Institute for Computational and Imaging Science in Cardiovascular Medicine, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
Helios Hospital Berlin Buch, Berlin, Germany.
Biomed Eng Online. 2019 Mar 25;18(1):35. doi: 10.1186/s12938-019-0657-y.
Geometric parameters have been proposed for prediction of cerebral aneurysm rupture risk. Predicting the rupture risk for incidentally detected unruptured aneurysms could help clinicians in their treatment decision. However, assessment of geometric parameters depends on several factors, including the spatial resolution of the imaging modality used and the chosen reconstruction procedure. The aim of this study was to investigate the uncertainty of a variety of previously proposed geometric parameters for rupture risk assessment, caused by variability of reconstruction procedures.
26 research groups provided segmentations and surface reconstructions of five cerebral aneurysms as part of the Multiple Aneurysms AnaTomy CHallenge (MATCH) 2018. 40 dimensional and non-dimensional geometric parameters, describing aneurysm size, neck size, and irregularity of aneurysm shape, were computed. The medians as well as the absolute and relative uncertainties of the parameters were calculated. Additionally, linear regression analysis was performed on the absolute uncertainties and the median parameter values.
A large variability of relative uncertainties in the range between 3.9 and 179.8% was found. Linear regression analysis indicates that some parameters capture similar geometric aspects. The lowest uncertainties < 6% were found for the non-dimensional parameters isoperimetric ratio, convexity ratio, and ellipticity index. Uncertainty of 2D and 3D size parameters was significantly higher than uncertainty of 1D parameters. The most extreme uncertainties > 80% were found for some curvature parameters.
Uncertainty analysis is essential on the road to clinical translation and use of rupture risk prediction models. Uncertainty quantification of geometric rupture risk parameters provided by this study may help support development of future rupture risk prediction models.
已经提出了几何参数来预测脑动脉瘤破裂风险。预测偶然发现的未破裂动脉瘤的破裂风险可以帮助临床医生做出治疗决策。然而,几何参数的评估取决于几个因素,包括所使用的成像方式的空间分辨率和所选的重建过程。本研究的目的是研究由于重建过程的可变性,各种先前提出的用于破裂风险评估的几何参数的不确定性。
26 个研究小组作为 2018 年多动脉瘤解剖挑战(MATCH)的一部分,提供了五个脑动脉瘤的分割和表面重建。计算了 40 个尺寸和非尺寸的几何参数,描述了动脉瘤的大小、颈部大小和动脉瘤形状的不规则性。计算了参数的中位数以及绝对和相对不确定性。此外,还对绝对不确定性和参数中位数进行了线性回归分析。
发现相对不确定性的范围在 3.9%到 179.8%之间存在很大的差异。线性回归分析表明,一些参数捕捉到了相似的几何方面。等周比、凸度比和椭圆率指数等非尺寸参数的不确定性最低,<6%。2D 和 3D 尺寸参数的不确定性明显高于 1D 参数的不确定性。一些曲率参数的不确定性最高,>80%。
在向临床转化和使用破裂风险预测模型的道路上,不确定性分析至关重要。本研究提供的破裂风险几何参数的不确定性量化可能有助于支持未来破裂风险预测模型的开发。