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形态学特征伸长可预测颅内动脉瘤管道栓塞后的闭塞状态。

Morphologic Feature Elongation Can Predict Occlusion Status Following Pipeline Embolization of Intracranial Aneurysms.

作者信息

Zhang Yupeng, Ma Chao, Liang Shikai, Yan Peng, Liang Fei, Guo Feng, Jiang Chuhan

机构信息

Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.

出版信息

World Neurosurg. 2018 Nov;119:e934-e940. doi: 10.1016/j.wneu.2018.08.007. Epub 2018 Aug 10.

Abstract

OBJECTIVE

To explore whether computed morphologic features can be used as independent predictors of incomplete occlusion of aneurysms treated with the Pipeline embolization device.

METHODS

From January 2016 to September 2017, 58 patients with 58 aneurysms were treated with the Pipeline embolization device. Aneurysms were manually segmented from the Digital Imaging and Communications in Medicine file, and we calculated 16 shape features voxel by voxel on the segmented aneurysm image. Along with 13 other clinical and radiographic variables, we performed univariate and multivariate analysis to explore predictors of incomplete occlusion.

RESULTS

At last angiographic follow-up (median 6.2 months), complete occlusion was achieved in 41 aneurysms (70.7%). In multivariate analysis, malapposition of stent (odds ratio = 0.03; 95% confidence interval, 0.00-0.32; P = 0.004) and higher elongation value (odds ratio = 0.03; 95% confidence interval, 0.01-0.17; P < 0.001) were independently associated with incomplete occlusion of aneurysms. Compared with aneurysms with complete occlusion, incompletely occluded aneurysms had higher elongation values (median 0.890 vs. 0.766; P < 0.001); the optimal cutoff value of elongation for occlusion status classification was 0.862. Predicting accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve of the logistic regression model were 0.879, 0.902, 0.824, 0.925, 0.778, and 0.872.

CONCLUSIONS

Malapposition of stent and higher elongation value were independent negative predictors of aneurysm occlusion following flow diversion.

摘要

目的

探讨计算机形态学特征能否作为使用Pipeline栓塞装置治疗的动脉瘤不完全闭塞的独立预测指标。

方法

2016年1月至2017年9月,58例患者的58个动脉瘤接受了Pipeline栓塞装置治疗。从医学数字成像和通信文件中手动分割动脉瘤,并在分割后的动脉瘤图像上逐体素计算16个形状特征。连同其他13个临床和影像学变量,我们进行了单因素和多因素分析以探索不完全闭塞的预测指标。

结果

在最后一次血管造影随访时(中位时间6.2个月),41个动脉瘤(70.7%)实现了完全闭塞。在多因素分析中,支架贴壁不良(比值比=0.03;95%置信区间,0.00-0.32;P=0.004)和较高的伸长值(比值比=0.03;95%置信区间,0.01-0.17;P<0.001)与动脉瘤不完全闭塞独立相关。与完全闭塞的动脉瘤相比,不完全闭塞的动脉瘤具有更高的伸长值(中位值0.890对0.766;P<0.001);用于闭塞状态分类的伸长最佳截断值为0.862。逻辑回归模型的预测准确性、敏感性、特异性、阳性预测值、阴性预测值和曲线下面积分别为0.879、0.902、0.824、0.925、0.778和0.872。

结论

支架贴壁不良和较高的伸长值是血流导向术后动脉瘤闭塞的独立负性预测指标。

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