The high correlation between the visceral fat volume and the development of arteriosclerotic diseases is well known [
In recent years, multislice CT scanners have come into global use. To meet the growing demand for reconstructed images, CT volume data has been acquired and accumulated in many institutions. Using the accumulated CT volume data, it is possible to calculate a patient’s visceral fat volume by manual segmentation of the visceral fat region in every slice of the CT volume data. However, since this manual calculation of the visceral fat volume is extremely time-consuming, it has not been used in previous large-scale studies. Automatic visceral fat calculation software would be a useful tool for large-scale research with accumulated CT volume data.
Although software for calculating the visceral fat volume from CT volume data has been developed [
Although some software for measuring the 3D fat volume from thick-slice 3D MR data has been developed [
The purpose of this study is to develop automatic calculation software to calculate the entire visceral fat volume from CT volume data and to evaluate its feasibility.
We used 24 sets of whole-body CT volume data with anthropometric measurement data. All the CT volumes (voxel size:
The true visceral fat region was defined as the region with CT values from −190 to −30 Hounsfield units (HU) [
Software to automatically calculate the true visceral fat volume was developed using region segmentation based on morphological analysis with CT value thresholding. Details of the calculation method and implementation are described later. The calculated visceral fat volume is defined as the volume calculated automatically with this software.
The true visceral fat volume and calculated visceral fat volume of 24 subjects were compared by correlation analysis, and the ratio of error including calculated visceral fat volume was also evaluated.
Three major indices used as substitutes for visceral fat volumes, that is, the WC at the umbilicus level, the BMI, and the visceral fat area on an axial CT slice at the umbilicus level, were also evaluated by correlation analysis with the true visceral fat volume.
Figure
Flowchart of proposed fat volume calculation method.
To reduce the calculation time for image processing, the CT volume data is scaled to half the original size by changing the voxel size to
The body trunk region is extracted by threshold processing and connection component analysis in each axial slice. In each slice, the largest binarized area with a CT value of −400 HU or higher is selected (corresponding to a region of bone, muscle, and fat). Moreover, the areas with a CT value of lower than −400 HU that do not touch the edge of the slice are also selected (corresponding to lung and intestinal gas regions). The selected regions are connected in three dimensions, and morphological closing is performed using a spherical kernel with a radius of 1.5 voxels.
The body trunk region is segmented into bone, muscle, fat, and air regions by performing various processes on the 3D volume as follows.
Next, the superior-inferior range of fat volume measurement is defined as follows. The superior end surface is obtained by radial basis function interpolation [
From the bone, muscle, and air regions obtained by the above processing, the visceral region is drawn to include the abdominal wall muscle, abdominal organs, and visceral fat. Namely, morphological dilation processing is performed using a spherical kernel with a radius of 20.0 voxels on the seeds of the visceral region consisting of muscle, bone, and air regions. After the blanks of the dilated combined region are extracted and added to the dilated region, morphological erosion using a spherical kernel with a 20.0 voxel radius is applied to the combined region.
All fat regions are classified as either visceral fat tissue or subcutaneous fat tissue. Fat regions inside the visceral region are classified as visceral fat regions, while fat regions outside the visceral region are classified as subcutaneous fat regions.
In this study, the fat volume calculation software based on the proposed method is implemented in C++ language. The developed software handles DICOM-format CT data. The developed software is operated through CIRCUS CS (Clinical Infrastructure for Radiologic Computation of United Solutions Clinical Server) [
The computer used to calculate the visceral fat volumes has an Intel Quad Xeon CPU 2.0 GHz processor and 3.0 GB RAM with Windows XP SP 2 installed.
Automatic calculation results for the visceral fat volume from all 24 sets of CT volume data were successfully obtained with the developed software. The average calculation time was 252.7 seconds with a standard deviation of 66.7 seconds. A selection of automatically segmented fat regions is shown in Figure
Example of successful automatic extraction of fat regions. Red/blue regions are visceral/subcutaneous fat regions.
Automatically extracted fat regions
True fat regions
The true visceral fat volume and calculated visceral fat volume for each data set are shown in Table
List of data sets with substitute indices for visceral fat volume, calculated true visceral fat volume, and automatically calculated visceral fat volume.
Height (m) | Weight (kg) | Substitute indices | Visceral fat volumes |
| ||||
---|---|---|---|---|---|---|---|---|
BMI (kg/m2) | Waist circumference (cm) | Visceral fat area (cm2) | True (cm3) | Calculated (cm3) | ||||
Female | 1.64 | 41 | 15.2 | 70.0 | 50 | 833 | 926 | 93 |
1.57 | 42 | 17.0 | 65.5 | 21 | 216 | 243 | 27 | |
1.53 | 43 | 18.4 | 75.5 | 22 | 73 | 195 | 122 | |
1.47 | 44 | 20.4 | 68.5 | 36 | 1003 | 1054 | 51 | |
1.44 | 47 | 22.7 | 83.0 | 66 | 1598 | 1697 | 99 | |
1.56 | 59 | 24.2 | 80.5 | 116 | 3463 | 3565 | 102 | |
1.53 | 65 | 27.8 | 98.0 | 120 | 4955 | 5076 | 121 | |
1.40 | 56 | 28.6 | 98.0 | 111 | 3198 | 3340 | 142 | |
1.55 | 71 | 29.6 | 104.5 | 153 | 1955 | 2026 | 71 | |
1.57 | 77 | 31.2 | 112.5 | 217 | 5936 | 6149 | 213 | |
1.47 | 69 | 31.9 | 101.0 | 99 | 3805 | 3910 | 105 | |
1.55 | 84 | 35.0 | 115.0 | 203 | 5159 | 5426 | 267 | |
|
||||||||
Male | 1.68 | 50 | 17.7 | 71.0 | 30 | 603 | 624 | 21 |
1.62 | 47 | 17.9 | 72.0 | 44 | 891 | 908 | 17 | |
1.79 | 59 | 18.4 | 77.0 | 66 | 1306 | 1348 | 42 | |
1.68 | 62 | 22.0 | 78.0 | 99 | 3074 | 3239 | 165 | |
1.56 | 58 | 23.8 | 87.0 | 99 | 3081 | 3266 | 185 | |
1.65 | 66 | 24.2 | 85.0 | 124 | 3583 | 3726 | 143 | |
1.75 | 84 | 27.4 | 97.5 | 141 | 4647 | 4820 | 173 | |
1.71 | 81 | 27.7 | 89.0 | 117 | 4029 | 4137 | 108 | |
1.61 | 74 | 28.5 | 88.0 | 125 | 5393 | 5595 | 202 | |
1.58 | 78 | 31.2 | 111.0 | 192 | 4587 | 4748 | 161 | |
1.77 | 100 | 31.9 | 106.0 | 188 | 7837 | 8170 | 333 | |
1.80 | 109 | 33.6 | 115.0 | 220 | 5819 | 6069 | 250 |
Correlation between automatically calculated visceral fat volumes and true volumes. The correlation coefficient for the female data set is 0.9998 and the coefficient for the male data set is 0.9999.
All these substitute indices (BMI, WC at umbilicus level, and area of 2D visceral fat region on axial CT slice at umbilicus level) showed a positive correlation with the true visceral fat volume (Figure
Correlation coefficients with the substitute indices for visceral fat volume and true/calculated visceral fat volume.
Visceral fat volume | |||
---|---|---|---|
True | Calculated | ||
Female | BMI | 0.8540 | 0.8550 |
Waist Circumference | 0.8473 | 0.8510 | |
Visceral fat area | 0.8826 | 0.8860 | |
|
|||
Male | BMI | 0.9321 | 0.9304 |
Waist Circumference | 0.8378 | 0.8369 | |
Visceral fat area | 0.8904 | 0.8901 |
Linear correlations between the true visceral fat volume and the substitute indices for the visceral fat volume and their linear regression lines.
BMI
WC at umbilical level
Visceral fat area on axial CT slice at umbilical level
Software to automatically calculate the entire visceral fat volume from CT volume data was successfully developed. The software proved to be feasible for calculating the visceral fat volume with high accuracy in a reasonably short time. To the best of our knowledge, this is the first software to automatically calculate the entire visceral fat volume in the region from the upper abdomen to the pelvis. By applying the developed software through the CIRCUS platform, a large quantity of CT volume data can be processed automatically. This will be a useful tool in large-scale research involving the visceral fat volume when accumulated CT volume data is available.
The correlations with the substitute indices showed that they are not perfect for predicting the actual visceral fat volume. However, since these results were obtained using a small number of CT volume data sets, larger data sets are necessary to perform an accurate evaluation of the correlations between the indices and the fat volume.
In the automatic extraction of visceral fat regions, small false positive regions were often observed in the muscle gap (shown in Figure
Examples of overestimation of visceral fat area by the proposed software.
Example of overestimating visceral fat within muscle layers (left: automatically extracted result and right: true region)
Another example of overestimating visceral fat within muscle (left: automatically extracted result and right: true region)
In conclusion, we developed automatic calculation software to calculate the entire visceral fat volume from whole-body CT volume data. The developed software proved to be feasible for accurately calculating the visceral fat volume in a reasonably short time.
The authors declare that there is no conflict of interests regarding the publication of this paper.