摘要
目的探讨脑深部区域纹状体及黑质的脑细胞间隙(ECS)的形态结构与生理特征,检测磁示踪法探测脑深部结构的准确性,发展新型脑深部结构成像技术。材料与方法 20只雄性SD大鼠随机分为纹状体、黑质两组,每组10只,分别在2个脑区ECS内注入示踪剂钆喷酸葡胺,应用MRI仪探测示踪剂扩散过程图像,利用自主研发的软件计算有效扩散系数(D*)、清除率(k')、示踪剂最大扩散范围(Vd-max%)及半衰期(t*1/2)等ECS扩散参数。结果纹状体区D为(3.23±0.60)×10^(-4) mm2/s,高于黑质区的(2.24±0.54)×10^(-4) mm2/s,差异有统计学意义(t=3.842,P<0.05);两组k'值分别为(0.69±0.93)×10^(-4)/s、(0.82±0.20)×10^(-4)/s,差异无统计学意义(t=-1.823,P>0.05);纹状体区Vd-max%值及t_(1/2)分别为(8.91±0.66)%、(84.57±2.62)min,均较黑质区的(3.49±0.32)%、(70.95±2.08)min大,差异有统计学意义(t=7.390、4.069,P<0.05)。结论应用新型磁示踪法可以在全脑尺度动态显示细胞间隙内组织液的运动、分布与清除过程,并对脑深部组织的细胞间隙进行成像与定量分析。
Purpose To investigate the morphological structure and physiological properties of extracellular space(ECS) of striatum and substantia nigra, and test the accuracy of the magnetic tracer-based method so as to develop a new imaging technology to detect deep brain structure. Materials and Methods Twenty male Sprague-Dawley rats were randomly divided into two groups: striatum and substantia nigra(n=10, respectively). As a tracer, gadolinium-diethylene triaminepentaacetic acid was injected into the ECS, then rats were scanned by MRI to detect the process of the tracer diffusion. The diffusion parameters including effective diffusion coefficient(D*), clearance rate(k'), the maximal distribution volume ratio(Vd-max%) and half-life(t1/2) were calculated by using selfdeveloped software. Results Compared with substantia nigra group, D*, Vd-max% and k' were significantly larger in striatum group [(3.23±0.60)×10^(-4) mm^2/s vs.(2.24±0.54)×10^(-4) mm^2/s;(8.91±0.66)% vs.(3.49±0.32)%;(84.57±2.62) min vs.(70.95±2.08) min](t=3.842, 7.390 and 4.069, P〈0.05), but there was no significant difference of the k' value between two groups [(0.69±0.93)×10^(-4)/s vs.(0.82±0.20)×10^(-4)/s](t=- 1.823, P〈0.05). Conclusion These results suggest that the novel magnetic tracer-based method can show the movement, distribution and drainage process of interstitial fluid in the whole brain ECS, image and quantitatively analyze the deep brain region ECS.
出处
《中国医学影像学杂志》
CSCD
北大核心
2016年第6期401-406,共6页
Chinese Journal of Medical Imaging
基金
国家自然科学基金项目(61450004
81471633)
高等学校博士学科点专项科研基金项目(20130001130013)