TY - JOUR
T1 - Design-Based stereology and binary image histomorphometry in nerve assessment
AU - Hunter, Daniel A.
AU - Pan, Deng
AU - Wood, Matthew D.
AU - Snyder-Warwick, Alison K.
AU - Moore, Amy M.
AU - Feldman, Eva L.
AU - Mackinnon, Susan E.
AU - Brenner, Michael J.
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/4/15
Y1 - 2020/4/15
N2 - Background: Stereology and histomorphometry are widely used by investigators to quantify nerve characteristics in normal and pathological states, including nerve injury and regeneration. While these methods of analysis are complementary, no study to date has systematically compared both approaches in peripheral nerve. This study investigated the reliability of design-based stereology versus semi-automated binary imaging histomorphometry for assessing healthy peripheral nerve characteristics. New Method: Stereological analysis was compared to histomorphometry with binary image analysis on uninjured sciatic nerves to determine nerve fiber number, nerve area, neural density, and fiber distribution. Results: Sciatic nerves were harvested from 6 male Lewis rats, aged 8–12 weeks for comprehensive analysis of 6 nerve specimens. From each animal, sciatic nerve specimens were fixed, stained, and sectioned for analysis by light and electron microscopy. Both histomorphometry and stereological peripheral nerve analyses were performed on all specimens by two blinded and independent investigators who quantified nerve fiber count, fiber width, density, and related distribution parameters. Comparison with existing methods: Histomorphometry and stereological analysis provided similar outcomes in nerve fiber number and total nerve area. However, the light microscopy, but not electron microscopy, stereological analysis yielded higher nerve fiber area compared to histomorphometry or manual measurement. Conclusion: Both methods measure similar fiber number and overall nerve fiber area; however, stereology with light microscopy quantified higher fiber area. Histomorphometry optimizes throughput and comprehensive analysis but requires user thresholding.
AB - Background: Stereology and histomorphometry are widely used by investigators to quantify nerve characteristics in normal and pathological states, including nerve injury and regeneration. While these methods of analysis are complementary, no study to date has systematically compared both approaches in peripheral nerve. This study investigated the reliability of design-based stereology versus semi-automated binary imaging histomorphometry for assessing healthy peripheral nerve characteristics. New Method: Stereological analysis was compared to histomorphometry with binary image analysis on uninjured sciatic nerves to determine nerve fiber number, nerve area, neural density, and fiber distribution. Results: Sciatic nerves were harvested from 6 male Lewis rats, aged 8–12 weeks for comprehensive analysis of 6 nerve specimens. From each animal, sciatic nerve specimens were fixed, stained, and sectioned for analysis by light and electron microscopy. Both histomorphometry and stereological peripheral nerve analyses were performed on all specimens by two blinded and independent investigators who quantified nerve fiber count, fiber width, density, and related distribution parameters. Comparison with existing methods: Histomorphometry and stereological analysis provided similar outcomes in nerve fiber number and total nerve area. However, the light microscopy, but not electron microscopy, stereological analysis yielded higher nerve fiber area compared to histomorphometry or manual measurement. Conclusion: Both methods measure similar fiber number and overall nerve fiber area; however, stereology with light microscopy quantified higher fiber area. Histomorphometry optimizes throughput and comprehensive analysis but requires user thresholding.
KW - Binary image analysis
KW - Design-Based stereology
KW - Electron microscopy
KW - Nerve injury
KW - Nerve regeneration
KW - Quantitative histomorphometry
UR - http://www.scopus.com/inward/record.url?scp=85080065814&partnerID=8YFLogxK
U2 - 10.1016/j.jneumeth.2020.108635
DO - 10.1016/j.jneumeth.2020.108635
M3 - Article
C2 - 32070676
AN - SCOPUS:85080065814
SN - 0165-0270
VL - 336
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
M1 - 108635
ER -