Computed tomographic abdominal fat volume estimation - a handy tool to predict the risk of metabolic syndrome

Abstract

Purpose: Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients.

Material and methods: This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome.

Results: The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome (p = 0.001), with visceral fat volume predicting a higher risk in females (p = 0.026).

Conclusions: Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition.

Keywords: abdominal subcutaneous fat; abdominal visceral fat; body mass index; computed tomography; metabolic syndrome.

Figure 1

Non-contrast abdominal computed tomography axial section at the level of L2-L3 intervertebral disc defining subcutaneous (A) and visceral fat (B) – blue coloured area

Figure 2

Graph demonstrating comparison of the mean parameters between the groups using independent sample t-test

Figure 3

Graph demonstrating comparison of the mean parameters within the groups between gender using independent sample t-test

Figure 4

Graph demonstrating comparison of the mean parameters based on gender between the groups using independent sample t-test

Figure 5

A 55-year-old old male patient with hypertension and diabetes with waist circumference of 95 cm and BMI of 31. Axial sections of abdominal CT showing (A) subcutaneous and visceral fat distribution, (B) subcutaneous fat volume (blue coloured area), and (C) visceral fat volume (blue coloured area). In this case: VFV 930 cc, SFV 1835 cc, and TFV 2765 cc

Figure 6

A 54-year-old female patient with hypertension and dyslipidaemia with waist circumference of 95 cm and a normal BMI of 23. Axial sections of abdominal CT showing (A) subcutaneous and visceral fat distribution, (B) subcutaneous fat volume (blue coloured area), and (C) visceral fat volume (blue coloured area). In this case: VFV 731 cc, SFV 1755 cc, and TFV 2486 cc

Figure 7

A 47-year-old male patient without hypertension/diabetes/dyslipidaemia with waist circumference of 86 cm and normal BMI of 20. Axial sections of abdominal CT showing (A) subcutaneous and visceral fat distribution, (B) subcutaneous fat volume (blue coloured area), and (C) visceral fat volume (blue coloured area). In this case: VFV 550 cc, SFV 1220 cc, and TFV 1770 cc

Figure 8

A 35-year-old female patient with hypertension and diabetes with waist circumference of 96 cm and increased BMI of 32. Axial sections of abdominal CT showing (A) subcutaneous and visceral fat distribution, (B) subcutaneous fat volume (blue coloured area), and (C) visceral fat volume (blue coloured area). In this case: VFV 595 cc, SFV 711 cc, and TFV 1305 cc