Development of Three Dimensional Automatic Body Fat Measurement Software from CT, and Its Validation and Evaluation

Young Jae Kim^1,2, Jun Yong Jeong³, Su Youn Nam⁴, Min Ju Kim³, Jae Hwan Oh⁵, Kwang Gi Kim^1*, Dae Kyung Sohn^1,5

¹Biomedical Engineering Branch, Division of Convergence Technology, Research Institute, National Cancer Center, Goyang, Korea.
²Department of Plasma Bio Display, Kwangwoon University, Seoul, Korea.
³Department of Radiology, Hospital, National Cancer Center, Goyang, Korea.
⁴Center for Cancer Prevention and Detection, Hospital, National Cancer Center, Goyang, Korea.
⁵Center for Colorectal Cancer, Hospital, National Cancer Center, Goyang, Korea.

DOI: 10.4236/jbise.2015.810063                

Abstract

Abdominal obesity describes the accumulation of excessive fat in the abdomen. It is known that depending on its distribution, visceral obesity presents a greater danger to health than subcutaneous obesity. To properly prevent and treat visceral obesity, accurate evaluation methods are necessary, and hence quantitative VAT estimation is extremely important. CT scans are the most accurate method for estimating VAT, but it requires a great deal of time and effort, limiting its use in studying or evaluating obesity in patients. This paper proposed automatic measurement software that could quickly differentiate between and measure VAT and SAT. The method was verified using a total of 100 abdominal CT data values; this paper measured the SAT and VAT in the entire abdomen using the automatic measurement software. Additionally, through a comparative evaluation between the automated measurements and manual measurements such as BMI and waist circumference, clinical reliability and viability were validated and evaluated. Between automated measurements and manual measurements, the TAT (r = 0.995, p = 0.01), SAT (r = 0.987, p = 0.01) and VAT (r = 0.993, p = 0.01) showed high correlation. Using BMI as the main metric, the TAT for automated measurements (r = 0.674, p = 0.01) and the TAT for manual measurements (r = 0.703, p = 0.01) showed the strongest correlation. When using waist circumference, the VAT for automated measurements (r = 0.826, p = 0.01) and the VAT for manual measurements (r = 0.822, p = 0.01) showed the strongest correlation. With these results, the reliability and viability of the automatic measurement software were confirmed. The software is expected to help greatly in reducing the time and in providing objective data of VAT measurements from CT scans for clinical research.

Keywords

Abdominal Obesity, Visceral Adipose Tissue (VAT), Subcutaneous Adipose Tissue (SAT), Computer-Aided Diagnosis (CAD), Computed Tomography (CT)

Conflicts of Interest

The authors declare no conflicts of interest.

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