Epidermal Nerve Fiber Length Density Estimation Using Global Spatial Sampling in Healthy Subjects and Neuropathy Patients

• Published in: Journal of neuropathology and experimental neurology Vol. 72; no. 3; pp. 186 - 193
• Main Authors: Karlsson, Páll, Møller, Anette Torvin, Jensen, Troels Staehelin, Nyengaard, Jens Randel
• Format: Journal Article
• Language: English
• Published: England American Association of Neuropathologists, Inc 01.03.2013; Oxford University Press
• Subjects: Adult; Aged; Aged, 80 and over; Biopsy; Epidermis - innervation; Female; Humans; Immunohistochemistry; Male; Medical research; Middle Aged; Nerve Fibers - pathology; Peripheral Nervous System Diseases - pathology; Ratios; Studies; Wound healing
• ISSN: 0022-3069; 1554-6578; 1554-6578
• DOI: 10.1097/NEN.0b013e318284e849

ABSTRACTAssessment of intraepidermal nerve fiber density (IENFD) has become a useful tool for the investigation of patients with suspected small-fiber neuropathy (SFN). Here, we estimate epidermal nerve fiber lengths in 12 patients with SFN and 36 healthy controls using global spatial sampling and compare the lengths with IENFD and axonal swelling ratios. Skin biopsies were analyzed on 50-μm-thick free-floating sections immunostained for the neuronal cytoplasmic marker PGP 9.5. Mean IENFD in SFN patients was 2.22 ± 1.63 mm versus 7.51 ± 2.17 mm in controls; mean length density was 112 ± 82.6 mm in SFN patients versus 565 ± 240 mm in controls (p < 0.001 for both). The correlation between the nerve fiber length and the IENFD was r = 0.16 for healthy subjects and r = 0.39 for patients, suggesting that these variables provide different quantitative information. There were significant differences in axonal swelling ratios between healthy subjects and patients, that is, per IENFD and per nerve fiber length. Together, these results suggest that, although length estimation requires more time and additional equipment, it is as effective as IENFD in differentiating SFN patients from healthy subjects. Estimating nerve fiber length may increase mechanistic understanding beyond IENFD estimation and improve efficiency in diagnosing SFN.