A simple and robust method for automating analysis of naïve and regenerating peripheral nerves

Abstract

Background Manual axon histomorphometry (AH) is time- and resource-intensive, which has inspired many attempts at automation. However, there has been little investigation on implementation of automated programs for widespread use. Ideally such a program should be able to perform AH across imaging modalities and nerve states. AxonDeepSeg (ADS) is an open source deep learning program that has previously been validated in electron microscopy. We evaluated the robustness of ADS for peripheral nerve axonal histomorphometry in light micrographs prepared using two different methods. Methods Axon histomorphometry using ADS and manual analysis (gold-standard) was performed on light micrographs of naïve or regenerating rat median nerve cross-sections prepared with either toluidine-resin or osmium-paraffin embedding protocols. The parameters of interest included axon count, axon diameter, myelin thickness, and g-ratio. Results Manual and automatic ADS axon counts demonstrated good agreement in naïve nerves and moderate agreement on regenerating nerves. There were small but consistent differences in measured axon diameter, myelin thickness and g-ratio; however, absolute differences were small. Both methods appropriately identified differences between naïve and regenerating nerves. ADS was faster than manual axon analysis. Conclusions Without any algorithm retraining, ADS was able to appropriately identify critical differences between naïve and regenerating nerves and work with different sample preparation methods of peripheral nerve light micrographs. While there were differences between absolute values between manual and ADS, ADS performed consistently and required much less time. ADS is an accessible and robust tool for AH that can provide consistent analysis across protocols and nerve states.

Rapid, automated nerve histomorphometry through open-source artificial intelligence

“…Previous models were trained specifically for electron microscopic images 24 . Notably, their applicability was demonstrated in cross-sectional transmission electron microscopy images of the mouse striatum 25 and tested in light microscopic images of peripheral nerves 26 . We aimed to extend the AxonDeepSeg framework by adding a model specifically trained for axon/myelin segmentation in light microscopic images of osmium tetroxide-stained rat peripheral nerve cross-sections.…”

The Role of Nerve Fibers in the Tumor Immune Microenvironment of Solid Tumors

“…This technology was used to study peripheral nerves with AxonDeepSeg, an open source deep learning program that allow to count axons. [ 8 ] AI has also proven to be a useful tool in the assessment of peripheral nerves, including a study of PNI of prostate cancer were annotations created by trained pathologists were used to build algorithms based on pixels‐wise predictions. [ 156 ]…”

“…This technology was used to study peripheral nerves with AxonDeepSeg, an open source deep learning program that allow to count axons. [8] AI has also proven to be a useful tool in the assessment of peripheral nerves, including…”

“…[ 6 ] There are many techniques that can be used to evaluate nerve fibers in tissue, namely, routine hematoxylin and eosin (H&E) staining combined with microscopy evaluation and more advanced technologies including artificial intelligence or hi‐plex techniques that allow the analysis of several biomarkers in limited tissue samples. [ 7,8 ]…”

“…[6] There are many techniques that can be used to evaluate nerve fibers in tissue, namely, routine hematoxylin and eosin (H&E) staining combined with micro scopy evaluation and more advanced technologies including artificial intelligence or hi-plex techniques that allow the analysis of several biomarkers in limited tissue samples. [7,8] More importantly, understanding the mutual interactions between nerves and solid tumors may accelerate the development of novel drugs and surgical therapeutic approaches. [9] Nerves seem to have a trophic and immune impact in tumors similarly to the well-known nerve functions in tissue regeneration, and in immunity, these features can potentially be exploited to develop novel and more efficacious therapeutic approaches.…”