Current state-of-the-art and future perspectives of robotic technology in neurosurgery

Neurosurgical robots in China: State of the art and future prospect

Neurosurgical robots have developed for decades and can effectively assist surgeons to carry out a variety of surgical operations, such as biopsy, stereo-electroencephalography (SEEG), deep brain stimulation (DBS), and so forth. In recent years, neurosurgical robots in China have developed rapidly. This article will focus on several key skills in neurosurgical robots, such as medical imaging systems, automatic manipulator, lesion localization techniques, multimodal image fusion technology, registration method, and vascular imaging technology; introduce the clinical application of neurosurgical robots in China, and look forward to the potential improvement points in the future based on our experience and research in the field.

Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI's role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O'Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient's prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

Technical evolution of pediatric neurosurgery: the evolution of intraoperative imaging

Imaging has always been fundamental to neurosurgery, and its evolution over the last century has made a dramatic transformation in the ability of neurosurgeons to define pathology and preserve normal tissue during their operations. In the mid-70 s, the development of computerized cross-sectional imaging with CT scan and subsequently MRI have revolutionized the practice of neurosurgery. Later, further advances in computer technology and medical engineering have allowed the combination of many modalities to bring them into the operating theater. This evolution has allowed real-time intraoperative imaging, in the hope of helping neurosurgeons achieve accuracy, maximal safe resection, and the implementation of minimally invasive techniques in brain and spine pathologies. Augmented reality and robotic technologies are also being applied as useful intra-operative techniques that will improve surgical planning and outcomes in the future. In this article, we will review imaging modalities and provide our institutional perspective on how we have integrated them into our practice.

Advances in artificial intelligence, robotics, augmented and virtual reality in neurosurgery

Neurosurgical practitioners undergo extensive and prolonged training to acquire diverse technical proficiencies, while neurosurgical procedures necessitate a substantial amount of pre-, post-, and intraoperative clinical data acquisition, making decisions, attention, and convalescence. The past decade witnessed an appreciable escalation in the significance of artificial intelligence (AI) in neurosurgery. AI holds significant potential in neurosurgery as it supplements the abilities of neurosurgeons to offer optimal interventional and non-interventional care to patients by improving prognostic and diagnostic outcomes in clinical therapy and assisting neurosurgeons in making decisions while surgical interventions to enhance patient outcomes. Other technologies including augmented reality, robotics, and virtual reality can assist and promote neurosurgical methods as well. Moreover, they play a significant role in generating, processing, as well as storing experimental and clinical data. Also, the usage of these technologies in neurosurgery is able to curtail the number of costs linked with surgical care and extend high-quality health care to a wider populace. This narrative review aims to integrate the results of articles that elucidate the role of the aforementioned technologies in neurosurgery.

Learning curves in robotic neurosurgery: a systematic review

The transition to performing procedures robotically generally entails a period of adjustment known as a learning curve as the surgeon develops a familiarity with the technology. However, no study has comprehensively examined robotic learning curves across the field of neurosurgery. We conducted a systematic review to characterize the scope of literature on robotic learning curves in neurosurgery, assess operative parameters that may involve a learning curve, and delineate areas for future investigation. PubMed, Embase, and Scopus were searched. Following deduplication, articles were screened by title and abstract for relevance. Remaining articles were screened via full text for final inclusion. Bibliographic and learning curve data were extracted. Of 746 resultant articles, 32 articles describing 3074 patients were included, of which 23 (71.9%) examined spine, 4 (12.5%) pediatric, 4 (12.5%) functional, and 1 (3.1%) general neurosurgery. The parameters assessed for learning curves were heterogeneous. In total, 8 (57.1%) of 14 studies found reduced operative time with increased cases, while the remainder demonstrated no learning curve. Six (60.0%) of 10 studies reported reduced operative time per component with increased cases, while the remainder indicated no learning curve. Radiation time, radiation time per component, robot time, registration time, setup time, and radiation dose were assessed by ≤ 4 studies each, with 0-66.7% of studies demonstrated a learning curve. Four (44.4%) of 9 studies on accuracy showed improvement over time, while the others indicated no improvement over time. The number of cases required to reverse the learning curve ranged from 3 to 75. Learning curves are common in robotic neurosurgery. However, existing studies demonstrate high heterogeneity in assessed parameters and the number of cases that comprise the learning curve. Future studies should seek to develop strategies to reduce the number of cases required to reach the learning curve.

The future of artificial intelligence in neurosurgery: A narrative review

Background:

Artificial intelligence (AI) and machine learning (ML) algorithms are on the tremendous rise for being incorporated into the field of neurosurgery. AI and ML algorithms are different from other technological advances as giving the capability for the computer to learn, reason, and problem-solving skills that a human inherits. This review summarizes the current use of AI in neurosurgery, the challenges that need to be addressed, and what the future holds.

Methods:

A literature review was carried out with a focus on the use of AI in the field of neurosurgery and its future implication in neurosurgical research.

Results:

The online literature on the use of AI in the field of neurosurgery shows the diversity of topics in terms of its current and future implications. The main areas that are being studied are diagnostic, outcomes, and treatment models.

Conclusion:

Wonders of AI in the field of medicine and neurosurgery hold true, yet there are a lot of challenges that need to be addressed before its implications can be seen in the field of neurosurgery from patient privacy, to access to high-quality data and overreliance on surgeons on AI. The future of AI in neurosurgery is pointed toward a patient-centric approach, managing clinical tasks, and helping in diagnosing and preoperative assessment of the patients.

Development of a Robotic Spine Surgery Program: Rationale, Strategy, Challenges, and Monitoring of Outcomes After Implementation

Surgical robots were invented in the 1980s, and since then, robotic-assisted surgery has become commonplace. In the field of spine surgery, robotic assistance is utilized mainly to place pedicle screws, and multiple studies have demonstrated that robots can increase the accuracy of screw placement and reduce radiation exposure to the patient and the surgeon. However, this may be at the cost of longer operative times, complications, and the risk of errors in mapping the patient's anatomy.

Robotics in neurosurgery: Current prevalence and future directions

Background:

The first instance of a robotic-assisted surgery occurred in neurosurgery; however, it is now more common in other fields such as urology and gynecology. This study aims to characterize the prevalence of robotic surgery among current neurosurgery programs as well as identify trends in clinical trials pertaining to robotic neurosurgery.

Methods:

Each institution’s website was analyzed for the mention of a robotic neurosurgery program and procedures. The future potential of robotics in neurosurgery was assessed by searching for current clinical trials pertaining to neurosurgical robotic surgery.

Results:

Of the top 100 programs, 30 offer robotic cranial and 40 offer robotic spinal surgery. No significant differences were observed with robotic surgical offerings between geographic regions in the US. Larger programs (faculty size 16 or over) had 20 of the 30 robotic cranial programs (66.6%), whereas 21 of the 40 robotic spinal programs (52.5%) were at larger programs. An initial search of clinical trials revealed 223 studies, of which only 13 pertained to robotic neurosurgery. Spinal fixation was the most common intervention (six studies), followed by Deep Brain Stimulation (DBS, two studies), Cochlear implants (two studies), laser ablation (LITT, one study), and endovascular embolization (one study). Most studies had industry sponsors (9/13 studies), while only five studies had hospital sponsors.

Conclusion:

Robotic neurosurgery is still in its infancy with less than half of the top programs offering robotic procedures. Future directions for robotics in neurosurgery appear to be focused on increased automation of stereotactic procedures such as DBS and LITT and robot-assisted spinal surgery.

Robotic guidance platform for laser interstitial thermal ablation and stereotactic needle biopsies: a single center experience

While laser ablation has become an increasingly important tool in the neurosurgical oncologist's armamentarium, deep seated lesions, and those located near critical structures require utmost accuracy during stereotactic laser catheter placement. Robotic devices have evolved significantly over the past two decades becoming an accurate and safe tool for stereotactic neurosurgery. Here, we present our single center experience with the MedTech ROSA ONE Brain robot for robotic guidance in laser interstitial thermal therapy (LITT) and stereotactic biopsies. We retrospectively analyzed the first 70 consecutive patients treated with ROSA device at a single academic medical center. Forty-three patients received needle biopsy immediately followed by LITT with the catheter placed with robotic guidance and 27 received stereotactic needle biopsy alone. All the procedures were performed frameless with skull bone fiducials for registration. We report data regarding intraoperative details, mortality and morbidity, diagnostic yield and lesion characteristics on MRI. Also, we describe the surgical workflow for both procedures. The mean age was 60.3 ± 15 years. The diagnostic yield was positive in 98.5% (n = 69). Sixty-three biopsies (90%) were supratentorial and seven (10%) were infratentorial. Gliomas represented 54.3% of the patients (n = 38). There were two postoperative deaths (2.8%). No permanent morbidity related to surgery were observed. We did not find intraoperative technical problems with the device. There was no need to reposition the needle after the initial placement. Stereotactic robotic guided placement of laser ablation catheters and biopsy needles is safe, accurate, and can be implemented into a neurosurgical workflow.

The Path to Surgical Robotics in Neurosurgery

Robotic systems may help efficiently execute complicated tasks that require a high degree of accuracy, and this, in large part, explains why robotics have garnered widespread use in a variety of neurosurgical applications, including intracranial biopsies, spinal instrumentation, and placement of intracranial leads. The use of robotics in neurosurgery confers many benefits, and inherent limitations, to both surgeons and their patients. In this narrative review, we provide a historical overview of robotics and its implementation across various surgical specialties, and discuss the various robotic systems that have been developed specifically for neurosurgical applications. We also discuss the relative advantages of robotic systems compared to traditional surgical techniques, particularly as it pertains to integration of image guidance with the ability of the robotic arm to reliably execute pre-planned tasks. As more neurosurgeons adopt the use of robotics in their practice, we postulate that further technological advancements will become available that will help achieve improved technical capabilities, user experience, and overall patient clinical outcomes.

Design and Modelling of a Continuum Robot for Distal Lung Sampling in Mechanically Ventilated Patients in Critical Care

In this paper, we design and develop a novel robotic bronchoscope for sampling of the distal lung in mechanically-ventilated (MV) patients in critical care units. Despite the high cost and attributable morbidity and mortality of MV patients with pneumonia which approaches 40%, sampling of the distal lung in MV patients suffering from range of lung diseases such as Covid-19 is not standardised, lacks reproducibility and requires expert operators. We propose a robotic bronchoscope that enables repeatable sampling and guidance to distal lung pathologies by overcoming significant challenges that are encountered whilst performing bronchoscopy in MV patients, namely, limited dexterity, large size of the bronchoscope obstructing ventilation, and poor anatomical registration. We have developed a robotic bronchoscope with 7 Degrees of Freedom (DoFs), an outer diameter of 4.5 mm and inner working channel of 2 mm. The prototype is a push/pull actuated continuum robot capable of dexterous manipulation inside the lung and visualisation/sampling of the distal airways. A prototype of the robot is engineered and a mechanics-based model of the robotic bronchoscope is developed. Furthermore, we develop a novel numerical solver that improves the computational efficiency of the model and facilitates the deployment of the robot. Experiments are performed to verify the design and evaluate accuracy and computational cost of the model. Results demonstrate that the model can predict the shape of the robot in <0.011s with a mean error of 1.76 cm, enabling the future deployment of a robotic bronchoscope in MV patients.

A Historical Review of Medical Robotic Platforms

This paper provides a brief history of medical robotic systems. Since the first use of robots in medical procedures, there have been countless companies competing to developed robotic systems in hopes to dominate a field. Many companies have succeeded, and many have failed. This review paper shows the timeline history of some of the old and most successful medical robots and new robotic systems. As the patents of the most successful system, i.e., Da Vinci® Surgical System, have expired or are expiring soon, this paper can provide some insights for new designers and manufacturers to explore new opportunities in this field.

Robotic Surgical Approach to the Mesial Temporal Region: A Preliminary Three-Dimensional Cadaveric Study of Technical Feasibility

OBJECTIVE

Robotic surgical systems are used worldwide in various fields. In this study, we present the advantages and disadvantages of the most common robotic surgical system, the da Vinci Xi system, in the supracerebellar transtentorial approach to the mesial temporal region and discuss options for its integration into neurosurgery.

METHODS

Our study was conducted at the Advanced Simulation and Applied Endoscopic Surgery Training and Research Center and Anatomy Laboratory. Four formalin-fixed human cadaveric head specimens with red silicone dye injected into their arterial structures and blue silicone dye injected into their venous structures were used in the study. Dissections were performed in microscopic and robotic stages. All phases were photographed using a three-dimensional photographic technique.

RESULTS

The mesial temporal lobe could be accessed via the supracerebellar transtentorial route with the use of the robotic system. We show that the robotic system can be used in difficult approaches and narrow regions with a wider exposure and superior image quality than with the microscopic approach, improving the ergonomics for the surgeon. The shortcomings of robotic systems are examined and innovative solutions are offered.

CONCLUSIONS

This study shows the advantages and disadvantages of the robotic surgical approach to the mesial temporal region via the supracerebellar transtentorial route. Robotic surgical systems can play a major role in neurosurgical practices with the tools designed and the innovative solutions determined in this study. Nevertheless, further research and development of these systems and related instruments are necessary to ensure their wider implementation in neurosurgery.

A Fully Actuated Robotic Assistant for MRI-Guided Precision Conformal Ablation of Brain Tumors

This paper reports the development of a fully actuated robotic assistant for magnetic resonance imaging (MRI)-guided precision conformal ablation of brain tumors using an interstitial high intensity needle-based therapeutic ultrasound (NBTU) ablator probe. The robot is designed with an eight degree-of-freedom (DOF) remote center of motion (RCM) manipulator driven by piezoelectric actuators, five for aligning the ultrasound thermal ablator to the target lesions and three for inserting and orienting the ablator and its cannula to generate a desired ablation profile. The 8-DOF fully actuated robot can be operated in the scanner bore during imaging; thus, alleviating the need of moving the patient in or out of the scanner during the procedure, and therefore potentially reducing the procedure time and streamlining the workflow. The free space positioning accuracy of the system is evaluated with the OptiTrack motion capture system, demonstrating the root mean square (RMS) error of the tip position to be 1.11±0.43mm. The system targeting accuracy in MRI is assessed with phantom studies, indicating the RMS errors of the tip position to be 1.45±0.66mm and orientation to be 1.53±0.69°. The feasibility of the system to perform thermal ablation is validated through a preliminary ex-vivo tissue study with position error less than 4.3mm and orientation error less than 4.3°.

Neuroendovascular-specific engineering modifications to the CorPath GRX Robotic System

OBJECTIVE

The aim of this study was to evaluate new, neuroendovascular-specific engineering and software modifications to the CorPath GRX Robotic System for their ability to support safer and more effective cranial neurovascular interventions in a preclinical model.

METHODS

Active device fixation (ADF) control software, permitting automated manipulation of the guidewire relative to the microcatheter, and a modified drive cassette suitable for neuroendovascular instruments were the respective software and hardware modifications to the current CorPath GRX robot, which was cleared by the FDA for percutaneous coronary and peripheral vascular intervention. The authors then trialed the modified system in a live porcine model with simulated neuroendovascular pathology. Femoral access through the aortic arch to the common carotid artery was accomplished manually (without robotic assistance), and the remaining endovascular procedures were performed with robotic assistance. The system was tested for the enhanced ability to navigate and manipulate neurovascular-specific guidewires and microcatheters. The authors specifically evaluated the movement of the wire forward and backward during the advancement of the microcatheter.

RESULTS

Navigation of the rete mirabile and an induced aneurysm within the common carotid artery were successful. The active device fixation feature enabled independent advancement and retraction of the guidewire and working device relative to the microcatheter. When ADF was inactive, the mean forward motion of the guidewire was 5 mm and backward motion was 0 mm. When ADF was active, the mean forward motion of the guidewire was 0 mm and backward motion was 1.5 mm. The modifications made to the robotic cassette enabled the system to successfully manipulate the microcatheter and guidewire safely and in a manner more suited to neuroendovascular procedures than before. There were no occurrences of dissection, extravasation, or thrombosis.

CONCLUSIONS

The robotic system was originally designed to navigate and manipulate devices for cardiac and peripheral vascular intervention. The current modifications described here improved its utility for the more delicate and tortuous neurovascular environment. This will set the stage for the development of a neurovascular-specific robot.

Robotic oesophago-gastric cancer surgery

A postoperative complications rate of nearly 50% has compelled oesophago-gastric practice to adopt minimally invasive techniques such as robotic surgery

Robotics in neurosurgery

One of the first surgical specialties to adopt robotic procedures and one that continues to innovate

Robot Integrated User Interface for Physical Interaction with the DLR MIRO in Versatile Medical Procedures

To enhance the capability of the DLR MIRO for physical human robot interaction (pHRI), six buttons were integrated as additional input interface along the robot structure. A ring of eight RGB-LEDs at the instrument interface informs the user as additional output interface about the robot’s state. The mechatronic design, which is transferable to other robots, adapts to the existing communication infrastructure of the robot and therefore offers real-time capability. Besides the interaction with the robot itself, it also allows the control of third party devices connected to its communication network. Both interfaces can be flexibly programmed e.g. in C++ or Simulink.

State of the art of robotic surgery related to vision: brain and eye applications of newly available devices

Background

Robot-assisted surgery has revolutionized many surgical subspecialties, mainly where procedures have to be performed in confined, difficult to visualize spaces. Despite advances in general surgery and neurosurgery, in vivo application of robotics to ocular surgery is still in its infancy, owing to the particular complexities of microsurgery. The use of robotic assistance and feedback guidance on surgical maneuvers could improve the technical performance of expert surgeons during the initial phase of the learning curve.

Evidence acquisition

We analyzed the advantages and disadvantages of surgical robots, as well as the present applications and future outlook of robotics in neurosurgery in brain areas related to vision and ophthalmology.

Discussion

Limitations to robotic assistance remain, that need to be overcome before it can be more widely applied in ocular surgery.

Conclusion

There is heightened interest in studies documenting computerized systems that filter out hand tremor and optimize speed of movement, control of force, and direction and range of movement. Further research is still needed to validate robot-assisted procedures.

Robot-Assisted Stereotactic Biopsy of Diffuse Intrinsic Pontine Glioma: A Single-Center Experience

BACKGROUND

Diffuse intrinsic pontine glioma (DIPG) is a childhood tumor with a dismal prognosis. Emerging molecular signatures have paved the way for stereotactic biopsy in selected centers. We present our experience in DIPG stereotactic needle biopsy using the Robotic Stereotactic-Assisted system (ROSA) in a series of consecutive pediatric patients.

METHODS

All stereotactic biopsy procedures for DIPG performed during the last year at our institution were considered. All procedures were carried out using the ROSA surgical assistant through a precoronary approach. All children underwent a postoperative computed tomography scan to document possible surgical complications and confirm the site of biopsy. Postoperative clinical changes were recorded to test morbidity of the procedure.

RESULTS

In the last year, we performed 7 pontine needle biopsies. Specimens were diagnostic and useful for molecular analysis in all cases. No surgical complications were observed. One child showed a transient neurologic worsening related to the biopsy that resolved within 2 weeks. The combination of the precoronary approach and use of the stereotactic ROSA system allowed single-session surgeries in all cases.

CONCLUSIONS

Pontine biopsy for DIPG is a safe procedure in selected centers. The advantages of the single-session procedure we described might be of particular interest in the pediatric setting.

Neurosurgical robotic arm drilling navigation system

BACKGROUND

The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process.

METHODS

The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled-through. Three kinds of experiment were designed.

RESULTS

The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto-stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non-drilled-through cases (8.42% and 4.21% in control groups 1 and 2).

CONCLUSIONS

The system may be useful for neurosurgical robotic arm drilling navigation.

Stereotactic robot-assisted MRI-guided laser thermal ablation of radiation necrosis in the posterior cranial fossa: technical note

Laser interstitial thermal therapy (LITT) is a minimally invasive procedure used to treat a variety of intracranial lesions. Utilization of robotic assistance with stereotactic procedures has gained attention due to potential for advantages over conventional techniques. The authors report the first case in which robot-assisted MRI-guided LITT was used to treat radiation necrosis in the posterior fossa, specifically within the cerebellar peduncle. The use of a stereotactic robot allowed the surgeon to perform LITT using a trajectory that would be extremely difficult with conventional arc-based techniques.

A 60-year-old man presented with facial weakness and brainstem symptoms consistent with radiation necrosis. He had a history of anaplastic astrocytoma that was treated with CyberKnife radiosurgery 1 year prior to presentation, and he did well for 11 months until his symptoms recurred. The location and form of the lesion precluded excision but made the patient a suitable candidate for LITT. The location and configuration of the lesion required a trajectory for LITT that was too low for arc-based stereotactic navigation, and thus the ROSA robot (Medtech) was used. Using preoperative MRI acquisitions, the lesion in the posterior fossa was targeted. Bone fiducials were used to improve accuracy in registration, and the authors obtained an intraoperative CT image that was then fused with the MR image by the ROSA robot. They placed the laser applicator and then ablated the lesion under real-time MR thermometry. There were no complications, and the patient tolerated the procedure well. Postoperative 2-month MRI showed complete resolution of the lesion, and the patient had some improvement in symptoms.

Medical telerobotic systems: current status and future trends

Teleoperated medical robotic systems allow procedures such as surgeries, treatments, and diagnoses to be conducted across short or long distances while utilizing wired and/or wireless communication networks. This study presents a systematic review of the relevant literature between the years 2004 and 2015, focusing on medical teleoperated robotic systems which have witnessed tremendous growth over the examined period. A thorough insight of telerobotics systems discussing design concepts, enabling technologies (namely robotic manipulation, telecommunications, and vision systems), and potential applications in clinical practice is provided, while existing limitations and future trends are also highlighted. A representative paradigm of the short-distance case is the da Vinci Surgical System which is described in order to highlight relevant issues. The long-distance telerobotics concept is exemplified through a case study on diagnostic ultrasound scanning. Moreover, the present review provides a classification into short- and long-distance telerobotic systems, depending on the distance from which they are operated. Telerobotic systems are further categorized with respect to their application field. For the reviewed systems are also examined their engineering characteristics and the employed robotics technology. The current status of the field, its significance, the potential, as well as the challenges that lie ahead are thoroughly discussed.

Robotics in Neurosurgery: Evolution, Current Challenges, and Compromises

BACKGROUND

Advances in technology have pushed the boundaries of neurosurgery. Surgeons play a major role in the neurosurgical field, but robotic systems challenge the current status quo. Robotic-assisted surgery has revolutionized several surgical fields, yet robotic-assisted neurosurgery is limited by available technology.

METHODS

The literature on the current robotic systems in neurosurgery and the challenges and compromises of robotic design are reviewed and discussed.

RESULTS

Several robotic systems are currently in use, but the application of these systems is limited in the field of neurosurgery. Most robotic systems are suited to assist in stereotactic procedures. Current research and development teams focus on robotic-assisted microsurgery and minimally invasive surgery. The tasks of miniaturizing the current tools and maximizing control challenge manufacturers and hinder progress. Furthermore, loss of haptic feedback, proprioception, and visualization increase the time it takes for users to master robotic systems.

CONCLUSIONS

Robotic-assisted surgery is a promising field in neurosurgery, but improvements and breakthroughs in minimally invasive and endoscopic robotic-assisted surgical systems must occur before robotic assistance becomes commonplace in the neurosurgical field.

Development and preliminary assessment of a robotic platform for neuroendoscopy based on a lightweight robot

BACKGROUND

Ventriculostomy is a widely performed neurosurgical procedure; some risk factors can be mitigated by computer/robot-assisted approaches. Platforms fostering synergistic robot-surgeon integration are pursued, for which lightweight robots with compliant controlled joints must be assessed (because compliance hampers accuracy).

METHODS

We developed a platform encompassing, in particular, a lightweight robot and an optical tracker also used to enhance robot accuracy. Based on specifications by neurosurgeons, we designed a neuroendoscope-handling interface and assessed targeting accuracy in a model ventriculostomy where the robot was operated both autonomously and in hands-on (i.e. co-operative) mode.

RESULTS

Targeting errors were systematically below the procedure accuracy threshold (1 mm); the rms targeting errors were 0.51 and 0.54 mm for autonomous and hands-on control, respectively. No significant difference was observed between the considered control modes. Very positive feedback was gathered from neurosurgeons.

CONCLUSIONS

Accurate tool targeting under both autonomous and hands-on control was achieved.