阳性神经元面积百分比和染色灰度相对强度值的结合在大鼠脑组织免疫组化图像定量分析中的应用

目的：通过下丘脑弓状核乙酰胆碱表达的检测、图像处理、图像分析,应用阳性神经元面积百分比（APPN）和染色灰度相对强度值（RISGL）相结合的方法,探讨免疫组化（IHC）图像定量分析的特点。方法：样本来源于运动性免疫抑制过程中SD大鼠下丘脑弓状核胆碱能阳性神经元乙酰胆碱表达的免疫组化切片,包括第0、2、4、6周与每周Control、Immediately after exercise、3 hours after exercise三组共计12组（n=6）。采用免疫组化技术测定其乙酰胆碱（ACh）的表达,并根据ACh阳性神经元总面积（TAPN）、阳性神经元灰度平均强度值（AISGL）、APPN、RISGL、APPN/RISGL参数进行免疫组化图像的定量分析,从而比较APPN和RISGL在定量分析中与传统参数的不同及其优势。结果：APPN与TAPN的变化呈现几乎一致的变化特征,能发现相应差异的显著性意义（P < 0.05）,但APPN的敏感性和抗干扰性更强。RISGL与AISGL呈现的结果并不完全一致,而且APPN结合RISGL比单参数更能反映阳性表达情况。结论：APPN和RISGL免疫组化图像分析参数能较可靠地、准确地进行图像定量分析,APPN与RISGL的结合不仅可反映阳性表达的数量情况,还可以帮助分析其作用机理,优于传统分析参数。

Application of area percent of positive neuron and relative intensity of staining grey level in the image quantitative analysis of rat brain tissues immunohistochemistry

Objective: The acetylcholine expression in hypothalamus arcuate nucleus is detected and then the images are processed and analyzed. The features of the image quantitative analysis of immunohistochemistry (IHC) with the method combining two parameters of area percent of positive neuron (APPN) and relative intensity of staining grey level (RISGL) were investigated. Methods: Samples were the im-munohistochemical slices of acetylcholine(ACh)expression of hypothalamic arcuate nucleus cholinergic neurons in the process of exercise in-duced immunosuppression, which included twelve groups of "0 w, 2 w, 4 w, 6 w" and three groups of "control, immediately after exercise, 3 hours after exercise" in every week. IHC technology was used to detect the ACh expression. The image quantitative analysis of IHC was con-ducted in accordance with the parameters of ACh total area of positive neuron (TAPN), average intensity of staining grey level (AISGL), APPN, RISGL, APPN/RISGL. Then the differences among APPN, RISGL and traditional parameters in the quantitative analysis were com-pared and the advantages were found. Results: The changes of TAPN and APPN showed almost the same variation. Namely the corresponding significant differences could be found through these two parameters(P < 0.05), but the sensitivity and anti-interference of APPN was higher. The results of AISGL and RISGL were not coincident completely. Furthermore, with the combination of APPN and RISGL, the positive expres-sion could be reflected better than any single parameter. Conclusion: The parameters of immunohistochemical image analysis, APPN and RIS-GL, can be reliable and accurate in image quantitative analysis of IHC. The combination of APPN and RISGL can not only reflect the expres-sion of positive neurons, but also help analyze its mechanism, which is better than traditional analysis parameters.