期刊
CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY
卷 40, 期 6, 页码 626-633出版社
WILEY-BLACKWELL
DOI: 10.1111/j.1442-9071.2011.02741.x
关键词
axon; experimental glaucoma; nerve degeneration; optic nerve
资金
- NHMRC [565202, 626964]
- Ophthalmic Research Institute of Australia
Background: Full axon counting of optic nerve cross-sections represents the most accurate method to quantify axonal damage, but such analysis is very labour intensive. Recently, a new method has been developed, termed targeted sampling, which combines the salient features of a grading scheme with axon counting. Preliminary findings revealed the method compared favourably with random sampling. The aim of the current study was to advance our understanding of the effect of sampling patterns on axon counts by comparing estimated axon counts from targeted sampling with those obtained from fixed-pattern sampling in a large collection of optic nerves with different severities of axonal injury. Methods: Chronic ocular hypertension was induced in adult Sprague-Dawley rats for 1-7 weeks by translimbal laser photocoagulation of the trabecular meshwork. Axonal damage on resin-embedded cross-sections was estimated using three different methods: (i) semi-quantitative damage grading; (ii) semi-quantitative, automated axon counting using targeted sampling; and (iii) semi-quantitative, automated axon counting using fixed-pattern sampling. Results: Estimated axon counts, as generated by targeted sampling and fixed-pattern sampling, correlated equally well with the semi-quantitative grading scheme. Estimated counts obtained with targeted sampling were not statistically different from those yielded by fixed-pattern sampling. Bland-Altman analysis showed a good agreement between the two methods. Conclusions: The results of our study validate the use of both fixed-pattern sampling and targeted sampling for estimation of axonal damage but do not indicate that the latter method is superior for detection of axon loss in animals with minor damage.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据