# Technical report: Efficient and accurate assessment of neurite outgrowth in spiral ganglion explants using Sholl analysis and repeated measurement ANOVA

## TL;DR

This study introduces an efficient automated method using Sholl analysis and repeated measures ANOVA to assess neurite growth in spiral ganglion explants, reducing manual labor.

## Contribution

The study introduces an improved Sholl analysis with repeated measures ANOVA for high-throughput, accurate, and efficient neurite outgrowth assessment.

## Key findings

- Sholl analysis outperformed manual and Gray Value methods in time and precision.
- Sholl analysis with rm ANOVA showed minimal deviation from manual measurements.
- Gray Value analysis correlated with neuronal survival based on explant brightness.

## Abstract

Cultivating three-dimensional spiral ganglion explants is a well-established in-vitro assay for assessing the neurotrophic potential of compounds. The manual neurite measurement remains common but hinders high-throughput experimentation. The present study aimed to automate this process, comparing two methods, Sholl and Gray Value analysis, with manual neurite measurement to enhance this time-consuming and labor-intensive evaluation. The explants were cultured with brain-derived neurotrophic factor (BDNF), and both neurons and neurites were marked immunohistochemically. The comparison of methods included significance of treatment group differences, accuracy, precision, time and interference. Sholl analysis outperformed manual measurements in time and precision, exhibiting fewer interferences compared to Gray Value analysis. It effectively distinguished between control and BDNF concentrations, paralleling manual tracing outcomes. The Sholl intersections per radius analysis, employing repeated measures (rm) ANOVA across 31 measurement points, exhibited the smallest deviation from manual measurement. Gray Value analysis introduced inner explant brightness as a parameter that parallels neuronal survival within the explant. The present study demonstrates, that Sholl analysis with rm ANOVA emerged as the most efficient, with reduced time and manpower requirements. This positions the improved Sholl analysis as a potent tool for high-throughput, automated assessments of neurotrophic potential, marking a significant advancement in the field.