Intraepidermal nerve fiber analysis using immunofluorescence with and without confocal microscopy

2015 ◽  
Vol 51 (4) ◽  
pp. 501-504 ◽  
Author(s):  
Vincenzo Provitera ◽  
Maria Nolano ◽  
Annamaria Stancanelli ◽  
Giuseppe Caporaso ◽  
Dino F. Vitale ◽  
...  
Keyword(s):  
Confocal Microscopy ◽  
Nerve Fiber ◽  
Fiber Analysis ◽  
Nerve Fiber Analysis ◽  
Intraepidermal Nerve Fiber

scholarly journals Intraepidermal Nerve Fiber Analysis in Human Patients and Animal Models of Peripheral Neuropathy: A Comparative Review

2019 ◽  
Vol 48 (1) ◽  
pp. 59-70 ◽  
Author(s):  
Lisa M. Mangus ◽  
Deepa B. Rao ◽  
Gigi J. Ebenezer
Keyword(s):  
Peripheral Neuropathy ◽  
Animal Models ◽  
Skin Biopsy ◽  
Nerve Fiber ◽  
Sensory Nerve ◽  
Nerve Fibers ◽  
Fiber Analysis ◽  
Comparative Review ◽  
Nerve Fiber Analysis ◽  
Intraepidermal Nerve Fiber

Analysis of intraepidermal nerve fibers (IENFs) in skin biopsy samples has become a standard clinical tool for diagnosing peripheral neuropathies in human patients. Compared to sural nerve biopsy, skin biopsy is safer, less invasive, and can be performed repeatedly to facilitate longitudinal assessment. Intraepidermal nerve fiber analysis is also more sensitive than conventional nerve histology or electrophysiological tests for detecting damage to small-diameter sensory nerve fibers. The techniques used for IENF analysis in humans have been adapted for large and small animal models and successfully used in studies of diabetic neuropathy, chemotherapy-induced peripheral neuropathy, HIV-associated sensory neuropathy, among others. Although IENF analysis has yet to become a routine end point in nonclinical safety testing, it has the potential to serve as a highly relevant indicator of sensory nerve fiber status in neurotoxicity studies, as well as development of neuroprotective and neuroregenerative therapies. Recently, there is also interest in the evaluation of IENF via skin biopsy as a biomarker of small fiber neuropathy in the regulatory setting. This article provides an overview of the anatomic and pathophysiologic principles behind IENF analysis, its use as a diagnostic tool in humans, and applications in animal models with focus on comparative methodology and considerations for study design.

scholarly journals Deep Learning-Based Analysis of Macaque Corneal Sub-Basal Nerve Fibers in Confocal Microscopy Images

2019 ◽  
Author(s):  
Jonathan D. Oakley ◽  
Daniel B. Russakoff ◽  
Megan E. McCarron ◽  
Rachel L. Weinberg ◽  
Jessica M. Izzi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Confocal Microscopy ◽  
Nerve Fiber ◽  
Ground Truth ◽  
Automated Analysis ◽  
Nerve Fibers ◽  
Fiber Analysis ◽  
Quantitative Measurements ◽  
Nerve Fiber Analysis

AbstractPurposeTo describe and assess different deep learning-based methods for automated measurement of macaque corneal sub-basal nerves using in vivo confocal microscopy (IVCM).MethodsThe automated assessment of corneal nerve fiber length (CNFL) in IVCM images is of increasing clinical interest. These measurements are important biomarkers in a number of diseases including diabetes mellitus, human immunodeficiency virus, Parkinson’s disease and multiple sclerosis. Animal models of these and other diseases play an important role in understanding the disease processes as efforts toward developing new and effective therapeutics are made. And while automated methods exist for nerve fiber analysis in clinical data, differences in anatomy and image quality make the macaque data more challenging and has motivated the work reported here.Toward this goal, nerves in macaque corneal IVCM images were manually labelled using an ImageJ plugin (NeuronJ). Different deep convolutional neural network (CNN) architectures were evaluated for accuracy relative to the ground truth manual tracings. The best performing model was used on separately acquired macaque ICVM images to additionally compare inter-reader variability.ConclusionsDeep learning-based segmentation of sub-basal nerves in IVCM images shows excellent correlation to manual segmentations in macaque data. The technique is indistinguishable across readers and paves the way for more widespread adoption of objective automated analysis of sub-basal nerves in IVCM.Translational RelevanceQuantitative measurements of corneal sub-basal nerves are important biomarkers for disease screening and management. This work reports on different approaches that, in using deep learning-based techniques, leverage state of the art analysis methods to demonstrate performance akin to human graders. In application, the approach is robust, rapid and objective, offering utility to a variety of clinical studies using IVCM.

scholarly journals Morphometric Nerve Fiber Analysis and Aging Process of the Human Abducent Nerve

1998 ◽  
Vol 74 (6) ◽  
pp. 337-343 ◽  
Author(s):  
Yoshiharu SAWABE ◽  
Kiyoshi MATSUMOTO ◽  
Noboru GOTO ◽  
Naruhito OTSUKA ◽  
Nobusuke KOBAYASHI
Keyword(s):  
Nerve Fiber ◽  
Aging Process ◽  
Fiber Analysis ◽  
Nerve Fiber Analysis ◽  
Abducent Nerve

scholarly journals Morphometric Nerve Fiber Analysis and Aging Process of the Human Inferior Alveolar Nerve

2001 ◽  
Vol 78 (2-3) ◽  
pp. 55-59 ◽  
Author(s):  
Narumi SAGARA ◽  
Hiroshi MORIYAMA ◽  
Yasushi MIYAUCHI ◽  
Hiroaki TAM ◽  
Noboru GOTO
Keyword(s):  
Nerve Fiber ◽  
Aging Process ◽  
Inferior Alveolar Nerve ◽  
Fiber Analysis ◽  
Nerve Fiber Analysis

Nerve Fiber Analysis of the Facial Nerve

1989 ◽  
Vol 98 (9) ◽  
pp. 732-735 ◽  
Author(s):  
Mayumi Fujii ◽  
Noboru Goto
Keyword(s):  
Facial Nerve ◽  
Nerve Fiber ◽  
Myelin Sheath ◽  
Staining Method ◽  
Statistical Analyses ◽  
Simultaneous Observation ◽  
Fiber Analysis ◽  
Nerve Fiber Analysis ◽  
Average Size

Nerve fiber analyses were conducted on the human facial nerve with use of a new staining method (Luxol-PAS-hematoxylin stain; discriminative staining method) that permits simultaneous observation of the axon and surrounding myelin sheath. The following combination of equipment was employed in the study: An image-analyzing digitizer, a microscope with a drawing tube, and a computer for storing the data and performing statistical analyses. The numbers, transverse areas, and circularity ratios of axons were measured in 11 cases. The average number of axons composing one facial nerve was 6,254, and the average size of the axons was 6.23 μm2. The results indicated that although the numbers of axons became reduced with age, the transverse areas and circularity ratios of the axons did not change with age.

Polarimetric Nerve Fiber Analysis in Patients with Visible Optic Nerve Head Drusen

2001 ◽  
Vol 21 (4) ◽  
pp. 245-249 ◽  
Author(s):  
Sinan Tatlipinar ◽  
Sibel Kadayif??ilar ◽  
Banu Bozkurt ◽  
??ansal Gedik ◽  
Ergun Karaa??ao??lu ◽  
...  
Keyword(s):  
Optic Nerve ◽  
Nerve Fiber ◽  
Optic Nerve Head ◽  
Fiber Analysis ◽  
Optic Nerve Head Drusen ◽  
Nerve Fiber Analysis

scholarly journals Unmyelinated Nerve Fiber Analysis of the Human Oculomotor Nerve

2000 ◽  
Vol 77 (2-3) ◽  
pp. 59-62 ◽  
Author(s):  
Noriyoshi KAWAMURA ◽  
Kiyoshi MATSUMOTO ◽  
Akira WADA ◽  
Noboru GOTO
Keyword(s):  
Nerve Fiber ◽  
Oculomotor Nerve ◽  
Fiber Analysis ◽  
Nerve Fiber Analysis ◽  
Unmyelinated Nerve
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