Search Results (19)

Background: BCI and AI-driven image segmentation are revolutionizing precision neurosurgery by enhancing surgical accuracy, reducing human error, and improving patient outcomes. Methods: This systematic review explores the integration of AI techniques—particularly DL and CNNs—with neuroimaging modalities such as MRI, CT, EEG, and ECoG for automated brain mapping and tissue classification. Eligible clinical and computational studies, primarily published between 2015 and 2025, were identified via PubMed, Scopus, and IEEE Xplore. The review follows PRISMA guidelines and is registered with the OSF (registration number: J59CY). Results: AI-based segmentation methods have demonstrated Dice similarity coefficients exceeding 0.91 in glioma boundary delineation and tumor segmentation tasks. Concurrently, BCI systems leveraging EEG and SSVEP paradigms have achieved information transfer rates surpassing 22.5 bits/min, enabling high-speed neural decoding with sub-second latency. We critically evaluate real-time neural signal processing pipelines and AI-guided surgical robotics, emphasizing clinical performance and architectural constraints. Integrated systems improve targeting precision and postoperative recovery across select neurosurgical applications. Conclusions: This review consolidates recent advancements in BCI and AI-driven medical imaging, identifies barriers to clinical adoption—including signal reliability, latency bottlenecks, and ethical uncertainties—and outlines research pathways essential for realizing closed-loop, intelligent neurosurgical platforms. Full article

This review aims to place open, laparoscopic, computerized (robotic), and image-guided robotic surgical interventions in the context of complex medical surgeries, taking into account patient well-being, staff effort, and task reliability. It deduces the specificities of each technique and subsequently focuses on image-guided interventions and their practice in staff training, preparation, and implementation of a possible autonomous intervention. These complex interventions are intended to be minimally invasive (MI), precise, and safe therapies. The accuracy of robotic positioning could be improved by reductions in complexity and uncertainty involved in the intervention procedure. These can be achieved by matching the real controlled procedure and its virtual replica. The contribution discusses considerations for staff training and/or the planning of surgical interventions using real and virtual phantoms, and the use of augmented matched digital twins (DTs) for real interventions. This paper successively approaches open, laparoscopic and robotic surgeries, image-guided robotic interventions, the control and DT monitoring of MRI-assisted interventions, MRI field ruling equations and MRI compatibility, DT monitoring involvements in surgical interventions, and it ends with a discussion and main conclusions. The different topics presented in this article, although explicit, are reinforced by examples from the literature to facilitate a deeper understanding. The outcome of this review highlights the importance of robotic imaging-assisted procedures involving MI, nonionizing, and precise interventions. It also illustrates the potential of DTs combined with digital tools to offer an effective solution for the management of these interventions. The exploitation of such a suitable digital environment allows the planning, forecasting, prospecting, training, and execution, with staff in the loop, of surgical activities in general. This methodology allows for the precise consideration of specific anatomies, particularly in microsurgery and neurosurgery. Full article

Background/Objectives: Robotic-assisted surgery has revolutionised modern medicine, enabling greater precision and control, particularly in microsurgical procedures. This systematic review evaluates the current state of robotic-assisted surgery across various specialties, focusing on four major robotic systems: Symani, Da Vinci, ZEUS, and MUSA. Methods: The review systematically analyses the effectiveness of these systems in performing vascular, lymphatic, and nervous anastomoses, comparing key metrics such as procedure time, success rates, and learning curves against manual techniques. It includes 48 studies, highlighting the technological capabilities and limitations of these systems in direct comparisons. Results: Results indicate that while robotic procedures often take longer than manual methods, significant improvements in efficiency are observed as surgeons gain experience. Conclusions: Overall, this study provides insights into the future potential of robotic-assisted surgery and highlights areas that require further research. It ultimately aims to promote the application of robotic systems in cranial neurosurgery, with a particular focus on advancing neurovascular techniques, such as microsuturing for bypass procedures. Full article

This review systematically examines the recent research from the past decade on diverse path-planning algorithms tailored for stereotactic neurosurgery applications. Our comprehensive investigation involved a thorough search of scholarly papers from Google Scholar, PubMed, IEEE Xplore, and Scopus, utilizing stringent inclusion and exclusion criteria. The screening and selection process was meticulously conducted by a multidisciplinary team comprising three medical students, robotic experts with specialized knowledge in path-planning techniques and medical robotics, and a board-certified neurosurgeon. Each selected paper was reviewed in detail, and the findings were synthesized and reported in this review. The paper is organized around three different types of intervention tools: straight needles, steerable needles, and concentric tube robots. We provide an in-depth analysis of various path-planning algorithms applicable to both single and multi-target scenarios. Multi-target planning techniques are only discussed for straight tools as there is no published work on multi-target planning for steerable needles and concentric tube robots. Additionally, we discuss the imaging modalities employed, the critical anatomical structures considered during path planning, and the current status of research regarding its translation to clinical human studies. To the best of our knowledge and as a conclusion from this systematic review, this is the first review paper published in the last decade that reports various path-planning techniques for different types of tools for minimally invasive neurosurgical applications. Furthermore, this review outlines future trends and identifies existing technology gaps within the field. By highlighting these aspects, we aim to provide a comprehensive overview that can guide future research and development in path planning for stereotactic neurosurgery, ultimately contributing to the advancement of safer and more effective neurosurgical procedures. Full article

The integration of Virtual Reality with radiology is the focus of this study. A narrative review has been proposed to delve into emerging themes within the integration of Virtual Reality in radiology by scrutinizing reviews gathered from PubMed and Scopus. The proposed approach was based on a standard narrative checklist and a qualification process. The selection process identified 20 review studies. Integration of Virtual Reality (VR) in radiology offers potential transformative opportunities also integrated with other emerging technologies. In medical education, VR and AR, using 3D images from radiology, can enhance learning, emphasizing the need for standardized integration. In radiology, VR combined with Artificial Intelligence (AI) and Augmented Reality (AR) shows promising prospectives to give a complimentary contribution to diagnosis, treatment planning, and education. Challenges in clinical integration and User Interface design must be addressed. Innovations in medical education, like 3D modeling and AI, has the potential to enable personalized learning, but face standardization challenges. While robotics play a minor role, advancements and potential perspectives are observed in neurosurgery and endovascular systems. Ongoing research and standardization efforts are crucial for maximizing the potential of these integrative technologies in healthcare. In conclusion, the synthesis of these findings underscores the opportunities for advancements in digital radiology and healthcare through the integration of VR. However, challenges exist, and continuous research, coupled with technological refinements, is imperative to unlock the full potential of these integrative approaches in the dynamic and evolving field of medical imaging. Full article

Background: We propose a three-dimensional path-planning method to generate optimized surgical trajectories for steering flexible needles along curved paths while avoiding critical tracts in the context of surgical glioma resection. Methods: Our approach is based on an application of the rapidly exploring random tree algorithm for multi-trajectory generation and optimization, with a cost function that evaluates different entry points and uses the information of MRI images as segmented binary maps to compute a safety trajectory. As a novelty, an avoidance module of the critical neuronal tracts defined by the neurosurgeon is included in the optimization process. The proposed strategy was simulated in real-case 3D environments to reach a glioma and bypass the tracts of the forceps minor from the corpus callosum. Results: A formalism is presented that allows for the evaluation of different entry points and trajectories and the avoidance of selected critical tracts for the definition of new neurosurgical approaches. This methodology can be used for different clinical cases, allowing the constraints to be extended to the trajectory generator. We present a clinical case of glioma at the base of the skull and access it from the upper area while avoiding the minor forceps tracts. Conclusions: This path-planning method offers alternative curved paths with which to reach targets using flexible tools. The method potentially leads to safer paths, as it permits the definition of groups of critical tracts to be avoided and the use of segmented binary maps from the MRI images to generate new surgical approaches. Full article

The introduction of robotic systems in medical surgery has achieved the goal of decreasing procedures’ invasiveness, positively impacting the patient’s prognosis by reducing the incision size, surgical infections, and hospitalization time. Nowadays, robotic surgery is used as an integral part of urology, gynecology, abdominal, and cardiac interventions. Despite its adoption in several surgical specialties, robotic technology remains limited in the area of microsurgery. In this paper, we present the development of a robotic system providing sub-millimeter motion resolution for the potential manipulation of fine structures. The design is based on linear delta robotic geometry. The motion, resolution, and repeatability of the developed system were simulated, followed by proof-of-concept experimental testing. The developed system achieved a motion resolution of 3.37 ± 0.17 µm in both the X- and Y-axes and 1.32 ± 0.2 µm in the Z-axis. We evaluated the system navigation, setting a zigzag trajectory with dimensions below those found in blood vessels (300 to 800 µm), and found that the system is capable of achieving a maximum resolution of 3.06 ± 0.03 µm. These results demonstrate the potential application of the here-presented robotic system for its use in microsurgical applications such as neurosurgery, plastic, and breast cancer surgeries. Full article

The landscape of cranial base surgery has undergone monumental transformations over the past several decades. This article serves as a comprehensive survey, detailing both the historical and current techniques and technologies that have propelled this field into an era of unprecedented capabilities and sophistication. In the prologue, we traverse the historical evolution from rudimentary interventions to the state-of-the-art neurosurgical methodologies that define today’s practice. Subsequent sections delve into the anatomical complexities of the anterior, middle, and posterior cranial fossa, shedding light on the intricacies that dictate surgical approaches. In a section dedicated to advanced techniques and modalities, we explore cutting-edge evolutions in minimally invasive procedures, pituitary surgery, and cranial base reconstruction. Here, we highlight the seamless integration of endocrinology, biomaterial science, and engineering into neurosurgical craftsmanship. The article emphasizes the paradigm shift towards “Functionally” Guided Surgery facilitated by intraoperative neuromonitoring. We explore its historical origins, current technologies, and its invaluable role in tailoring surgical interventions across diverse pathologies. Additionally, the digital era’s contributions to cranial base surgery are examined. This includes breakthroughs in endoscopic technology, robotics, augmented reality, and the potential of machine learning and AI-assisted diagnostic and surgical planning. The discussion extends to radiosurgery and radiotherapy, focusing on the harmonization of precision and efficacy through advanced modalities such as Gamma Knife and CyberKnife. The article also evaluates newer protocols that optimize tumor control while preserving neural structures. In acknowledging the holistic nature of cranial base surgery, we advocate for an interdisciplinary approach. The ecosystem of this surgical field is presented as an amalgamation of various medical disciplines, including neurology, radiology, oncology, and rehabilitation, and is further enriched by insights from patient narratives and quality-of-life metrics. The epilogue contemplates future challenges and opportunities, pinpointing potential breakthroughs in stem cell research, regenerative medicine, and genomic tailoring. Ultimately, the article reaffirms the ethos of continuous learning, global collaboration, and patient-first principles, projecting an optimistic trajectory for the field of cranial base surgery in the coming decade. Full article

Microsurgical techniques have been widely utilized in various surgical specialties, such as ophthalmology, neurosurgery, and otolaryngology, which require intricate and precise surgical tool manipulation on a small scale. In microsurgery, operations on delicate vessels or tissues require high standards in surgeons’ skills. This exceptionally high requirement in skills leads to a steep learning curve and lengthy training before the surgeons can perform microsurgical procedures with quality outcomes. The microsurgery robot (MSR), which can improve surgeons’ operation skills through various functions, has received extensive research attention in the past three decades. There have been many review papers summarizing the research on MSR for specific surgical specialties. However, an in-depth review of the relevant technologies used in MSR systems is limited in the literature. This review details the technical challenges in microsurgery, and systematically summarizes the key technologies in MSR with a developmental perspective from the basic structural mechanism design, to the perception and human–machine interaction methods, and further to the ability in achieving a certain level of autonomy. By presenting and comparing the methods and technologies in this cutting-edge research, this paper aims to provide readers with a comprehensive understanding of the current state of MSR research and identify potential directions for future development in MSR. Full article

Background and Objectives: Neurosurgery has been underrepresented in the medical school curriculum. Advances in augmented reality and 3D printing have opened the way for early practical training through simulations. We assessed the usability of the UpSurgeOn simulation-based training model and report first experiences from a hands-on neurosurgery course for medical students. Materials and Methods: We organized a two-day microneurosurgery simulation course tailored to medical students. On day one, three neurosurgeons demonstrated anatomical explorations with the help of life-like physical simulators (BrainBox, UpSurgeOn). The surgical field was projected onto large high-definition screens by a robotic-assisted exoscope (RoboticScope, BHS Technologies). On day two, the students were equipped with microsurgical instruments to explore the surgical anatomy of the pterional, temporal and endoscopic retrosigmoid approaches. With the help of the RoboticScope, they simulated five clipping procedures using the Aneurysm BrainBox. All medical students filled out a digital Likert-scale-based questionnaire to evaluate their experiences. Results: Sixteen medical students participated in the course. No medical students had previous experience with UpSurgeOn. All participants agreed that the app helped develop anatomical orientation. They unanimously agreed that this model should be part of residency training. Fourteen out of sixteen students felt that the course solidified their decision to pursue neurosurgery. The same fourteen students rated their learning experience as totally positive, and the remaining two rated it as rather positive. Conclusions: The UpSurgeOn educational app and cadaver-free models were perceived as usable and effective tools for the hands-on neuroanatomy and neurosurgery teaching of medical students. Comparative studies may help measure the long-term benefits of UpSurgeOn-assisted teaching over conventional resources. Full article

A minimally-invasive manipulator characterized by hyper-redundant kinematics and embedded sensing modules is presented in this work. The bending angles (tilt and pan) of the robot tip are controlled through tendon-driven actuation; the transmission of the actuation forces to the tip is based on a Bowden-cable solution integrating some channels for optical fibers. The viability of the real-time measurement of the feedback control variables, through optoelectronic acquisition, is evaluated for automated bending of the flexible endoscope and trajectory tracking of the tip angles. Indeed, unlike conventional catheters and cannulae adopted in neurosurgery, the proposed robot can extend the actuation and control of snake-like kinematic chains with embedded sensing solutions, enabling real-time measurement, robust and accurate control of curvature, and tip bending of continuum robots for the manipulation of cannulae and microsurgical instruments in neurosurgical procedures. A prototype of the manipulator with a length of 43 mm and a diameter of 5.5 mm has been realized via 3D printing. Moreover, a multiple regression model has been estimated through a novel experimental setup to predict the tip angles from measured outputs of the optoelectronic modules. The sensing and control performance has also been evaluated during tasks involving tip rotations. Full article

Personalized care models are dominating modern medicine. These models are rooted in teaching future physicians the skill set to keep up with innovation. In orthopedic surgery and neurosurgery, education is increasingly influenced by augmented reality, simulation, navigation, robotics, and in some cases, artificial intelligence. The postpandemic learning environment has also changed, emphasizing online learning and skill- and competency-based teaching models incorporating clinical and bench-top research. Attempts to improve work–life balance and minimize physician burnout have led to work-hour restrictions in postgraduate training programs. These restrictions have made it particularly challenging for orthopedic and neurosurgery residents to acquire the knowledge and skill set to meet the requirements for certification. The fast-paced flow of information and the rapid implementation of innovation require higher efficiencies in the modern postgraduate training environment. However, what is taught typically lags several years behind. Examples include minimally invasive tissue-sparing techniques through tubular small-bladed retractor systems, robotic and navigation, endoscopic, patient-specific implants made possible by advances in imaging technology and 3D printing, and regenerative strategies. Currently, the traditional roles of mentee and mentor are being redefined. The future orthopedic surgeons and neurosurgeons involved in personalized surgical pain management will need to be versed in several disciplines ranging from bioengineering, basic research, computer, social and health sciences, clinical study, trial design, public health policy development, and economic accountability. Solutions to the fast-paced innovation cycle in orthopedic surgery and neurosurgery include adaptive learning skills to seize opportunities for innovation with execution and implementation by facilitating translational research and clinical program development across traditional boundaries between clinical and nonclinical specialties. Preparing the future generation of surgeons to have the aptitude to keep up with the rapid technological advances is challenging for postgraduate residency programs and accreditation agencies. However, implementing clinical protocol change when the entrepreneur–investigator surgeon substantiates it with high-grade clinical evidence is at the heart of personalized surgical pain management. Full article

Background: Brainstem tumors are rare and extremely heterogeneous and present significant challenges in surgical treatment. Thus, biopsies often set the foundation for the diagnosis of brainstem tumors. Multimodal, image-guided, robot-assisted frameless stereotactic biopsies are increasingly popular in neurosurgery centers. This study aimed to compare the safety, efficacy, and duration of the Remebot robot-assisted (Remebot) frameless brainstem tumor biopsy versus those of frame-based stereotactic biopsy. Method: A retrospective analysis of 33 patients with brainstem tumors who underwent stereotactic brainstem biopsies in the department of neurosurgery from January 2016 to January 2021 was conducted. The patients were divided into two groups: the Remebot group (n = 22) and the frame-based group (n = 11). The clinical characteristics, trajectory strategy, duration of procedure, diagnostic yielding, histopathological diagnosis, and postoperative complications were retrospectively analyzed and compared between the groups. Results: More pediatric patients performed Remebot frameless brainstem tumor biopsy than frame-based biopsy, with a mean age of 17.3 ± 18.7 vs. 32.8 ± 17.1 (p = 0.027). The diagnostic yield had no significant difference in the two groups, with the diagnostic yield of frame-based biopsy and Remebot frameless brain biopsy being 90.9% and 95.5%, respectively. The time of the total process was 124.5 min for the frame-based biopsy and 84.7 min for the Remebot frameless brain biopsy (p < 0.001). There were no significant differences with respect to the occurrence of complication or the duration of the operation between the two groups. Conclusion: Remebot frameless stereotactic brainstem biopsy is as safe and efficacious as frame-based stereotactic biopsy. However, Remebot frameless biopsy can reduce the total duration of the procedure and has better application in young pediatric patients. Remebot frameless stereotactic biopsies can be a better option towards the safe and efficient treatment of brainstem tumors. Full article

Background: While several publications have focused on the intuitive role of augmented reality (AR) and virtual reality (VR) in neurosurgical planning, the aim of this review was to explore other avenues, where these technologies have significant utility and applicability. Methods: This review was conducted by searching PubMed, PubMed Central, Google Scholar, the Scopus database, the Web of Science Core Collection database, and the SciELO citation index, from 1989–2021. An example of a search strategy used in PubMed Central is: “Virtual reality” [All Fields] AND (“neurosurgical procedures” [MeSH Terms] OR (“neurosurgical” [All Fields] AND “procedures” [All Fields]) OR “neurosurgical procedures” [All Fields] OR “neurosurgery” [All Fields] OR “neurosurgery” [MeSH Terms]). Using this search strategy, we identified 487 (PubMed), 1097 (PubMed Central), and 275 citations (Web of Science Core Collection database). Results: Articles were found and reviewed showing numerous applications of VR/AR in neurosurgery. These applications included their utility as a supplement and augment for neuronavigation in the fields of diagnosis for complex vascular interventions, spine deformity correction, resident training, procedural practice, pain management, and rehabilitation of neurosurgical patients. These technologies have also shown promise in other area of neurosurgery, such as consent taking, training of ancillary personnel, and improving patient comfort during procedures, as well as a tool for training neurosurgeons in other advancements in the field, such as robotic neurosurgery. Conclusions: We present the first review of the immense possibilities of VR in neurosurgery, beyond merely planning for surgical procedures. The importance of VR and AR, especially in “social distancing” in neurosurgery training, for economically disadvantaged sections, for prevention of medicolegal claims and in pain management and rehabilitation, is promising and warrants further research. Full article

Interventional surgical robots are widely used in neurosurgery to improve surgeons’ working environment and surgical safety. Based on the actual operational needs of surgeons’ feedback during preliminary in vivo experiments, this paper proposed an isomorphic interactive master controller for the master–slave interventional surgical robot. The isomorphic design of the controller allows surgeons to utilize their surgical skills during remote interventional surgeries. The controller uses the catheter and guidewire as the operating handle, the same as during actual surgeries. The collaborative operational structure design and the working methods followed the clinical operational skills. The linear force feedback and torque feedback devices were designed to improve the safety of surgeries under remote operating conditions. An eccentric force compensation was conducted to achieve accurate force feedback. Several experiments were carried out, such as calibration experiments, master–slave control performance evaluation experiments, and operation comparison experiments on the novel and previously used controllers. The experimental results show that the proposed controller can perform complex operations in remote surgery applications and has the potential for further animal experiment evaluations. Full article