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

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  • معلومة اضافية
    • المصدر:
      Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One
    • بيانات النشر:
      Original Publication: San Francisco, CA : Public Library of Science
    • الموضوع:
      Nerve Regeneration*/physiology ; Axons*/physiology ; Peripheral Nerves*/physiology; Animals ; Rats ; Myelin Sheath/physiology ; Automation ; Median Nerve/physiology ; Image Processing, Computer-Assisted/methods ; Deep Learning ; Male
    • نبذة مختصرة :
      Competing Interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: Mathieu Boudreau and Julien Cohen-Adad worked on the original development of AxonDeepSeg, which is an open source program. They were involved in technical support and writing but were not involved in data acquisition or analysis. Neither received or stand to receive financial compensation for this work. This does not alter our adherence to all PLOS ONE policies on sharing data and materials.
      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.
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    • الموضوع:
      Date Created: 20210708 Date Completed: 20240724 Latest Revision: 20240724
    • الموضوع:
      20250114
    • الرقم المعرف:
      PMC8263263
    • الرقم المعرف:
      10.1371/journal.pone.0248323
    • الرقم المعرف:
      34234376