The efficiency of design-based stereology in estimating spiral ganglion populations in mice

Abstract

Accurate quantification of cell populations is essential in assessing and evaluating neural survival and degeneration in experimental groups. Estimates obtained through traditional two-dimensional counting methods are heavily biased by the counting parameters in relation to the size and shape of the neurons to be counted, resulting in a large range of inaccurate counts. In contrast, counting every cell in a population can be extremely labor-intensive. The present study hypothesizes that design-based stereology provides estimates of the total number of cochlear spiral ganglion neurons (SGNs) in mice that are comparable to those obtained by other accurate cell-counting methods, such as a serial reconstruction, while being a more efficient method. SGNs are indispensable for relaying auditory information from hair cells to the auditory brainstem, and investigating factors affecting their degeneration provides insight into the physiological basis for the progression of hearing dysfunction. Stereological quantification techniques offer the benefits of efficient sampling that is independent of the size and shape of the SGNs. Population estimates of SGNs in cochleae from young C57 mice with normal-hearing and C57 mice with age-related hearing loss were obtained using the optical fractionator probe and traditional two-dimensional counting methods. The average estimated population of SGNs in normal-hearing mice was 7009, whereas the average estimated population in mice with age-related hearing loss was 5096. The estimated population of SGNs in normal-hearing mice fell within the range of values previously reported in the literature. The reduction in the SGN population in animals with age-related hearing loss was statistically significant. Stereological measurements required less time per section compared to two-dimensional methods while optimizing the amount of cochlear tissue analyzed. These findings demonstrate that design-based stereology provides a practical alternative to other counting methods such as the Abercrombie correction method, which has been shown to notably underestimate cell populations, and labor-intensive protocols that account for every cell individually.