The Changing Face of Technologically Integrated Neurosurgery: Today's High-Tech Operating Room

Neuro-oncology access in Sub-Saharan Africa: A literature review of challenges and opportunities

Background

Ensuring equitable access to treatments and therapies in the constantly evolving field of neuro-oncology is an imperative global health issue. With its unique demographic, cultural, socioeconomic, and infrastructure characteristics, Sub-Saharan Africa faces distinct challenges. This literature review highlights specific barriers to neuro-oncology care in the region and explores potential opportunities for enhancing access.

Methods

Predetermined keyword searches were employed to screen titles and abstracts using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. Inclusion criteria were studies published between January 1, 2003, and June 20, 2023, specifically addressing the capacity and challenges of neuro-oncology in the Sub-Saharan African region. The data sources queried were PubMed and Google Scholar. Systematic reviews and meta-analyses were deliberately excluded. All authors conducted independent screening and structured data extraction meticulously.

Results

Our paper identified multiple challenges that impede access to quality treatment for brain tumors. These include constrained resources, insufficient training of healthcare professionals, certain cultural beliefs, and a general lack of awareness about brain tumors, all contributing to delayed diagnosis and treatment. Furthermore, the lack of detailed data on the incidence and prevalence of primary central nervous system tumors impairs the accurate assessment of disease burden and precise identification of areas requiring improvement. However, we discovered that ongoing research, advocacy, enhanced training, mentorship, and collaborative efforts present valuable opportunities for substantial progress in neuro-oncology access.

Conclusions

While we provide a glimpse of the current state, we hope these results will help stimulate dialogue and catalyze initiatives to surmount highlighted obstacles and improve neuro-oncology outcomes across Sub-Saharan Africa.

Exoscopic Microsurgery: A Change of Paradigm in Brain Tumor Surgery? Comparison with Standard Operative Microscope

BACKGROUND

The exoscope is a high-definition telescope recently introduced in neurosurgery. In the past few years, several reports have described the advantages and disadvantages of such technology. No studies have compared results of surgery with standard microscope and exoscope in patients with glioblastoma multiforme (GBM).

METHODS

Our retrospective study encompassed 177 patients operated on for GBM (WHO 2021) between February 2017 and August 2022. A total of 144 patients were operated on with a microscope only and the others with a 3D4K exoscope only. All clinical and radiological data were collected. Progression-free survival (PFS) and overall survival (OS) have been estimated in the two groups and compared by the Cox model adjusting for potential confounders (e.g., sex, age, Karnofsky performance status, gross total resection, MGMT methylated promoter, and operator's experience).

RESULTS

IDH was mutated in 9 (5.2%) patients and MGMT was methylated in 76 (44.4%). Overall, 122 patients received a gross total resection, 14 patients received a subtotal resection, and 41 patients received a partial resection. During follow-up, 139 (73.5%) patients experienced tumor recurrence and 18.7% of them received a second surgery. After truncation to 12 months, the median PFS for patients operated on with the microscope was 8.82 months, while for patients operated on with the exoscope it was >12 months. Instead, the OS was comparable in the two groups. The multivariable Cox model showed that the use of microscope compared to the exoscope was associated with lower progression-free survival (hazard ratio = 3.55, 95%CI = 1.66-7.56, p = 0.001).

CONCLUSIONS

The exoscope has proven efficacy in terms of surgical resection, which was not different to that of the microscope. Furthermore, patients operated on with the exoscope had a longer PFS. A comparable OS was observed between microscope and exoscope, but further prospective studies with longer follow-up are needed.

Machine Learning-Based Surgical Planning for Neurosurgery: Artificial Intelligent Approaches to the Cranium

Objectives

Artificial intelligence (AI) applications in neurosurgery have an increasing momentum as well as the growing number of implementations in the medical literature. In recent years, AI research define a link between neuroscience and AI. It is a connection between knowing and understanding the brain and how to simulate the brain. The machine learning algorithms, as a subset of AI, are able to learn with experiences, perform big data analysis, and fulfill human-like tasks. Intracranial surgical approaches that have been defined, disciplined, and developed in the last century have become more effective with technological developments. We aimed to define individual-safe, intracranial approaches by introducing functional anatomical structures and pathological areas to artificial intelligence.

Methods

Preoperative MR images of patients with deeply located brain tumors were used for planning. Intracranial arteries, veins, and neural tracts are listed and numbered. Voxel values of these selected regions in cranial MR sequences were extracted and labeled. Tumor tissue was segmented as the target. Q-learning algorithm which is a model-free reinforcement learning algorithm was run on labeled voxel values (on optimal paths extracted from the new heuristic-based path planning algorithm), then the algorithm was assigned to list the cortico-tumoral pathways that aim to remove the maximum tumor tissue and in the meantime that functional anatomical tissues will be least affected.

Results

The most suitable cranial entry areas were found with the artificial intelligence algorithm. Cortico-tumoral pathways were revealed using Q-learning from these optimal points.

Conclusions

AI will make a significant contribution to the positive outcomes as its use in both preoperative surgical planning and intraoperative technique equipment assisted neurosurgery, its use increased.

Robotics for neuroendovascular intervention: Background and primer

The simultaneous growth of robotic-assisted surgery and telemedicine in recent years has only been accelerated by the recent coronavirus disease 2019 pandemic. Robotic assistance for neurovascular intervention has garnered significant interest due to opportunities for tele-stroke models of care for remote underserved areas. Lessons learned from medical robots in interventional cardiology and neurosurgery have contributed to incremental but vital advances in medical robotics despite important limitations. In this article, we discuss robot types and their clinical justification and ethics, as well as a general overview on available robots in thoracic/abdominal surgery, neurosurgery, and cardiac electrophysiology. We conclude with current clinical research in neuroendovascular intervention and a perspective on future directions.

Efficacy of an opioid-sparing analgesic protocol in pain control after less invasive cranial neurosurgery

An opioid-sparing protocol for postoperative pain management in less invasive cranial neurosurgery significantly lowered opioid usage while reducing pain scores.

Introduction:

Opioid overuse in postoperative patients is a worrisome trend, and potential alternatives exist which warrant investigation. Nonsteroidal anti-inflammatory drug use in treating postoperative cranial surgery pain has been hampered by concern for inadequate pain control and increased risk of hemorrhagic complications. A safe and effective alternative to opioid-based pain management is critical to improving postoperative care.

Objective:

The objective of this retrospective study was to determine whether an NSAID-based opioid-sparing pain management protocol (OSP) is effective in analgesic control of less invasive cranial surgery patients at 6-, 12-, and 24-hour postoperatively. Secondary aims included investigating differences in hemorrhagic complications.

Methods:

Five hundred sixty-six consecutive patients who underwent cranial surgery before and after implementation of the celecoxib-based OSP were eligible. Propensity score matching was used to match patients in each cohort.

Results:

The opioid-sparing cohort had lower pain scores at 6 hours (3.45 vs 4.19, P = 0.036), 12 hours (3.21 vs 4.00, P = 0.006), and 24 hours (2.90 vs 3.59, P = 0.010). Rates of postoperative hemorrhage were not significantly different (5% intervention vs 8% control, P = 0.527). The opioid-sparing pain management protocol provided comparable or better pain control in the first 24 hours after less invasive cranial surgery. Hemorrhage rates did not change with the use of an NSAID-based OSP.

Conclusion:

An effective alternative to the current standard opioid-based pain management is feasible for less invasive cranial surgery. Determinations of hemorrhage risk and more complex cranial surgery will require larger prospective randomized trials.

Acquisition of Basic Micro-Neurosurgical Skills Using Cavitron Ultrasonic Aspirator in Low-Cost Readily Available Models: The Egg Model

BACKGROUND

Attainment of micro-neurosurgical skills is a challenge in teaching hospitals throughout training. Models that mimic the workflow as well as haptics are time-consuming, expensive, and unsuitable to serve as a routine platform. Our objective was to present a model and a set of tasks, based on a hard-boiled egg, microscope, and a Cavitron ultrasonic aspirator (CUSA; Integra Lifesciences Corp., Tullamore, Ireland), which is cheap, easy to setup and can be used for training microsurgery and CUSA skills, required for removal of deep-seated tumors.

METHODS

The goal was to remove the egg yolk from within a hard-boiled egg, representing an intrinsic brain tumor, surrounded by the egg's white, representing adjacent brain tissue, while preserving it. Assessment was based on the yolk's exposure, completeness of removal, and collateral damage and task completion duration, with repeated trials (n = 4), for validation purposes, for 6 operators with different experience levels.

RESULTS

Improvement in overall score (mean of 47.5 ± 19 in the first trial vs. 80.0 ± 12 in the fourth trial, P < 0.01), and task duration completion (mean initial duration of 21:25 ± 4:52 minutes to 15:30 ± 5:17 minutes, P < 0.01) was observed. Parameters gradually improved on repeated attempts, and experience level of the operators correlated with scores.

CONCLUSIONS

The egg model is an easy-to-handle, cheap model that enables the acquisition of basic micro-neurosurgical skills and basic workflow required for removing of intrinsic brain tumors. This study has validated and defined reproducible tasks that can be scored, correlated with performance. This model can be incorporated into a resident's routine and potentially provide an accessible training platform for neurosurgical trainees.

Stereoscopy in Surgical Neuroanatomy: Past, Present, and Future

Since the dawn of antiquity, scientists, philosophers, and artists have pondered the nature of optical stereopsis-the perception of depth that arises from binocular vision. The early 19th century saw the advent of stereoscopes, devices that could replicate stereopsis by producing a 3D illusion from the super-imposition of 2D photographs. This phenomenon opened up a plethora of possibilities through its usefulness as an educational tool-particularly in medicine. Before long, photographers, anatomists, and physicians were collaborating to create some of the first stereoscopic atlases available for the teaching of medical students and residents. In fields like neurosurgery-where a comprehensive visuospatial understanding of neuro-anatomical correlates is crucial-research into stereoscopic modalities are of fundamental importance. Already, medical institutions all over the world are capitalizing on new and immersive technologies-such as 3D intraoperative recording, and 3D endoscopes-to refine their pedagogical efforts as well as improve their clinical capacities. The present paper surveys the history of stereoscopy from antiquity to the modern era-with a focus on its role in neurosurgery and medical education. Through the tracking of this evolution, we can discuss potential benefits, future directions, and highlight areas in which further research is needed. By anticipating these factors, we may strive to take full advantage of an emergent field of technology, for our ultimate goal of improving patient care.

On-Demand Intraoperative 3-Dimensional Printing of Custom Cranioplastic Prostheses

BACKGROUND

Currently, implantation of patient-specific cranial prostheses requires reoperation after a period for design and formulation by a third-party manufacturer. Recently, 3-dimensional (3D) printing via fused deposition modeling has demonstrated increased ease of use, rapid production time, and significantly reduced costs, enabling expanded potential for surgical application. Three-dimensional printing may allow neurosurgeons to remove bone, perform a rapid intraoperative scan of the opening, and 3D print custom cranioplastic prostheses during the remainder of the procedure.

OBJECTIVE

To evaluate the feasibility of using a commercially available 3D printer to develop and produce on-demand intraoperative patient-specific cranioplastic prostheses in real time and assess the associated costs, fabrication time, and technical difficulty.

METHODS

Five different craniectomies were each fashioned on 3 cadaveric specimens (6 sides) to sample regions with varying topography, size, thickness, curvature, and complexity. Computed tomography-based cranioplastic implants were designed, formulated, and implanted. Accuracy of development and fabrication, as well as implantation ability and fit, integration with exiting fixation devices, and incorporation of integrated seamless fixation plates were qualitatively evaluated.

RESULTS

All cranioprostheses were successfully designed and printed. Average time for design, from importation of scan data to initiation of printing, was 14.6 min and average print time for all cranioprostheses was 108.6 min.

CONCLUSION

On-demand 3D printing of cranial prostheses is a simple, feasible, inexpensive, and rapid solution that may help improve cosmetic outcomes; significantly reduce production time and cost-expanding availability; eliminate the need for reoperation in select cases, reducing morbidity; and has the potential to decrease perioperative complications including infection and resorption.

Machine learning applications to clinical decision support in neurosurgery: an artificial intelligence augmented systematic review

Machine learning (ML) involves algorithms learning patterns in large, complex datasets to predict and classify. Algorithms include neural networks (NN), logistic regression (LR), and support vector machines (SVM). ML may generate substantial improvements in neurosurgery. This systematic review assessed the current state of neurosurgical ML applications and the performance of algorithms applied. Our systematic search strategy yielded 6866 results, 70 of which met inclusion criteria. Performance statistics analyzed included area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, and specificity. Natural language processing (NLP) was used to model topics across the corpus and to identify keywords within surgical subspecialties. ML applications were heterogeneous. The densest cluster of studies focused on preoperative evaluation, planning, and outcome prediction in spine surgery. The main algorithms applied were NN, LR, and SVM. Input and output features varied widely and were listed to facilitate future research. The accuracy (F_(2,19) = 6.56, p < 0.01) and specificity (F_(2,16) = 5.57, p < 0.01) of NN, LR, and SVM differed significantly. NN algorithms demonstrated significantly higher accuracy than LR. SVM demonstrated significantly higher specificity than LR. We found no significant difference between NN, LR, and SVM AUC and sensitivity. NLP topic modeling reached maximum coherence at seven topics, which were defined by modeling approach, surgery type, and pathology themes. Keywords captured research foci within surgical domains. ML technology accurately predicts outcomes and facilitates clinical decision-making in neurosurgery. NNs frequently outperformed other algorithms on supervised learning tasks. This study identified gaps in the literature and opportunities for future neurosurgical ML research.