Liu Nan, Chen Hui, Wu Bing, Li Ying, Wintermark Max, Jackson Alan, Hu Jun, Zhang Yongwei, Su Zihua, Zhu Guangming, Zhang Weiwei
Third Military Medical University, Chongqing, 400038, China.
Department of Neurology, Military General Hospital of Beijing PLA, Beijing, 100700, China.
Mol Neurobiol. 2017 May;54(4):2539-2546. doi: 10.1007/s12035-016-9838-x. Epub 2016 Mar 18.
In this study, we determined whether a prediction of final infarct volume (FIV) and clinical outcomes in patients with an acute stroke is improved by using a contrast transfer coefficient (K ) as a biomarker for blood-brain barrier (BBB) dysfunction. Here, consecutive patients admitted with signs and symptoms suggesting acute hemispheric stroke were included in this study. Ninety-eight participants with intra-arterial therapy were assessed (46 female). Definition of predicted FIV was performed using conventional perfusion CT (PCT-PIV) parameters alone and in combination with K (K -PIV). Multiple logistic regression analyses and linear regression modeling were conducted to determine independent predictors of the 90-day modified Rankin score (mRS) and FIV, respectively. We found that patients with favorable outcomes were younger and had lower National Institutes of Health Stroke Scale (NIHSS) score, smaller PCT-PIV, K -PIV, and smaller FIV (P < 0.001). K -PIV showed good correlation with FIV (P < 00.001, R = 0.6997). In the regression analyses, K -PIV was the best predictor of clinical outcomes (P = 0.009, odds ratio (OR) = 1.960) and also the best predictor for FIV (F = 75.590, P < 0.0001). In conclusion, combining PCT and K maps derived from first-pass PCT can identify at-risk cerebral ischemic tissue more precisely than perfusion parameters alone. This provides improved accuracy in predicting FIV and clinical outcomes.
在本研究中，我们确定了使用对比剂转移系数（K）作为血脑屏障（BBB）功能障碍的生物标志物，是否能改善急性中风患者最终梗死体积（FIV）和临床结局的预测。在此，本研究纳入了有提示急性半球性中风体征和症状的连续入院患者。对98名接受动脉内治疗的参与者进行了评估（46名女性）。单独使用传统灌注CT（PCT - PIV）参数并结合K（K - PIV）来定义预测的FIV。进行了多项逻辑回归分析和线性回归建模，以分别确定90天改良Rankin量表（mRS）和FIV的独立预测因素。我们发现，预后良好的患者更年轻，美国国立卫生研究院卒中量表（NIHSS）评分更低，PCT - PIV、K - PIV更小，FIV也更小（P < 0.001）。K - PIV与FIV显示出良好的相关性（P < 0.001，R = 0.6997）。在回归分析中，K - PIV是临床结局的最佳预测指标（P = 0.009，比值比（OR）= 1.960），也是FIV的最佳预测指标（F = 75.590，P < 0.0001）。总之，将首次通过灌注CT得出的PCT和K图相结合，比单独使用灌注参数能更精确地识别有风险的脑缺血组织。这在预测FIV和临床结局方面提高了准确性。
