WO2026018118A1 - Surgical robotic system and method for preoperative planning - Google Patents

Abstract

A surgical robotic system and method are provided for preoperative planning and precise navigation during minimally invasive surgical procedures. The system integrates various navigation technologies, such as electromagnetic and optical tracking, to monitor the position and orientation of robotic arms and surgical instruments in real time. A 3D model of the patient's anatomy, generated from preoperative imaging, is used to develop a preoperative plan, which includes critical structures and planned trajectories. During surgery, the system continuously registers the instruments' positions with the 3D model, compensating for tissue movement and deformation. This ensures accurate execution of the surgical plan, enhancing precision and control. The system provides real-time feedback through visual, haptic, and/or auditory cues, aiding the surgeon in navigating and manipulating the instruments effectively.

Description

SURGICAL ROBOTIC SYSTEM AND METHOD FOR PREOPERATIVE PLANNING

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63/673,309, filed July 19, 2024, the entire content of which is incorporated herein by reference.

BACKGROUND

[0002] Surgical robotic systems are currently being used in a variety of surgical procedures, including laparoscopic and endoluminal minimally invasive procedures. Laparoscopic surgical robotic systems include a surgeon console for controlling a surgical robotic arm and a surgical instrument having an end effector (e.g., forceps or grasping instrument coupled to and actuated by the robotic arm). In operation, the robotic arm is moved to a position over a patient and then guides the surgical instrument into a small incision via a surgical port to position the end effector at a work site within the patient’s body. The robotic arm and the instrument are actuated using motors, which may be controlled using various parameters.

[0003] Some surgical robotic systems do not provide users with a clear understanding of where the instruments are located and the direction the instruments need to be moved. In certain procedures, such as lung resections, preoperative planning is used to determine the proper position and orientation of the instruments used in the procedure. Lung resection procedures include wedge resection, segmentectomy, lobectomy, and pneumonectomy. A wedge resection involves the removal of lung cancer along with a wedge-shaped section of tissue surrounding the tumor. This procedure removes less lung tissue than a lobectomy. Like wedge resection, segmentectomy is a limited resection procedure, with wedge resection often being associated with less parenchyma and other tissue removal, less intraoperative blood loss, and shorter operative time, than segmentectomy. In lobectomy, one or multiple lobes are removed from the lungs. A lobectomy removes one of these lobes that may be damaged from disease or an infection. Lobectomy is usually the main treatment for people with: early stages of lung cancer, tuberculosis, emphysema, bronchiectasis, non- cancerous (benign) tumors, and fungal infections. In pneumonectomy, the entire lung is removed because of cancer, trauma, or some other condition. [0004] Preoperative planning for lung resection utilizes preoperative images to generate a 3D model of the tissue to analyze unique patient anatomy. In addition, various markers (e.g., dye, radiopaque, etc.) are also added to the tissue to define the boundary of the tissue being resected. However, these methods do not provide for tracking end effector location on a preoperative 3D model during the resection procedure.

SUMMARY

[0005] The present disclosure provides for a robotic system and method that uses one or more navigation technologies (e.g., electromagnetic, optical navigation, combinations thereof) to track the position of the system’s components. The robotic system includes a surgeon console for displaying a 3D model and/or video feeds provided by endoluminal and/or laparoscopic cameras. A preoperative plan may include the 3D tissue model constructed from various imaging modalities.

[0006] The system also includes one or more robotic arms, each having an instrument. A navigation system includes a tracker for tracking sensors disposed on the robotic arms and instruments. Various optical or electromagnetic sensors detect the position and orientation of sensors attached to these components. Electromagnetic tracking utilizes magnetic fields generated by coils to determine the location of the sensors, while optical tracking uses infrared and/or visible light imaging devices to capture the sensors’ positions. In addition, kinematic data (e.g., joint angles, etc.) obtained from robotic arm and instruments sensors (e.g., torque sensors, position sensors and encoders, etc.) may be used along with electromagnetic and optical tracking.

[0007] This tracking data is then processed to accurately register the robotic arms and instruments within the preoperative plan, which is then used during the procedure enabling precise navigation and manipulation during surgery. This registration ensures that the movements of the robotic system correspond accurately to the virtual model, allowing for enhanced control and precision in surgical procedures. The end effectors of the instruments as well as other devices being controlled by the arms, such as a laparoscopic camera, are visualized on the preoperative 3D plan.

[0008] The preoperative plan may include a segmented 3D model of the organ, e.g., lung, incorporating prior segmentations of critical structures to avoid and planned trajectories/paths required to perform the procedure. This allows the surgeon to navigate and act upon live updates displayed on a visualized map. The segmented map includes preplanned paths for the end effectors and a live feedback mechanism that shows the current position and provides real-time suggestions on where to navigate with the instrument and what actions to perform.

[0009] The system also incorporates deformation compensation algorithms that account for tissue movement and deformation during surgery. These algorithms leverage external sensors (e.g., electromagnetic or optical cameras tracking patient movements, etc.) and/or internal sensors (e.g., endoluminal catheters, embedded trackers, etc.) to continuously monitor and adjust for deformations. This ensures accurate and precise navigation and execution of the surgical procedure, maintaining the integrity of the preoperative plan.

[0010] According to one embodiment of the present disclosure, a method for preoperative planning and navigation in a surgical robotic system is disclosed. The method includes obtaining a 3D model of an organ using at least one imaging modality. The method includes generating a preoperative plan from the 3D model, the preoperative plan including a planned position for a surgical robotic instrument. The method also includes registering the 3D model and the preoperative plan with the organ. The method further includes using a navigation system to track a position of a robotic arm and the surgical robotic instrument coupled thereto, the navigation system including tracking sensors disposed on the robotic arm and the surgical robotic instrument. The method additionally includes registering the robotic arm and instruments with the organ and within the 3D model and the preoperative plan. The method also includes displaying movements of the robotic arm and the surgical robotic instrument on a display screen showing the preoperative plan in real-time and providing feedback through a visualized map that shows a current position of the surgical robotic instrument and provides directions for moving the surgical robotic instrument to attain the planned position.

[0011] Implementations of the above embodiment may include one or more of the following features. According to one aspect of the above embodiment, registering the 3D model and the preoperative plan may include registering the 3D model and the preoperative plan with an intraoperative camera video feed. The method may include compensating for tissue movement and deformation using deformation compensation algorithms using external and internal sensors disposed on or inside a patient. The method may include providing deformation compensation for the 3D model using the external and internal sensors. The 3D model may be obtained using imaging modalities selected from computed tomography (CT), cone-beam computed tomography (CBCT), magnetic resonance imaging (MRI), fluoroscopic imaging, positron emission tomography (PET), and/or ultrasound imaging. The navigation system may include an external vision tracking unit having one or more cameras or infrared sensors configured to track the position of the robotic arm and the surgical robotic instrument. The navigation system may also include an electromagnetic tracking unit that uses magnetic fields generated by an electromagnetic field generator to track the position of the robotic arm and the surgical robotic instrument. The method may include using kinematic data obtained from the robotic arm and the surgical robotic instrument. The kinematic data may include joint angles, torque, and position data. The preoperative plan and the 3D model may be displayed on the display screen as an augmented reality overlay over an intraoperative camera video feed. The feedback may include haptic feedback, graphical user interface (GUI) directions, and auditory alerts. The preoperative plan may also include segmented critical structures.

BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Various embodiments of the present disclosure are described herein with reference to the drawings wherein:

[0013] FIG. 1 is a perspective view of a surgical robotic system including a control tower, a console, and one or more surgical robotic arms each disposed on a movable cart according to an embodiment of the present disclosure;

[0014] FIG. 2 is a perspective view of a surgical robotic arm of the surgical robotic system of FIG. 1 according to an embodiment of the present disclosure;

[0015] FIG. 3 is a perspective view of a movable cart having a setup arm with the surgical robotic arm of the surgical robotic system of FIG. 1 according to an embodiment of the present disclosure;

[0016] FIG. 4 is a schematic diagram of a computer architecture of the surgical robotic system of FIG. 1 according to an embodiment of the present disclosure;

[0017] FIG. 5 is a plan schematic view of movable carts of FIG. 1 positioned about a surgical table according to an aspect of the present disclosure;

[0018] FIG. 6 is a schematic diagram of a system for determining phases of a surgical procedure according to an embodiment of the present disclosure; and [0019] FIG. 7 shows a flow chart of a method for preoperative plan generation and execution for the surgical robotic system according to an embodiment of the present disclosure.

DETAILED DESCRIPTION

[0020] Embodiments of the presently disclosed surgical robotic system are described in detail with reference to the drawings, in which like reference numerals designate identical or corresponding elements in each of the several views.

[0021] With reference to FIG. 1, a surgical robotic system 10 includes a control tower 20, which is connected to all of the components of the surgical robotic system 10 including a surgeon console 30 and one or more movable carts 60. Each of the movable carts 60 includes a robotic arm 40 having a surgical instrument 50 coupled thereto. The robotic arms 40 also couple to the movable carts 60. The robotic system 10 may include any number of movable carts 60 and/or robotic arms 40.

[0022] The surgical instrument 50 is configured for use during minimally invasive surgical procedures. In embodiments, the surgical instrument 50 may be configured for open surgical procedures. In further embodiments, the surgical instrument 50 may be an electrosurgical forceps configured to seal tissue by compressing tissue between jaw members and applying electrosurgical current thereto. In yet further embodiments, the surgical instrument 50 may be a surgical stapler including a pair of jaws configured to grasp and clamp tissue while deploying a plurality of tissue fasteners, e.g., staples, and cutting stapled tissue. In yet further embodiments, the surgical instrument 50 may be a surgical clip applier including a pair of jaws configured to apply a surgical clip onto tissue. However, it will be understood that various types of surgical instruments for use during minimally invasive surgical procedures are contemplated and within the scope of this disclosure.

[0023] One of the robotic arms 40 may include an endoscopic camera 51 configured to capture video of the surgical site. The endoscopic camera 51 may be a stereoscopic endoscope configured to capture two side-by-side (i.e., left and right) images of the surgical site to produce a video stream of the surgical scene. The endoscopic camera 51 is coupled to a video processing device 56, which may be disposed within the control tower 20. The video processing device 56 may be any computing device as described below configured to receive the video feed from the endoscopic camera 51 and output the processed video stream.

[0024] The surgeon console 30 includes a first display 32, which displays a video feed of the surgical site provided by camera 51 disposed on the robotic arm 40, and a second display 34, which displays a user interface for controlling the surgical robotic system 10. The first display 32 and second display 34 may be touchscreens allowing for displaying various graphical user inputs.

[0025] The surgeon console 30 also includes a plurality of user interface devices, such as foot pedals 36 and a pair of handle controllers 38a and 38b which are used by a user to remotely control robotic arms 40. The surgeon console further includes an armrest 33 used to support clinician’s arms while operating the handle controllers 38a and 38b.

[0026] The control tower 20 includes a display 23, which may be a touchscreen that may display the graphical user interfaces (GUIs). The control tower 20 also acts as an interface between the surgeon console 30 and one or more robotic arms 40. In particular, the control tower 20 is configured to control the robotic arms 40, such as to move the robotic arms 40 and the corresponding surgical instrument 50, based on a set of programmable instructions and/or input commands from the surgeon console 30, in such a way that robotic arms 40 and the surgical instrument 50 execute a desired movement sequence in response to input from the foot pedals 36 and the handle controllers 38a and 38b. The foot pedals 36 may be used to enable and lock the handle controllers 38a and 38b, repositioning camera movement and electrosurgical activation/deactivation. In particular, the foot pedals 36 may be used to perform a clutching action on the handle controllers 38a and 38b. Clutching is initiated by pressing one of the foot pedals 36, which disconnects (i.e., prevents movement inputs) the handle controllers 38a and/or 38b from the robotic arm 40 and corresponding instrument 50 or camera 51 attached thereto. This allows the user to reposition the handle controllers 38a and 38b without moving the robotic arm(s) 40 and the instrument 50 and/or camera 51. This is useful when reaching control boundaries of the surgical space.

[0027] Each of the control tower 20, the surgeon console 30, and the robotic arm 40 includes a respective computer 21, 31, 41. The computers 21 , 31 , 41 are interconnected to each other using any suitable communication network based on wired or wireless communication protocols. The term “network,” whether plural or singular, as used herein, denotes a data network, including, but not limited to, the Internet, Intranet, a wide area network, or a local area network, and without limitation as to the full scope of the definition of communication networks as encompassed by the present disclosure. Suitable protocols include, but are not limited to, transmission control protocol/intemet protocol (TCP/IP), datagram protocol/intemet protocol (UDP/IP), and/or datagram congestion control protocol (DCCP). Wireless communication may be achieved via one or more wireless configurations, e.g., radio frequency, optical, Wi-Fi, Bluetooth (an open wireless protocol for exchanging data over short distances, using short length radio waves, from fixed and mobile devices, creating personal area networks (PANs), ZigBee® (a specification for a suite of high level communication protocols using small, low-power digital radios based on the IEEE 122. 15.4-1203 standard for wireless personal area networks (WPANs)).

[0028] The computers 21, 31, 41 may include any suitable processor (not shown) operably connected to a memory (not shown), which may include one or more of volatile, nonvolatile, magnetic, optical, or electrical media, such as read-only memory (ROM), random access memory (RAM), electrically erasable programmable ROM (EEPROM), non-volatile RAM (NVRAM), or flash memory. The processor may be any suitable processor (e.g., control circuit) adapted to perform the operations, calculations, and/or set of instructions described in the present disclosure including, but not limited to, a hardware processor, a field programmable gate array (FPGA), a digital signal processor (DSP), a central processing unit (CPU), a microprocessor, and combinations thereof. Those skilled in the art will appreciate that the processor may be substituted by using any logic processor (e.g., control circuit) adapted to execute algorithms, calculations, and/or set of instructions described herein.

[0029] With reference to FIG. 2, each of the robotic arms 40 may include a plurality of links 42a, 42b, 42c, which are interconnected at joints 44a, 44b, 44c, respectively. Other configurations of links and joints may be utilized as known by those skilled in the art. The joint 44a is configured to secure the robotic arm 40 to the movable cart 60 and defines a first longitudinal axis. With reference to FIG. 3, the movable cart 60 includes a lift 67 and a setup arm 61, which provides a base for mounting of the robotic arm 40. The lift 67 allows for vertical movement of the setup arm 61. The movable cart 60 also includes a display 69 for displaying information pertaining to the robotic arm 40. In embodiments, the robotic arm 40 may include any type and/or number of joints. [0030] The setup arm 61 includes a first link 62a, a second link 62b, and a third link 62c, which provide for lateral maneuverability of the robotic arm 40. The links 62a, 62b, 62c are interconnected at joints 63a and 63b, each of which may include a motor (not shown) for rotating the links 62b and 62b relative to each other and the link 62c. In particular, the links 62a, 62b, 62c are movable in their corresponding lateral planes that are parallel to each other, thereby allowing for extension of the robotic arm 40 relative to the patient (e.g., surgical table). In embodiments, the robotic arm 40 may be coupled to the surgical table (not shown). The setup arm 61 includes controls 65 for adjusting movement of the links 62a, 62b, 62c as well as the lift 67. In embodiments, the setup arm 61 may include any type and/or number of joints.

[0031] The third link 62c may include a rotatable base 64 having two degrees of freedom. In particular, the rotatable base 64 includes a first motor 64a and a second motor 64b. The first motor 64a is rotatable about a first stationary arm axis which is perpendicular to a plane defined by the third link 62c and the second motor 64b is rotatable about a second stationary arm axis which is transverse to the first stationary arm axis. The first and second motors 64a and 64b allow for full three-dimensional orientation of the robotic arm 40.

[0032] The motor 48b of the joint 44b is coupled to the joint 44c via the belt 45a, and the joint 44c is in turn coupled to the joint 46b via the belt 45b. Joint 44c may include a transfer case coupling the belts 45a and 45b, such that the motor 48b is configured to rotate each of the links 42b, 42c and a holder 46 relative to each other. More specifically, links 42b, 42c, and the holder 46 are passively coupled to the motor 48b which enforces rotation about a pivot point “P” which lies at an intersection of the first axis defined by the link 42a and the second axis defined by the holder 46. In other words, the pivot point “P” is a remote center of motion (RCM) for the robotic arm 40. Thus, the motor 48b controls the angle 0 between the first and second axes allowing for orientation of the surgical instrument 50. Due to the interlinking of the links 42a, 42b, 42c, and the holder 46 via the belts 45a and 45b, the angles between the links 42a, 42b, 42c, and the holder 46 are also adjusted in order to achieve the desired angle 0. In embodiments, some or all of the joints 44a, 44b, 44c may include a motor to obviate the need for mechanical linkages.

[0033] The joints 44a and 44b include a motor 48a and 48b configured to drive the joints 44a, 44b, 44c relative to each other through a series of belts 45a and 45b or other mechanical linkages such as a drive rod, a cable, or a lever and the like. In particular, the motor 48a is configured to rotate the robotic arm 40 about a longitudinal axis defined by the link 42a.

[0034] With reference to FIG. 2, the holder 46 defines a second longitudinal axis and configured to receive an instrument drive unit (IDU) 52 (FIG. 1). The IDU 52 is configured to couple to an actuation mechanism of the surgical instrument 50 and the camera 51 and is configured to move (e.g., rotate) and actuate the instrument 50 and/or the camera 51. IDU 52 transfers actuation forces from its motors to the surgical instrument 50 to actuate components of an end effector 49 of the surgical instrument 50. The holder 46 includes a sliding mechanism 46a, which is configured to move the IDU 52 along the second longitudinal axis defined by the holder 46. The holder 46 also includes a joint 46b, which rotates the holder 46 relative to the link 42c. During endoscopic procedures, the instrument 50 may be inserted through an endoscopic access port 55 (FIG. 3) held by the holder 46. The holder 46 also includes a port latch 46c for securing the access port 55 to the holder 46 (FIG. 2).

[0035] The IDU 52 is attached to the holder 46, followed by a sterile interface module (SIM) 43 being attached to a distal portion of the IDU 52. The SIM 43 is configured to secure a sterile drape (not shown) to the IDU 52. The instrument 50 is then attached to the SIM 43. The instrument 50 is then inserted through the access port 55 by moving the IDU 52 along the holder 46. The SIM 43 includes a plurality of drive shafts configured to transmit rotation of individual motors of the IDU 52 to the instrument 50 thereby actuating the instrument 50. In addition, the SIM 43 provides a sterile barrier between the instrument 50 and the other components of robotic arm 40, including the IDU 52.

[0036] The robotic arm 40 also includes a plurality of manual override buttons 53 (FIG. 1) disposed on the IDU 52 and the setup arm 61, which may be used in a manual mode. The user may press one or more of the buttons 53 to move the component associated with the one or more buttons 53.

[0037] With reference to FIG. 4, each of the computers 21, 31, 41 of the surgical robotic system 10 may include a plurality of controllers, which may be embodied in hardware and/or software. The computer 21 of the control tower 20 includes a controller 21a and safety observer 2 lb. The controller 21a receives data from the computer 31 of the surgeon console 30 about the current position and/or orientation of the handle controllers 38a and 38b and the state of the foot pedals 36 and other buttons. The controller 21a processes these input positions to determine desired drive commands for each joint of the robotic arm 40 and/or the IDU 52 and communicates these to the computer 41 ofthe robotic arm 40. The controller 21a also receives the actual joint angles measured by encoders of the motors 48a and 48b and uses this information to determine force feedback commands that are transmitted back to the computer 31 of the surgeon console 30 to provide haptic feedback through the handle controllers 38a and 38b. The safety observer 2 lb performs validity checks on the data going into and out of the controller 21a and notifies a system fault handler if errors in the data transmission are detected to place the computer 21 and/or the surgical robotic system 10 into a safe state.

[0038] The computer 41 includes a plurality of controllers, namely, a main cart controller 41a, a setup arm controller 41b, a robotic arm controller 41c, and an instrument drive unit (IDU) controller 4 Id. The main cart controller 41a receives and processes joint commands from the controller 21a of the computer 21 and communicates them to the setup arm controller 41b, the robotic arm controller 41c, and the IDU controller 4 Id. The main cart controller 41a also manages instrument exchanges and the overall state of the movable cart 60, the robotic arm 40, and the IDU 52. The main cart controller 41a also communicates actual joint angles back to the controller 21a.

[0039] Each of joints 63a and 63b and the rotatable base 64 of the setup arm 61 are passive joints (i.e., no motors are present therein) allowing for manual adjustment thereof by a user. The joints 63a and 63b and the rotatable base 64 include brakes that are disengaged by the user to configure the setup arm 61. The setup arm controller 41b monitors slippage of each of joints 63a and 63b and the rotatable base 64 ofthe setup arm 61, when brakes are engaged or can be freely moved by the operator when brakes are disengaged, but do not impact controls of other joints. The robotic arm controller 41c controls each joint 44a and 44b of the robotic arm 40 and calculates desired motor torques required for gravity compensation, friction compensation, and closed loop position control of the robotic arm 40. The robotic arm controller 41c calculates a movement command based on the calculated torque. The calculated motor commands are then communicated to one or more of the motors 48a and 48b in the robotic arm 40. The actual joint positions are then transmitted by the motors 48a and 48b back to the robotic arm controller 41c.

[0040] The IDU controller 4 Id receives desired joint angles for the surgical instrument 50, such as wrist and jaw angles, and computes desired currents for the motors in the IDU 52. The IDU controller 4 Id calculates actual angles based on the motor positions and transmits the actual angles back to the main cart controller 41a.

[0041] The robotic arm 40 is controlled in response to a pose of the handle controller controlling the robotic arm 40, e.g., the handle controller 38a, which is transformed into a desired pose of the robotic arm 40 through a hand eye transform function executed by the controller 21a. The hand eye function, as well as other functions described herein, is/are embodied in software executable by the controller 21a or any other suitable controller described herein. The pose of one of the handle controllers 38a may be embodied as a coordinate position and roll-pitch-yaw (RPY) orientation relative to a coordinate reference frame, which is fixed to the surgeon console 30. The desired pose of the instrument 50 is relative to a fixed frame on the robotic arm 40. The pose of the handle controller 38a is then scaled by a scaling function executed by the controller 21a. In embodiments, the coordinate position may be scaled down and the orientation may be scaled up by the scaling function. In addition, the controller 21a may also execute a clutching function, which disengages the handle controller 38a from the robotic arm 40. In particular, the controller 21a stops transmitting movement commands from the handle controller 38a to the robotic arm 40 if certain movement limits or other thresholds are exceeded and in essence acts like a virtual clutch mechanism, e.g., limits mechanical input from effecting mechanical output.

[0042] The desired pose of the robotic arm 40 is based on the pose of the handle controller 38a and is then passed by an inverse kinematics function executed by the controller 21a. The inverse kinematics function calculates angles for the joints 44a, 44b, 44c of the robotic arm 40 that achieve the scaled and adjusted pose input by the handle controller 38a. The desired angles are then passed to the robotic arm controller 41c, which includes a joint axis controller having a proportional-derivative (PD) controller, the friction estimator module, the gravity compensator module, and a two-sided saturation block, which is configured to limit the commanded torque of the motors of the joints 44a, 44b, 44c. In aspects, handle controller 38a may be substituted for and/or employed in conjunction with handle controller 38b. While reference is made above to handle controller 38a, handle controller 38b may also be used in a similar manner.

[0043] With reference to FIG. 5, the surgical robotic system 10 is setup around a surgical table. The system 10 includes mobile carts 60a-d, which may be numbered “1” through “4.” During setup, each of the carts 60a-d are positioned around the surgical table. Position and orientation of the carts 60a-d depends on a plurality of factors, such as placement of a plurality of access ports 55a-d, which in turn, depends on the surgery being performed. Once the port placement is determined, the access ports 55a-d are inserted into the patient, and carts 60a-d are positioned to insert instruments 50 and the laparoscopic camera 51 into corresponding ports 55a-d.

[0044] During use, each of the robotic arms 40a-d is attached to one of the access ports 55a- d that is inserted into the patient by attaching the latch 46c (FIG. 2) to the access port 55 (FIG. 3). The IDU 52 is attached to the holder 46, followed by the SIM 43 being attached to a distal portion of the IDU 52. Thereafter, the instrument 50 is attached to the SIM 43. The instrument 50 is then inserted through the access port 55 by moving the IDU 52 along the holder 46. The SIM 43 includes a plurality of drive shafts configured to transmit rotation of individual motors of the IDU 52 to the instrument 50 thereby actuating the instrument 50. In addition, the SIM 43 provides a sterile barrier between the instrument 50 and the other components of robotic arm 40, including the IDU 52. The SIM 43 is also configured to secure a sterile drape (not shown) to the IDU 52.

[0045] During use, each of the robotic arms 40b-d is attached to one of the access ports 55b- d that is inserted into the patient by attaching the latch 46c (FIG. 2) to the access port 55 (FIG. 3). The IDU 52 is attached to the holder 46, followed by the SIM 43 being attached to a distal portion of the IDU 52. Thereafter, the instrument 50 is attached to the SIM 43. The instrument 50 is then inserted through the access port 55 by moving the IDU 52 along the holder 46.

[0046] With reference to FIG. 6, the surgical robotic system 10 may include an AI/MU processing system 310 that processes the surgical data using one or more MU models to identify one or more features, such as surgical phase, instrument, anatomical structure, etc., in the surgical data. The MU processing system 310 includes a MU training system 325, which may be a separate device (e.g., server) that stores its output as one or more trained MU models 330. The MU models 330 are accessible by a MU execution system 340. The MU execution system 340 may be separate from the MU training system 325, namely, devices that “train” the models are separate from devices that “infer,” i.e., perform real-time processing of surgical data using the trained MU models 330.

[0047] System 10 includes a data reception system 305 that collects surgical data, including the video data and surgical instrumentation data. The data reception system 305 can include one or more devices (e.g., one or more user devices and/or servers) located within and/or associated with a surgical operating room and/or control center. The data reception system 305 can receive surgical data in real-time, i.e., as the surgical procedure is being performed. [0048] The ML processing system 310, in some examples, may further include a data generator 315 to generate simulated surgical data, such as a set of virtual or masked images, or record the video data from the image processing device 56, to train the ML models 330 as well as other sources of data, e.g., user input, arm movement, etc. Data generator 315 can access (read/write) a data store 320 to record data, including multiple images and/or multiple videos.

[0049] The ML processing system 310 also includes a phase detector 350 that uses the ML models to identify a phase within the surgical procedure. Phase detector 350 uses a particular procedural tracking data structure 355 from a list of procedural tracking data structures. Phase detector 350 selects the procedural tracking data structure 355 based on the type of surgical procedure that is being performed. In one or more examples, the type of surgical procedure is predetermined or input by user. The procedural tracking data structure 355 identifies a set of potential phases that may correspond to a part of the specific type of surgical procedure.

[0050] In some examples, the procedural tracking data structure 355 may be a graph that includes a set of nodes and a set of edges, with each node corresponding to a potential phase. The edges may provide directional connections between nodes that indicate (via the direction) an expected order during which the phases will be encountered throughout an iteration of the surgical procedure. The procedural tracking data structure 355 may include one or more branching nodes that feed to multiple next nodes and/or may include one or more points of divergence and/or convergence between the nodes. In some instances, a phase indicates a procedural action (e.g., surgical action) that is being performed or has been performed and/or indicates a combination of actions that have been performed. In some instances, a phase relates to a biological state of a patient undergoing a surgical procedure. For example, the biological state may indicate a complication (e.g., blood clots, clogged arteries/veins, etc.), pre-condition (e.g., lesions, polyps, etc.). In some examples, the ML models 330 are trained to detect an “abnormal condition,” such as hemorrhaging, arrhythmias, blood vessel abnormality, etc. [0051] The phase detector 350 outputs the phase prediction associated with a portion of the video data that is analyzed by the ML processing system 310. The phase prediction is associated with the portion of the video data by identifying a start time and an end time of the portion of the video that is analyzed by the ML execution system 340. The phase prediction that is output may include an identity of a surgical phase as detected by the phase detector 350 based on the output of the ML execution system 340. Further, the phase prediction, in one or more examples, may include identities of the structures (e.g., instrument, anatomy, etc.) that are identified by the ML execution system 340 in the portion of the video that is analyzed. The phase prediction may also include a confidence score of the prediction. Other examples may include various other types of information in the phase prediction that is output. The predicted phase may be used by the controller 21 a to determine when to provide guidance using the preoperative plan.

[0052] FIG. 7 illustrates a flowchart of a method 500 for generating a preoperative plan including a 3D model of the organ (e.g., lung) and providing navigational guidance to the user of the robotic system 10. Method 500 may be implemented, at least in part, by the processor (e.g., controller 21a) executing instructions stored in the memory. Additionally, the particular sequence of steps shown in method 500 is provided by way of example and not limitation. Thus, the steps of method 500 may be executed in sequences other than the sequences shown in FIG. 7 without departing from the scope of the present disclosure. Further, some steps shown in method 500 may be concurrently executed with respect to one another instead of sequentially executed with respect to one another.

[0053] At step 502, a 3D model is obtained using any suitable imaging modality such as computed tomography (CT), cone-beam computed tomography (CBCT), magnetic resonance imaging (MRI), fluoroscopic imaging (such as with a C-arm device), positron emission tomography (PET), and ultrasound imaging (US) or any other imaging modality capable of obtaining or constructing 3D images. In addition, the 3D model segments critical structures (e.g., blood vessels).

[0054] At step 504, the 3D model is used to generate a preoperative plan which includes creating boundaries (also referred to as margins) for the resection procedure as well as step- by-step movements for positioning and orienting the laparoscopic instruments 50 and camera 51 being used in the procedure, e.g., planned trajectories and paths needed to perform the procedure and avoid critical structures. [0055] At step 506, the 3D model of the preoperative plan is registered with the organ intraoperative endoscopic and/or laparoscopic video feeds. The preoperative plan and the 3D model may be displayed on the display screen 32 and/or 34, as an augmented reality overlay over the video feed or in any suitable manner. Any method of global registration between the intra-operative image in the form of texture point cloud and the pre-operative 3D model. One such approach could be a semi-automatic registration of two sets of point clouds. This includes first sampling the point cloud from the 3D model to generate a point cloud representation of the 3D model, followed by automatically extracting the voxels, vertices, and meshes corresponding to the clamping location. In this semi-automatic registration approach, the system provides a user interface for the user through the robotic system 10, specifically through the hand controllers 38a and/or 38b and the first screen 32 which allows the user to point the corresponding anatomical landmarks on the endoscope video feed. In this semi-automatic registration approach, a plurality of the same anatomical points or surfaces are provided as a match between the preoperative 3D model and the intraoperative point cloud.

[0056] Additionally, any global registration approach can be used to align the preoperative 3D model with the intraoperative textured point cloud, such as Fast Global Registration or the Iterative Closest Point (ICP) registration. Furthermore, the system can train a pose estimation neural network from the preoperative 3D model during surgery pre-planning stage and use the trained neural network to estimate the pose of the 3D model in the intraoperative scene, hence solving the global registration problem. The controller 2 la may globally register the 3D model with an intraoperative image, e.g., endoscopic and/or laparoscopic video feeds. In embodiments, the intraoperative image and the depth map may be used to generate textured point clouds, which may be used for registration with the 3D model. The controller 21a may also segment externally visible vessels and organ surfaces from intraoperative images and locally register these tissue features. In one embodiment, the controller 21a may divide the 3D model into multiple sub-meshes and deform each of the sub-meshes separately in order to improve the local registration. The controller 21a can use any of the global registration approaches for the sub-meshes towards the local deformable registration.

[0057] At step 508, the robotic arms 40a-d, the instruments 50, the camera 51, and any other movable components are registered with the organ using an electromagnetic and/or optical navigation system. The navigation system may include an external vision tracking unit 170 (FIG. 1) having one or more cameras or infrared sensors or other imaging devices configured to track the locations of the robotic arms 40a-d, which may have one or more sensors 172 disposed thereon. The tracking unit 170 and /or its associated components (e.g., the one or more sensors 172 or other optical sensors) may be disposed on the control tower 20, the IDU 52, or any other location in the operating room. The tracking unit 170 may include one or more position sensors, which may be any suitable white light or infrared cameras, electromagnetic sensors, magnetoresistance sensors, radio frequency sensors, or any other sensor adapted to sufficiently sense the position of a navigation sensor. The tracking unit 170 may be configured to detect sensors 172 disposed on the robotic arms 40a- d, i.e., the holder 46. The sensors 172 may be passive tracking elements (e.g., reflectors) for transmitting light signals (e.g., reflecting light emitted from the tracking unit 170). Alternatively, the sensors 172 may include a radiopaque material that is identified and trackable by the tracking unit 170. In other configurations, active tracking sensors can be employed. The active tracking sensors can be, for example, light emitting diodes transmitting light, such as infrared light. Active and passive arrangements are possible. The sensors may be arranged in a defined or known position and orientation relative to the other sensors in order to allow the tracking unit 170 to determine the position of the robotic arms 40, and in particular the holders 46, relative to each other. Tracking the position and orientation of the holders 46 allows the surgical robotic system 10 to determine the position and/or orientation of the instruments 50 and the camera 51 within a defined space, such as the surgical field.

[0058] The navigation system may also include an electromagnetic field generator 90, which is positioned beneath the patient. Electromagnetic field generator 90 and a plurality of reference sensors 91 may be connected to the tracking unit 170, which derives the location of each reference sensor 91 as well as the sensors 172. The position ofthe reference sensors is sent to the controller 21a, which uses data collected by sensors 172 to calculate a coordinate frame of reference for the robotic arms 40a-d. The reference sensors 91 may be disposed on or in the patient. These sensors 91 allow the tracking unit 170 to determine deformation of the tissue and the 3D model, which is then used in the navigation. In the lungs, tissue deformation could involve the movement and shape changes between inflated and deflated lungs. [0059] Additionally, a ventilator can be integrated to provide real-time feedback on the respiratory cycle, specifically indicating when the lungs are inflating or deflating. This feedback may be used for accurately modeling lung dynamics and compensating for tissue movement during navigation. By synchronizing with the ventilator data, the system 10 can enhance the precision of the 3D model, ensuring that navigation adjustments are made in response to the actual physiological changes in the lung tissue.

[0060] At step 510, the instruments 50 and the end effectors 49 are visualized on the preoperative plan and the 3D model in real-time, such that the movement of the instruments 50 is reflected on the preoperative plan/3D model. The 3D model includes segmented critical structures that are to be avoided during navigation of the instruments 50. In particular, the instruments 50 are navigated based on the trajectories and paths of the preoperative plan. The current or live position of the instruments 50 is provided using the navigation system described above at step 508. The current position may be displayed along with the planned trajectory and paths for the instruments 50. The user may then manually move the instruments 50 to match the current position from the navigation system to the planned paths. Live feedback may be provided through the surgeon console 30 via haptic, GUI directions, e.g., arrows, auditory alerts, and the like.

[0061] It will be understood that various modifications may be made to the embodiments disclosed herein. Therefore, the above description should not be construed as limiting, but merely as exemplifications of various embodiments. Those skilled in the art will envision other modifications within the scope and spirit of the claims appended thereto.

Claims

WHAT IS CLAIMED IS:

1. A method for preoperative planning and navigation in a surgical robotic system, comprising: obtaining a 3D model of an organ using at least one imaging modality; generating a preoperative plan from the 3D model, the preoperative plan including a planned position for a surgical robotic instrument; registering the 3D model and the preoperative plan with the organ; using a navigation system to track a position of a robotic arm and the surgical robotic instrument coupled thereto, the navigation system including tracking sensors disposed on the robotic arm and the surgical robotic instrument; registering the robotic arm and instruments with the organ and within the 3D model and the preoperative plan; displaying movements of the robotic arm and the surgical robotic instrument on a display screen showing the preoperative plan in real-time; and providing feedback through a visualized map that shows a current position of the surgical robotic instrument and provides directions for moving the surgical robotic instrument to attain the planned position.

2. The method of claim 1, wherein registering the 3D model and the preoperative plan includes registering the 3D model and the preoperative plan with an intraoperative camera video feed.

3. The method of claim 1, further comprising compensating for tissue movement and deformation using one or more deformation compensation algorithms, wherein the one or more deformation compensation algorithms uses data collected from one or more sensors associated with an anatomy of a patient.

4. The method of claim 3, further comprising providing deformation compensation for the 3D model using the one or more sensors.

5. The method of claim 1, wherein the 3D model is obtained using imaging modalities selected from the group consisting of computed tomography (CT), cone-beam computed tomography (CBCT), magnetic resonance imaging (MRI), fluoroscopic imaging, positron emission tomography (PET), and ultrasound imaging.

6. The method of claim 1, wherein the navigation system includes an external vision tracking unit having one or more cameras or infrared sensors configured to track the position of the robotic arm and the surgical robotic instrument.

7. The method of claim 1, wherein the navigation system includes an electromagnetic tracking unit that uses magnetic fields generated by an electromagnetic field generator to track the position of the robotic arm and the surgical robotic instrument.

8. The method of claim 1, further comprising using kinematic data obtained from the robotic arm and the surgical robotic instrument, the kinematic data including joint angles, torque, and position data.

9. The method of claim 1, wherein the preoperative plan and the 3D model are displayed on the display screen as an augmented reality overlay over an intraoperative camera video feed.

10. The method of claim 1, wherein the feedback includes haptic feedback, graphical user interface (GUI) directions, or auditory alerts.

11. The method of claim 1, wherein the preoperative plan includes segmented critical structures.