Morphometrical analysis of myelinated nerve fibers: is there a room for improvement?

Abstract

Despite advancements in automatic approaches for histomorphometry analysis of peripheral nerves, manual and semi-automated methods are widely utilized. Standard software functions are often unsuitable for analysis due to their irregular shapes, especially in pathological conditions. This study aims to assess the reproducibility of nerves morphometric analysis and compare results obtained using both default and new alternative algorithms. Sciatic nerves from Wistar rats (untreated and after administration of intraperitoneal hydrargyrum chloride), previously embedded in resin, were used. Morphometric analysis (diameters, myelin thickness, g-ratio, and circularity) was conducted using ImageJ on semithin sections, with axon and myelin boundaries manually outlined. Default diameters were calculated as the mean of Feret diameters, with subsequent calculations for myelin thickness and g-ratio. The alternative approach estimated diameters based on the geometric center of axons, iterating through selected coordinates; myelin thickness was obtained using line equations. In the control group, inter-rater agreement was higher or within expected reliability (0.8 ± 0.05). However, in the experimental group, myelin thickness, g-ratio, and axon circularity showed lower agreement (0.66, 0.58, and 0.68, respectively) without visible patterns on Bland–Altman plots. The alternative approach did not reveal significant differences between approaches, except for g-ratio in the control group and fiber diameter in the experimental group (p < 0.05), with effect sizes of 0.29–0.30 and 0.19–0.20, respectively. This study highlights reduced agreement among investigators analyzing nerve fibers under pathological conditions, raising concerns about the current standard measurement methods. The proposed approach, based on a single geometric center, provides more natural estimations for irregular fibers, and can be implemented in automated nerve fibers acquisition systems.