title: A semi-automated method to assess intraepidermal nerve fibre density in human skin biopsies.
abstract: OBJECTIVE
  Evaluation of intraepidermal nerve fibres (IENFs) in skin biopsies is used in the diagnosis of small-fibre neuropathies. The number of IENFs is assessed manually under a microscope, with an inter-rater variability of ~25%. Unless the images are digitized, there is no documentation. Our aim was to develop a method for standardized semi-automated quantification (SAQ) and documentation of IENF density.
  
  
  RESULTS
  We analysed samples from four different university centres that were immunostained according to local protocols. Images were acquired through the Z-plane with a whole slide scanner. orbit image analysis software was used to create an analysable image and develop a reliable algorithm for IENF detection. Rebuilt images revealed well-contrasted nerves, allowing detection of IENFs (automated). The software presented the detected nerves for confirmation by the operator (manual). As compared with the conventional microscopy count, the SAQ achieved correlation coefficients of 0.99 and 0.96 and interfacility variabilities of 19% and 23%, respectively. We found better reproducibility with fluorescence-stained specimens than with bright-field images.
  
  
  CONCLUSIONS
  The new semi-automated method has high experimenter-independent reproducibility when based on nerve detection by fluorescence and is easy to perform, even by untrained users. The IENF counting is electronically well documented.
authors.affiliation: Department of Translational Science, Actelion Pharmaceuticals Ltd, Allschwil, Switzerland.
authors.forename: Shanon
authors.identifier: http://orcid.org/0000-0003-1374-2559
authors.initials: S
authors.lastname: Seger
authors.affiliation: Department of Information Management Drug Discovery, Actelion Pharmaceuticals Ltd, Allschwil, Switzerland.
authors.forename: Manuel
authors.initials: M
authors.lastname: Stritt
authors.affiliation: Department of Neurology, University Hospital Würzburg, Würzburg, Germany.
authors.forename: Kathrin
authors.initials: K
authors.lastname: Doppler
authors.affiliation: Department of Neuropathology, University Hospital Basel, Basel, Switzerland.
authors.forename: Stephan
authors.initials: S
authors.lastname: Frank
authors.affiliation: Nerve-Muscle Unit, Department of Clinical Neurosciences, Lausanne University Hospital CHUV, Lausanne, Switzerland.
authors.forename: Adrian
authors.initials: A
authors.lastname: Panaite
authors.affiliation: Nerve-Muscle Unit, Department of Clinical Neurosciences, Lausanne University Hospital CHUV, Lausanne, Switzerland.
authors.forename: Thierry
authors.initials: T
authors.lastname: Kuntzer
authors.affiliation: Department of Neurology, University Hospital Basel, Basel, Switzerland.
authors.forename: Andreas
authors.initials: A
authors.lastname: Steck
authors.affiliation: Department of Neuropathology, University Hospital Giessen and Marburg, Marburg, Germany.
authors.forename: Axel
authors.initials: A
authors.lastname: Pagenstecher
authors.affiliation: Department of Neurology, University Hospital Würzburg, Würzburg, Germany.
authors.forename: Claudia
authors.initials: C
authors.lastname: Sommer
authors.affiliation: Department of Translational Science, Actelion Pharmaceuticals Ltd, Allschwil, Switzerland.
authors.forename: Anna K
authors.initials: AK
authors.lastname: Stalder
mesh_terms: D057205:Automation, Laboratory; D001706:Biopsy; D006801:Humans; D007091:Image Processing, Computer-Assisted; D009412:Nerve Fibers / Q000473:pathology*; D015203:Reproducibility of Results; D012867:Skin / Q000294:innervation*
keywords: IENF; automated quantification; image analysis; peripheral neuropathies; skin biopsy