Department of Biology, Chemistry and Process Technology, Lausitz University of Applied Sciences, Senftenberg, Germany.
Autoimmun Rev. 2009 Sep;9(1):17-22. doi: 10.1016/j.autrev.2009.02.033. Epub 2009 Feb 24.
Analysis of autoantibodies (AAB) by indirect immunofluorescence (IIF) remains the hallmark of diagnosing autoimmune diseases despite the introduction of multiplex techniques. Non-organ specific AAB are screened in routine diagnostics by IIF on HEp-2 cells. However, IIF results vary due to objective (e.g., cell fixation) and subjective factors (e.g., expert knowledge). Therefore, inter- and intralaboratory variance is relatively high. Standardisation of AAB testing by IIF remains a critical issue in and between routine laboratories and may be improved by automated interpretation systems. An overview of existing interpretation techniques will be given taking into account own data of the first fully automated reading system AKLIDES. The novel system provides fully automated reading of IIF images and software algorithms for the mathematical description of IIF AAB patterns. It can be used for screening and preclassification of non-organ specific AAB in routine diagnostics regarding systemic autoimmune and autoimmune liver diseases. Furthermore, this system paves the way for economic data processing of cell-based IIF assays and can contribute to the reduction of interlaboratory variance of AAB testing. More sophisticated pattern recognition algorithms and novel calibration systems will improve standardised quantifications of IIF image interpretation.
尽管已经引入了多重技术,但间接免疫荧光 (IIF) 分析自身抗体 (AAB) 仍然是诊断自身免疫性疾病的标志。非器官特异性 AAB 通过在 HEp-2 细胞上进行 IIF 在常规诊断中进行筛选。然而,由于客观因素(例如细胞固定)和主观因素(例如专业知识),IIF 结果会有所不同。因此,实验室间和实验室内部的差异相对较高。通过 IIF 标准化 AAB 检测仍然是常规实验室内部和之间的一个关键问题,可以通过自动化解释系统得到改善。在考虑到第一个全自动阅读系统 AKLIDES 的自有数据的情况下,将对现有的解释技术进行概述。该新型系统可全自动读取 IIF 图像,并提供用于描述 IIF AAB 模式的数学软件算法。它可用于系统性自身免疫和自身免疫性肝病的常规诊断中筛选和预分类非器官特异性 AAB。此外,该系统为基于细胞的 IIF 检测的经济数据处理铺平了道路,并有助于减少 AAB 检测的实验室间差异。更复杂的模式识别算法和新型校准系统将改善 IIF 图像解释的标准化定量。