Robotic-Assisted Minimally Invasive Cranial Neurosurgery: Surgical Applications and Anatomy—A Systematic Review

Abstract

BACKGROUND: The adoption of robotic systems in cranial neurosurgery remains limited, with most applications confined to stereotactic procedures. However, recent advancements in robotic engineering and the rise of minimally invasive neurosurgery have renewed interest in their transcranial and skull base applications. This systematic review analyzes current uses, technical limitations, and translational potential of robotic-assisted cranial neurosurgery. METHODS: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines, a systematic review of 3 databases was conducted. Eligible studies included robot-assisted cranial procedures (transcranial, transnasal, or transoral) beyond stereotactic navigation or endoscope-holding. Exclusion criteria comprised spinal, peripheral nerve, and purely endoscopic or non-neurosurgical interventions. Extracted data included study type, robotic platform, approach, and outcomes. RESULTS: Twenty-seven studies (2002-2025) met inclusion criteria: 19 preclinical, 6 clinical, and 2 translational. Most preclinical studies used human donor heads or synthetic phantoms to simulate transnasal or transcranial robotic access. Clinical reports included skull base resections, third ventriculostomy, orbital tumor surgery, and microvascular anastomosis. The da Vinci system was most commonly used, while platforms like NeuRobot, Concentric Tube Robots, and SmartArm offered superior dexterity in confined spaces. Despite limitations such as bulk and lack of haptics, early clinical data support feasibility for robotic-assisted keyhole and skull base cranial procedures. CONCLUSIONS: Robotics holds promise for minimally invasive cranial neurosurgery, but current systems are suboptimal for keyhole access. Targeted translational studies are needed to refine robotic design, optimize trajectory compatibility, and evaluate materials suited to cranial microsurgical demands. Future developments should focus on miniaturized, neuronavigation-compatible platforms tailored for high-precision intracranial manipulation.