Open-source software to calculate the static sciatic index automatically

The static sciatic index is commonly used in rat models of nerve crush injury to quantify functional recovery from new therapies under evaluation. However, it is challenging to standardize these measurements across different investigations, and the process is labor intensive.

A new machine learning method was previously developed that performs these measurements automatically and consistently. Here, the approach is tested using two data sets that use different experimental setups, and end-user requirements are evaluated.

The model's outputs presented a nerve regeneration profile comparable to the manual measurements and outperformed the latter by having a much tighter standard deviation (± 5- ± 10 compared to ± 10 - ± 50).

An inexpensive automatic tool that can perform functional analysis for nerve repair research was developed and tested. The software is available open source to facilitate its dissemination and use in quantifying recovery from peripheral nerve crush injury.