Tool-tissue Interaction Research Articles

Sclera Force Evaluation During Vitreoretinal Surgeries in Ex Vivo Porcine Eye Model.

Vitreoretinal surgery is among the most challenging microsurgical procedures as it requires precise tool manipulation in a constrained environment, while the tool-tissue interaction forces are at the human perception limits. While tool tip forces are certainly important, the scleral forces at the tool insertion ports are also important. Clinicians often rely on these forces to manipulate the eyeball position during surgery. Measuring sclera forces could enable valuable sensory input to avoid tissue damage, especially for a cooperatively controlled robotic assistant that otherwise removes the sensation of these familiar intraoperative forces. Previously, our group has measured sclera forces in phantom experiments. However, to the best of our knowledge, there are no published data measuring scleral forces in biological (ex-vivo/in-vivo) eye models. In this paper, we measured sclera forces in ex-vivo porcine eye model. A Fiber Bragg Grating (FBG) based force sensing instrument with a diameter of ~900 μm and a resolution of ~1 mN was used to measure the forces while the clinician-subject followed retinal vessels in manual and robot-assisted modes. Analysis of measured forces show that the average sclera force in manual mode was 133.74 mN while in robot-assisted mode was 146.03 mN.

Texture differentiation using audio signal analysis with robotic interventional instruments

Robotic minimally invasive surgery (RMIS) has played an important role in the last decades. In traditional surgery, surgeons rely on palpation using their hands. However, during RMIS, surgeons use the visual-haptics technique to compensate the missing sense of touch. Various sensors have been widely used to retrieve this natural sense, but there are still issues like integration, costs, sterilization and the small sensing area that prevent such approaches from being applied. A new method based on acoustic emission has been recently proposed for acquiring audio information from tool-tissue interaction during minimally invasive procedures that provide user guidance feedback. In this work the concept was adapted for acquiring audio information from a RMIS grasper and a first proof of concept is presented. Interactions of the grasper with various artificial and biological texture samples were recorded and analyzed using advanced signal processing and a clear correlation between audio spectral components and the tested texture were identified.

The Role of Tissue Slip Feedback in Robot-Assisted Surgery

Slip, or accidental loss, of grasped biological tissue can have negative consequences in all types of surgery (open, laparoscopic, robot-assisted). This work focuses on slip in robot-assisted surgery (RAS) with the goal of improving the quality of grasping and tool–tissue interactions. We report on a survey of 112 RAS surgeons, the results of which support the value of detecting and reducing slip in a variety of procedures. We conducted validation tests using a thermal slip sensor in a surgical grasper on tissue in vivo and ex vivo. The results of the survey and validation informed a user study to assess whether tissue slip feedback can improve performance and reduce effort in a phantom tissue manipulation task. With slip feedback, experienced subjects were significantly faster to complete the task, dropped tissue less (3% versus 38%), and experienced decreased mental demands and situational stress. These results provide motivation to further develop the sensor technology and incorporate it in robotic surgical equipment.

A sensorless force-feedback system for robot-assisted laparoscopic surgery

The existing surgical robots for laparoscopic surgery offer no or limited force feedback, and there are many problems for the traditional sensor-based solutions. This paper builds a teleoperation surgical system and validates the effectiveness of sensorless force feedback. The tool-tissue interaction force at the surgical grasper tip is estimated using the driving motor's current, and fed back to the master robot with a position-force bilateral control algorithm. The stiffness differentiation experiment and tumor detection experiment were conducted. In the stiffness differentiation experiment, 43 out of 45 pairs of ranking relationships were identified correctly, yielding a success rate of 96%. In the tumor detection experiment, 4 out of 5 participants identified the correct tumor location with force feedback, yielding a success rate of 80%. The proposed sensorless force-feedback system for robot-assisted laparoscopic surgery can help surgeons regain tactile information and distinguish between the healthy and cancerous tissue.

A sensorless force-feedback system for robot-assisted laparoscopic surgery

The existing surgical robots for laparoscopic surgery offer no or limited force feedback, and there are many problems for the traditional sensor-based solutions. This paper builds a teleoperation surgical system and validates the effectiveness of sensorless force feedback. The tool-tissue interaction force at the surgical grasper tip is estimated using the driving motor’s current, and fed back to the master robot with position-force bilateral control algorithm. The stiffness differentiation experiment and tumor detection experiment were conducted. In the stiffness differentiation experiment, 43 out of 45 pairs of ranking relationships were identified correctly, yielding a success rate of 96%. In the tumor detection experiment, 4 out of 5 participants identified the correct tumor location with force feedback, yielding a success rate of 80%. The proposed sensorless force-feedback system for robot-assisted laparoscopic surgery can help surgeons regain tactile information and distinguish between the healthy and cancerous tissue.

Development of a 1-DOF Force Sensor Prototype Incorporating Tapered Fiber Bragg Grating for Microsurgical Instruments

Decoupling between axial and transversal forces is an essential during tool-tissue interaction in many medicine surgeries; in particular where fine and precise manipulation is required to save the delicate tissues. One example of which is the vitreoretinal microsurgery (VRMS). When fiber Bragg grating based sensing technique is utilized, the cross-talk noise between the axial and transversal forces always show up severely due to its conventional wavelength shift method. To address the challenge, we have introduced theoretical method in which a combination of tapered FBG (TFBG) and bandwidth modulation method instead are used. Here in this paper, first phase of our ongoing progress to proof the concept and validate the simulation results is demonstrated experimentally. We have developed a prototype incorporated TFBG mimicking the structure of the ophthalmia's needle to measure temperature-insensitive 1-DOF axial forces. High speed plug and play (I-MON-256USB (Ibsen)) is used to monitor the reflection spectrum of the prototype sensor. An automated calibration system using LabVIEW with efficient algorithms have been developed to calculate and keep track the bandwidth variations as different values of axial forces applied. Calibration procedures are repeated three times to validate the consistency of the sensor response. Experimental results show that, the estimated force values of our prototype are consistent with their actual values with RMS error less than 0.356 N over the range (1N-10N), while temperature insensitivity is guaranteed.

Miniaturised optical fibre based palpations instrument for minimally invasive surgery

The lack of tactile and force perception during robot-assisted surgeries could lead to application of inadvertent forces resulting in tissue trauma and accidental tissue damage. In order to perform surgical procedures within tight spaces surrounded by sensitive soft tissues, surgeon’s ability to manoeuvre instruments with precision and control must be enhanced. Further, the tools with built-in tactile and force sensors enable surgeons to investigate surrounding tissues to determine surgical margins for dissection. This paper proposes a novel optical fibre based tactile probe capable of modelling tool tissue interactions to estimate tissue abnormalities. Tissue stiffness is estimated through an indentation technique. The proposed method allows rapid acquisition of tactile data as the instrument rolls over tissue surface in a near frictionless manner. The probe can concurrently measure both indentation force and indentation depth, which can be combined to develop a pseudo-colour stiffness image of the investigated tissue with abnormal regions clearly highlighted.

Proximally placed signal acquisition sensoric for robotic tissue tool interactions

Abstract Robotic surgeries are still limited with respect to the surgeon’s natural senses. The tactile sense is exceptional important in conventional clinical procedures. To identify critical structures inside the tissue, palpation is a commonly used technique in conventional open surgeries. The underlying organ or pathological structures conditions (healthy, abnormally hard or soft) can for example be localized and assessed through this process. Palpation needs a tactile sense; however, that is commonly not available or limited in robotic surgeries. The palpation need was already addressed by several research groups that integrated complex sensor-feedback-systems into prototype surgical instruments for robotic systems. We propose a new technique to acquire data of the tissue tool interaction of the surgical instruments. The structure borne transmission path is used to measure acoustic emission (AE) at the outpatient (proximal) end of the instruments with the help of different sensors attached to the surface of the surgical tool. Initial tests were performed using a microphone in combination with a stethoscope. This setup showed promising results and a more integrated prototype was subsequently designed. A piezoelectric charge accelerometer was used as vibration sensor and compared to a MEMS microphone. A signal acquisition system was developed to acquire signals from both sensors in parallel. The sensors were then attached onto the shaft of a daVinci Prograsp Forceps instrument. According to the surgery observation, a series of simulated experiments was conducted. The tip of the grasper was swiped manually over a human subject’s dorsal and palmar hand side, lateral side of neck and over the carotid artery. Additionally, contact with soft tissue and other instruments were evaluated since these are events of interest during surgery. Advanced signal processing techniques allowed the identification and characterization of significant events such as palpation dynamics, contact and pulsation. Signals acquired by the MEMS microphone showed the most promising results. This approach will now be used to build a prototype for further evaluation in a clinical setup. The paper presents the first results that show that this novel technique can provide valuable information about the tool-tissue interaction in robotic surgery that typically can only be obtained through advanced distal sensor systems or actual human touch.

Surgical Robot with Environment Reconstruction and Force Feedback.

We present a new surgical robot hardware-in-the-loop simulator, with 3D surgical field reconstruction in RGB-D sensor range, which allows tool-tissue interactions to be presented as haptic feedback and thus provides the situation awareness of unwanted collision. First, the point cloud of the complete surgical environment is constructed from multiple frames of sensor data to avoid the occlusion issue. Then the user selects a region of interest where the robot's tool must avoid (also called forbidden region). The real-time haptic force rendering algorithm computes the interaction force which is then communicated to a haptic device at 1 kHz, to assist the surgeon to perform safe actions. The robot used is a RAVEN II system, RGB-D sensor is used to scan the environment, and two Omni haptic devices provide the 3-DoF haptic force. A registration pipeline is presented to complete the surgical environment point cloud mapping in preoperative surgery planning phase, which improves quality of haptic rendering in the presence of occlusion. Furthermore, we propose a feasible and fast algorithm which extends the existing work on the proxy-based method for haptic rendering between a Haptic Interaction Point (HIP) and a point cloud. The proposed methodology has the potential of improving the safety of surgical robots.

Development of a 2-DOF Sensorized Surgical Grasper for Grasping and Axial Force Measurements

Minimally invasive surgery (MIS) has been limited from its inception by insufficient haptic feedback to surgeons. To address this, various force sensing methods have been developed that can provide information about tool–tissue interaction forces. However, the results have been unreliable in most of these studies, since there are many sources of error and uncertainty in the force acquisition method. Furthermore, none of the force sensing devices described in the literature can be fully cleaned or sterilized for use in surgery. To address this, a sterilizable needle-driver type grasper is presented in this paper that incorporates fiber Bragg gratings to measure axial and grasping forces. The results of its performance evaluation show that the two-degrees of freedom grasper is capable of measuring grasping and axial forces with an accuracy of 0.27 and 0.3 N, respectively. Integration of this device into a needle driver instrument will result in a sterilizable instrument capable of measuring tool–tissue interaction forces during MIS.

Forces of Tool-Tissue Interaction to Assess Surgical Skill Level

Importance The application of optimal forces between surgical instruments and tissue is fundamental to surgical performance and learning. To date, this force has not been measured clinically during the performance of microsurgery. Objectives To establish a normative catalog of force profiles during the performance of surgery, to compare force variables among surgeons with different skill levels, and to evaluate whether such a force-based metric determines or differentiates skill level. Design, Setting, and Participants Through installation of strain gauge sensors, a force-sensing bipolar forceps was developed, and force data were obtained from predetermined surgical tasks at the Foothills Medical Centre, University of Calgary, a tertiary care center that serves Southern Alberta, Canada. Sixteen neurosurgeons (3 groups: novice, intermediate, and experienced) performed surgery on 26 neurosurgical patients with various conditions. Normative baseline force ranges were obtained using the force profiles (mean and maximum forces and force variability) from the experienced surgeons. Standardized force profiles and force errors (high force error [HFE], low force error [LFE], and force variability error [FVE]) were analyzed and compared among surgeons with different skill levels. Main Outcomes and Measures Each trial of the forceps use was termed successful or unsuccessful . The force profiles and force errors were analyzed and compared. Results This study included 26 patients (10 [38%] male and 16 [62%] female; mean [SD] age, 43 [15] years) undergoing neurosurgery by 16 surgeons (6 in the novice group, 5 in the intermediate group, and 5 in the experienced group). Unsuccessful trial–incomplete significantly correlated with LFE and FVE, and unsuccessful trial–bleeding correlated with HFE and FVE. The force strengths exerted by novice surgeons were significantly higher than those of experienced surgeons (0.74 vs 0.00; P P Conclusions and Relevance Force-sensing bipolar forceps and force analysis may help distinguish surgeon skill level, which is particularly important as surgical education shifts to a competency-based paradigm.

Safe Tissue Manipulation in Retinal Microsurgery via Motorized Instruments with Force Sensing.

Retinal microsurgery involves careful manipulation of delicate tissues by applying very small amount of forces most of which lie below the tactile sensory threshold of the surgeons. Membrane peeling is a common task in this domain, where application of excessive peeling forces can easily lead to serious complications, hence needs to be avoided. To quantify tool-tissue interaction forces during retinal microsurgery, various force-sensing tools were developed based on fiber Bragg grating sensors, yet the most beneficial way of using the acquired force information is currently unknown. In this study, using a motorized force-sensing micro-forceps tool, we develop an assistive method that enhances safety during membrane peeling by automatically opening the forceps and releasing the tissue based on the detected peeling forces. Through peeling experiments using bandages, we demonstrate that our method can effectively maintain the peeling force at a safe level even in case of non-homogeneous adhesion properties of the membrane.

Towards Robot-Assisted Retinal Vein Cannulation: A Motorized Force-Sensing Microneedle Integrated with a Handheld Micromanipulator †.

Retinal vein cannulation is a technically demanding surgical procedure where therapeutic agents are injected into the retinal veins to treat occlusions. The clinical feasibility of this approach has been largely limited by the technical challenges associated with performing the procedure. Among the challenges to successful vein cannulation are identifying the moment of venous puncture, achieving cannulation of the micro-vessel, and maintaining cannulation throughout drug delivery. Recent advances in medical robotics and sensing of tool-tissue interaction forces have the potential to address each of these challenges as well as to prevent tissue trauma, minimize complications, diminish surgeon effort, and ultimately promote successful retinal vein cannulation. In this paper, we develop an assistive system combining a handheld micromanipulator, called “Micron”, with a force-sensing microneedle. Using this system, we examine two distinct methods of precisely detecting the instant of venous puncture. This is based on measured tool-tissue interaction forces and also the tracked position of the needle tip. In addition to the existing tremor canceling function of Micron, a new control method is implemented to actively compensate unintended movements of the operator, and to keep the cannulation device securely inside the vein following cannulation. To demonstrate the capabilities and performance of our uniquely upgraded system, we present a multi-user artificial phantom study with subjects from three different surgical skill levels. Results show that our puncture detection algorithm, when combined with the active positive holding feature enables sustained cannulation which is most evident in smaller veins. Notable is that the active holding function significantly attenuates tool motion in the vein, thereby reduces the trauma during cannulation.

Nonparametric bootstrap technique for calibrating surgical SmartForceps: theory and application

ABSTRACTKnowledge of forces, exerted on the brain tissue during the performance of neurosurgical tasks, is critical for quality assurance, case rehearsal, and training purposes. Quantifying the interaction forces has been made possible by developing SmartForceps, a bipolar forceps retrofitted by a set of strain gauges. The forces are estimated using voltages read from strain gauges. We therefore need to quantify the force-voltage relationship to estimate the interaction forces during microsurgery. This problem has been addressed in the literature by following the physical and deterministic properties of the force-sensing strain gauges without obtaining the precision associated with each estimate. In this paper, we employ a probabilistic methodology by using a nonparametric Bootstrap approach to obtain both point and interval estimates of the applied forces at the tool tips, while the precision associated with each estimate is provided. To show proof-of-concept, the Bootstrap technique is employed to estimate unknown forces, and construct necessary confidence intervals using observed voltages in data sets that are measured from the performance of surgical tasks on a cadaveric brain. Results indicate that the Bootstrap technique is capable of estimating tool-tissue interaction forces with acceptable level of accuracy compared to the linear regression technique under the normality assumption.

Design and Evaluation of a Sterilizable Force Sensing Instrument for Minimally Invasive Surgery

Although the inability to feel tool-tissue interaction forces during minimally invasive surgery (MIS) has been recognized as a significant difficulty encountered by surgeons during these procedures, existing sensorized technologies have not yet been approved for use in humans. The challenges of properly cleaning and sterilizing these instruments prevent them from being operating-room ready. The focus of this paper was to develop a sterilizable instrument that uses strain gauges, the most common force-sensing method, to measure the tool-tissue interaction forces in three degrees of freedom (DOFs) during MIS. A series of experiments is conducted to identify cables and connectors, as well as strain gauge adhesives and coatings to allow the instruments to successfully withstand autoclave sterilization. This resulted in the construction of a final prototype capable of measuring forces in three DOFs, which was able to withstand six sterilization cycles with good sensing performance (0.15–1.70 N accuracy, 0.02–1.20 N repeatability, and 0.11–1.05 N hysteresis depending on the measurement direction). This paper demonstrates that autoclave sterilization is possible for a strain-gauge instrumented device and can lead to more advances in the development of sensorized instruments for surgery and therapy.

Interactive soft tissue modelling for virtual reality surgery simulation and planning

While most existing virtual reality-based surgical simulators in the literature use linear deformation models, soft-tissues exhibit geometric and material nonlinearities that should be taken into account for realistic modelling of the deformations. In this paper, an interactive soft tissue model (ISTM) which enables flexible, accurate and robust simulation of surgical interventions on virtual patients is proposed. In ISTM, simulating the tool-tissue interactions using nonlinear dynamic analysis is formulated within a total Lagrangian framework, and the energy function is modified by adding a term in order to achieve material incompressibility. The simulation results show that ISTM increases the stability and eliminates integration errors in the dynamic solution, decreases calculation costs by a factor of 5-7, and leads to very stable and sufficiently accurate results. From the simulation results it can be concluded that the proposed model can successfully create acceptable soft tissue models and generate realistically visual effects of surgical simulation.

Interactive soft tissue modelling for virtual reality surgery simulation and planning

While most existing virtual reality-based surgical simulators in the literature use linear deformation models, soft-tissues exhibit geometric and material nonlinearities that should be taken into account for realistic modelling of the deformations. In this paper, an interactive soft tissue model (ISTM) which enables flexible, accurate and robust simulation of surgical interventions on virtual patients is proposed. In ISTM, simulating the tool-tissue interactions using nonlinear dynamic analysis is formulated within a total Lagrangian framework, and the energy function is modified by adding a term in order to achieve material incompressibility. The simulation results show that ISTM increases the stability and eliminates integration errors in the dynamic solution, decreases calculation costs by a factor of 5-7, and leads to very stable and sufficiently accurate results. From the simulation results it can be concluded that the proposed model can successfully create acceptable soft tissue models and generate realistically visual effects of surgical simulation.

A Force-Sensing Bipolar Forceps to Quantify Tool–Tissue Interaction Forces in Microsurgery

The ability to exert an appropriate amount of force on brain tissue during surgery is an important component of instrument handling. It allows surgeons to achieve the surgical objective effectively while maintaining a safe level of force in tool–tissue interaction. At the present time, this knowledge, and hence skill, is acquired through experience and is qualitatively conveyed from an expert surgeon to trainees. These forces can be assessed quantitatively by retrofitting surgical tools with sensors, thus providing a mechanism for improved performance and safety of surgery, and enhanced surgical training. This paper presents the development of a force-sensing bipolar forceps, with installation of a sensory system, that is able to measure and record interaction forces between the forceps tips and brain tissue in real time. This research is an extension of a previous research where a bipolar forceps was instrumented to measure dissection and coagulation forces applied in a single direction. Here, a planar forceps with two sets of strain gauges in two orthogonal directions was developed to enable measuring the forces with a higher accuracy. Implementation of two strain gauges allowed compensation of strain values due to deformations of the forceps in other directions (axial stiffening) and provided more accurate forces during microsurgery. An experienced neurosurgeon performed five neurosurgical tasks using the axial setup and repeated the same tasks using the planar device. The experiments were performed on cadaveric brains. Both setups were shown to be capable of measuring real-time interaction forces. Comparing the two setups, under the same experimental condition, indicated that the peak and mean forces quantified by planar forceps were at least 7% and 10% less than those of axial tool, respectively; therefore, utilizing readings of all strain gauges in planar forceps provides more accurate values of both peak and mean forces than axial forceps. Cross-correlation analysis between the two force signals obtained, one from each cadaveric practice, showed a high similarity between the two force signals.

Estimating Tool-Tissue Forces Using a 3-Degree-of-Freedom Robotic Surgical Tool.

Robot-assisted minimally invasive surgery (MIS) has gained popularity due to its high dexterity and reduced invasiveness to the patient; however, due to the loss of direct touch of the surgical site, surgeons may be prone to exert larger forces and cause tissue damage. To quantify tool-tissue interaction forces, researchers have tried to attach different kinds of sensors on the surgical tools. This sensor attachment generally makes the tools bulky and/or unduly expensive and may hinder the normal function of the tools; it is also unlikely that these sensors can survive harsh sterilization processes. This paper investigates an alternative method by estimating tool-tissue interaction forces using driving motors' current, and validates this sensorless force estimation method on a 3-degree-of-freedom (DOF) robotic surgical grasper prototype. The results show that the performance of this method is acceptable with regard to latency and accuracy. With this tool-tissue interaction force estimation method, it is possible to implement force feedback on existing robotic surgical systems without any sensors. This may allow a haptic surgical robot which is compatible with existing sterilization methods and surgical procedures, so that the surgeon can obtain tool-tissue interaction forces in real time, thereby increasing surgical efficiency and safety.

Vision-based deformation recovery for intraoperative force estimation of tool–tissue interaction for neurosurgery

PurposeIn microsurgery, accurate recovery of the deformation of the surgical environment is important for mitigating the risk of inadvertent tissue damage and avoiding instrument maneuvers that may cause injury. The analysis of intraoperative microscopic data can allow the estimation of tissue deformation and provide to the surgeon useful feedback on the instrument forces exerted on the tissue. In practice, vision-based recovery of tissue deformation during tool–tissue interaction can be challenging due to tissue elasticity and unpredictable motion.MethodsThe aim of this work is to propose an approach for deformation recovery based on quasi-dense 3D stereo reconstruction. The proposed framework incorporates a new stereo correspondence method for estimating the underlying 3D structure. Probabilistic tracking and surface mapping are used to estimate 3D point correspondences across time and recover localized tissue deformations in the surgical site.ResultsWe demonstrate the application of this method to estimating forces exerted on tissue surfaces. A clinically relevant experimental setup was used to validate the proposed framework on phantom data. The quantitative and qualitative performance evaluation results show that the proposed 3D stereo reconstruction and deformation recovery methods achieve submillimeter accuracy. The force–displacement model also provides accurate estimates of the exerted forces.ConclusionsA novel approach for tissue deformation recovery has been proposed based on reliable quasi-dense stereo correspondences. The proposed framework does not rely on additional equipment, allowing seamless integration with the existing surgical workflow. The performance evaluation analysis shows the potential clinical value of the technique.