Preclinical Evaluation of a Novel Steerable Robotic Neuroendoscope Tool.

BACKGROUND AND OBJECTIVES: To improve the outcomes of minimally invasive, endoscopic, intracranial procedures, steerable robotic tools have been developed but still require thorough evaluation before use in a clinical setting. This paper compares a novel steerable robotic neuroendoscope tool against a standard rigid tool. METHODS: Seventeen participants, 8 nonmedical and 9 medical (neurosurgery residents and fellows), were recruited. The evaluation trial consisted of a task that was completed using either a rigid tool or the steerable tool, followed by the completion of a qualitative survey. Target reach time and tool movement volume (TMV) were recorded for each trial and analyzed. The tools were evaluated within a realistic phantom model of the brain. RESULTS: Preclinical evaluation of both tools showed that average target reach time for the steerable tool among medical personnel (15.0 seconds) was longer than that of the rigid tool (5.9 seconds). However, the average TMV for the steerable tool (0.178 cm 3 ) was much lower than that of the rigid tool (0.501 cm 3 ) for medical personnel, decreasing the TMV by 64.47%. CONCLUSION: The steerable tool required more training and practice in comparison with the standard rigid tool, but it decreased the overall endoscope movement volume, which is a source of parenchymal injury associated with endoscopic procedures.

Real-time Pose Tracking for a Continuum Guidewire Robot under Fluoroscopic Imaging.

Atherosclerosis is a medical condition that causes buildup of plaque in the blood vessels and narrowing of the arteries. Surgeons often treat this condition through angioplasty with catheter placements. Continuum guidewire robots offer significant advantages for catheter placements due to their dexterity. Tracking these guidewire robots and their surrounding workspace under fluoroscopy in real-time can be useful for visualization and accurate control. This paper discusses algorithms and methods to track the shape and orientation of the guidewire and the surrounding workspaces of phantom vasculatures in real-time under C-arm fluoroscopy. The shape of continuum guidewires is found through a semantic segmentation architecture based on MobileNetv2 with a Tversky loss function to deal with class imbalances. This shape is refined through medial axis filtering and parametric curve fitting to quantitatively describe the guidewire's pose. Using a constant curvature assumption for the guidewire's bending segments, the parameters that describe the joint variables are estimated in real-time for a tendon-actuated COaxially Aligned STeerable (COAST) guidewire robot and tracked through its traversal of an aortic bifurcation phantom. The accuracy of the tracking is ~90% and the execution times are within 100ms, and hence this method is deemed suitable for real-time tracking.

Simultaneous Shape and Tip Force Sensing for the COAST Guidewire Robot.

Placement of catheters in minimally invasive cardiovascular procedures is preceded by navigating to the target lesion with a guidewire. Traversing through tortuous vascular pathways can be challenging without precise tip control, potentially resulting in the damage or perforation of blood vessels. To improve guidewire navigation, this paper presents 3D shape reconstruction and tip force sensing for the COaxially Aligned STeerable (COAST) guidewire robot using a triplet of adhered single core fiber Bragg grating sensors routed centrally through the robot's slender structure. Additionally, several shape reconstruction algorithms are compared, and shape measurements are utilized to enable tip force sensing. Demonstration of the capabilities of the robot is shown in free air where the shape of the robot is reconstructed with average errors less than 2mm at the guidewire tip, and the magnitudes of forces applied to the tip are estimated with an RMSE of 0.027N or less.

Model-based Design of the COAST Guidewire Robot for Large Deflection.

Minimally invasive endovascular procedures involve the manual placement of a guidewire, which is made difficult by vascular tortuosity and the lack of precise tip control. Steerable guidewire systems have been developed with tendon-driven, magnetic, and concentric tube actuation strategies to enable precise tip control, however, selecting machining parameters for such robots does not have a strict procedure. In this paper, we develop a systematic design procedure for selecting the tube pairs of the COaxially Aligned STeerable (COAST) guidewire robot. This includes the introduction of a mechanical model that accounts for micromachining-induced pre-curvatures with the goal of determining design parameters that reduce combined distal tip pre-curvature and minimize abrupt changes in actuated tip position for the COAST guidewire robot through selection of the best flexural rigidity between the tube pairs. We present adjustments in the kinematics modeling of COAST robot tip bending motion, and use these to characterize the bending behavior of the COAST robot for varying geometries of the micromachined tubes, with an average RMSE value for the tip position error of 0.816 mm in the validation study.

Design and Modeling of a Sub-2 mm Steerable Neuroendoscopic Grasping Tool.

Minimally invasive procedures, such as endoscopic third ventriculostomy (ETV), benefit from the increased dexterity and safety that surgical continuum robots can bring. However, due to their natural compliance, new compatible end-effectors, such as graspers or scissors, must be developed and their actuation must be considered when developing the robotic structures in which they are housed due to the inherent coupling that will be introduced. In this paper, we integrate a tendon-driven meso-scale grasper, with a closed configuration diameter of 1.69 mm, into a 2 degree-of-freedom (DoF) tendon-driven neurosurgical robot with an outer diameter of less than 2 mm. Furthermore, the kinematics of the grasper is validated and an analysis of the coupling between the grasper and the robotic joints is conducted in order to evaluate the design performance.

Fluoroscopic Image-Based 3-D Environment Reconstruction and Automated Path Planning for a Robotically Steerable Guidewire.

Cardiovascular diseases are the leading cause of death globally and surgical treatments for these often begin with the manual placement of a long compliant wire, called a guidewire, through different vasculature. To improve procedure outcomes and reduce radiation exposure, we propose steps towards a fully automated approach for steerable guidewire navigation within vessels. In this paper, we utilize fluoroscopic images to fully reconstruct 3-D printed phantom vasculature models by using a shape-from-silhouette algorithm. The reconstruction is subsequently de-noised using a deep learning-based encoder-decoder network and morphological filtering. This volume is used to model the environment for guidewire traversal. Following this, we present a novel method to plan an optimal path for guidewire traversal in three-dimensional vascular models through the use of slice planes and a modified hybrid A-star algorithm. Finally, the developed reconstruction and planning approaches are applied to an ex vivo porcine aorta, and navigation is demonstrated through the use of a tendon-actuated COaxially Aligned STeerable guidewire (COAST).

Kinematic Modeling and Jacobian-based Control of the COAST Guidewire Robot.

Manual guidewire navigation and placement for minimally invasive surgeries suffer from technical challenges due to imprecise tip motion control to traverse highly tortuous vasculature. Robotically steerable guidewires can address these challenges by actuating a compliant tip through multiple degrees-of-freedom for maneuvering through vascular pathways. In this paper, we detail the kinematic mapping of a COaxially Aligned STeerable (COAST) guidewire robot that is capable of executing follow-the-leader motion in three dimensional vascular pathways. We also develop an analytical Jacobian model to perform velocity kinematics for the robot and finally, we implement Jacobian-based control to demonstrate follow-the-leader motion of the guidewire in free space, within 3D-printed phantoms, and within ex vivo animal vasculature.

Dual-Resonance (16/32 MHz) Piezoelectric Transducer With a Single Electrical Connection for Forward-Viewing Robotic Guidewire.

Peripheral artery disease (PAD) affects more than 200 million people globally. Minimally invasive endovascular procedures can provide relief and salvage limbs while reducing injury rates and recovery times. Unfortunately, when a calcified chronic total occlusion is encountered, ~25% of endovascular procedures fail due to the inability to advance a guidewire using the view provided by fluoroscopy. To enable a sub-millimeter, robotically steerable guidewire to cross these occlusions, a novel single-element, dual-band transducer is developed that provides simultaneous multifrequency, forward-viewing imaging with high penetration depth and high spatial resolution while requiring only a single electrical connection. The design, fabrication, and acoustic characterization of this device are described, and proof-of-concept imaging is demonstrated in an ex vivo porcine artery after integration with a robotically steered guidewire. Measured center frequencies of the developed transducer were 16 and 32 MHz, with -6 dB fractional bandwidths of 73% and 23%, respectively. When imaging a 0.2-mm wire target at a depth of 5 mm, measured -6 dB target widths were 0.498 ± 0.02 and 0.268 ± 0.01 mm for images formed at 16 and 32 MHz, respectively. Measured SNR values were 33.3 and 21.3 dB, respectively. The 3-D images of the ex vivo artery demonstrate high penetration for visualizing vessel morphology at 16 MHz and ability to resolve small features close to the transducer at 32 MHz. Using images acquired simultaneously at both frequencies as part of an integrated forward-viewing, guidewire-based imaging system, an interventionalist could visualize the best path for advancing the guidewire to improve outcomes for patients with PAD.