Abstract The primary objective is to develop an artificial intelligence-centric, quantitative and noninvasive software platform that can be integrated into 3D angiographic scanners (DSA, CTA or MRA) to provide guidance regarding the diagnosis and management of intracranial aneurysms (IA). Hemorrhagic stroke secondary to ruptured IAs leads to significant morbidity and mortality and affects over 35,000 patients on a yearly basis in the United States. The diagnosis of asymptomatic IAs is on the rise with the increasing use of cerebral imaging. However, guidance regarding which aneurysms should be treated has not advanced. Leveraging recent advances in computational science and technology, particularly artificial intelligence, the proposed software platform built on two enabling technologies can (1) propel automated “patient-specific” hemodynamic evaluations into the clinical workflow and (2) conduct “data-driven” risk assessments of IA rupture on an individual basis. Specific research aims are to (1) develop a clinically-oriented CFD platform that enables automated “patient-specific” hemodynamic evaluations of IAs, (2) investigate data-driven analytics toward prediction of rupture risk for IAs and (3) evaluate the data-driven analytics in a blind study. Once validated, a follow-up R01 project is planned to examine the clinical utility of the proposed software platform in a prospective clinical study as a single gateway for computer-aided evaluation of cerebral aneurysms.

Public Health Relevance/Narrative This R01 proposal is to investigate the feasibility of developing an innovative, non-invasive and artificial intelligence-centric tool that can be used as a software add-on to clinical angiographic (e.g. DSA) scanners. The software can automatically select high-risk aneurysms for immediate treatments from a pool of patients with unruptured intracranial aneurysms, impacting the clinical management of intracranial aneurysms.