Sallinen P, Haapasalo H, Kerttula T, Rantala I, Kalimo H, Collan Y, Isola J, Helin H
Department of Pathology, Tampere University Hospital, Finland.
Anal Quant Cytol Histol. 1994 Aug;16(4):261-8.
The reproducibility in quantitation of proliferation activity, determined using the monoclonal antibody 19A2 to proliferating cell nuclear antigen (PCNA), was tested in visual and computer-assisted analyses of brain tumor material. The PCNA labeling index was scored using count (PCNA-LI, visual and computer analyses) and area (PCNA-LIa, computer analysis) estimates of immunopositivity. The quality of immunostaining was the most important reason for variation in the assessment results. Other significant variation sources in the assessment were experience in selecting microscopic fields and distinguishing immunopositive nuclei from immunonegative ones. Computer-assisted analysis improved the reproducibility of quantitation between different observers (visual rPCNA-LI = 0.624 versus computer assisted rPCNA-LI = 0.904). Also, the use of PCNA-LIa improved the intraobserver and interobserver reproducibility in different stainings (observer 1:rPCNA-LI = 0.857 versus rPCNA-LIa = 0.874; observers 1 and 2: rPCNA-LI = 0.904 versus rPCNA-LIa = 0.927; observers 3 and 4: rPCNA-LI = 0.848 versus rPCNA-LIa = 0.906). PCNA-LIa by computerized image analysis improves accuracy in the evaluation of the granularly expressed PCNA level. Furthermore, the effect of tumor heterogeneity on the assessment results can be diminished with the computerized method because large tissue areas can be analyzed faster.
在对脑肿瘤材料进行视觉和计算机辅助分析时,测试了使用针对增殖细胞核抗原(PCNA)的单克隆抗体19A2测定增殖活性定量的可重复性。使用免疫阳性的计数(PCNA-LI,视觉和计算机分析)和面积(PCNA-LIa,计算机分析)估计来对PCNA标记指数进行评分。免疫染色质量是评估结果差异的最重要原因。评估中的其他显著变异来源是选择显微镜视野以及区分免疫阳性细胞核与免疫阴性细胞核的经验。计算机辅助分析提高了不同观察者之间定量的可重复性(视觉rPCNA-LI = 0.624,而计算机辅助rPCNA-LI = 0.904)。此外,使用PCNA-LIa提高了不同染色中观察者内和观察者间的可重复性(观察者1:rPCNA-LI = 0.857,而rPCNA-LIa = 0.874;观察者1和2:rPCNA-LI = 0.904,而rPCNA-LIa = 0.927;观察者3和4:rPCNA-LI = 0.848,而rPCNA-LIa = 0.906)。通过计算机图像分析的PCNA-LIa提高了对颗粒状表达的PCNA水平评估的准确性。此外,由于可以更快地分析大组织区域,计算机化方法可以减少肿瘤异质性对评估结果的影响。