Artificial intelligence in neurosurgical decision-making: promise and peril in the United States practice

Abstract

The rapid integration of artificial intelligence (AI) into neurosurgical practices in the United States is transforming how diagnoses are interpreted, how surgical plans are developed, and how guidance is provided during operations as clinical needs continue to grow. Models based on radiomics and the Food and Drug Administration approved tools for tumor segmentation, aneurysm identification, and spinal navigation are showing enhanced accuracy and decreased variability among observers, highlighting AI's potential for significant change. Nevertheless, there are major concerns about the opacity of black-box models, inaccurate outputs, and the increasing legal uncertainties arising from AI-related errors. Ethical challenges, such as the risk of clinician de-skilling, diminished professional autonomy, and exacerbated inequities in rural areas with limited access to imaging, complicate responsible deployment. This letter emphasizes the necessity for transparent validation processes, oversight led by clinicians, diverse and inclusive datasets, and improved regulatory protections. Requiring AI competency training and nationally reporting adverse events associated with AI are crucial to ensure that AI enhances clinical judgment rather than replacing it, thereby maintaining patient safety, equity, and professional integrity in neurosurgical decision-making.

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