{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T13:02:32Z","timestamp":1780923752334,"version":"3.54.1"},"reference-count":19,"publisher":"Scientific Scholar","content-domain":{"domain":["surgicalneurologyint.com"],"crossmark-restriction":true},"short-container-title":[],"abstract":"\nBackground: <\/jats:title>\nDurable occlusion after endovascular coiling can be compromised by recanalization, underscoring the need for accurate cerebral aneurysm assessment. Precise volume measurement not only informs treatment decisions and detects subtle aneurysm growth but also refines calculations of packing density, historically linked to occlusion success. This study compares three volume-measurement approaches-traditional two-dimensional (2D) estimation, a semi-automated three-dimensional (3D) technique, and an artificial intelligence (AI)-based 3D method.<\/jats:p>\n<\/jats:sec>\n\nMethods: <\/jats:title>\nIn this retrospective analysis, 24 aneurysms were assessed using 3D rotational angiography. Manual segmentation by three specialists using ITK-SNAP or mimics served as the reference standard. These results were compared with volumes from a semi-automated 3D platform (Philips Advanced Visualization Workspace), an AI-based tool (RapidAI for Aneurysm), and traditional 2D estimations. Agreement with the reference standard was quantified through Passing-Bablok regression slopes and mean biases.<\/jats:p>\n<\/jats:sec>\n\nResults: <\/jats:title>\nPassing-Bablok slopes for the 2D, Philips, and RapidAI methods were 0.83, 0.87, and 0.94, respectively, while mean biases were \u201324.7 mm3<\/jats:sup> (2D), \u201319.5 mm3<\/jats:sup> (Philips), and \u201314.5 mm3<\/jats:sup> (RapidAI). RapidAI demonstrated the strongest correlation with the reference standard, whereas 2D estimations showed the largest discrepancy. The semi-automated 3D method exhibited intermediate accuracy, potentially influenced by the clinician input required for segmentation.<\/jats:p>\n<\/jats:sec>\n\nConclusion: <\/jats:title>\nAll methods underestimated aneurysm volumes compared to the reference standard, suggesting that inaccurate volume measurements may mask early aneurysm growth. Among the techniques assessed, the AI-based approach provided the closest agreement with the reference, indicating that improved volumetric methods-particularly AI-driven ones-can enhance early detection of aneurysm expansion, guide treatment decisions, and help establish more reliable follow-up strategies for both treated and conservatively managed aneurysms.<\/jats:p>\n<\/jats:sec>","DOI":"10.25259\/sni_1118_2024","type":"journal-article","created":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T09:52:51Z","timestamp":1748598771000},"page":"213","update-policy":"https:\/\/doi.org\/10.25259\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Enhancing precision in aneurysm volume measurement: A comparative study of techniques including an artificial intelligence-based method for endovascular coiling"],"prefix":"10.25259","volume":"16","author":[{"given":"Rafael Trindade","family":"Tatit","sequence":"first","affiliation":[{"name":"Interventional 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