This review highlights the role of minimally invasive neurosurgery and advances in AI for improving neurological outcomes in traumatic brain injury.
Traumatic brain injury (TBI) is a major global health concern, contributing to significant morbidity, mortality, and long-term disability. Traditional surgical interventions, such as open craniotomy, while effective, often result in substantial trauma and prolonged recovery. The current review explores the growing role of minimally invasive neurosurgical (MIN) techniques—including endoscopic evacuation, stereotactic aspiration, and robotic-assisted procedures—in the management of TBI. These approaches aim to reduce operative time, minimize disruption to healthy brain tissue, and improve neurological outcomes. Technological advancements, such as artificial intelligence (AI) and machine learning, have enhanced surgical planning and intraoperative precision, while personalized medicine is increasingly guiding treatment decisions based on patient-specific factors, including age, comorbidities, and genetic markers. The review also emphasizes the significance of neuroplasticity, rehabilitation, and ongoing monitoring in maximizing recovery. Although MIN techniques require specialized training and equipment and may be less effective in complex or diffuse injuries, evidence supports their use in appropriately selected patients. Multidisciplinary care models and integration of neurology and neurosurgery are essential for improving both short- and long-term outcomes. Furthermore, patient-centered outcomes, including quality of life and satisfaction, are increasingly recognized as critical metrics of success. Future directions include the development of disease-specific outcome measures, broader adoption of AI-driven tools, and continued refinement of surgical techniques to enhance precision and safety. Overall, MIN represents a transformative shift in TBI management, offering promising benefits in terms of recovery, functionality, and patient well-being.
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Rissardo et al. (2025) studied this question.
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