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Morphological descriptors as rupture indicators in middle cerebral artery aneurysms

机译:形态指标作为大脑中动脉瘤破裂指标

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The rupture of intracranial aneurysms is associated to significant morbidity and mortality rates. Although the mechanisms triggering this event are still unclear, morphology is among the factors considered by interventional neuroradiologists to decide treatment. The aim of this work is to explore the potential of morphological descriptors as rupture risk predictors in middle cerebral artery aneurysms (MCA) and to provide the subset showing the best predictive capabilities. The set of evaluated descriptors include basic shape descriptors related to the aneurysm size, and most sophisticated ones such as the Zernike Moment Invariants. The population analyzed included 71 patients harboring 86 MCA aneurysms (64 unruptured vs. 22 ruptured). An existing image-based processing pipeline was used to extract such descriptors from Three-Dimensional Rotational Angiography (3DRA) images routinely acquired during standard clinical practice. Univariate and multivariate statistical analyses have shown that among the evaluated descriptors, Zernike moment invariants computed on the aneurysm and a small portion of the surrounding vessels, together with the non-sphericity index, provide the best predictive capabilities of aneurysm rupture.
机译:颅内动脉瘤破裂与明显的发病率和死亡率有关。尽管触发该事件的机制仍不清楚,但形态是介入神经放射科医生决定治疗的因素之一。这项工作的目的是探讨形态学描述符作为脑中动脉瘤(MCA)破裂风险预测指标的潜力,并提供显示最佳预测功能的子集。评估描述符的集合包括与动脉瘤大小有关的基本形状描述符,以及最复杂的描述符,例如Zernike Moment Invariants。分析的人群包括71位患者,其中包含86个MCA动脉瘤(64例未破裂vs. 22例破裂)。现有的基于图像的处理管道用于从标准临床实践中常规获取的三维旋转血管造影(3DRA)图像中提取此类描述符。单变量和多变量统计分析表明,在评估的描述符中,在动脉瘤和一小部分周围血管上计算出的Zernike矩不变量与非球度指数一起提供了最佳的动脉瘤破裂预测能力。

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