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Osman OS, Selway JL, Kępczyńska MA, et al. A novel automated image analysis method for accurate adipocyte quantification. Adipocyte. 2013;2(3):160-4doi: 10.4161/adip.24652.
Osman, O. S., Selway, J. L., Kępczyńska, M. A., Stocker, C. J., O'Dowd, J. F., Cawthorne, M. A., Arch, J. R., Jassim, S., & Langlands, K. (2013). A novel automated image analysis method for accurate adipocyte quantification. Adipocyte, 2(3), 160-4. https://doi.org/10.4161/adip.24652
Osman, Osman S, et al. "A novel automated image analysis method for accurate adipocyte quantification." Adipocyte vol. 2,3 (2013): 160-4. doi: https://doi.org/10.4161/adip.24652
Osman OS, Selway JL, Kępczyńska MA, Stocker CJ, O'Dowd JF, Cawthorne MA, Arch JR, Jassim S, Langlands K. A novel automated image analysis method for accurate adipocyte quantification. Adipocyte. 2013 Jul 01;2(3):160-4. doi: 10.4161/adip.24652. Epub 2013 Apr 16. PMID: 23991362; PMCID: PMC3756104.
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Adipocyte. 2013 Jul 01;2(3):160-4. doi: 10.4161/adip.24652. Epub 2013 Apr 16.

A novel automated image analysis method for accurate adipocyte quantification.

Adipocyte

Osman S Osman, Joanne L Selway, Małgorzata A Kępczyńska, Claire J Stocker, Jacqueline F O'Dowd, Michael A Cawthorne, Jonathan Rs Arch, Sabah Jassim, Kenneth Langlands

Affiliations

  1. The Clore Laboratory; University of Buckingham; Buckingham, UK ; Department of Applied Computing; University of Buckingham; Buckingham, UK.

PMID: 23991362 PMCID: PMC3756104 DOI: 10.4161/adip.24652

Abstract

Increased adipocyte size and number are associated with many of the adverse effects observed in metabolic disease states. While methods to quantify such changes in the adipocyte are of scientific and clinical interest, manual methods to determine adipocyte size are both laborious and intractable to large scale investigations. Moreover, existing computational methods are not fully automated. We, therefore, developed a novel automatic method to provide accurate measurements of the cross-sectional area of adipocytes in histological sections, allowing rapid high-throughput quantification of fat cell size and number. Photomicrographs of H&E-stained paraffin sections of murine gonadal adipose were transformed using standard image processing/analysis algorithms to reduce background and enhance edge-detection. This allowed the isolation of individual adipocytes from which their area could be calculated. Performance was compared with manual measurements made from the same images, in which adipocyte area was calculated from estimates of the major and minor axes of individual adipocytes. Both methods identified an increase in mean adipocyte size in a murine model of obesity, with good concordance, although the calculation used to identify cell area from manual measurements was found to consistently over-estimate cell size. Here we report an accurate method to determine adipocyte area in histological sections that provides a considerable time saving over manual methods.

Keywords: adipocyte; automation; diet; high fat; histology; histomorphometry; image analysis; paraffin embedding

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