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临床试验/NCT05317169
NCT05317169招募中不适用

Aneurysm Genetic Risk in Patients With Changes in Quantitative Imaging Biomarkers Over Time

University of California, Los Angeles1 个研究点 分布在 1 个国家目标入组 120 人开始时间: 2018年12月12日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
120
试验地点
1
主要终点
Quantitative imaging biomarkers (QIB) change

研究概览

简要总结

Intracranial aneurysm rupture is a leading cause of hemorrhagic strokes which carry high mortality and disability rates as well as high healthcare costs. Unruptured intracranial aneurysms (UIA) are common in the general population, occurring in 1-2% of individuals. Previous studies have shown that UIA growth and rupture are strongly associated with each other, with growing aneurysms 9-12 times more likely to rupture, and nearly all aneurysms growing prior to rupture. Thanks to advanced medical imaging, UIA are now more and more often detected incidentally. However not all aneurysms qualify for preventive surgical or interventional procedures according to current International Study of Unruptured Intracranial Aneurysms (ISUIA) guidelines, and some must therefore be monitored for growth. Current guidelines are based heavily on size, an inconsistent predictor of future growth. To improve management strategies for individual patients and more comprehensively assess aneurysm risk, the investigators propose to identify risk factors related to growth.

Aneurysm etiology is multifactorial, with both genetic and environmental contributions to aneurysm formation, growth, and rupture. Exploring new risk factors based on aneurysm natural history and understanding the mechanisms underlying aneurysm rupture have been extensive research areas. As previous studies have shown that quantitative imaging biomarkers (QIB) can provide a more accurate assessment of the characteristics of aneurysms, the investigators propose a combined study which identifies QIB associated with aneurysm growth to identify factors related to growth.

详细描述

The objective of this study is to investigate intracranial aneurysms that have been followed with clinical 3D aneurysm images and create a matrix that can identify the risk of growth by integrating QIB with genetic predisposition risk factors. 120 Patients who have been followed by clinical aneurysm imaging study will be enrolled in this study. The study team will collect blood samples from the patients for genetic analysis.

To find the genetic factors, the blood samples will be processed with a focus on genetic variants 1) in pathways involved in endothelial and vascular function and 2) previously identified in genome-wide association studies of aneurysm risk. These analyses will include both common polymorphisms and rare alterations. These biomarkers have important implications for facilitating identification of high-risk subgroups for aneurysm growth and the development of improved evidence-based decision-making.

The investigators will perform aneurysm 3D analysis based on the aneurysm images to extract aneurysm QIB for these cases. Shape parameters such as aneurysm surface area shape indices will be collected for individual aneurysms as well as parameters capturing the aneurysm blood flow pattern. The study plans to address whether certain genetic variants for vascular function are present in patients with QIB change over time.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Patients with unruptured cerebral aneurysms followed yearly using non-invasive imaging techniques including Computed tomography (CT) and Magnetic resonance (MR) angiography.

排除标准

  • Patients with bleeding disorders. Patients who have severe intravenous CT or MR contrast allergy. Patients with evidence of kidney failure. Patients with severe claustrophobia. Patients with religious objections to phlebotomy.

结局指标

主要结局

Quantitative imaging biomarkers (QIB) change

时间窗: 3 years

Number of participants with changes in quantitative imaging biomarkers

次要结局

  • Genetic biomarkers in QIB change(3 years)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Aichi Chien, PhD

Professor

University of California, Los Angeles

研究点 (1)

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