Micro-force guided cooperative control for surgical manipulation of delicate tissue

A method and system for micro-force guided cooperative control that assists the operator in manipulating tissue in the direction of least resistance. A tool holder receives a surgical tool adapted to be held by a robot and a surgeon. A first sensor measures interaction forces between a tip of the surgical tool and tissue of a region of interest. A second sensor measures interaction forces between the surgeon and a handle to the surgical tool. A data processor is configured to perform an algorithm to actively guide the surgical tool by creating a bias towards a path of least resistance and limit directional tool forces of the surgical tool as a function of handle input forces and tip forces. This function offers assistance to challenging retinal membrane peeling procedures that require a surgeon to delicately delaminate fragile tissue that is susceptible to hemorrhage and tearing due to undesirable forces.

FIELD OF THE INVENTION

The present invention pertains to a method and system for cooperative control for surgical tools. More particularly, the present invention pertains to a method and system for micro-guided cooperative control fir surgical manipulation of delicate tissue.

BACKGROUND OF THE INVENTION

Retinal microsurgery is one of the most challenging set of surgical tasks due to human sensory-motor limitations, the need for sophisticated and miniature instrumentation, and the inherent difficulty of performing micron scale motor tasks in a small and fragile environment. In retinal surgery, surgeons are required to perform micron scale maneuvers while safely applying forces to the retinal tissue that are below sensory perception. Surgical performance is further challenged by imprecise instruments, physiological hand tremor, poor visualization, lack of accessibility to some structures, patient movement, and fatigue from prolonged operations. The surgical instruments in retinal surgery are characterized by long, thin shafts (typically 0.5 mm to 0.7 mm in diameter) that are inserted through the sclera (the visible white wall of the eye). The forces exerted by these tools are often far below human sensory thresholds.

The surgeon therefore must rely on visual cues to avoid exerting excessive forces on the retina. These visual cues are a direct result of the forces applied to the tissue, and a trained surgeon reacts to them by retracting the tool and re-grasping the tissue in search of an alternate approach. This interrupts the peeling process, and requires the surgeon to carefully re-approach the target. Sensing the imperceptible micro-force cues and preemptively reacting using robotic manipulators has the potential to allow for a continuous peel, increasing task completion time and minimizing the risk of complications. All of these factors contribute to surgical errors and complications that may lead to vision loss.

An example procedure is the peeling of the epiretinal membrane, where a thin membrane is carefully delaminated off the surface of the retina using delicate (20-25 Ga) surgical instruments. The forces exerted on retinal tissue are often far below human sensory thresholds. In current practice, surgeons have only visual cues to rely on to avoid exerting excessive farces, which have been observed to lead to retinal damage and hemorrhage with associated risk of vision loss.

Although robotic assistants such as the DAVINCI™ surgical robotic system have been widely deployed for laparoscopic surgery, systems targeted at microsurgery are still at the research stage. Microsurgical systems include teleoperation systems, freehand active tremor-cancellation systems, and cooperatively controlled hand-over-hand systems, such as the Johns Hopkins “Steady Hand” robots. In steady-hand control, the surgeon and robot both hold the surgical tool; the robot senses forces exerted by the surgeon on the tool handle, and moves to comply, filtering out any tremor. For retinal microsurgery, the tools typically pivot at the sclera insertion point, unless the surgeon wants to move the eyeball. This pivot point may either he enforced by a mechanically constrained remote center-of-motion or software. Interactions between the tool shaft and sclera complicate both the control of the robot and measurement of tool-to-retina forces.

To measure the tool-to-retina forces, an extremely sensitive (0.25 mN resolution) force sensor has been used, which is mounted on the tool shaft, distal to the sclera insertion point. The three sensor allows for measurement of the tool tissue forces while diminishing interference from tool-sclera forces.

In addition, a first-generation steady-hand robot has been specifically designed for vitreoretinal surgery. While this steady-hand robot was successfully used in ex-vivo robot assisted vessel cannulation experiments, it was found to be ergonomically limiting. For example, the first generation steady-hand robot had only a ±30% tool rotation limit. To further expand the tool rotation range, a second generation steady-hand robot has been developed which has increased this range to ±60%. The second generation steady-hand robot utilizes a parallel six-bar mechanism that mechanically provides isocentric motion, without introducing large concurrent joint velocities in the Cartesian stages, which occurred with the first generation steady-hand robots.

The second generation steady-hand robot incorporates both a significantly improved manipulator and an integrated microforce sensing tool, which provides for improved vitreoretinal surgery. However, because of the sensitivity of vitreoretinal surgery, there is still a need in the art for improved control of the tool, to avoid unnecessary complications. For example, complications in vitreoretinal surgery may result from excess and/or incorrect application of forces to ocular tissue. Current practice requires the surgeon to keep operative forces low and safe through slow and steady maneuvering. The surgeon must also rely solely on visual feedback that complicates the problem, as it takes time to detect, assess and then react to the faint cues; a task especially difficult for novice surgeons.

Accordingly, there is a need in the art for an improved control method for surgical tools used in vitreoretinal surgery and the like.

SUMMARY

According to a first aspect of the present invention, a method of cooperative control of a surgical tool, comprising providing a surgical tool to be manipulated during an operation, the surgical tool adapted to be held by a robot and a surgeon, measuring interaction forces between a tip of the surgical tool and tissue of a region of interest, measuring interaction forces between the surgeon and a handle to the surgical tool, actively guiding the surgical tool by creating a bias towards a path of least resistance, and limiting directional tool forces of the surgical tool as a function of handle input forces and tip forces.

According to a second aspect of the present invention, a system for cooperative control of a surgical tool comprises a tool holder for receiving a surgical tool adapted to be held by a robot and a surgeon, a first sensor for measuring interaction forces between a tip of the surgical tool and tissue of a region of interest, a second sensor for measuring interaction forces between the surgeon and a handle to the surgical tool, and a data processor is configured to perform an algorithm to actively guide the surgical tool by creating a bias towards a path of least resistance and limit directional tool forces of the surgical tool as a function of handle input forces and tip forces.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention pertains to a novel method and system for micro-force guided cooperative control that assists the operator in manipulating tissue in the direction of least resistance. This function has the potential to aid in challenging retinal membrane peeling procedures that require a surgeon to delicately delaminate fragile tissue that is susceptible to hemorrhage and tearing due to undesirable forces. It can also be useful in other microsurgical tasks such as controlled tearing of tissue in capsularhexis, blunt tissue dissection, or other delicate surgical tasks.

An exemplary embodiment of the invention provides for use of the system and method in cooperatively controlled hand-over-hand systems, such as the robotic assisted surgical system described in “Development and Application of a New Steady-Hand Manipulator for Retinal Surgery”, Mitchell et al., IEEE ICRA, pp. 623-629 (2007), and in “New Steady-Hand Eye Robot with Microforce Sensing for Vitreoretinal Surgery Research”, A. Uneri, M. Balicki, James Handa, Peter Gehlbach, R. Taylor, and I. Iordachita, International Conference on Biomedical Robotics and Biomechatronics (BIOROB), Tokyo, Sep. 26-29, 2010, pp. 814-819, the entire contents of which are incorporated by reference herein. In steady-hand control, the surgeon and robot both hold the surgical tool. The robot senses forces exerted by the surgeon on the tool handle, and moves to comply, filtering out any tremor. While a specific cooperative control system is described in connection with the above publication, it should be understood that the system and method of the present invention may also be applicable to other cooperatively controlled systems.

With reference toFIGS. 1 and 2, a first illustrative embodiment of a robotic-assisted surgical system to be used in connection with the present invention is shown. The system10may be used in micro-surgery of organs, for example, hollow organs, such as the human eye, but other applications are possible.

As shown inFIGS. 1 and 2, the system10includes a tool holder14for receiving as surgical tool16to be held both a robot12and a surgeon17. The tool holder14facilitates the attachment of a variety of surgical tools required during microsurgical procedures, including but not limited to, forceps, needle holder, and scissors. Preferably, the surgeon17holds the surgical tool16at a tool handle18, and cooperatively directs the surgical tool16with the robot12to perform surgery of a region of interest with a tool tip20. In addition, a force/torque sensor24may be mounted at the tool holder16, which senses forces exerted by the surgeon on the tool, liar use as command inputs to the robot. A number of other sensors known in the art may be used to detect the force between the tool handle14and the surgeon17. Examples include micro-switches, capacitive sensors, optical sensors, force sensors, or pressure sensors on the tool handle14.

Preferably, a custom mechanical RCM is provided, which improves the stiffness and precision of the robot stages. The RCM mechanism improves the general stability of the system by reducing range of motion and velocities in the Cartesian stages when operating in virtual RCM mode, which constrains the tool axis to always intersect the sclerotomy opening on the eye.

With reference toFIG. 3, an exemplary surgical tool30to be used in connection with the system and method of the present invention is illustrated. In particular, surgical tool30may be specifically designed for use in a cooperative manipulation, such as a system describe above, but may be used in a tele-operative robot as an end effector of a surgical robot. In addition, the surgical tool30may be specifically designed for operation on the human eye E.

With continued reference toFIG. 3, the surgical tool30includes a tool shaft32with a hooked end34. The surgical tool30is manufactured with a force sensor, preferably integrated fiber Bragg grating (FGB) sensors. FBGs are robust optical sensors capable of detecting changes in strain, without interference from electrostatic, electromagnetic or radio frequency sources. Preferably, a number of optical fibers36are placed along the tool shaft32, which allows measuring of the bending of the tool and for calculation of the three in the transverse plane (along Fxand Fy) with a sensitivity of 0.25 mN. Accordingly, a sensitive measurement of the forces between the tool and tip can be obtained.

For vitreoretinal microsurgical applications, a three sensor should be chosen that allows for sub-mN accuracy, requiring the sensing of forces that are routinely below 7.5 mN. As such, a very small instrument size is necessary to be inserted through a 25 Ga sclerotomy opening and the force sensor should be designed to be capable of measurements at the instrument's tip, below the sclera.

With reference back toFIGS. 1 and 2, the system10includes a processor26and a memory device28. The memory device28may include one or more computer readable storage media, as well as machine readable instructions for performing cooperative control of the robot. According to features of the claimed invention, depending upon the forces detected which are sent to the processor26(tool-hand forces and/or tool-tip forces), robot velocity is limited by a controller so as to provide a haptic feedback. In particular, a force scaling cooperative control method is used to generate robot response based on the scaled difference between tool-tissue and tool-hand forces.

As discussed above, complications in vitreoretinal surgery may result from excess and/or incorrect application of forces to ocular tissue. As shown inFIG. 4, the surgical tool30is used to peel the membrane42according to the trajectory shown therein, without generating a tear40of the membrane42.FIG. 4depicts a peeling process, with associated forces ft(tool-tip forces) and fh(user-tool forces). Current practice requires the surgeon to keep operative forces low and safe through slow and steady maneuvering. The surgeon must also rely solely on visual feedback that complicates the problem, as it takes time to detect, assess and the react to the faint cues; a task especially difficult for novice inventors.

According to the features of the present invention, the cooperative control method and system of the present invention uses real-time information to gently guide the operator towards lower forces in a peeling task. The method can be analyzed in two main components, as will be described below.

Safety Limits: The first layer of control enforces a global limit on the forces applied to the tissue at the robot tool tip. Setting a maximum force fmax, the limiting force fminon each axis would conventionally be defined as
flim=fmaxri, rt=|ft|/∥ft∥

However, this approach has the disadvantage of halting all motion when the tip force reaches the force limit, i.e., the operator has to back up the robot in order to apply a force in other directions. Distributing the limit with respect to the handle input forces
flim=fmaxrh, rh=|fh|/∥fh∥
gives more freedom to the operator, allowing him/her to explore alternative directions (i.e., search for maneuvers that would generate lower tip forces) even when ftis at its limit.

Considering the governing law,
{dot over (x)}=kpfh
where {dot over (x)}=velocity.
We apply the limit as follows:

x.lim=x.⁡(flim-|ft|llim)
Thus, Cartesian velocity is proportionally scaled with respect to current tip force, where a virtual spring of length llimis used to ensure stability at the limit boundary.

Active Guidance: The second layer is to guide the operator in order to prevent reaching the limit in the first place. This is achieved by actively biasing, the tool tip motion towards the direction of lower resistance. The ratio rtis used to update the operator input in the following fashion:
{dot over (x)}min=kp(1−rtsmin)fh
where sminis the sensitivity of minimization that sets the ratio of the handle force to be locally minimized. Note that smin=0% implies that the operator is not able to override the guided behavior.

Finally, for extra safety, if either sensor is detected as being engaged, e.g., the operator is not applying, any force at the handle (<0.1 N), the robot minimizes ftby “backing up”.
{dot over (x)}=kpft

With reference toFIG. 5, a state diagram presents a use-case from the perspective of the user (surgeon), i.e., how the control algorithm behaves and which state is dominant under which conditions. At100, the robot is at rest. The user then engages the handle at102. At104, the robot is cooperatively controlled. At106, the robot engages tissue. At108, the robot is actively guided creating a bias towards the path of least resistance. The robot continues this way as the tool tip forces approach the safely limits (110). At112, the robot is halted in the direction of resistance.

At this point, the user can engage in one of two tasks. First, the user can change direction, which redistributes the direction tip force limits (114). This will then direct the program back, to actively guiding the robot by creating a bias towards the path of least resistance. Second, the user can disengage the handle (116). The robot may then back up to reduce resistance, at118. At120, the robot disengages the tissue.

With reference toFIG. 6, a simplified control diagram shows the use of the handle and tip forces simultaneously to (1) actively guide the user such that the force exerted on the tissue are minimized; and (2) limit the magnitude of the forces exerted on the tissue, while allowing the user to control the geometric distribution of this limit. As shown inFIG. 6, the data (such as robot velocity or force information) is fed into the two control blocks140and142, in order to modify the control algorithm. That is, the data is sensed and used to manipulate the runtime parameters of the control algorithm, as described by the equations. According to the features of the present invention, the control method and system uses the surgeon's intention (handle forces) and tissue behavior (tip forces) in making a more informed decision.

EXAMPLE

The following Example has been included to provide guidance to one of ordinary skill in the art for practicing representative embodiments of the presently disclosed subject matter. In light of the present disclosure and the general level of skill in the art, those of skill can appreciate that the following Example is intended to be exemplary only and that numerous changes, modifications, and alterations can be employed without departing from the scope of the presently disclosed subject matter. The following Example is offered by way of illustration and not by way of limitation.

A series of experiments were performed on the inner shell membrane of raw chicken eggs with the aim of identifying and controlling the forces associated with peeling operations. The first set of experiments was carried out to assess the capability of the system in tissue resistance forces through controlled motion and high resolution sensing. Attaching the surgical hook to the sample tissue, a desired constant force was set and the translation was measured with the corrected displacement of the tool tip. The applied force was increased by 1 mN with a 10 s delay between each increment. The system was first tested against a spring, or known stiffness, seeFIG. 7(a), where a 2.8% error was observed as compared to the calibrated value.FIG. 7(b)shows a sample force profile for the inner shell membrane. For these trials, the surgical hook was first attached to the intact tissue and force was incrementally applied until failure. The membranes exhibit an average tearing force of 10 mN, after which, continuation of the tear is accomplished with lesser forces (˜6 mN).

The characteristic curve obtained reveals a similar pattern to those seen in fibrous tissue tearing. The toe region of the curve, the shape of which is due to recruitment of collagen fibers, is a “safe region” from a surgical point of view and is followed by a predictable linear response. Yielding occurs as bonds begin to break, resulting in a sudden drop on resistive forces due to complete failure. In the surgical setting, this marks the beginning of a membrane being peeled.

In a second set of experiments, the control algorithm was tested. A global limit of 7 mN was set, with a in sensitivity of 90%. An audio cue was also used to inform the operator when the limit was reached. The algorithm was first tested by stripping a piece of tape from a surface. This work revealed the direction of minimum resistance for this phantom. The operator was naturally guided away from the centerline of the tape, following a gradient of force towards a local minimum resistance. Due to mechanical advantage, this corresponded to peeling at ˜45° (FIG. 8(a)).

Repeating the experiments on the egg membrane, the egg tended to peel in circular trajectories (seeFIG. 8(b)). This behavior is consistent with the above trials with the added factor of continuously changing tear direction, i.e., tear follows the ˜45° direction of force application. Qualitatively, the algorithm was observed to magnify the perception of tip forces lateral to the operator's desired motion.

Upon reaching the force limit, the operator explored around the boundary in search of points of lower resistance that would enable continuation of peel. This was achieved smoothly without requiring the operator to back up, as the limits of axes were redistributed based on operator's application of handle force.

Accordingly, the present invention advantageously provides for a novel method and system for micro-force guided cooperative control that assists the operator in manipulating tissue in the direction of least resistance, particularly useful in helping surgeons during retinal membrane peeling procedures that require a surgeon to delicately delaminate fragile tissue that is susceptible to hemorrhage and tearing due to undesirable forces. The system and method directs the surgeon to a path of least resistance, instead of requiring the surgeon to back up.