RESUMEN
OBJECTIVES: To evaluate the abdominal visceral fat area (VFA), we developed novel ultrasonographic (US) methods for estimating. METHODS: 100 male volunteers were recruited, and their VFA was calculated by two novel US methods, the triangle method and the ellipse method. The VFA calculated by these methods was compared with the VFA calculated by CT. RESULTS: Both the VFA calculated by the triangle method (r = 0.766, p < 0.001) and the ellipse method (r = 0.781, p < 0.001) showed a high correlation coefficient with the VFA calculated by CT. Also, the VFA calculated by our novel methods were significantly increased in subjects with one or more metabolic risk factors than in those without any risk factors. Furthermore, the correlation coefficients obtained using the two methods were enhanced by the addition of multiple regression analysis (with the triangle method, r = 0.8586, p < 0.001; with the ellipse method, r = 0.8642, p < 0.001). CONCLUSIONS: The VFA calculated by the triangle or ellipse method showed a high correlation coefficient with the VFA calculated by CT. These US methods are easy to use, they involve no radiation exposure, and the measurements can be conducted frequently. We hope that our simple methods would be widely adopted for the evaluation of VFA.
RESUMEN
Ultrasonography-based visceral fat estimation is a promising method to assess central obesity, which is associated with metabolic syndrome. The key to this method is to measure three types of distance in the ultrasound image. The most important one is the distance from the skin surface to the posterior wall of the abdominal aorta. We present a novel automatic measurement method to calculate this distance using 1D ultrasound signal processing. It is different from the conventional 2D image processing based methods which have high failure rate when the target is blurred or partially imaged. The proposed method identifies the waveforms of the aorta along a group of ultrasound scan lines and a rating mechanism is introduced to choose the best waveform for distance calculation. The robustness and accuracy of the method were evaluated by experiments based on clinical data.