J Korean Neurosurg Soc.  2023 Nov;66(6):632-641. 10.3340/jkns.2021.0213.

Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review

• Agadi K
• Dominari A
• Tebha SS
• Mohammadi A
• Zahid S

• KMID: 2547457
• DOI: http://doi.org/10.3340/jkns.2021.0213

Abstract

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI’s role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O’Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient’s prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

Keyword

Artificial intelligence; Neurosurgery; Central nervous system neoplasms; Disease management

Figure

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  Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 flow chart. Modified from Page et al. [41].

Reference

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