Department of Radiology, Health Sciences University, Tepecik Educational and Research Hospital, 35180 Yenisehir, Konak, Izmir, Turkey.
Department of Radiology, Dokuz Eylul University School of Medicine, Izmir, Turkey.
Eur Radiol. 2021 Aug;31(8):6105-6115. doi: 10.1007/s00330-021-07720-4. Epub 2021 Feb 9.
To evaluate the performance of CT-based texture analysis (TA) for predicting clinical outcomes of mechanical thrombectomy (MT) in acute ischemic stroke (AIS).
This single-center, retrospective study contained 64 consecutive patients with AIS who underwent MT for large anterior circulation occlusion between December 2016 and January 2020. Patients were divided into 2 groups according to the modified Rankin scale (mRS) scores at 3 months as good outcome (mRS ≤ 2) and bad outcome (mRS > 2). Two observers examined the early ischemic changes for TA on baseline non-contrast CT images independently. Demographic, clinical, periprocedural, and texture variables were compared between the groups and ROC curves were made. Logistic regression analysis was used and a model was created to determine the independent predictors of a bad outcome.
Sixty-four patients (32 female, 32 male; mean age 63.03 ± 14.42) were included in the study. Fourteen texture parameters were significantly different between patients with good and bad outcomes. The long-run high gray-level emphasis (LRHGE), which is a gray-level run-length matrix (GLRLM) feature, showed the highest sensitivity (80%) and specificity (70%) rates to predict disability. The GLRLM_LRHGE value of > 4885.0 and the time from onset to puncture of > 237.5 mi were found as independent predictors of the bad outcome. The diagnostic rate was 80.0% when using the combination of the GLRLM_LRHGE and the time from onset to puncture cutoff values.
CT-based TA might be a promising modality to predict clinical outcome after MT in patients with AIS.
• The gray-level run-length matrix parameters displayed higher diagnostic performance among the texture features. • The long-run high gray-level emphasis showed the highest sensitivity and specificity rates for predicting a bad outcome in stroke patients undergoing mechanical thrombectomy. • The gray-level run-length matrix_long-run high gray-level emphasis value of > 4885.0 (OR = 11.06; 95% CI = 2.51 - 48.77; p = 0.001) and the time from onset to puncture of > 237.5 min (OR = 8.55; 95% CI = 1.96 - 37.21; p = 0.004) were found as independent predictors of the bad outcome.
评估基于 CT 的纹理分析(TA)在预测急性缺血性卒中(AIS)机械取栓(MT)临床结局中的性能。
本单中心回顾性研究纳入了 2016 年 12 月至 2020 年 1 月间因大血管前循环闭塞而接受 MT 的 64 例 AIS 连续患者。根据 3 个月时改良 Rankin 量表(mRS)评分,患者分为预后良好组(mRS≤2)和预后不良组(mRS>2)。两位观察者分别独立检查基线非对比 CT 图像上的早期缺血性改变进行 TA。比较两组间的人口统计学、临床、围手术期和纹理变量,并绘制 ROC 曲线。采用 logistic 回归分析,建立模型以确定不良结局的独立预测因素。
本研究纳入了 64 例患者(32 名女性,32 名男性;平均年龄 63.03±14.42 岁)。预后良好和不良患者间有 14 项纹理参数存在显著差异。长程高灰度强调(LRHGE),一种灰度游程矩阵(GLRLM)特征,对预测残疾的敏感性(80%)和特异性(70%)最高。LRHGE 值>4885.0 和发病至穿刺时间>237.5 分钟是不良结局的独立预测因素。当使用 GLRLM_LRHGE 和发病至穿刺时间截断值的组合时,诊断率为 80.0%。
基于 CT 的 TA 可能是预测 AIS 患者 MT 后临床结局的一种很有前途的方法。