editorial · Frontiers in Surgery
Neurosurgical research is increasingly driven by translational science, precision diagnostics, and artificial intelligence to inform clinical decisions. Key areas of focus include intracranial neuromodulation for children with drug-resistant epilepsy, providing critical insights into seizure control. In spinal care, comparative analyses of lateral lumbar interbody fusion techniques offer guidance for complex deformity correction as instrumentation becomes more modular and patient-specific. Research on acute ischaemic stroke expands the understanding of stroke as a neuroimmunological event, identifying microglial activation and cytokine cascades as therapeutic targets. Additionally, predictive analytics using machine learning and preoperative health records help assess surgical risk for endoscopic transsphenoidal pituitary adenoma resections. Together, these developments reflect an evolving workflow where artificial intelligence and advanced clinical insights personalize care across diverse neurosurgical subspecialties.
Neurosurgery is moving towards personalized treatments that integrate artificial intelligence, predictive tools, and modern biomedical science. These advancements help clinicians tailor surgical procedures, improve patient safety during complex spinal and skull base operations, and identify novel therapeutic pathways for conditions like stroke and childhood epilepsy.
The developments point to applications in clinical risk-prediction software, specialized spinal instrumentation, and neuroimmunological therapeutic targets. Users include neurosurgeons, spine specialists, and medical software providers. The technologies range from applied retrospective studies and clinical workflows to early-stage biological target discovery, though specific deployment timelines are not detailed.
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Their work reflects the breadth and depth of contemporary neurosurgical inquiry, spanning pediatric epilepsy, vascular anomalies, neuroinflammation, spinal biomechanics, and skull base neurosurgery.Together this work demonstrates neurosurgery's increasing reliance on translational science, precision diagnostics, and data-driven decision making. Moreover, the new age of artificial intelligence has arrived, and with it comes a profound shift in how neurosurgeons diagnose, prognosticate, and treat disease. From predictive analytics in perioperative care to molecular profiling of tumors and vascular malformations, the next generation of neurosurgeons will increasingly rely on artificial intelligence to personalize treatment and enhance clinical decision-making.For example, two contributions in pediatric neurosurgery exhibit this shift. The first represents institutional experience with intracranial neuromodulation in children with drug-resistant epilepsy by Uchitel et al. (1).While initial trials utilizing deep brain stimulation and responsive neurostimulation, excluded pediatric patients, important insights can be gleaned to achieve seizure control in this vulnerable population. This (4). In an aging population with an increasing number of comorbidities, regional techniques allow for precise neurologic monitoring and less hemodynamic stress. Similarly, Fischer et al. compare lateral lumbar interbody fusion (LLIF) with release of the anterior longitudinal ligament (so-called "anterior column realignment") versus standard LLIF techniques using expandable spacers (5). Their retrospective cohorts study provides valuable guidance for patients requiring complex deformity correction. As spine instrumentation becomes increasingly modular and patient-specific, this work helps refine surgical decision-making and support the personalization of care.Another innovative article by Levinson et al. highlights advances in our understanding of the role of neuroinflammation in acute ischemic stroke (6). The authors synthesize recent evidence on microglial activation, cytokine cascades, and peripheral immune interactions. Their discussion offers potential targets for therapeutic intervention and calls for a broader understanding of stroke as a neuroimmunologic event rather than a purely vascular problem.The issue also includes a study on risk prediction following endoscopic transsphenoidal resection of pituitary adenomas by Wang et al. (7). Here the authors seek to exemplify the role of predictive analytics in perioperative management in skull base surgery. Modeling surgical risk preoperatively will likely become an integral part of the neurosurgical workflow as machine learning techniques allows greater leveraging of electronic health records and preoperative data.Beyond the scientific content, the most striking feature of this collection may be the academic mentorship exhibited among the contributors. The senior authors serve as mentors, collaborators, and sponsors for the rising stars featured here. Their role in fostering early-career development is critical. In a field where time is scarce and clinical productivity is often prioritized; meaningful mentorship is a strategic investment in the future of the discipline. These partnerships are not incidental; they are foundational to the survival of the neurosurgeon-scientist model. The international representation in this issue is equally noteworthy.Contributors hail from institutions in the United States, Europe, and China, reflecting a growing recognition that academic neurosurgery must be inclusive and globally engaged.
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DOI: 10.3389/fsurg.2025.1641348
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