Personalized Management of Intracranial Aneurysms Using Computer-aided Analytics

使用计算机辅助分析对颅内动脉瘤进行个性化管理

基本信息

批准号：
10383658
负责人：
Jingfeng Jiang
金额：
$ 33.46万
依托单位：
MICHIGAN TECHNOLOGICAL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-07 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10383658
关键词：
3-Dimensional Affect Aneurysm Angiography Architecture Artificial Intelligence Benign Biomedical Computing Biomedical Engineering Brain hemorrhage Cerebral Aneurysm Cerebrum Clinical Clinical Management Clinical Research Clinical Trials Computational Geometry Computational Science Computer Assisted Computer software Data Development Diagnosis Engineering Ensure Evaluation Genetic Growth Human Image Individual Intracranial Aneurysm Knowledge Liquid substance Machine Learning Medicine Methods Michigan Morbidity - disease rate Morphology Natural History Neural Network Simulation Outcome Patients Physics Play Research Research Proposals Risk Risk Assessment Role Rupture Ruptured Aneurysm Secondary to Smoker Technology TensorFlow Testing Training Translational Research United States Universities Wisconsin Work analytical method base blind computer grid convolutional neural network deep learning flexibility follow-up hemodynamics high risk image guided innovation learning strategy mortality neurosurgery open source personalized management prevent prospective prototype public health relevance shear stress success tool

项目摘要

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.

抽象的主要目标是开发一款以人工智能为中心的、定量的、非侵入性的软件可集成到 3D 血管造影扫描仪（DSA、CTA 或 MRA）中以提供指导的平台关于继发于出血性中风的颅内动脉瘤（IA）的诊断和治疗。 IAs 破裂会导致严重的发病率和死亡率，每年影响超过 35,000 名患者随着脑电图使用的增加，无症状 IAs 的诊断呈上升趋势。然而，关于应治疗哪些动脉瘤的指导尚未取得进展。利用计算科学和技术，特别是人工智能的最新进展，拟议的基于两种使能技术的软件平台可以（1）推动自动化的“患者特定” 将血流动力学评估纳入临床工作流程，并 (2) 对 IA 进行“数据驱动”风险评估具体研究目标是（1）开发面向临床的 CFD 平台。实现 IAs 的自动化“患者特异性”血流动力学评估，(2) 研究数据驱动的预测 IAs 破裂风险的分析，以及 (3) 盲目评估数据驱动的分析学习。一旦验证，后续 R01 项目计划检查所提议软件的临床效用前瞻性临床研究中的平台作为计算机辅助评估脑损伤的单一网关动脉瘤。