inner dimension based on a percentage increase of the outer dimension of the catheter.

15. The method according to claim 12, further comprising determining the alignment of candidate airways with the volumetric center of the target tissue using an angle between an alignment vector of a working channel of the catheter and a vector from a position of the distal end portion of the catheter to the volumetric center of the target tissue.

16. A system for performing a surgical procedure, comprising: a catheter navigable within a luminal network of a patient; and a workstation operably coupled to the catheter, the workstation including a memory and a processor, the memory storing instructions thereon, which when executed by the processor cause the processor to: generate a 3D model of the luminal network of a patient’s lungs; identify target tissue in the generated 3D model; generate a plurality of proposed pathways through the luminal network to the identified target tissue; determine weighting factors based on the generated plurality of potential pathways, the weighting factors including at least two of: a distance to a selected portion of the target tissue from a distal end portion of the catheter; or an alignment of candidate airways of the luminal network with a selected portion of the target tissue; or a distance to a bifurcation of the luminal network nearest to a distal end portion of the catheter; or crossing of pleural or segmental boundaries of the patient’s lungs; or a volumetric overlap of expected trajectories of a surgical tool received within the catheter; or airways within the luminal network having an inner dimension that is less than a predetermined threshold; apply the weighting factors to the generated plurality of proposed pathways; rank the generated proposed pathways; and display the ranked proposed pathways to the target tissue.

17. The system according to claim 16, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to determine the predetermined threshold inner dimension based on a percentage of an outer dimension of the catheter.

18. The system according to claim 16, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to determine the predetermined threshold inner dimension based on a percentage increase of an outer dimension of the catheter.

19. The system according to claim 16, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to identify pleural or segmental boundaries between a distal end portion of the catheter and the target tissue that if crossed, may result in pneumothorax.

20. The system according to claim 16, wherein the memory stores thereon further instructions, which when executed by the processor cause the processor to determine a volumetric overlap between the proposed surgical tool path in the plurality of generated proposed pathways and a coverage of the volume of the target tissue.