Comparing the results of manual and automated quantitative corneal neuroanalysing modules for beginners

Abstract

This study aimed to evaluate the reliability of in vivo confocal microscopic neuroanalysis by beginners using manual and automated modules. Images of sub-basal corneal nerve plexus (SCNP) from 108 images of 18 healthy participants were analyzed by 7 beginner observers using manual (CCMetrics, [CCM]) and automated (ACCMetrics, [ACCM]) module. SCNP parameters analyzed included corneal nerve fiber density (NFD), corneal nerve branch density (NBD), corneal nerve fiber length (NFL), and tortuosity coefficient (TC). The intra-observer repeatability, inter-observer reliability, inter-module agreement, and left–right eye symmetry level of SCNP parameters were examined. All observers showed good intra-observer repeatability using CCM (intraclass correlation coefficient [ICC] > 0.60 for all), except when measuring TC. Two observers demonstrated especially excellent repeatability in analyzing NFD, NBD, and NFL using manual mode, indicating the quality of interpretation may still be observer-dependent. Among all SCNP parameters, NFL had the best inter-observer reliability (Spearman’s rank-sum correlation coefficient [SpCC] and ICC > 0.85 for the 3 original observers) and left–right symmetry level (SpCC and ICC > 0.60). In the additional analysis of inter-observer reliability using results by all 7 observers, only NFL showed good inter-observer reliability (ICC = 0.79). Compared with CCM measurements, values of ACCM measurements were significantly lower, implying a poor inter-module agreement. Our result suggested that performance of quantitative corneal neuroanalysis by beginners maybe acceptable, with NFL being the most reliable parameter, and automated method cannot fully replace manual work.

Semiautomated and Automated Quantitative Analysis of Corneal Sub-Basal Nerves in Patients With DED With Ocular Pain Using IVCM

“…The ACCMetrics software can partially replace semiautomated methods (18). The traditional semiautomated method has a high ICC and CoR between observers for the CNFD, CNBD, and CNFL (Table 1 and Figure 1).…”

“…The observers can obtain additional pathological details on factors, such as inflammatory cells, nerve ganglion, neuroma, and nerve endpoint, which helps them make a more accurate diagnosis of the situation (19). However, these methods are not only time and energy consuming, but also challenging to apply in a medical environment, particularly, when analyzing large amounts of data (18).…”

Segmentation and Evaluation of Corneal Nerves and Dendritic Cells From In Vivo Confocal Microscopy Images Using Deep Learning

“…This is in agreement with previous studies using ACCMetrics in which only images with high optical quality with regard to brightness, contrast, and sharpness were selected for the analysis. 69 , 70 In this context, Williams et al 43 proposed further research on interrupted CNF segments. Our proposed deep learning model was trained using low-quality images; thus, it seems able to segment more nerves in the category of low-quality images.…”

Corneal structural alterations in autism spectrum disorder: An in vivo confocal microscopy study

“…The obtained size of the 2‐dimensional image products was 384 × 384, with a transverse optical resolution of 10 um per pixel. All examinations were performed by an experienced technician according to the published protocols (Huang et al, 2017; Wu et al, 2021). The detailed procedure was introduced in our previous study (Wu et al, 2021).…”

“…All examinations were performed by an experienced technician according to the published protocols (Huang et al, 2017; Wu et al, 2021). The detailed procedure was introduced in our previous study (Wu et al, 2021). To avoid the pressure artifacts of the microscope from making contact with the eye, participants' head positions were maintained via a fixed chin rest, and the procedure was performed by the same technician using the same steps and pace for all participants.…”