From the Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto.
Instituto de investigação e inovação em Saúde da Universidade do Porto (i3S), Porto, Portugal.
J Neuropathol Exp Neurol. 2021 Aug 11;80(7):685-694. doi: 10.1093/jnen/nlab045.
Intraepidermal nerve fiber density (IENFD) measurements in skin biopsy are performed manually by 1-3 operators. To improve diagnostic accuracy and applicability in clinical practice, we developed an automated method for fast IENFD determination with low operator-dependency. Sixty skin biopsy specimens were stained with the axonal marker PGP9.5 and imaged using a widefield fluorescence microscope. IENFD was first determined manually by 3 independent observers. Subsequently, images were processed in their Z-max projection and the intradermal line was delineated automatically. IENFD was calculated automatically (fluorescent images automated counting [FIAC]) and compared with manual counting on the same fluorescence images (fluorescent images manual counting [FIMC]), and with classical manual counting (CMC) data. A FIMC showed lower variability among observers compared with CMC (interclass correlation [ICC] = 0.996 vs 0.950). FIMC and FIAC showed high reliability (ICC = 0.999). A moderate-to-high (ICC = 0.705) was observed between CMC and FIAC counting. The algorithm process took on average 15 seconds to perform FIAC counting, compared with 10 minutes for FIMC counting. This automated method rapidly and reliably detects small nerve fibers in skin biopsies with clear advantages over the classical manual technique.
表皮内神经纤维密度（IENFD）的测量是通过 1-3 名操作人员手动完成的。为了提高诊断准确性和临床实用性，我们开发了一种快速、低操作者依赖性的自动 IENFD 确定方法。对 60 个皮肤活检标本进行轴突标记物 PGP9.5 染色，并使用宽场荧光显微镜进行成像。首先由 3 名独立观察者手动确定 IENFD。随后，在 Z-最大值投影中处理图像，并自动描绘皮内线。自动计算 IENFD（荧光图像自动计数[FIAC]），并将其与相同荧光图像上的手动计数（荧光图像手动计数[FIMC]）和经典手动计数（CMC）数据进行比较。与 CMC 相比，FIMC 显示出观察者之间更低的变异性（组内相关系数[ICC] = 0.996 比 0.950）。FIMC 和 FIAC 显示出高度的可靠性（ICC = 0.999）。在 CMC 和 FIAC 计数之间观察到中等至高（ICC = 0.705）的相关性。与 FIMC 计数相比，FIAC 计数的算法处理平均耗时 15 秒。与经典的手动技术相比，这种自动方法在皮肤活检中快速可靠地检测小神经纤维具有明显的优势。
