Nagy Jozsef, Stroh-Holly Nico, Fenz Wolfgang, Thumfart Stefan, Maier Julia, Major Zoltan, Stefanits Harald, Gollwitzer Maria, Oberndorfer Johannes, Mazanec Vanessa, Giretzlehner Michael, Sonnberger Michael, Rauch Philip, Gruber Andreas, Gmeiner Matthias
eulerian-solutions e.U. Leonfeldnerstraße 245, Linz, Austria.
Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.
PLoS One. 2025 Sep 2;20(9):e0331297. doi: 10.1371/journal.pone.0331297. eCollection 2025.
The Anterior Communicating Artery complex (AComA) is one of the most common intracranial aneurysms locations. Accurate rupture risk assessment in patients with cerebral aneurysms is essential for optimizing treatment decisions. Computational fluid dynamics has significantly advanced insight into aneurysmal hemodynamics. Many studies concentrate predominantly on blood flow patterns, frequently neglecting the biomechanical properties of the aneurysm wall. Fluid-structure interaction analysis combines hemodynamic behavior with wall mechanics, potentially facilitating a more thorough evaluation of rupture risk assessment.
In this study, we employed advanced techniques to investigate several single and composite parameters to predict the rupture risk of AComA aneurysms in a cohort of 150 patients treated at the Kepler University Hospital in Linz, Austria. For this reason, clinical, morphological, hemodynamic, and structural mechanical parameters were assessed.
A subsequent workflow analysis, consisting of comparative analysis, collinearity analysis, predictive modeling, composite parameter, performance evaluation, and internal threshold validation, revealed the Gaussian curvature GLN (AUC = 0.91) with a sensitivity of 0.93 and specificity of 0.83 as a best-performing single parameter for aneurysm rupture prediction. Composite parameters like WGD (combination of wall shear stress, Gaussian curvature, and wall displacement) achieved an AUC of 0.89, and WG (combination of wall shear stress and Gaussian curvature) an AUC of 0.88. An internal validation with 25 independent ruptured aneurysms was performed, and the previous results were confirmed with very high sensitivity values of 0.92 for GLN.
Our findings indicate that the investigated morphological, hemodynamic, and structural, mechanical parameters could provide a potential tool for evaluating rupture risk for AComA aneurysms. The single morphological parameter GLN offers, followed by composite parameters WGD and WG, excellent prediction power for the aneurysm rupture state, as confirmed by internal validation. Further studies are warranted to evaluate the prospective clinical application of these parameters.
前交通动脉复合体（AComA）是颅内动脉瘤最常见的发病部位之一。准确评估脑动脉瘤患者的破裂风险对于优化治疗决策至关重要。计算流体动力学极大地增进了我们对动脉瘤血流动力学的认识。许多研究主要集中在血流模式上，常常忽略了动脉瘤壁的生物力学特性。流固耦合分析将血流动力学行为与血管壁力学相结合，有可能促进对破裂风险评估进行更全面的评估。
在本研究中，我们采用先进技术调查了几个单一参数和复合参数，以预测奥地利林茨开普勒大学医院治疗的150例患者队列中AComA动脉瘤的破裂风险。因此，对临床、形态学、血流动力学和结构力学参数进行了评估。
随后的工作流程分析，包括对比分析、共线性分析、预测建模、复合参数、性能评估和内部阈值验证，结果显示高斯曲率GLN（曲线下面积[AUC]=0.91）作为预测动脉瘤破裂的最佳单一参数，敏感性为0.93，特异性为0.83。像WGD（壁面剪应力、高斯曲率和壁面位移的组合）这样的复合参数AUC为0.89，而WG（壁面剪应力和高斯曲率的组合）AUC为0.88。对25个独立破裂动脉瘤进行了内部验证，GLN的敏感性高达0.92，证实了先前的结果。
我们的研究结果表明，所研究的形态学、血流动力学和结构力学参数可为评估AComA动脉瘤的破裂风险提供一个潜在工具。单一形态学参数GLN以及复合参数WGD和WG对动脉瘤破裂状态具有出色的预测能力，内部验证证实了这一点。有必要进一步开展研究以评估这些参数在临床中的应用前景。
