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The fibro-adipose structure of the female breast: A dissection study.

Kathryn M GaskinGregory E PeoplesDeirdre E McGhee
Published in: Clinical anatomy (New York, N.Y.) (2019)
A paucity of dissection evidence and quantitative data exists to base anatomical descriptions and illustrations of the fibro-adipose structure of the female breast. The aim of this study was to dissect and provide quantitative data of the fibro-adipose structure of the female breast. The fibro-adipose structure of female embalmed breasts were dissected in the coronal (n = 15) and sagittal planes (n = 3). Quantitative data of breast volume, surface area, fibro-adipose pocket number, size and regional variation were collected. Pearson's correlations were used to investigate pocket number and size with breast volume and surface area. Regional variation in pocket number and size were compared using T tests. Throughout the dissection, photographic evidence was collected to support detailed anatomical descriptions. The mean (SD; range) number of pockets located in the superficial region of the breast was 199 ± 53 (108-306) and the mean pocket surface area was 0.88 ± 0.37 cm2 (0.31-1.97). A strong correlation was found between mean pocket number and breast surface area (r2 = 0.8064) and a very weak correlation between mean individual pocket surface area and breast surface area (r2 = -0.1427; P < 0.01). The pockets located anterior to the corpus mamma were significantly larger and less in number (P < 0.05) than those located posterior. The fibro-adipose structure of the female breast is formed by complex scaffolding, consisting of layers of fibrous tissue pockets embedded with adipose tissue which surrounds the corpus mamma and is firmly attached to the perimeter of the breast. Detailed descriptions are supported by quantitative data and photographic evidence. Clin. Anat. 32:146-155, 2019. © 2019 Wiley Periodicals, Inc.
Keyphrases
  • adipose tissue
  • insulin resistance
  • electronic health record
  • high resolution
  • type diabetes
  • high fat diet
  • skeletal muscle
  • deep learning
  • artificial intelligence