Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK.
Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK.
J Peripher Nerv Syst. 2024 Sep;29(3):329-338. doi: 10.1111/jns.12650. Epub 2024 Aug 20.
To develop a standardised, automated protocol for detecting protein gene product 9.5 (PGP9.5) positive intra-epidermal nerve fibres (IENFs) in skin biopsies, transitioning from the established manual technique to an automated platform. This automated method, although currently intended for research applications, may improve the accessibility of this diagnostic test for small fibre neuropathy in clinical settings.
Skin biopsies (n = 274) from 100 participants (fibromyalgia syndrome n = 62; idiopathic small fibre neuropathy: n = 16; healthy volunteers: n = 22) were processed using an automated immunohistochemistry platform. IENF quantification was performed by blinded examiners, with reliability assessed via a two-way mixed-effects model to evaluate inter- and intra-observer variability.
The automated staining system reproduced intra-epidermal nerve fibre density (IENFD) counts consistent with free-floating sections (mean ± standard deviation: free-floating: 5.6 ± 3.4 fibres/mm; automated: 5.9 ± 3.2 fibres/mm). A median difference of 0.3 with a lower bound 95% Confidence Interval (CI) at -0.00005 established non-inferiority against a margin of -0.4 (p = .08). Specifically, the inter-class correlation coefficient (class denotes consistency in measured observations) was 99% (95% CI: 0.9-1), indicating excellent agreement between free-floating and automated methods. The inter- and intra-class coefficient between examiners were both 99% (95% CI: 0.9-0.1) for IENFD, demonstrating high reliability using sections stained using the automated method.
Automated immunohistochemistry provides high-throughput reliable and reproducible intra-epidermal nerve fibre quantification. This method, although currently proof-of-concept, for research use only, may be more widely deployed in histopathology laboratories to increase the adoption of IENFD assessment for the diagnosis of peripheral neuropathies.
开发一种标准化、自动化的检测皮肤活检中蛋白基因产物 9.5（PGP9.5）阳性表皮内神经纤维（IENF）的方法，从现有的手动技术过渡到自动化平台。这种自动化方法虽然目前仅用于研究应用，但可能会提高临床中小纤维神经病患者进行这种诊断测试的可及性。
对 100 名参与者（纤维肌痛综合征 n=62；特发性小纤维神经病：n=16；健康志愿者：n=22）的皮肤活检标本（n=274）进行了自动化免疫组化平台处理。盲法观察者进行了 IENF 定量，通过双向混合效应模型评估可靠性，以评估观察者间和观察者内的变异性。
自动化染色系统复制了与游离切片一致的表皮内神经纤维密度（IENFD）计数（平均值±标准差：游离切片：5.6±3.4 纤维/mm；自动化：5.9±3.2 纤维/mm）。中位差异为 0.3，下限 95%置信区间（CI）为-0.00005，表明与-0.4 的边缘值相比具有非劣效性（p=0.08）。具体来说，类内相关系数（类表示测量观察值的一致性）为 99%（95%CI：0.9-1），表明游离切片和自动化方法之间具有极好的一致性。IENFD 检查者之间的组内和组间系数均为 99%（95%CI：0.9-0.1），表明使用自动化方法染色的切片具有很高的可靠性。
自动化免疫组化提供了高通量可靠且可重复的表皮内神经纤维定量。这种方法虽然目前仅用于研究用途，但可能会在组织病理学实验室中得到更广泛的应用，以增加对 IENFD 评估用于外周神经病变诊断的采用。
