Scleral Forces Research Articles

Cooperative vs. Teleoperation Control of the Steady Hand Eye Robot with Adaptive Sclera Force Control: A Comparative Study.

A surgeon's physiological hand tremor can significantly impact the outcome of delicate and precise retinal surgery, such as retinal vein cannulation (RVC) and epiretinal membrane peeling. Robot-assisted eye surgery technology provides ophthalmologists with advanced capabilities such as hand tremor cancellation, hand motion scaling, and safety constraints that enable them to perform these otherwise challenging and high-risk surgeries with high precision and safety. Steady-Hand Eye Robot (SHER) with cooperative control mode can filter out surgeon's hand tremor, yet another important safety feature, that is, minimizing the contact force between the surgical instrument and sclera surface for avoiding tissue damage cannot be met in this control mode. Also, other capabilities, such as hand motion scaling and haptic feedback, require a teleoperation control framework. In this work, for the first time, we implemented a teleoperation control mode incorporated with an adaptive sclera force control algorithm using a PHANTOM Omni haptic device and a force-sensing surgical instrument equipped with Fiber Bragg Grating (FBG) sensors attached to the SHER 2.1 end-effector. This adaptive sclera force control algorithm allows the robot to dynamically minimize the tool-sclera contact force. Moreover, for the first time, we compared the performance of the proposed adaptive teleoperation mode with the cooperative mode by conducting a vessel-following experiment inside an eye phantom under a microscope.

Autonomous Needle Navigation in Subretinal Injections via iOCT.

Subretinal injection is an effective method for direct delivery of therapeutic agents to treat prevalent subretinal diseases. Among the challenges for surgeons are physiological hand tremor, difficulty resolving single-micron scale depth perception, and lack of tactile feedback. The recent introduction of intraoperative Optical Coherence Tomography (iOCT) enables precise depth information during subretinal surgery. However, even when relying on iOCT, achieving the required micron-scale precision remains a significant surgical challenge. This work presents a robot-assisted workflow for high-precision autonomous needle navigation for subretinal injection. The workflow includes online registration between robot and iOCT coordinates; tool-tip localization in iOCT coordinates using a Convolutional Neural Network (CNN); and tool-tip planning and tracking system using real-time Model Predictive Control (MPC). The proposed workflow is validated using a silicone eye phantom and ex vivo porcine eyes. The experimental results demonstrate that the mean error to reach the user-defined target and the mean procedure duration are within an acceptable precision range. The proposed workflow achieves a 100% success rate for subretinal injection, while maintaining scleral forces at the scleral insertion point below 15mN throughout the navigation procedures.

Autonomous Needle Navigation in Retinal Microsurgery: Evaluation in ex vivo Porcine Eyes.

Important challenges in retinal microsurgery include prolonged operating time, inadequate force feedback, and poor depth perception due to a constrained top-down view of the surgery. The introduction of robot-assisted technology could potentially deal with such challenges and improve the surgeon's performance. Motivated by such challenges, this work develops a strategy for autonomous needle navigation in retinal microsurgery aiming to achieve precise manipulation, reduced end-to-end surgery time, and enhanced safety. This is accomplished through real-time geometry estimation and chance-constrained Model Predictive Control (MPC) resulting in high positional accuracy while keeping scleral forces within a safe level. The robotic system is validated using both open-sky and intact (with lens and partial vitreous removal) ex vivo porcine eyes. The experimental results demonstrate that the generation of safe control trajectories is robust to small motions associated with head drift. The mean navigation time and scleral force for MPC navigation experiments are 7.208 s and 11.97 mN, which can be considered efficient and well within acceptable safe limits. The resulting mean errors along lateral directions of the retina are below 0.06 mm, which is below the typical hand tremor amplitude in retinal microsurgery.

Force-based Control for Safe Robot-assisted Retinal Interventions: In Vivo Evaluation in Animal Studies.

In recent years, robotic assistance in vitreoretinal surgery has moved from a benchtop environment to the operating rooms. Emerging robotic systems improve tool manoeuvrability and provide precise tool motions in a constrained intraocular environment and reduce/remove hand tremor. However, often due to their stiff and bulky mechanical structure, they diminish the perception of tool-to-sclera (scleral) forces, on which the surgeon relies, for eyeball manipulation. In this paper we measure these scleral forces and actively control the robot to keep them under a predefined threshold. Scleral forces are measured using a Fiber Bragg Grating (FBG) based force sensing instrument in an in vivo rabbit eye model in manual, cooperative robotic assistance with no scleral force control (NC), adaptive scleral force norm control (ANC) and adaptive scleral force component control (ACC) methods. To the best of our knowledge, this is the first time that the scleral forces are measured in an in vivo eye model during robot assisted vitreoretinal procedures. An experienced retinal surgeon repeated an intraocular tool manipulation (ITM) task 10 times in four in vivo rabbit eyes and a phantom eyeball, for a total of 50 repetitions in each control mode. Statistical analysis shows that the ANC and ACC control schemes restrict the duration of the undesired scleral forces to 4.41% and 14.53% as compared to 43.30% and 35.28% in manual and NC cases, respectively during the in vivo studies. These results show that the active robot control schemes can maintain applied scleral forces below a desired threshold during robot-assisted vitreoretinal surgery. The scleral forces measurements in this study may enable a better understanding of tool-to-sclera interactions during vitreoretinal surgery and the proposed control strategies could be extended to other microsurgery and robot-assisted interventions.

Stochastic Force-based Insertion Depth and Tip Position Estimations of Flexible FBG-Equipped Instruments in Robotic Retinal Surgery.

Vitreoretinal surgery is among the most delicate surgical tasks during which surgeon hand tremor may severely attenuate surgeon performance. Robotic assistance has been demonstrated to be beneficial in diminishing hand tremor. Among the requirements for reliable assistance from the robot is to provide precise measurements of system states e.g. sclera forces, tool tip position and tool insertion depth. Providing this and other sensing information using existing technology would contribute towards development and implementation of autonomous robot-assisted tasks in retinal surgery such as laser ablation, guided suture placement/assisted needle vessel cannulation, among other applications. In the present work, we use a state-estimating Kalman filtering (KF) to improve the tool tip position and insertion depth estimates, which used to be purely obtained by robot forward kinematics (FWK) and direct sensor measurements, respectively. To improve tool tip localization, in addition to robot FWK, we also use sclera force measurements along with beam theory to account for tool deflection. For insertion depth, the robot FWK is combined with sensor measurements for the cases where sensor measurements are not reliable enough. The improved tool tip position and insertion depth measurements are validated using a stereo camera system through preliminary experiments and a case study. The results indicate that the tool tip position and insertion depth measurements are significantly improved by 77% and 94% after applying KF, respectively.

Adaptive Control Improves Sclera Force Safety in Robot-Assisted Eye Surgery: A Clinical Study.

The integration of robotics into retinal microsurgery leads to a reduction in surgeon perception of tool-to-tissue interaction forces. This blunting of human tactile sensory input, which is due to the inflexible mass and large inertia of the robotic arm as compared to the milli-Newton scale of the interaction forces and fragile tissues during ophthalmic surgery, identifies a potential iatrogenic risk during robotic eye surgery. In this paper, we aim to evaluate two variants of an adaptive force control scheme implemented on the Steady-Hand Eye Robot (SHER) that are intended to mitigate the risk of unsafe scleral forces. The present study enrolled ten retina fellows and ophthalmology residents into a simulated procedure, which simply asked the trainees to follow retinal vessels in a model retina surgery environment. For this purpose, we have developed a force-sensing (equipped with Fiber Bragg Grating (FBG)) instrument to attach to the robot. A piezo-actuated linear stage for creating random lateral motions to the eyeball phantom has been provided to simulate disturbances during surgery. The SHER and all of its dependencies were set up in an operating room in the Wilmer Eye Institute at the Johns Hopkins Hospital. The clinicians conducted robot-assisted experiments with the adaptive controls incorporated as well as freehand manipulations. The results indicate that the Adaptive Norm Control (ANC) method, is able to maintain scleral forces at predetermined safe levels better than even freehand manipulations. Novice clinicians in robot training however, subjectively preferred freehand maneuvers over robotic manipulations. Clinician preferences once highly skilled with the robot is not assessed in this study.

Force-based Safe Vein Cannulation in Robot-assisted Retinal Surgery: A Preliminary Study.

Retinal vein cannulation (RVC) is a potential treatment for retinal vein occlusion (RVO). Manual surgery has limitations in RVC due to extremely small vessels and instruments involved, as well as the presence of physiological hand tremor. Robot-assisted retinal surgery may be a better approach to smooth and accurate instrument manipulation during this procedure. Motion of the retina and cornea related to heartbeat may be associated with unexpected forces between the tool and eyeball. In this paper, we propose a force-based control strategy to automatically compensate for the movement of the retina maintaining the tip force and sclera force in a predetermined small range. A dual force-sensing tool is used to monitor the tip force, sclera force and tool insertion depth, which will be used to derive a desired joint velocity for the robot via a modified admittance controller. Then the tool is manipulated to compensate for the movement of the retina as well as reduce the tip force and sclera force. Quantitative experiments are conducted to verify the efficacy of the control strategy and a user study is also conducted by a retinal surgeon to demonstrate the advantages of our automatic compensation approach.

Auditory Feedback Effectiveness for Enabling Safe Sclera Force in Robot-Assisted Vitreoretinal Surgery: a Multi-User Study.

Robot-assisted retinal surgery has become increasingly prevalent in recent years in part due to the potential for robots to help surgeons improve the safety of an immensely delicate and difficult set of tasks. The integration of robots into retinal surgery has resulted in diminished surgeon perception of tool-to-tissue interaction forces due to robot's stiffness. The tactile perception of these interaction forces (sclera force) has long been a crucial source of feedback for surgeons who rely on them to guide surgical maneuvers and to prevent damaging forces from being applied to the eye. This problem is exacerbated when there are unfavorable sclera forces originating from patient movements (dynamic eyeball manipulation) during surgery which may cause the sclera forces to increase even drastically. In this study we aim at evaluating the efficacy of providing warning auditory feedback based on the level of sclera force measured by force sensing instruments. The intent is to enhance safety during dynamic eye manipulations in robot-assisted retinal surgery. The disturbances caused by lateral movement of patient's head are simulated using a piezo-actuated linear stage. The Johns Hopkins Steady-Hand Eye Robot (SHER), is then used in a multi-user experiment. Twelve participants are asked to perform a mock retinal surgery by following painted vessels inside an eye phantom using a force sensing instrument while auditory feedback is provided. The results indicate that the users are able to handle the eye motion disturbances while maintaining the sclera forces within safe boundaries when audio feedback is provided.

Robotic Retinal Surgery Impacts on Scleral Forces: In Vivo Study.

PurposeThis study aims to map force interaction between instrument and sclera of in vivo rabbits during retinal procedures, and verify if a robotic active force control could prevent unwanted increase of forces on the sclera.MethodsExperiments consisted in the performance of intraocular movements of a force sensing instrument, adjacent to the retinal surface, in radial directions, from the center to the periphery and back, and compared manual manipulations with robotic assistance and also robotic assistance with an active force control. This protocol was approved by the Animal Use and Ethical Committee and experiments were according to ARVO Statement of Animal Use.ResultsMean forces using manual manipulations were 115 ± 51 mN. Using robotic assistance, mean forces were 118 ± 49 mN. Using an active force control method, overall mean forces reduced to 69 ± 15, with a statistical difference compared with other methods (P < 0.001). Comparing intraocular directions, superior sector required higher forces and the force control method reduced differences in forces between users and retained the same force pattern between them.ConclusionsResults validate that the introduction of robotic assistance might increase the dynamic interactions between instrument and sclera, and the addition of an active force control method reduces the forces at levels lower than manual manipulations.Translational RelevanceAll marketing benefits from extreme accuracy and stability from robots, however, redundancy of safety mechanisms during intraocular manipulations, especially on force control and surgical awareness, would allow all utility of robotic assistance in ophthalmology.

Scleral Force Evaluation During Vitreoretinal Surgery: in an In Vivo Rabbit Eye Model.

During vitreoretinal surgery, the surgeon is required to precisely manipulate multiple tools in a confined intraocular environment, while the tool tip to retina contact forces are at the limit of human sensation limits. During typical vitrectomy procedures, the surgeon inserts various tools through small incisions performed on the sclera of the eye (sclerotomies), and manipulates them to perform surgical tasks. During intraocular procedures, tool-tissue interactions occur at the sclerotomy ports and at the tool-tip when it contacts retina. Measuring such interactions may be valuable for providing force feedback necessary for robotic guidance. In this paper, we measure and analyze force measurements at the sclerotomy ports. To the best of our knowledge, this is the first time that the scleral forces are measured in an in vivo eye model. A force sensing instrument utilizing Fiber Bragg Grating (FBG) strain sensors was used to measure the scleral forces while two retinal surgeons performed intraocular tool manipulation (ITM) task in rabbit eyes as well as a dry phantom. The mean of the measured sclera forces were 129.11 mN and 80.45 mN in in vivo and dry phantom experiments, respectively.

Automatic Light Pipe Actuating System for Bimanual Robot-Assisted Retinal Surgery.

Retinal surgery is a bimanual operation in which surgeons operate with an instrument in their dominant hand (more capable hand) and simultaneously hold a light pipe (illuminating pipe) with their non-dominant hand (less capable hand) to provide illumination inside the eye. Manually holding and adjusting the light pipe places an additional burden on the surgeon and increases the overall complexity of the procedure. To overcome these challenges, a robot-assisted automatic light pipe actuating system is proposed. A customized light pipe with force-sensing capability is mounted at the end effector of a follower robot and is actuated through a hybrid force-velocity controller to automatically illuminate the target area on the retinal surface by pivoting about the scleral port (incision on the sclera). Static following-accuracy evaluation and dynamic light tracking experiments are carried out. The results show that the proposed system can successfully illuminate the desired area with negligible offset (the average offset is 2.45 mm with standard deviation of 1.33 mm). The average scleral forces are also below a specified threshold (50 mN). The proposed system not only can allow for increased focus on dominant hand instrument control, but also could be extended to three-arm procedures (two surgical instruments held by surgeon plus a robot-holding light pipe) in retinal surgery, potentially improving surgical efficiency and outcome.

Real Time Prediction of Sclera Force with LSTM Neural Networks in Robot-Assisted Retinal Surgery.

Retinal microsurgery is one of the most technically demanding surgeries, during which the surgical tool needs to be inserted into the eyeball and is constantly constrained by the sclerotomy port. During the surgery, any unexpected manipulation could cause extreme tool-sclera contact force leading to sclera damage. Although, a robot assistant could reduce hand tremor and improve the tool positioning accuracy, it cannot prevent or alarm the surgeon about the upcoming danger caused by surgeon's misoperations, i.e., applying excessive force on the sclera. In this paper, we present a new method based on a Long Short Term Memory recurrent neural network for predicting the user behavior, i.e., the contact force between the tool and sclera (sclera force) and the insertion depth of the tool from sclera contact point (insertion depth) in real time (40Hz). The predicted force information is provided to the user through auditory feedback to alarm any unexpected sclera force. The user behavior data is collected in a mock retinal surgical operation on a dry eye phantom with Steady Hand Eye Robot and a novel multi-function sensing tool. The Long Short Term Memory recurrent neural network is trained on the collected time series of sclera force and insertion depth. The network can predict the sclera force and insertion depth 100 milliseconds in the future with 95.29% and 96.57% accuracy, respectively, and can help reduce the fraction of unsafe sclera forces from 40.19% to 15.43%.

Toward Improving Patient Safety and Surgeon Comfort in a Synergic Robot-Assisted Eye Surgery: A Comparative Study.

When robotic assistance is present into vitreoretinal surgery, the surgeon will experience reduced sensory input that is otherwise derived from the tool's interaction with the eye wall (sclera). We speculate that disconnecting the surgeon from this sensory input may increase the risk of injury to the eye and affect the surgeon's usual technique. On the other hand, robot autonomous motion to enhance patient safety might inhibit the surgeons tool manipulation and diminish surgeon comfort with the procedure. In this study, to investigate the parameters of patient safety and surgeon comfort in a robot-assisted eye surgery, we implemented three different approaches designed to keep the scleral force in a safe range during a synergic eye manipulation task. To assess the surgeon comfort during these procedures, the amount of interference with the surgeons usual maneuvers has been analyzed by defining quantitative comfort metrics. The first two utilized scleral force control approaches are based on an adaptive force control method in which the robot actively counteracts any excessive force on the sclera. The third control method is based on a virtual fixture approach in which a virtual wall is created for the surgeon in the unsafe directions of manipulation. The performance of the utilized approaches was evaluated in user studies with two experienced retinal surgeons and the outcomes of the procedure were assessed using the defined safety and comfort metrics. Results of these analyses indicate the significance of the opted control paradigm on the outcome of a safe and comfortable robot-assisted eye surgery.

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.

Towards securing the sclera against patient involuntary head movement in robotic retinal surgery.

Retinal surgery involves manipulating very delicate tissues within the confined area of eyeball. In such demanding practices, patient involuntary head movement might abruptly raise tool-to-eyeball interaction forces which would be detrimental to eye. This study is aimed at implementing different force control strategies and evaluating how they contribute to attaining sclera force safety while patient head drift is present. To simulate patient head movement, a piezoelectric-actuated linear stage is used to produce random motions in a single direction in random time intervals. Having an eye phantom attached to the linear stage then an experienced eye surgeon is asked to manipulate the eye and repeat a mock surgical task both with and without the assist of the Steady-Hand Eye Robot. For the freehand case, warning sounds were provided to the surgeon as auditory feedback to alert him about excessive slclra forces. For the robot-assisted experiments two variants of an adaptive sclera force control and a virtual fixture method were deployed to see how they can maintain eye safety under head drift circumstances. The results indicate that the developed robot control strategies are able to compensate for head drift and keep the sclera forces under safe levels as well as the free hand operation.

Adaptive Control of Sclera Force and Insertion Depth for Safe Robot-Assisted Retinal Surgery.

One of the significant challenges of moving from manual to robot-assisted retinal surgery is the loss of perception of forces applied to the sclera (sclera forces) by the surgical tools. This damping of force feedback is primarily due to the stiffness and inertia of the robot. The diminished perception of tool-to-eye interactions might put the eye tissue at high risk of injury due to excessive sclera forces or extreme insertion of the tool into the eye. In the present study therefore a 1-dimensional adaptive control method is customized for 3-dimensional control of sclera force components and tool insertion depth and then implemented on the velocity-controlled Johns Hopkins Steady-Hand Eye Robot. The control method enables the robot to perform autonomous motions to make the sclera force and/or insertion depth of the tool tip to follow pre-defined desired and safe trajectories when they exceed safe bounds. A robotic light pipe holding application in retinal surgery is also investigated using the adaptive control method. The implementation results indicate that the adaptive control is able to achieve the imposed safety margins and prevent sclera forces and insertion depth from exceeding safe boundaries.

Enabling Technology for Safe Robot-Assisted Retinal Surgery: Early Warning for Unsafe Scleral Force.

Retinal microsurgery is technically demanding and requires high surgical skill with very little room for manipulation error. During surgery the tool needs to be inserted into the eyeball while maintaining constant contact with the sclera. Any unexpected manipulation could cause extreme tool-sclera contact force (scleral force) thus damage the sclera. The introduction of robotic assistance could enhance and expand the surgeon's manipulation capabilities during surgery. However, the potential intra-operative danger from surgeon's misoperations remains difficult to detect and prevent by existing robotic systems. Therefore, we propose a method to predict imminent unsafe manipulation in robot-assisted retinal surgery and generate feedback to the surgeon via auditory substitution. The surgeon could then react to the possible unsafe events in advance. This work specifically focuses on minimizing sclera damage using a force-sensing tool calibrated to measure small scleral forces. A recurrent neural network is designed and trained to predict the force safety status up to 500 milliseconds in the future. The system is implemented using an existing "steady hand" eye robot. A vessel following manipulation task is designed and performed on a dry eye phantom to emulate the retinal surgery and to analyze the proposed method. Finally, preliminary validation experiments are performed by five users, the results of which indicate that the proposed early warning system could help to reduce the number of unsafe manipulation events.

Sclera Force Control in Robot-assisted Eye Surgery: Adaptive Force Control vs. Auditory Feedback.

Surgeon hand tremor limits human capability during microsurgical procedures such as those that treat the eye. In contrast, elimination of hand tremor through the introduction of microsurgical robots diminishes the surgeons tactile perception of useful and familiar tool-to-sclera forces. While the large mass and inertia of eye surgical robot prevents surgeon microtremor, loss of perception of small scleral forces may put the sclera at risk of injury. In this paper, we have applied and compared two different methods to assure the safety of sclera tissue during robot-assisted eye surgery. In the active control method, an adaptive force control strategy is implemented on the Steady-Hand Eye Robot in order to control the magnitude of scleral forces when they exceed safe boundaries. This autonomous force compensation is then compared to a passive force control method in which the surgeon performs manual adjustments in response to the provided audio feedback proportional to the magnitude of sclera force. A pilot study with three users indicate that the active control method is potentially more efficient.

Preliminary study of an RNN-based active interventional robotic system (AIRS) in retinal microsurgery.

Retinal microsurgery requires highly dexterous and precise maneuvering of instruments inserted into the eyeball through the sclerotomy port. During such procedures, the sclera can potentially be injured from extreme tool-to-sclera contact force caused by surgeon's unintentional misoperations. We present an active interventional robotic system to prevent such iatrogenic accidents by enabling the robotic system to actively counteract the surgeon's possible unsafe operations in advance of their occurrence. Relying on a novel force sensing tool to measure and collect scleral forces, we construct a recurrent neural network with long short-term memory unit to oversee surgeon's operation and predict possible unsafe scleral forces up to the next 200ms. We then apply a linear admittance control to actuate the robot to reduce the undesired scleral force. The system is implemented using an existing "steady hand" eye robot platform. The proposed method is evaluated on an artificial eye phantom by performing a "vessel following" mock retinal surgery operation. Empirical validation over multiple trials indicates that the proposed active interventional robotic system could help to reduce the number of unsafe manipulation events. We develop an active interventional robotic system to actively prevent surgeon's unsafe operations in retinal surgery. The result of the evaluation experiments shows that the proposed system can improve the surgeon's performance.

Real-Time Sclera Force Feedback for Enabling Safe Robot-Assisted Vitreoretinal Surgery.

One of the major yet little recognized challenges in robotic vitreoretinal surgery is the matter of tool forces applied to the sclera. Tissue safety, coordinated tool use and interactions between tool tip and shaft forces are little studied. The introduction of robotic assist has further diminished the surgeon's ability to perceive scleral forces. Microsurgical tools capable of measuring such small forces integrated with robotmanipulators may therefore improve functionality and safety by providing sclera force feedback to the surgeon. In this paper, using a force-sensing tool, we have conducted robotassisted eye manipulation experiments to evaluate the utility of providing scleral force feedback. The work assesses 1) passive audio feedback and 2) active haptic feedback and evaluates the impact of these feedbacks on scleral forces in excess of aboundary. The results show that in presence of passive or active feedback, the duration of experiment increases, while the duration for which scleral forces exceed a safe threshold decreases.