Robotic Assistance for Intraocular Microsurgery: Challenges and Perspectives.

Intraocular surgery, one of the most challenging discipline of microsurgery, requires sensory and motor skills at the limits of human physiological capabilities combined with tremendously difficult requirements for accuracy and steadiness. Nowadays, robotics combined with advanced imaging has opened conspicuous and significant directions in advancing the field of intraocular microsurgery. Having patient treatment with greater safety and efficiency as the final goal, similar to other medical applications, robotics has a real potential to fundamentally change microsurgery by combining human strengths with computer and sensor-based technology in an information-driven environment. Still in its early stages, robotic assistance for intraocular microsurgery has been accepted with precaution in the operating room and successfully tested in a limited number of clinical trials. However, owing to its demonstrated capabilities including hand tremor reduction, haptic feedback, steadiness, enhanced dexterity, micrometer-scale accuracy, and others, microsurgery robotics has evolved as a very promising trend in advancing retinal surgery. This paper will analyze the advances in retinal robotic microsurgery, its current drawbacks and limitations, as well as the possible new directions to expand retinal microsurgery to techniques currently beyond human boundaries or infeasible without robotics.

Introducer Design Concepts for an Epicardial Parallel Wire Robot.

BACKGROUND: Cardiac gene therapies lack effective delivery methods to the myocardium. While direct injection has demonstrated success over a small region, homogenous gene expression requires many injections over a large area. To address this need, we developed a minimally invasive flexible parallel wire robot for epicardial interventions. To accurately deploy it onto the beating heart, an introducer mechanism is required. METHODS: Two mechanisms are presented. Assessment of the robot's positioning, procedure time, and pericardium insertion forces are performed on an artificial beating heart. RESULTS: Successful positioning was demonstrated. The mean procedure time was 230 ± 7 seconds for mechanism I and 259 ± 4 seconds for mechanism II. The mean pericardium insertion force was 2.2 ± 0.4 N anteriorly and 3.1 ± 0.4 N posteriorly. CONCLUSION: Introducer mechanisms demonstrate feasibility in facilitating the robot's deployment on the epicardium. Pericardium insertion forces and procedure times are consistent and reasonable.

Coronary vessel detection methods for organ-mounted robots.

BACKGROUND: HeartLander is a tethered robot walker that utilizes suction to adhere to the beating heart. HeartLander can be used for minimally invasive administration of cardiac medications or ablation of tissue. In order to administer injections safely, HeartLander must avoid coronary vasculature. METHODS: Doppler ultrasound signals were recorded using a custom-made cardiac phantom and used to classify different coronary vessel properties. The classification was performed by two machine learning algorithms, the support vector machines and a deep convolutional neural network. These algorithms were then validated in animal trials. RESULTS: Accuracy of identifying vessels above turbulent flow reached greater than 92% in phantom trials and greater than 98% in animal trials. CONCLUSIONS: Through the use of two machine learning algorithms, HeartLander has shown the ability to identify different sized vasculature proximally above turbulent flow. These results indicate that it is feasible to use Doppler ultrasound to identify and avoid coronary vasculature during cardiac interventions using HeartLander.

EyeSAM: graph-based localization and mapping of retinal vasculature during intraocular microsurgery.

PURPOSE: Robot-assisted intraocular microsurgery can improve performance by aiding the surgeon in operating on delicate micron-scale anatomical structures of the eye. In order to account for the eyeball motion that is typical in intraocular surgery, there is a need for fast and accurate algorithms that map the retinal vasculature and localize the retina with respect to the microscope. METHODS: This work extends our previous work by a graph-based SLAM formulation using a sparse incremental smoothing and mapping (iSAM) algorithm. RESULTS: The resulting technique, "EyeSAM," performs SLAM for intraoperative vitreoretinal surgical use while avoiding spurious duplication of structures as with the previous simpler technique. The technique also yields reduction in average pixel error in the camera motion estimation. CONCLUSIONS: This work provides techniques to improve intraoperative tracking of retinal vasculature by handling loop closures and achieving increased robustness to quick shaky motions and drift due to uncertainties in the motion estimation.

Organ-mounted robot localization via function approximation.

BACKGROUND: Organ-mounted robots adhere to the surface of a mobile organ as a platform for minimally invasive interventions, providing passive compensation of physiological motion. This approach is beneficial during surgery on the beating heart. Accurate localization in such applications requires accounting for the heartbeat and respiratory motion. Previous work has described methods for modeling quasi-periodic motion of a point and registering to a static preoperative map. The existing techniques, while accurate, require several respiratory cycles to converge. METHODS: This paper presents a general localization technique for this application, involving function approximation using radial basis function (RBF) interpolation. RESULTS: In an experiment in the porcine model in vivo, the technique yields mean localization accuracy of 1.25 mm with a 95% confidence interval of 0.22 mm. CONCLUSIONS: The RBF approximation provides accurate estimates of robot location instantaneously.

Toward Improving Safety in Neurosurgery with an Active Handheld Instrument.

Microsurgical procedures, such as petroclival meningioma resection, require careful surgical actions in order to remove tumor tissue, while avoiding brain and vessel damaging. Such procedures are currently performed under microscope magnification. Robotic tools are emerging in order to filter surgeons' unintended movements and prevent tools from entering forbidden regions such as vascular structures. The present work investigates the use of a handheld robotic tool (Micron) to automate vessel avoidance in microsurgery. In particular, we focused on vessel segmentation, implementing a deep-learning-based segmentation strategy in microscopy images, and its integration with a feature-based passive 3D reconstruction algorithm to obtain accurate and robust vessel position. We then implemented a virtual-fixture-based strategy to control the handheld robotic tool and perform vessel avoidance. Clay vascular phantoms, lying on a background obtained from microscopy images recorded during petroclival meningioma surgery, were used for testing the segmentation and control algorithms. When testing the segmentation algorithm on 100 different phantom images, a median Dice similarity coefficient equal to 0.96 was achieved. A set of 25 Micron trials of 80 s in duration, each involving the interaction of Micron with a different vascular phantom, were recorded, with a safety distance equal to 2 mm, which was comparable to the median vessel diameter. Micron's tip entered the forbidden region 24% of the time when the control algorithm was active. However, the median penetration depth was 16.9 µm, which was two orders of magnitude lower than median vessel diameter. Results suggest the system can assist surgeons in performing safe vessel avoidance during neurosurgical procedures.

Beating-heart registration for organ-mounted robots.

BACKGROUND: Organ-mounted robots address the problem of beating-heart surgery by adhering to the heart, passively providing a platform that approaches zero relative motion. Because of the quasi-periodic deformation of the heart due to heartbeat and respiration, registration must address not only spatial registration but also temporal registration. METHODS: Motion data were collected in the porcine model in vivo (N = 6). Fourier series models of heart motion were developed. By comparing registrations generated using an iterative closest-point approach at different phases of respiration, the phase corresponding to minimum registration distance is identified. RESULTS: The spatiotemporal registration technique presented here reduces registration error by an average of 4.2 mm over the 6 trials, in comparison with a more simplistic static registration that merely averages out the physiological motion. CONCLUSIONS: An empirical metric for spatiotemporal registration of organ-mounted robots is defined and demonstrated using data from animal models in vivo.

Techniques for robot-aided intraocular surgery using monocular vision.

This paper presents techniques for robot-aided intraocular surgery using monocular vision in order to overcome erroneous stereo reconstruction in an intact eye. We propose a new retinal surface estimation method based on a structured-light approach. A handheld robot known as the Micron enables automatic scanning of a laser probe, creating projected beam patterns on the retinal surface. Geometric analysis of the patterns then allows planar reconstruction of the surface. To realize automated surgery in an intact eye, monocular hybrid visual servoing is accomplished through a scheme that incorporates surface reconstruction and partitioned visual servoing. We investigate the sensitivity of the estimation method according to relevant parameters and also evaluate its performance in both dry and wet conditions. The approach is validated through experiments for automated laser photocoagulation in a realistic eye phantom in vitro. Finally, we present the first demonstration of automated intraocular laser surgery in porcine eyes ex vivo.

EyeSLAM: Real-time simultaneous localization and mapping of retinal vessels during intraocular microsurgery.

BACKGROUND: Fast and accurate mapping and localization of the retinal vasculature is critical to increasing the effectiveness and clinical utility of robot-assisted intraocular microsurgery such as laser photocoagulation and retinal vessel cannulation. METHODS: The proposed EyeSLAM algorithm delivers 30 Hz real-time simultaneous localization and mapping of the human retina and vasculature during intraocular surgery, combining fast vessel detection with 2D scan-matching techniques to build and localize a probabilistic map of the vasculature. RESULTS: In the harsh imaging environment of retinal surgery with high magnification, quick shaky motions, textureless retina background, variable lighting and tool occlusion, EyeSLAM can map 75% of the vessels within two seconds of initialization and localize the retina in real time with a root mean squared (RMS) error of under 5.0 pixels (translation) and 1° (rotation). CONCLUSIONS: EyeSLAM robustly provides retinal maps and registration that enable intelligent surgical micromanipulators to aid surgeons in simulated retinal vessel tracing and photocoagulation tasks.

Tip Design for Safety of Steerable Needles for Robot-Controlled Brain Insertion.

BACKGROUND: Current practice in neurosurgical needle insertion is limited by the straight trajectories inherent with rigid probes. One technique allowing curvilinear trajectories involves flexible bevel-tipped needles, which bend during insertion due to their asymmetry. In the brain, safety will require avoidance of the sharp tips often used in laboratory studies, in favor of a more rounded profile. Steering performance, on the other hand, requires maximal asymmetry. Design of safe bevel-tipped brain needles thus involves management of this tradeoff by adjusting needle gauge, bevel angle, and fillet (or tip) radius to arrive at a design that is suitably asymmetrical while producing strain, strain rate, and stress below the levels that would damage brain tissue. METHODS: Designs with a variety of values of needle radius, bevel angle, and fillet radius were evaluated in finite-element simulations of simultaneous insertion and rotation. Brain tissue was modeled as a hyperelastic, linear viscoelastic material. Based on the literature available, safety thresholds of 0.19 strain, 10 s-1 strain rate, and 120 kPa stress were used. Safe values of needle radius, bevel angle, and fillet radius were selected, along with an appropriate velocity envelope for safe operation. The resulting needle was fabricated and compared with a Sedan side-cutting brain biopsy needle in a study in the porcine model in vivo (N=3). RESULTS: The prototype needle selected was 1.66 mm in diameter, with bevel angle of 10° and fillet radius of 0.25 mm. Upon examination of postoperative CT and histological images, no differences in tissue trauma or hemorrhage were noted between the prototype needle and the Sedan needle. CONCLUSIONS: The study indicates a general design technique for safe bevel-tipped brain needles based on comparison with relevant damage thresholds for strain, strain rate, and stress. The full potential of the technique awaits the determination of more exact safety thresholds.