Discover how the groundbreaking development and validation of an AI-powered smartphone app is revolutionizing the field of skull base neurosurgery by enabling rapid intraoperative identification of pituitary adenomas.
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Development and prospective validation of an artificial intelligence-based smartphone app for rapid intraoperative pituitary adenoma identification.
Bou-Nassif et al., Commun Med (Lond) 2024
<!– DOI: 10.1038/s43856-024-00469-z //–>
https://doi.org/10.1038/s43856-024-00469-z
The development of an artificial intelligence-based smartphone app for intraoperative pathology consultation represents a significant advancement in surgical oncology. This app, designed to differentiate between pituitary adenoma and normal pituitary gland tissue using stimulated Raman histology, offers near-instantaneous results during surgery. Its effectiveness was demonstrated in a three-part study, culminating in a prospective evaluation involving 40 patients and 194 samples. The app’s performance metrics are impressive, with a sensitivity of 96.1%, specificity of 92.7%, positive predictive value of 98%, and negative predictive value of 86.4%. An external validation further confirmed its sensitivity at 93.7%.
This innovation is particularly crucial for improving intraoperative decisions and potentially enhancing oncologic outcomes. Its ability to provide rapid and accurate tissue differentiation is invaluable, especially in settings with limited access to specialized pathologists. Moreover, the app’s potential for expansion to other tumor types and optical images broadens its applicability, making it a versatile tool for both community hospitals and regions with scarce medical resources.