Autofluorescent imprint of chronic constriction nerve injury identified by deep learning

Neurobiology of Disease

Ayad G. Anwer¹  Ewa M. Goldys²  Mark R. Hutchinson²  Saabah B. Mahbub³  Sanam Mustafa³  Vasiliki Staikopoulos⁴  Martin E. Gosnell⁵ 

[1] Adelaide Medical School, University of Adelaide, Adelaide 5005, Australia;Graduate School of Biomedical Engineering, UNSW Sydney, NSW 2052, Australia;ARC Centre of Excellence for Nanoscale Biophotonics, UNSW Sydney, NSW 2052, Australia;ARC Centre of Excellence for Nanoscale Biophotonics, University of Adelaide, Adelaide 5005, Australia;Quantitative Pty Ltd, 118 Great Western Highway, Mount Victoria, NSW 2786, Australia;

关键词: Chronic pain;    Autofluorescence imaging;    Spinal cord;    Allodynia;    Nerve injury;    Deep learning;   

DOI  :  

来源: DOAJ

【 摘 要 】

Our understanding of chronic pain and the underlying molecular mechanisms remains limited due to a lack of tools to identify the complex phenomena responsible for exaggerated pain behaviours. Furthermore, currently there is no objective measure of pain with current assessment relying on patient self-scoring. Here, we applied a fully biologically unsupervised technique of hyperspectral autofluorescence imaging to identify a complex signature associated with chronic constriction nerve injury known to cause allodynia. The analysis was carried out using deep learning/artificial intelligence methods. The central element was a deep learning autoencoder we developed to condense the hyperspectral channel images into a four- colour image, such that spinal cord tissue based on nerve injury status could be differentiated from control tissue.This study provides the first validation of hyperspectral imaging as a tool to differentiate tissues from nerve injured vs non-injured mice. The auto-fluorescent signals associated with nerve injury were not diffuse throughout the tissue but formed specific microscopic size regions. Furthermore, we identified a unique fluorescent signal that could differentiate spinal cord tissue isolated from nerve injured male and female animals. The identification of a specific global autofluorescence fingerprint associated with nerve injury and resultant neuropathic pain opens up the exciting opportunity to develop a diagnostic tool for identifying novel contributors to pain in individuals.

【 授权许可】

Unknown