Towards a Procedure-Optimised Steerable Catheter for Deep-Seated Neurosurgery.

In recent years, steerable needles have attracted significant interest in relation to minimally invasive surgery (MIS). Specifically, the flexible, programmable bevel-tip needle (PBN) concept was successfully demonstrated in vivo in an evaluation of the feasibility of convection-enhanced delivery (CED) for chemotherapeutics within the ovine model with a 2.5 mm PBN prototype. However, further size reductions are necessary for other diagnostic and therapeutic procedures and drug delivery operations involving deep-seated tissue structures. Since PBNs have a complex cross-section geometry, standard production methods, such as extrusion, fail, as the outer diameter is reduced further. This paper presents our first attempt to demonstrate a new manufacturing method for PBNs that employs thermal drawing technology. Experimental characterisation tests were performed for the 2.5 mm PBN and the new 1.3 mm thermally drawn (TD) PBN prototype described here. The results show that thermal drawing presents a significant advantage in miniaturising complex needle structures. However, the steering behaviour was affected due to the choice of material in this first attempt, a limitation which will be addressed in future work.

Modular robotic platform for precision neurosurgery with a bio-inspired needle: System overview and first in-vivo deployment.

Over the past 10 years, minimally invasive surgery (MIS) has shown significant benefits compared to conventional surgical techniques, with reduced trauma, shorter hospital stays, and shorter patient recovery times. In neurosurgical MIS procedures, inserting a straight tool (e.g. catheter) is common practice in applications ranging from biopsy and laser ablation, to drug delivery and fluid evacuation. How to handle tissue deformation, target migration and access to deep-seated anatomical structures remain an open challenge, affecting both the preoperative planning phase and eventual surgical intervention. Here, we present the first neurosurgical platform in the literature, able to deliver an implantable steerable needle for a range of diagnostic and therapeutic applications, with a short-term focus on localised drug delivery. This work presents the system's architecture and first in vivo deployment with an optimised surgical workflow designed for pre-clinical trials with the ovine model, which demonstrate appropriate function and safe implantation.

Insights into Infusion-Based Targeted Drug Delivery in the Brain: Perspectives, Challenges and Opportunities.

Targeted drug delivery in the brain is instrumental in the treatment of lethal brain diseases, such as glioblastoma multiforme, the most aggressive primary central nervous system tumour in adults. Infusion-based drug delivery techniques, which directly administer to the tissue for local treatment, as in convection-enhanced delivery (CED), provide an important opportunity; however, poor understanding of the pressure-driven drug transport mechanisms in the brain has hindered its ultimate success in clinical applications. In this review, we focus on the biomechanical and biochemical aspects of infusion-based targeted drug delivery in the brain and look into the underlying molecular level mechanisms. We discuss recent advances and challenges in the complementary field of medical robotics and its use in targeted drug delivery in the brain. A critical overview of current research in these areas and their clinical implications is provided. This review delivers new ideas and perspectives for further studies of targeted drug delivery in the brain.

Inverse Reinforcement Learning Intra-Operative Path Planning for Steerable Needle.

OBJECTIVE: This paper presentsa safe and effective keyhole neurosurgery intra-operative planning framework for flexible neurosurgical robots. The framework is intended to support neurosurgeons during the intra-operative procedure to react to a dynamic environment. METHODS: The proposed system integrates inverse reinforcement learning path planning algorithm combined with 1) a pre-operative path planning framework for fast and intuitive user interaction, 2) a realistic, time-bounded simulator based on Position-based Dynamics (PBD) simulation that mocks brain deformations due to catheter insertion and 3) a simulated robotic system. RESULTS: Simulation results performed on a human brain dataset show that the inverse reinforcement learning intra-operative planning method can guide a steerable needle with bounded curvature to a predefined target pose with an average targeting error of 1.34 ± 0.52 (25 th = 1.02, 75 th = 1.36) mm in position and 3.16 ± 1.06 (25 th = 2, 75 th = 4.94) degrees in orientation under a deformable simulated environment, with a re-planning time of 0.02 sec and a success rate of 100%. CONCLUSION: With this work, we demonstrate that the presented intra-operative steerable needle path planner is able to avoid anatomical obstacles while optimising surgical criteria. SIGNIFICANCE: The results demonstrate that the proposed method is fast and can securely steer flexible needles with high accuracy and robustness.

Raman Spectroscopy and Machine Learning for IDH Genotyping of Unprocessed Glioma Biopsies.

Isocitrate dehydrogenase (IDH) mutational status is pivotal in the management of gliomas. Patients with IDH-mutated (IDH-MUT) tumors have a better prognosis and benefit more from extended surgical resection than IDH wild-type (IDH-WT). Raman spectroscopy (RS) is a minimally invasive optical technique with great potential for intraoperative diagnosis. We evaluated the RS's ability to characterize the IDH mutational status onto unprocessed glioma biopsies. We extracted 2073 Raman spectra from thirty-eight unprocessed samples. The classification performance was assessed using the eXtreme Gradient Boosted trees (XGB) and Support Vector Machine with Radial Basis Function kernel (RBF-SVM). Measured Raman spectra displayed differences between IDH-MUT and IDH-WT tumor tissue. From the 103 Raman shifts screened as input features, the cross-validation loop identified 52 shifts with the highest performance in the distinction of the two groups. Raman analysis showed differences in spectral features of lipids, collagen, DNA and cholesterol/phospholipids. We were able to distinguish between IDH-MUT and IDH-WT tumors with an accuracy and precision of 87%. RS is a valuable and accurate tool for characterizing the mutational status of IDH mutation in unprocessed glioma samples. This study improves RS knowledge for future personalized surgical strategy or in situ target therapies for glioma tumors.

Development and in vivo assessment of a novel MRI-compatible headframe system for the ovine animal model.

BACKGROUND: The brain of sheep has primarily been used in neuroscience as an animal model because of its similarity to the human brain, in particular if compared to other models such as the lissencephalic rodent brain. Their brain size also makes sheep an ideal model for the development of neurosurgical techniques using conventional clinical CT/MRI scanners and stereotactic systems for neurosurgery. METHODS: In this study, we present the design and validation of a new CT/MRI compatible head frame for the ovine model and software, with its assessment under two real clinical scenarios. RESULTS: Ex-vivo and in vivo trial results report an average linear displacement of the ovine head frame during conventional surgical procedures of 0.81 mm for ex-vivo trials and 0.68 mm for in vivo tests, respectively. CONCLUSIONS: These trial results demonstrate the robustness of the head frame system and its suitability to be employed within a real clinical setting.

Glioma biopsies Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples.

Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies deployed on fresh untreated tissue. We aimed to probe RS on untreated brain biopsies exploring novel Raman bands useful in distinguishing glioma and normal brain tissue. Sixty-three fresh tissue biopsies were analyzed within few minutes after resection. A total of 3450 spectra were collected, with 1377 labelled as Healthy and 2073 as Tumor. Machine learning methods were used to classify spectra compared to the histo-pathological standard. The algorithms extracted information from 60 different Raman peaks identified as the most representative among 135 peaks screened. We were able to distinguish between tumor and healthy brain tissue with accuracy and precision of 83% and 82%, respectively. We identified 19 new Raman shifts with known biological significance. Raman spectroscopy was effective and accurate in discriminating glioma tissue from healthy brain ex-vivo in fresh samples. This study added new spectroscopic data that can contribute to further develop Raman Spectroscopy as an intraoperative tool for in-vivo glioma detection.

Path Replanning for Orientation-Constrained Needle Steering.

INTRODUCTION: Needle-based neurosurgical procedures require high accuracy in catheter positioning to achieve high clinical efficacy. Significant challenges for achieving accurate targeting are (i) tissue deformation (ii) clinical obstacles along the insertion path (iii) catheter control. OBJECTIVE: We propose a novel path-replanner able to generate an obstacle-free and curvature bounded three-dimensional (3D) path at each time step during insertion, accounting for a constrained target pose and intraoperative anatomical deformation. Additionally, our solution is sufficiently fast to be used in a closed-loop system: needle tip tracking via electromagnetic sensors is used by the path-replanner to automatically guide the programmable bevel-tip needle (PBN) while surgical constraints on sensitive structures avoidance are met. METHODS: The generated path is achieved by combining the "Bubble Bending" method for online path deformation and a 3D extension of a convex optimisation method for path smoothing. RESULTS: Simulation results performed on a realistic dataset show that our replanning method can guide a PBN with bounded curvature to a predefined target pose with an average targeting error of 0.65  ± 0.46 mm in position and 3.25  ± 5.23 degrees in orientation under a deformable simulated environment. The proposed algorithm was also assessed in-vitro on a brain-like gelatin phantom, achieving a target error of 1.81  ± 0.51 mm in position and 5.9  ± 1.42 degrees in orientation. CONCLUSION: The presented work assessed the performance of a new online steerable needle path-planner able to avoid anatomical obstacles while optimizing surgical criteria. SIGNIFICANCE: This method is particularly suited for surgical procedures demanding high accuracy on the desired goal pose under tissue deformations and real-world inaccuracies.

Design and Evaluation of the Kinect-Wheelchair Interface Controlled (KWIC) Smart Wheelchair for Pediatric Powered Mobility Training.

BACKGROUND: Children with severe disabilities are sometimes unable to access powered mobility training. Thus, we developed the Kinect-Wheelchair Interface Controlled (KWIC) smart wheelchair trainer that converts a manual wheelchair into a powered wheelchair. The KWIC Trainer uses computer vision to create a virtual tether with adaptive shared-control between the wheelchair and a therapist during training. It also includes a mixed-reality video game system. METHODS: We performed a year-long usability study of the KWIC Trainer at a local clinic, soliciting qualitative and quantitative feedback on the device after extended use. RESULTS: Eight therapists used the KWIC Trainer for over 50 hours with 8 different children. Two of the children obtained their own powered wheelchair as a result of the training. The therapists indicated the device allowed them to provide mobility training for more children than would have been possible with a demo wheelchair, and they found use of the device to be as safe as or safer than conventional training. They viewed the shared control algorithm as counter-productive because it made it difficult for the child to discern when he or she was controlling the chair. They were enthusiastic about the video game integration for increasing motivation and engagement during training. They emphasized the need for additional access methods for controlling the device. CONCLUSION: The therapists confirmed that the KWIC Trainer is a useful tool for increasing access to powered mobility training and for engaging children during training sessions. However, some improvements would enhance its applicability for routine clinical use.

A low-cost, high-field-strength magnetic resonance imaging-compatible actuator.

To perform minimally invasive surgical interventions with the aid of robotic systems within a magnetic resonance imaging scanner offers significant advantages compared to conventional surgery. However, despite the numerous exciting potential applications of this technology, the introduction of magnetic resonance imaging-compatible robotics has been hampered by safety, reliability and cost concerns: the robots should not be attracted by the strong magnetic field of the scanner and should operate reliably in the field without causing distortion to the scan data. Development of non-conventional sensors and/or actuators is thus required to meet these strict operational and safety requirements. These demands commonly result in expensive actuators, which mean that cost effectiveness remains a major challenge for such robotic systems. This work presents a low-cost, high-field-strength magnetic resonance imaging-compatible actuator: a pneumatic stepper motor which is controllable in open loop or closed loop, along with a rotary encoder, both fully manufactured in plastic, which are shown to perform reliably via a set of in vitro trials while generating negligible artifacts when imaged within a standard clinical scanner.

Rate dependency during needle insertions with a biologically inspired steering system: an experimental study.

Percutaneous intervention is a common Minimally Invasive (MI) surgical procedure for the treatment of various disorders. It generally involves the insertion of slender needles deep within tissue, as lesions can be several centimetres below skin level. Consequently, deviations might occur which need to be accounted for and corrected by steering the needle tip during the insertion process. Needle steering systems, however, are necessarily disruptive to the substrate, with the potential to cause larger migrations of deep-seated targets, as well as potentially increasing the extent of tissue trauma at the needle interface, when compared to straight needles. This study aims to investigate different insertion modalities for a biologically inspired multi-segment needle, which is able to steer along three-dimensional trajectories by exploiting a quasi-linear relationship between the relative displacement of the needle segments and the curvature magnitude and direction plane at the tip. We demonstrate that different segment insertion speeds do not affect this relationship during experiments in gelatine, and thus a new steering approach is proposed to steer the needle into the substrate which substantially improves upon the manoeuvrability (i.e. the rate of change of steering angle) of the needle.

Substituting auditory for visual feedback to adapt to altered dynamic and kinematic environments during reaching.

The arm movement control system often relies on visual feedback to drive motor adaptation and to help specify desired trajectories. Here we studied whether kinematic errors that were indicated with auditory feedback could be used to control reaching in a way comparable with when vision was available. We randomized twenty healthy adult subjects to receive either visual or auditory feedback of their movement trajectory error with respect to a line as they performed timed reaching movements while holding a robotic joystick. We delivered auditory feedback using spatialized pink noise, the loudness and location of which reflected kinematic error. After a baseline period, we unexpectedly perturbed the reaching trajectories using a perpendicular viscous force field applied by the joystick. Subjects adapted to the force field as well with auditory feedback as they did with visual feedback and exhibited comparable after effects when the force field was removed. When we changed the reference trajectory to be a trapezoid instead of a line, subjects shifted their trajectories by about the same amount with either auditory or visual feedback of error. These results indicate that arm motor networks can readily incorporate auditory feedback to alter internal models and desired trajectories, a finding with implications for the organization of the arm motor control adaptation system as well as sensory substitution and motor training technologies.

Effect of visual distraction and auditory feedback on patient effort during robot-assisted movement training after stroke.

BACKGROUND: Practicing arm and gait movements with robotic assistance after neurologic injury can help patients improve their movement ability, but patients sometimes reduce their effort during training in response to the assistance. Reduced effort has been hypothesized to diminish clinical outcomes of robotic training. To better understand patient slacking, we studied the role of visual distraction and auditory feedback in modulating patient effort during a common robot-assisted tracking task. METHODS: Fourteen participants with chronic left hemiparesis from stroke, five control participants with chronic right hemiparesis and fourteen non-impaired healthy control participants, tracked a visual target with their arms while receiving adaptive assistance from a robotic arm exoskeleton. We compared four practice conditions: the baseline tracking task alone; tracking while also performing a visual distracter task; tracking with the visual distracter and sound feedback; and tracking with sound feedback. For the distracter task, symbols were randomly displayed in the corners of the computer screen, and the participants were instructed to click a mouse button when a target symbol appeared. The sound feedback consisted of a repeating beep, with the frequency of repetition made to increase with increasing tracking error. RESULTS: Participants with stroke halved their effort and doubled their tracking error when performing the visual distracter task with their left hemiparetic arm. With sound feedback, however, these participants increased their effort and decreased their tracking error close to their baseline levels, while also performing the distracter task successfully. These effects were significantly smaller for the participants who used their non-paretic arm and for the participants without stroke. CONCLUSIONS: Visual distraction decreased participants effort during a standard robot-assisted movement training task. This effect was greater for the hemiparetic arm, suggesting that the increased demands associated with controlling an affected arm make the motor system more prone to slack when distracted. Providing an alternate sensory channel for feedback, i.e., auditory feedback of tracking error, enabled the participants to simultaneously perform the tracking task and distracter task effectively. Thus, incorporating real-time auditory feedback of performance errors might improve clinical outcomes of robotic therapy systems.

Improving robotics for neurorehabilitation: enhancing engagement, performance, and learning with auditory feedback.

This paper reports on an ongoing research collaboration between the University of Padua and the University of California Irvine, on the use of continuous auditory-feedback in robot-assisted neurorehabilitation of post-stroke patients. This feedback modality is mostly underexploited in current robotic rehabilitation systems, that usually implement very basic auditory feedback interfaces. The results of this research show that generating a proper sound cue during robot assisted movement training can help patients in improving engagement, performance and learning in the exercise.