影响梗死体积增长的因素,包括使用计算机断层扫描评估急性大动脉闭塞患者的侧支循环状态。
Factors influencing infarct growth including collateral status assessed using computed tomography in acute stroke patients with large artery occlusion.
机构信息
1 Department of Radiology, Neuroradiology Section, Stanford University School of Medicine, Stanford, USA.
2 Department of Medicine, Quantitative Sciences Unit, Stanford University, Stanford, USA.
出版信息
Int J Stroke. 2019 Aug;14(6):603-612. doi: 10.1177/1747493019851278. Epub 2019 May 17.
In major ischemic stroke caused by a large artery occlusion, neuronal loss varies considerably across individuals without revascularization. This study aims to identify which patient characteristics are most highly associated with this variability. Demographic and clinical information were retrospectively collected on a registry of 878 patients. Imaging biomarkers including Alberta Stroke Program Early CT score, noncontrast head computed tomography infarct volume, perfusion computed tomography infarct core and penumbra, occlusion site, collateral score, and recanalization status were evaluated on the baseline and early follow-up computed tomography images. Infarct growth rates were calculated by dividing infarct volumes by the time elapsed between the computed tomography scan and the symptom onset. Collateral score was graded into four levels (0, 1, 2, and 3) in comparison with the normal side. Correlation of perfusion computed tomography and noncontrast head computed tomography infarct volumes and infarct growth rates were estimated with the nonparametric Spearman's rank correlation. Conditional inference trees were used to identify the clinical and imaging biomarkers that were most highly associated with the infarct growth rate and modified Rankin Scale at 90 days. Two hundred and thirty-two patients met the inclusion criteria for this study. The median infarct growth rates for perfusion computed tomography and noncontrast head computed tomography were 11.2 and 6.2 ml/log(min) in logarithmic model, and 18.9 and 10.4 ml/h in linear model, respectively. Noncontrast head computed tomography and perfusion computed tomography infarct volumes and infarct growth rates were significantly correlated (rho=0.53; P < 0.001). Collateral status was the strongest predictor for infarct growth rates. For collateral=0, the perfusion computed tomography and noncontrast head computed tomography infarct growth rate were 31.56 and 16.86 ml/log(min), respectively. Patients who had collateral >0 and penumbra volumes>92 ml had the lowest predicted perfusion computed tomography infarct growth rates (6.61 ml/log(min)). Collateral status was closely related to the diversity of infarct growth rates, poor collaterals were associated with a faster infarct growth rates and vice versa.
在没有再通的情况下,大动脉闭塞引起的大面积脑梗死患者的神经元丢失差异很大。本研究旨在确定哪些患者特征与这种变异性高度相关。我们回顾性地收集了 878 例患者的登记资料,包括人口统计学和临床资料。在基线和早期随访 CT 图像上评估了影像学生物标志物,包括 Alberta 卒中项目早期 CT 评分、非对比头 CT 梗死体积、灌注 CT 梗死核心和半暗带、闭塞部位、侧支循环评分和再通状态。通过将梗死体积除以 CT 扫描和症状发作之间的时间来计算梗死生长率。侧支循环评分与健侧相比分为 4 个等级(0、1、2 和 3)。估计灌注 CT 和非对比头 CT 梗死体积和梗死生长率之间的相关性,采用非参数 Spearman 秩相关。条件推理树用于识别与 90 天梗死生长率和改良 Rankin 量表最相关的临床和影像学生物标志物。本研究纳入了 232 例患者。灌注 CT 和非对比头 CT 的梗死生长率中位数分别为对数模型中的 11.2 和 6.2ml/log(min),线性模型中的 18.9 和 10.4ml/h。非对比头 CT 和灌注 CT 梗死体积和梗死生长率显著相关(rho=0.53;P<0.001)。侧支循环状态是梗死生长率的最强预测因素。对于侧支循环=0,灌注 CT 和非对比头 CT 的梗死生长率分别为 31.56 和 16.86ml/log(min)。侧支循环>0 且半暗带体积>92ml 的患者具有最低的预测灌注 CT 梗死生长率(6.61ml/log(min))。侧支循环状态与梗死生长率的差异密切相关,较差的侧支循环与较快的梗死生长率相关,反之亦然。