当前位置: X-MOL 学术Neurosurg. Rev. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A scoring system to discriminate blood blister-like aneurysms: a multidimensional study using patient-specific model
Neurosurgical Review ( IF 2.5 ) Pub Date : 2021-01-03 , DOI: 10.1007/s10143-020-01465-2
Shanwen Chen 1 , Qingyuan Liu 1 , Baogang Ren 2 , Maogui Li 1, 3 , Pengjun Jiang 1, 3 , Yi Yang 1, 3 , Nuochuan Wang 4 , Yanan Zhang 4 , Bin Gao 5 , Yong Cao 1, 3 , Jun Wu 1, 3 , Shuo Wang 1, 3
Affiliation  

Presurgical discrimination of blood blister-like aneurysms (BBAs) can assist neurosurgeons in clinical decision-making. The aim of this study was to investigate the characteristics of BBAs and construct a useful tool to distinguish BBAs. This study reviewed patients with small/median, hemispherical, and wide-necked aneurysms of the internal carotid artery in our institution. BBAs were identified via their intraoperative findings. A hemodynamic analysis was performed using a patient-specific model. The independent risk factors of BBAs were investigated using a logistic analysis. A scoring system was then established to discriminate BBAs, in which its predicting value was analyzed using receiver operating characteristic (ROC) analysis. A total of 67 aneurysms comprising 21 BBAs were enrolled. Comparing features between BBAs and non-BBAs, statistical significances were found in the aspect ratio (AR), height-to-width ratio, aneurysm angle (AA), wall shear stress gradient (WSSG), and normalized wall shear stress average. A multivariate logistic analysis identified AR (OR = 0.29, p = 0.021), WSSG (OR = 1.54, p = 0.017) and AA (OR = 2.49, p = 0.039) as independent risk factors for BBAs. A scoring system was constructed using these parameters, effectively distinguishing BBAs (AUC = 0.931, p < 0.01). Our multidimensional scoring system may effectively assist in the discrimination of BBAs from wide-necked non-BBAs.



中文翻译:

区分血泡样动脉瘤的评分系统:使用患者特定模型的多维研究

血泡样动脉瘤 (BBA) 的术前鉴别可以帮助神经外科医生进行临床决策。本研究的目的是调查 BBA 的特征并构建一个有用的工具来区分 BBA。本研究回顾了我们机构的颈内动脉小/正中、半球形和宽颈动脉瘤的患者。BBAs 是通过他们的术中发现来确定的。使用特定于患者的模型进行血液动力学分析。BBA 的独立危险因素使用逻辑分析进行了调查。然后建立一个评分系统来区分 BBA,其中使用接收器操作特征 (ROC) 分析来分析其预测值。共纳入 67 个动脉瘤,包括 21 个 BBA。比较 BBA 和非 BBA 之间的功能,在纵横比 (AR)、高宽比、动脉瘤角度 (AA)、壁剪切应力梯度 (WSSG) 和归一化壁剪切应力平均值中发现了统计学显着性。多变量逻辑分析确定了 AR(OR = 0.29,p = 0.021)、WSSG (OR = 1.54, p = 0.017) 和 AA (OR = 2.49, p = 0.039) 作为BBA 的独立危险因素。使用这些参数构建了一个评分系统,有效区分了 BBA(AUC = 0.931,p < 0.01)。我们的多维评分系统可以有效地帮助区分 BBA 与宽颈非 BBA。

更新日期:2021-01-03
down
wechat
bug