Christoforidis G A, Vakil P, Ansari S A, Dehkordi F H, Carroll T J
From the Department of Radiology (G.A.C., S.A.A., T.J.C.), University of Chicago, Chicago, Illinois
College of Medicine (P.V.), University of Illinois, Chicago, Illinois.
AJNR Am J Neuroradiol. 2017 Feb;38(2):270-275. doi: 10.3174/ajnr.A5003. Epub 2016 Nov 17.
Cerebral infarction evolves at different rates depending on available blood flow suggesting that treatment time windows vary depending on the degree of pial collateral recruitment. This work sought to mathematically model infarct growth and determine whether infarct volume growth can be predicted by angiographic assessment of pial collateral recruitment in an experimental MCA occlusion animal model.
Pial collateral recruitment was quantified by using DSA, acquired 15 minutes following permanent MCA occlusion in 6 canines based on a scoring system (average pial collateral score) and arterial arrival time. MR imaging-based infarct volumes were measured 60, 90, 120, 180, 240 and 1440 minutes following MCA occlusion and were parameterized in terms of the growth rate index and final infarct volume (V) as () = [1 - ] (t = time). Correlations of the growth rate index and final infarct volume to the average pial collateral score and arterial arrival time were assessed by linear bivariate analysis. Correlations were used to generate asymptotic models of infarct growth for average pial collateral score or arterial arrival time values. Average pial collateral score- and arterial arrival time-based models were assessed by tests and residual errors.
Evaluation of pial collateral recruitment at 15 minutes postocclusion was strongly correlated with 24-hour infarct volumes (average pial collateral score: = 0.96, < .003; arterial arrival time: = 0.86, < .008). Infarct growth and the growth rate index had strong and moderate linear relationships to the average pial collateral score = 0.89; < .0033) and arterial arrival time ( = 0.69; < .0419), respectively. Final infarct volume and the growth rate index were algebraically replaced by angiographically based collateral assessments to model infarct growth. The test demonstrated no statistical advantage to using the average pial collateral score- over arterial arrival time-based predictive models, despite lower residual errors in the average pial collateral score-based model ( < .03).
In an experimental permanent MCA occlusion model, assessment of pial collaterals correlates with the infarct growth rate index and has the potential to predict asymptotic infarct volume growth.
脑梗死根据可获得的血流以不同速率发展,这表明治疗时间窗因软脑膜侧支循环的募集程度而异。本研究旨在通过数学模型模拟梗死灶生长,并确定在实验性大脑中动脉闭塞动物模型中,能否通过软脑膜侧支循环募集的血管造影评估来预测梗死灶体积的增长。
在6只犬永久性大脑中动脉闭塞后15分钟,使用数字减影血管造影(DSA)基于评分系统(平均软脑膜侧支评分)和动脉到达时间对软脑膜侧支循环募集进行量化。在大脑中动脉闭塞后60、90、120、180、240和1440分钟测量基于磁共振成像的梗死灶体积,并根据生长速率指数和最终梗死灶体积(V)进行参数化,公式为V(t)=V[1 - e^(-kt)](t为时间)。通过线性双变量分析评估生长速率指数和最终梗死灶体积与平均软脑膜侧支评分和动脉到达时间的相关性。利用相关性生成基于平均软脑膜侧支评分或动脉到达时间值的梗死灶生长渐近模型。通过F检验和残差误差评估基于平均软脑膜侧支评分和动脉到达时间的模型。
闭塞后15分钟对软脑膜侧支循环募集的评估与24小时梗死灶体积密切相关(平均软脑膜侧支评分:r = 0.96,P <.003;动脉到达时间:r = 0.86,P <.008)。梗死灶生长和生长速率指数与平均软脑膜侧支评分(r = 0.89;P <.0033)和动脉到达时间(r = 0.69;P <.0419)分别具有强和中等程度的线性关系。用基于血管造影的侧支循环评估代数替换最终梗死灶体积和生长速率指数以模拟梗死灶生长。F检验表明,尽管基于平均软脑膜侧支评分的模型残差误差较低(P <.03),但使用基于平均软脑膜侧支评分的预测模型与基于动脉到达时间的预测模型相比无统计学优势。
在实验性永久性大脑中动脉闭塞模型中,软脑膜侧支循环评估与梗死灶生长速率指数相关,并有潜力预测渐近性梗死灶体积增长。