Colombi Davide, Bodini Flavio Cesare, Rossi Beatrice, Bossalini Margherita, Risoli Camilla, Morelli Nicola, Petrini Marcello, Sverzellati Nicola, Michieletti Emanuele
Radiology Unit, Department of Radiology, "Guglielmo da Saliceto" Hospital, Via Taverna 49, 29121 Piacenza, Italy.
Unit "Scienze Radiologiche", Department of Medicine and Surgery (DiMeC), University of Parma, Via Gramsci 14, 43126 Parma, Italy.
Diagnostics (Basel). 2021 Nov 27;11(12):2214. doi: 10.3390/diagnostics11122214.
Novel biomarkers are advocated to manage carotid plaques. Therefore, we aimed to test the association between textural features of carotid plaque at computed tomography angiography (CTA) and unfavorable outcome after carotid artery stenting (CAS). Between January 2010 and January 2021, were selected 172 patients (median age, 77 years; 112/172, 65% men) who underwent CAS with CTA of the supra-aortic vessels performed within prior 6 months. Standard descriptors of the density histogram were derived by open-source software automated analysis obtained by CTA plaque segmentation. Multiple logistic regression analysis, receiver operating characteristic (ROC) curve analysis and the area under the ROC (AUC) were used to identify potential prognostic variables and to assess the model performance for predicting unfavorable outcome (periprocedural death or myocardial infarction and any ipsilateral acute neurological event). Unfavorable outcome occurred in 17/172 (10%) patients (median age, 79 years; 12/17, 70% men). Kurtosis was an independent predictor of unfavorable outcome (odds ratio, 0.79; confidence interval, 0.65-0.97; = 0.029). The predictive model for unfavorable outcome including CTA textural features outperformed the model without textural features (AUC 0.789 vs. 0.695, = 0.004). In patients with stenotic carotid plaque, kurtosis derived by CTA density histogram analysis is an independent predictor of unfavorable outcome after CAS.
新型生物标志物被提倡用于管理颈动脉斑块。因此，我们旨在测试计算机断层扫描血管造影（CTA）下颈动脉斑块的纹理特征与颈动脉支架置入术（CAS）后不良结局之间的关联。在2010年1月至2021年1月期间，我们选择了172例患者（中位年龄77岁；112/172，65%为男性），这些患者在过去6个月内接受了CAS并进行了主动脉弓血管的CTA检查。密度直方图的标准描述符通过CTA斑块分割获得的开源软件自动分析得出。采用多因素逻辑回归分析、受试者操作特征（ROC）曲线分析和ROC曲线下面积（AUC）来识别潜在的预后变量，并评估预测不良结局（围手术期死亡或心肌梗死以及任何同侧急性神经事件）的模型性能。172例患者中有17例（10%）出现不良结局（中位年龄79岁；12/17，70%为男性）。峰度是不良结局的独立预测因素（比值比，0.79；置信区间，0.65 - 0.97；P = 0.029）。包括CTA纹理特征的不良结局预测模型优于无纹理特征的模型（AUC 0.789对0.695，P = 0.004）。在患有狭窄性颈动脉斑块的患者中，通过CTA密度直方图分析得出的峰度是CAS后不良结局的独立预测因素。
