Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China.
Department of Neurology, Minhang Hospital, Fudan University, Shanghai, China; Department of Electronic Engineering, Fudan University, Shanghai, China.
Clin Imaging. 2020 Nov;67:152-159. doi: 10.1016/j.clinimag.2020.06.013. Epub 2020 Jun 11.
To explore the feasibility of texture analysis based on T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) images and apparent diffusion coefficient (ADC) maps in the assessment of the severity and prognosis of ischaemic stroke using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin scale (mRS) scores, respectively.
Overall, 116 patients diagnosed with subacute ischaemic stroke were included in this retrospective study. Based on T2-FLAIR images and ADC maps, 15 texture features were extracted from the ROIs of each patient using grey-level co-occurrence matrix (GLCM) and local binary pattern histogram Fourier (LBP-HF) methods. The correlations of NIHSS score on admission (NIHSS), NIHSS score 24 h after stroke onset (NIHSS) and mRS score with the texture features were evaluated using Spearman's partial correlations. The receiver operating characteristic (ROC) curve was used to compare the performance of the selected texture features in the evaluation of stroke severity and prognosis.
Texture features derived from the T2-FLAIR images and ADC maps were correlated with NIHSS score and mRS score. Entropy and 0.75Quantile showed the best diagnostic performance for assessing stroke severity. The combination of Entropy and 0.75Quantile achieved a better performance in the evaluation of stroke severity (AUC = 0.7, p = 0.01) than either feature alone. Only 0.05Quantile was found to be correlated with mRS score, and none of the texture features were predictive of mRS score.
Texture features derived from T2-FLAIR images and ADC maps might serve as biomarkers to evaluate stroke severity, but were insufficient to predict stroke prognosis.
利用美国国立卫生研究院卒中量表（NIHSS）和改良 Rankin 量表（mRS）评分，分别探讨基于 T2 加权液体衰减反转恢复（T2-FLAIR）图像和表观扩散系数（ADC）图的纹理分析在评估缺血性卒中严重程度和预后中的可行性。
本回顾性研究共纳入 116 例诊断为亚急性缺血性卒中的患者。基于 T2-FLAIR 图像和 ADC 图，使用灰度共生矩阵（GLCM）和局部二值模式直方图傅里叶（LBP-HF）方法从每位患者的 ROI 中提取 15 个纹理特征。使用 Spearman 部分相关评估入院时 NIHSS 评分（NIHSS）、卒中后 24 小时 NIHSS 评分（NIHSS）和 mRS 评分与纹理特征的相关性。采用受试者工作特征（ROC）曲线比较所选纹理特征在评估卒中严重程度和预后中的性能。
来自 T2-FLAIR 图像和 ADC 图的纹理特征与 NIHSS 评分和 mRS 评分相关。熵和 0.75Quantile 在评估卒中严重程度方面具有最佳的诊断性能。熵和 0.75Quantile 的组合在评估卒中严重程度方面的性能优于单独使用任一特征（AUC=0.7，p=0.01）。仅 0.05Quantile 与 mRS 评分相关，且无任何纹理特征可预测 mRS 评分。
T2-FLAIR 图像和 ADC 图衍生的纹理特征可能成为评估卒中严重程度的生物标志物，但不足以预测卒中预后。
