Suppr超能文献

术前磁共振成像显示的脑小血管疾病与颈动脉内膜切除术后脑血流过度灌注相关。

Pre-operative Cerebral Small Vessel Disease on MR Imaging Is Associated With Cerebral Hyperperfusion After Carotid Endarterectomy.

作者信息

Fan Xiaoyuan, Lai Zhichao, Lin Tianye, You Hui, Wei Juan, Li Mingli, Liu Changwei, Feng Feng

机构信息

Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Department of Vascular Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Front Cardiovasc Med. 2021 Nov 18;8:734392. doi: 10.3389/fcvm.2021.734392. eCollection 2021.

Abstract

To determine whether pre-operative cerebral small vessel disease is associated with cerebral hyperperfusion (CH) after carotid endarterectomy (CEA). Seventy-seven patients (mean age of 66 years and 58% male) undergoing CEA for carotid stenosis were investigated using brain MRI before and after surgery. CH was defined as an increase in cerebral blood flow > 100% compared with pre-operative values on arterial spin labeling MR images. The grade or the number of four cerebral small vessel disease markers (white matter hyperintensities, lacunes, perivascular spaces, and cerebral microbleeds) were evaluated based on pre-operative MRI. Cerebral small vessel disease markers were correlated with CH by using multivariate logistic regression analysis. The cutoff values of cerebral small vessel disease markers for predicting CH were assessed by receiver-operating characteristic curve analysis. CH after CEA was observed in 16 patients (20.78%). Logistic regression analysis revealed that white matter hyperintensities (OR 3.09, 95% CI 1.72-5.54; < 0.001) and lacunes (OR 1.37, 95% CI 1.06-1.76; = 0.014) were independently associated with post-operative CH. Receiver-operating characteristic curve analysis showed that Fazekas score of white matter hyperintensities ≥3 points [area under the curve (AUC) = 0.84, sensitivity = 81.3%, specificity = 73.8%, positive predictive value (PPV) = 44.8% and negative predictive value (NPV) = 93.8%] and number of lacunes ≥ 2 (AUC = 0.73, sensitivity = 68.8%, specificity = 78.7%, PPV = 45.8% and NPV = 90.6%) were the optimal cutoff values for predicting CH. In patients with carotid stenosis, white matter hyperintensities and lacunes adversely affect CH after CEA. Based on the NPVs, pre-operative MR imaging can help identify patients who are not at risk of CH.

摘要

确定术前脑小血管疾病是否与颈动脉内膜剥脱术(CEA)后的脑过度灌注(CH)相关。对77例因颈动脉狭窄接受CEA手术的患者(平均年龄66岁,男性占58%)在手术前后进行脑部MRI检查。CH定义为动脉自旋标记磁共振图像上脑血流量较术前值增加>100%。根据术前MRI评估四种脑小血管疾病标志物(白质高信号、腔隙、血管周围间隙和脑微出血)的分级或数量。通过多因素逻辑回归分析评估脑小血管疾病标志物与CH的相关性。通过受试者工作特征曲线分析评估预测CH的脑小血管疾病标志物的截断值。16例患者(20.78%)术后出现CH。逻辑回归分析显示,白质高信号(比值比3.09,95%可信区间1.72 - 5.54;P<0.001)和腔隙(比值比1.37,95%可信区间1.06 - 1.76;P = 0.014)与术后CH独立相关。受试者工作特征曲线分析表明,白质高信号Fazekas评分≥3分[曲线下面积(AUC)= 0.84,敏感性 = 81.3%,特异性 = 73.8%,阳性预测值(PPV)= 44.8%,阴性预测值(NPV)= 93.8%]和腔隙数量≥2(AUC = 0.73,敏感性 = 68.8%,特异性 = 78.7%,PPV = 45.8%,NPV = 90.6%)是预测CH的最佳截断值。在颈动脉狭窄患者中,白质高信号和腔隙对CEA术后的CH有不利影响。根据NPV,术前磁共振成像有助于识别无CH风险的患者。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验