Explore the cutting-edge integration of artificial intelligence in enhancing the precision and outcomes of pituitary adenoma surgeries with our comprehensive scoping review.
– by James
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Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review.
Maroufi et al., Pituitary 2024
DOI: 10.1007/s11102-023-01369-6
Integration of AI/ML in Pituitary Adenoma Surgery: A Scoping Review
What’s New: This scoping review provides a comprehensive analysis of the application of artificial intelligence (AI) and machine learning (ML) in pituitary adenoma surgery, detailing the types of algorithms used and their outcomes.
Importance: The review underscores the potential of AI/ML to enhance surgical decision-making, improve outcomes, and provide real-time feedback in the complex field of pituitary adenoma surgery.
Contribution to Literature: The review systematically categorizes existing studies into clinicopathological and imaging input types and evaluates their outcomes, complications, costs, and adenoma-related factors. It also addresses the challenges in implementing AI/ML in this surgical domain.
Results Summary: Out of 2438 articles screened, 44 studies met the inclusion criteria, employing seventeen different algorithms. The outcomes assessed were surgical results (like remission and gross-total resection), complications (such as CSF leak and hyponatremia), cost-effectiveness, and adenoma characteristics (including aggressiveness and Ki-67 labeling). Additionally, three studies on workflow analysis and real-time navigation were separately discussed.
Conclusion: AI/ML technologies show promise in advancing pituitary adenoma surgery. However, challenges like algorithm selection, data diversity, and ethical considerations need to be addressed to fully harness the potential of these technologies in neurosurgery.