Investigation of the quantitative intracranial aneurysm wall enhancement and geometric features associated with aneurysm volume growth

摘要： 全世界每年有近50万人死于颅内动脉瘤破裂(IAS) 一半的受害者年龄在50岁以下。未破裂的颅内动脉瘤(UIA)可以通过以下方法治疗 血管内和显微外科干预以防止破裂，然而，治疗携带非 发病率(5%-7%)和死亡率(1%-2%)的风险可以忽略不计。目前的指南建议对 当破裂风险高于介入风险时，UIAs大于7 mm。然而，超过50%的 破裂的IAS均小于7 mm。识别容易破裂的小动脉瘤并进行 选择性介入有可能防止这些小动脉瘤破裂。最近的一项荟萃分析 包括平均随访4年的4000多次UIA显示动脉瘤在 随访组破裂的可能性是非生长组的30倍(3.1%比0.1%)。 识别预测动脉瘤生长的因素有助于选择这些高危UIA进行治疗。 动脉瘤壁强化(炎症的替代标志物，由增强血管识别 壁磁共振)和动脉瘤几何因素(如成像上确定的形状或大小比率)是两个因素 有希望的标志物可以预测动脉瘤的增长。然而，目前对这些因素的评估是 受限于具有流动伪影、长扫描时间和主观性的非优化成像技术， 定性图像分析。该项目将开发最佳加速和血液抑制成像 评价UIA管壁强化和几何形状的方法和定量图像分析方法 特征，并通过纵向UIA研究与动脉瘤体积增长相关的参数 使用MRI进行评估。第一，开发优化血液抑制和成像加速 使用体外体模和患者体内测试的技术。第二，我们将开发自动化 评价UIA壁强化和几何构型的分割和量化方法(放射组学)。 最后，我们将对200名患有3 mm尿失禁的患者进行为期长达4年的MRI跟踪调查。 哪些临床和定量成像参数可以预测UIA的体积增长。

Abstract: There are almost 500,000 deaths worldwide each year caused by rupture of intracranial aneurysms (IAs) with half the victims younger than age 50. Unruptured intracranial aneurysms (UIAs) can be treated by endovascular and microsurgical interventions to prevent rupture, however, the treatment carries a non- negligible risk of morbidity (5%–7%) and mortality (1%–2%). Current guidelines recommend intervention for UIAs larger than 7mm, when their rupture risk is higher than the intervention risk. However, more than 50% of ruptured IAs are smaller than 7mm. Identifying small aneurysms that are prone to rupture and performing selective intervention can potentially prevent rupture of these small aneurysms. A recent meta-analysis including more than 4000 UIAs with an average of 4 years’ follow-up showed aneurysms that grew during the follow-up were 30 times more likely to rupture than the non-growing aneurysms (3.1% vs. 0.1%). Identifying the factors that predict aneurysm growth can help select these high risk UIAs for treatment. Aneurysm wall enhancement (a surrogate marker of inflammation, identified by contrast-enhanced vessel wall MRI) and aneurysm geometric factors (such as shape or size ratio as identified on imaging) are two promising markers that may predict aneurysm growth. However, the current evaluation of these factors is limited by non-optimized imaging techniques that have flow artifacts, long scan time and subjective, qualitative image analysis. This project will develop optimally accelerated and blood suppressed imaging methods and quantitative image analysis methods for the evaluation of UIA wall enhancement and geometric characteristics, and investigate the parameters associated with aneurysm volume growth by longitudinal UIA evaluation using MRI. First, we will develop and optimize blood suppression and imaging acceleration techniques using in vitro phantoms and in vivo testing in patients. Second, we will develop automatic segmentation and quantification methods (Radiomics) for evaluating UIA wall enhancement and geometry. Finally, we will follow 200 patients with >3mm UIAs using MRI each year for up to 4 years, and investigate which clinical and quantitative imaging parameters are predictive of UIA volume growth.