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Research Paper

Whole-slide image analysis outperforms micrograph acquisition for adipocyte size quantification

ORCID Icon, ORCID Icon, , ORCID Icon, ORCID Icon & ORCID Icon
Pages 567-575 | Received 28 Mar 2020, Accepted 09 Sep 2020, Published online: 20 Sep 2020
 

ABSTRACT

The distinction between biological processes of adipose tissue expansion is crucial to understanding metabolic derangements, but a robust method for quantifying adipocyte size has yet to be standardized. Here, we compared three methods for histological analysis in situ: one conventional approach using individual micrographs acquired by digital camera, and two with whole-slide image analysis pipelines involving proprietary (Visiopharm) and open-source software (QuPath with a novel ImageJ plugin). We found that micrograph analysis identified 10–40 times fewer adipocytes than whole-slide methods, and this small sample size resulted in high variances that could lead to statistical errors. The agreement of the micrograph method to measure adipocyte area with each of the two whole-slide methods was substantially less (R2 of 0.6644 and 0.7125) than between the two whole-slide methods (R2 of 0.9402). These inconsistencies were more pronounced in samples from high-fat diet fed mice. While the use of proprietary software resulted in the highest adipocyte count, the lower cost, ease of use, and minimal variances of the open-source software provided a distinct advantage for measuring the number and size of adipocytes. In conclusion, we recommend whole-slide image analysis methods to consistently measure adipocyte area and avoid unintentional errors due to small sample sizes.

Acknowledgements

The authors would like to thank Cynthia Tiley Hutchison for her technical expertise.

Disclosure statement

The authors report no conflict of interest.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported in part by the Boshell Diabetes and Metabolic Diseases Program and the Center for Neuroscience initiative Graduate Fellowship program at Auburn University.