Open AccessThe Aneurysm Occlusion Assistant, an AI platform for real time surgical guidance of intracranial aneurysms
Author(s) -
Kyle Williams,
Alexander R. Podgorsak,
Mohammad Mahdi Shiraz Bhurwani,
Ryan A. Rava,
K. Sommer,
Ciprian N. Ionita
Publication year - 2021
Publication title -
pubmed central
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
pISSN - 0277-786X
DOI - 10.1117/12.2581003
Subject(s) - occlusion , computer science , aneurysm , segmentation , artificial intelligence , radiology , angiography , computer vision , interface (matter) , software , medicine , surgery , bubble , maximum bubble pressure method , parallel computing , programming language
In recent years, endovascular treatment has become the dominant approach to treat intracranial aneurysms (IAs). Despite tremendous improvement in surgical devices and techniques, 10-30% of these surgeries require retreatment. Previously, we developed a method which combines quantitative angiography with data-driven modeling to predict aneurysm occlusion within a fraction of a second. This is the first report on a semi-autonomous system, which can predict the surgical outcome of an IA immediately following device placement, allowing for therapy adjustment. Additionally, we previously reported various algorithms which can segment IAs, extract hemodynamic parameters via angiographic parametric imaging, and perform occlusion predictions.