Use of Artificial Intelligence Software to Detect Intracranial Aneurysms: A Comprehensive Stroke Center Experience

OBJECTIVE: To evaluate variability in aneurysm detection and the potential of artificial intelligence (AI) software as a screening tool by comparing conventional computed tomography angiography (CTA) images (standard care) with AI software. METHODS: Neuroradiologists reviewed 770 CTA images and reported the presence or absence of saccular aneurysms. Subsequently, the images were analyzed by AI software. If the software suspected an aneurysm, it flagged the corresponding image. In cases where there was a mismatch between the radiologist 's report and the AI findings, an expert neurosurgeon evaluated CTA images providing a definitive conclusion on the presence or absence of an aneurysm. RESULTS: AI software flagged 33 cases as potential aneurysms; 16 cases were positively identified as aneurysms by radiologists, and 17 were dismissed. A total of 737 cases were considered negative by AI software, while in the same group, radiologists identified aneurysms in 28 CTA images. Compared with the radiologist 's report, AI performance had a sensitivity of 36%, specificity of 97.6%, and negative predictive value of 96.2%. There were 45 mismatch cases between AI and radiologists. AI flagged 17 images as showing an aneurysm that was unreported by radiologists; the expert neurosurgeon confirmed that 7 of the 17 images showed an aneurysm. In 28 images considered negative by AI, radiologists indicated aneurysms; 17 of those confirmed by the neurosurgeon. CONCLUSIONS: AI has the potential to increase the diagnosis of unruptured intracranial aneurysms. However, it must be used as an adjacent tool within the standard of care due to limited applicability in real-world settings.