Personalized Management of Intracranial Aneurysms Using Computer-aided Analytics

摘要 主要目标是开发一个以人工智能为中心的、定量的、非侵入性的软件 可集成到3D血管造影仪(DSA、CTA或MRA)中以提供指导的平台 关于颅内动脉瘤(IA)的诊断和治疗。继发性出血性卒中 IAS破裂导致严重的发病率和死亡率，每年影响超过35,000名患者 美国。随着脑血管造影应用的增加，无症状间歇性脊柱炎的诊断呈上升趋势。 成像。然而，关于应该治疗哪些动脉瘤的指导意见并未取得进展。 利用计算科学和技术，特别是人工智能的最新进展， 建议的基于两种使能技术的软件平台可以(1)推动自动化的“针对患者的” 将血流动力学评估纳入临床工作流程，以及(2)对IA进行“数据驱动”的风险评估 在个人基础上破裂。具体研究目标是：(1)开发面向临床的CFD平台 这使得能够对IAS进行自动化的“特定于患者”的血流动力学评估，(2)调查数据驱动 对IAS破裂风险预测的分析以及(3)盲法评估数据驱动的分析 学习。 一旦得到验证，计划进行后续的R01项目，以检查所提议的软件的临床应用 前瞻性临床研究中的平台，作为计算机辅助评估大脑的单一门户 动脉瘤。

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.