Pipeline栓塞后动脉瘤闭塞预测：基于血管造影参数成像的集成模型
本研究回顾性纳入306例接受Pipeline栓塞装置治疗颅内动脉瘤的患者，从3D旋转血管造影和DSA提取临床、形态学及血流动力学特征，构建加权软投票集成模型预测≥6个月随访时的动脉瘤闭塞。外部测试集AUC为0.902，准确率88.9%，敏感度93.9%，特异度71.4%；分支受累、子囊和年龄较大是不完全闭塞的独立预测因素。
要点
- DSA衍生的定量血流动力学和形态学特征可用于预测PED术后动脉瘤闭塞。
- 集成模型外部测试AUC 0.902，敏感度93.9%，特异度71.4%。
- 分支受累、子囊和年龄较大提示不完全闭塞风险。
核心结论
- DSA衍生的定量血流动力学和形态学特征是预测PED疗效的有价值生物标志物，集成模型表现稳健（AUC 0.902；95% CI 0.82-0.98），可能有助于风险分层和个体化治疗规划。
研究设计与样本
- 回顾性研究纳入2016年1月至2023年6月接受PED治疗的306例颅内动脉瘤患者（平均年龄52.9±10.9岁，女性192例），从临床记录、三维旋转血管造影和DSA提取特征。
- 构建加权软投票集成模型预测≥6个月随访时动脉瘤闭塞，最终预测结合五种算法的加权预测概率而非简单多数投票；性能采用AUC和混淆矩阵指标，特征重要性采用SHAP分析。
关键影像表现/征象
- 预PED和后PED血流动力学特征被提取，共31个特征纳入建模（13个临床/形态学特征，18个后PED血流动力学特征——动脉瘤和载瘤动脉感兴趣区各9个）。
- 不完全闭塞的独立预测因素为分支受累、子囊和年龄较大。
- 后PED变化（达峰时间、平均通过时间、脑血容量）与结局相关；完全闭塞与较高的动脉瘤最大密度投影和载瘤动脉脑血流量相关。
诊断标准与关键数值
- 外部测试集：AUC 0.902（95% CI 0.82-0.98），准确率88.9%（95% CI 78.5-95.2%），敏感度93.9%（95% CI 82.8-98.7%），特异度71.4%（95% CI 45.0-88.3%）。
- 完全闭塞率：内部数据集202/243个动脉瘤（83.1%），外部测试集49/63个（77.8%）。
临床应用与阅片要点
- 可利用DSA定量血流动力学参数（如达峰时间、平均通过时间、脑血容量）辅助评估PED术后闭塞可能性。
- 阅片时注意分支受累和子囊等形态学特征，结合患者年龄进行风险分层。
以上解读依据论文摘要（全文未开放获取或许可不允许翻译转载）。
英文原文（摘要）· 点击展开
BACKGROUND AND PURPOSE: The Pipeline Embolization Device (PED) revolutionized endovascular treatment of intracranial aneurysms (IAs), especially complex wide-neck lesions, but incomplete occlusion remains common. This study aimed to develop an ensemble model integrating clinical, morphological, and hemodynamic features for predicting post-PED occlusion outcomes.
MATERIALS AND METHODS: This retrospective study included 306 patients with IAs treated with PED from January 2016 to June 2023. Clinical, morphological, and hemodynamic features were extracted from clinical records, three-dimensional rotational angiography, and digital subtraction angiography (DSA) to develop a weighted soft-voting ensemble model for predicting aneurysm occlusion at ≥6-month follow-up. The final prediction was generated by combining the weighted predicted probabilities from five individual algorithms rather than by a simple majority vote. Performance used area under the receiver operating characteristic curve (AUC) and confusion-matrix metrics; feature importance used SHapley Additive exPlanations (SHAP).
RESULTS: Among 306 patients (mean age 52.9±10.9 years; 192 women), pre- and post-PED hemodynamic features were extracted; 31 features (13 clinical/morphological, 18 post-PED hemodynamic-9 each from aneurysm and parent-artery regions of interest) were modeled. Complete occlusion was observed in 202/243 aneurysms (83.1%) in the internal dataset and 49/63 (77.8%) in the external test set. In the external test set, the ensemble achieved an AUC of 0.902 (95% CI, 0.82-0.98), an accuracy of 88.9% (95% CI, 78.5-95.2%), a sensitivity of 93.9% (95% CI, 82.8-98.7%), and a specificity of 71.4% (95% CI, 45.0-88.3%). Independent predictors of incomplete occlusion were branch involvement, daughter sacs, and older age. Post-PED changes (time-to-peak, mean-transit-time, cerebral-blood-volume) correlated with outcomes; complete occlusion associated with higher aneurysmal maximum intensity projection and parent-artery cerebral blood flow.
CONCLUSIONS: DSA-derived quantitative hemodynamic and morphological features are valuable biomarkers for PED efficacy. The ensemble showed robust performance (AUC 0.902; 95% CI 0.82-0.98) and may aid risk stratification and personalized IA treatment planning.
引用
- Zhu H, Song Y, Zhang Y, et al. Predicting Aneurysm Occlusion After Pipeline Embolization: an Ensemble Model Using Angiographic Parametric Imaging. AJNR Am J Neuroradiol. 2026. PMID: 42134997. doi:10.3174/ajnr.A9415
供执业医师工作参考，不替代临床判断；数值与分级以指南原文为准。