Robotics in neurosurgery: Current prevalence and future directions

The Feasibility of Robot-assisted Laser Interstitial Thermal Therapy (LITT) for Brain Tumors in Octogenarians

BACKGROUND

The use of robot-assisted laser interstitial thermal therapy (LITT) is emerging as a viable treatment option for brain tumors in patients aged 80-90 years (octogenarians). Correspondingly, the aim of this study was to describe the clinical feasibility of octogenarians undergoing LITT procedure for brain tumors at our institution.

METHODS

A retrospective review was conducted of all robot-assisted LITT procedures performed at our institution between 2013 and 2023 for octogenarians. Comparison of continuous variables was by Student t tests, and Kaplan-Meier estimates were used to estimate survival outcomes.

RESULTS

A total of 20 of 311 (6%) LITT patients in the search cohort were octogenarians. Mean age was 82.6 years (range, 80.1-88.0 years) with 13 (65%) female patients. Brain tumor lesions most commonly were located on the left side (65%), and, for ablation, all were single trajectories with mean number of 2.3 ablations. No operative complications were seen during hospitalization, with mean length of stay of 1.6 days and most common disposition destination being home (95%). There were no 30- or 90-day readmissions or emergency department presentations. Mean follow-up was 12.4 months without any complications in that time. The most common pathology in our cohort was glioblastoma (55%).

CONCLUSIONS

Robot-assisted LITT is a safe and effective treatment option for brain tumors in octogenarians with a very low morbidity risk. Therefore, further investigation is required to understand how LITT can translate to therapeutic benefit in patients aged over 80 years old with brain tumors.

7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery

Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in artificial intelligence (AI) and robot-assisted neurosurgery. The potential of submillimetre fMRI mapping can help better appreciate uncertainty on resection margins, though geometric distortions at UHF might lessen the accuracy of fMRI maps. A useful trade-off for UHF fMRI is to collect data with 1-mm isotropic resolution to ensure high sensitivity and subsequently a low risk of false negatives. Scanning at UHF might yield a revival interest in slow event-related fMRI, thereby offering a richer depiction of the dynamics of fMRI responses. The potential applications of AI concern denoising and artefact removal, generation of super-resolution fMRI maps, and accurate fusion or coregistration between anatomical and fMRI maps. The latter can benefit from the use of T1-weighted echo-planar imaging for better visualization of brain activations. Such AI-augmented fMRI maps would provide high-quality input data to robotic surgery systems, thereby improving the accuracy and reliability of robot-assisted neurosurgery. Ultimately, the advancement in fMRI at UHF would promote clinically useful synergies between fMRI, AI, and robotic neurosurgery.Relevance statement This review highlights the potential synergies between fMRI at UHF, AI, and robotic neurosurgery in improving the accuracy and reliability of fMRI-based presurgical mapping.Key points• Presurgical fMRI mapping at UHF improves spatial resolution and sensitivity.• Slow event-related designs offer a richer depiction of fMRI responses dynamics.• AI can support denoising, artefact removal, and generation of super-resolution fMRI maps.• AI-augmented fMRI maps can provide high-quality input data to robotic surgery systems.

Artificial Intelligence in Endodontic Education

AIMS

The future dental and endodontic education must adapt to the current digitalized healthcare system in a hyper-connected world. The purpose of this scoping review was to investigate the ways an endodontic education curriculum could benefit from the implementation of artificial intelligence (AI) and overcome the limitations of this technology in the delivery of healthcare to patients.

METHODS

An electronic search was carried out up to December 2023 using MEDLINE, Web of Science, Cochrane Library, and a manual search of reference literature. Grey literature, ongoing clinical trials were also searched using ClinicalTrials.gov.

RESULTS

The search identified 251 records, of which 35 were deemed relevant to artificial intelligence (AI) and Endodontic education. Areas in which AI might aid students with their didactic and clinical endodontic education were identified as follows: 1) radiographic interpretation; 2) differential diagnosis; 3) treatment planning and decision-making; 4) case difficulty assessment; 5) preclinical training; 6) advanced clinical simulation and case-based training, 7) real-time clinical guidance; 8) autonomous systems and robotics; 9) progress evaluation and personalized education; 10) calibration and standardization.

CONCLUSIONS

AI in endodontic education will support clinical and didactic teaching through individualized feedback; enhanced, augmented, and virtually generated training aids; automated detection and diagnosis; treatment planning and decision support; and AI-based student progress evaluation, and personalized education. Its implementation will inarguably change the current concept of teaching Endodontics. Dental educators would benefit from introducing AI in clinical and didactic pedagogy; however, they must be aware of AI's limitations and challenges to overcome.

Revitalizing neurosurgical frontiers: The EANS frontiers in neurosurgery committee's strategic framework

Introduction

The field of neurosurgery faces challenges with the increasing involvement of other medical specialties in areas traditionally led by neurosurgeons. This paper examines the implications of this development for neurosurgical practice and patient care, with a focus on specialized areas like pain management, peripheral nerve surgery, and stereotactic radiosurgery.

Research question

To assess the implications of the expanded scope of other specialties for neurosurgical practice and to consider the response of the EANS Frontiers in Neurosurgery Committee to these challenges.

Materials and methods

Analysis of recent trends in neurosurgery, including the shift in various procedures to other specialties, demographic challenges, and the emergence of minimally invasive techniques. This analysis draws on relevant literature and the initiatives of the Frontiers in Neurosurgery Committee.

Results

We explore a possible decrease in neurosurgical involvement in certain areas, which may have implications for patient care and access to specialized neurosurgical interventions. The Frontiers in Neurosurgery Committee's role in addressing these concerns is highlighted, particularly in terms of training, education, research, and networking for neurosurgeons, especially those early in their careers.

Discussion and conclusion

The potential decrease in neurosurgical involvement in certain specialties warrants attention. This paper emphasizes the importance of carefully considered responses by neurosurgical societies, such as the EANS, to ensure neurosurgeons continue to play a vital role in managing neurological diseases. Emphasis on ongoing education, integration of minimally invasive techniques, and multidisciplinary collaboration is essential for maintaining the field's competence and quality in patient care.

Spinal Robotics in Adult Spinal Deformity Surgery: A Systematic Review

Spinal robotics have the potential to improve the consistency of outcomes in adult spinal deformity (ASD) surgery. The objective of this paper is to assess the accuracy of pedicle and S2 alar-iliac (S2AI) screws placed with robotic guidance in ASD patients. PubMed Central, Google Scholar, and an institutional library database were queried until May 2023. Articles were included if they described ASD correction via robotic guidance and pedicle and/or S2AI screw accuracy. Articles were excluded if they described pediatric/adolescent spinal deformity or included outcomes for both ASD and non-ASD patients without separating the data. Methodological quality was assessed using the Newcastle-Ottawa scale. Primary endpoints were pedicle screw accuracy based on the Gertzbein-Robbins Scale and self-reported accuracy percentages for S2AI screws. Data were extracted for patient demographics, operative details, and perioperative outcomes and assessed using descriptive statistics. Five studies comprising 138 patients were included (mean age 66.0 years; 85 females). A total of 1,508 screws were inserted using robotic assistance (51 S2AI screws). Two studies assessing pedicle screws reported clinically acceptable trajectory rates of 98.7% and 96.0%, respectively. Another study reported a pedicle screw accuracy rate of 95.5%. Three studies reported 100% accuracy across 51 total S2AI screws. Eight total complications and 4 reoperations were reported. Current evidence supports the application of robotics in ASD surgery as safe and effective for placement of both screw types. However, due to the paucity of data, a comprehensive assessment of its incremental benefit over other techniques cannot be made. Further work using expanded cohorts is merited.

Advancements in robotic surgery: innovations, challenges and future prospects

The use of robots has revolutionized healthcare, wherein further innovations have led to improved precision and accuracy. Conceived in the late 1960s, robot-assisted surgeries have evolved to become an integral part of various surgical specialties. Modern robotic surgical systems are equipped with highly dexterous arms and miniaturized instruments that reduce tremors and enable delicate maneuvers. Implementation of advanced materials and designs along with the integration of imaging and visualization technologies have enhanced surgical accuracy and made robots safer and more adaptable to various procedures. Further, the haptic feedback system allows surgeons to determine the consistency of the tissues they are operating upon, without physical contact, thereby preventing injuries due to the application of excess force. With the implementation of teleoperation, surgeons can now overcome geographical limitations and provide specialized healthcare remotely. The use of artificial intelligence (AI) and machine learning (ML) aids in surgical decision-making by improving the recognition of minute and complex anatomical structures. All these advancements have led to faster recovery and fewer complications in patients. However, the substantial cost of robotic systems, their maintenance, the size of the systems and proper surgeon training pose major challenges. Nevertheless, with future advancements such as AI-driven automation, nanorobots, microscopic incision surgeries, semi-automated telerobotic systems, and the impact of 5G connectivity on remote surgery, the growth curve of robotic surgery points to innovation and stands as a testament to the persistent pursuit of progress in healthcare.

Clinical applications of robotic surgery platforms: a comprehensive review

Robotic surgery has expanded globally across various medical specialties since its inception more than 20 years ago. Accompanying this expansion were significant technological improvements, providing tremendous benefits to patients and allowing the surgeon to perform with more precision and accuracy. This review lists some of the different types of platforms available for use in various clinical applications. We performed a literature review of PubMed and Web of Science databases in May 2023, searching for all available articles describing surgical robotic platforms from January 2000 (the year of the first approved surgical robot, da Vinci® System, by Intuitive Surgical) until May 1st, 2023. All retrieved robotic platforms were then divided according to their clinical application into four distinct groups: soft tissue robotic platforms, orthopedic robotic platforms, neurosurgery and spine platforms, and endoluminal robotic platforms. Robotic surgical technology has undergone a rapid expansion over the last few years. Currently, multiple robotic platforms with specialty-specific applications are entering the market. Many of the fields of surgery are now embracing robotic surgical technology. We review some of the most important systems in clinical practice at this time.

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.