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Updated: May 24, 2025
Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
Published on: April 4, 2012
A New and Validated Computed Tomography-Based Method for Measurement of Facial Fat Volume
Mengyuan Jiang1,2, Hao Shao3, Qingchun Li4
1Department of Plastic and Aesthetic Surgery, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Nangang District, Harbin, Heilongjiang, 150081, People's Republic of China.
Background:
A consensus on effectively measuring facial fat volume by computed tomography (CT) or magnetic resonance imaging is lacking. This study aimed to assess the validity and reproducibility of a new CT-based method for measuring facial fat volume.
Methods:
Volume was measured using a new semiautomatic segmentation method. Two observers measured the volume of the fat layers in four soft tissue models constructed using the three-dimensional viewer software. These measurements were compared with previously reported standard volumes. Fat volume in the area of interest was measured from 16 hemifacial CT images by two independent observers. Based on the acquired data, inter-class correlation coefficients and Bland-Altman analyses were performed.
Results:
The mean difference (ml) ± SEM in comparison with the known volume was - 0.87 ± 4.11 (observer MY) and 3.42 ± 4.68 (observer HW), respectively. The fat volume of pork tissue (PFV) measured using MY (P = 0.846 > 0.05) and HW (P = 0.518 > 0.05) did not differ significantly from the standard volume. ICC calculations and Bland-Altman analysis indicated good agreement between inter- and intra-observer (ICC = 0.992 and 0.970 > 0.90, P<0.001).
Conclusions:
This new volumetric analysis for facial fat using a semiautomatic segmentation technique on CT scans is an effective and reliable tool.
Level Of Evidence Iv:
This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
