## 2 Materials and Methods
### Image Analysis  
EAT was detected and analyzed with a semi-automatic approach, exploited to implement a custom tool--provided with a user-friendly Graphical User Interface (GUI)--able to support the radiologists in the procedure of EAT segmentation and quantification. The tool takes the CCT series as input and with few simple steps yields the EAT and automatically performs the quantification of the fat quartiles and their distribution around the heart. The whole semi-automatic procedure significantly minimizes user intervention [13].  
With more details [13], the evaluation of the clinical value of statin administration was performed by segmenting two CCT series at subsequent time points and quantifying the difference in terms of EAT volume, density, and quartile distribution. Figure 1 shows the overall flow diagram of the computer-assisted approach with the processing pipeline.  
In the processing chain, the main steps are related to:  
* **ROI Selection**: after loading the CCT series, the operator selects the regions containing the heart trough free hand or polygonal lasso strategies, this procedure was implemented and ameliorated by receiving clinician's feedback.
* **ROI Interpolation**: after reference ROIs are selected by the operator, the system interpolates the missing ROIs in the other slices included in the volume of interest. This procedure made it possible to reduce manual effort of the operator.
* **ROI Refinement**: This option allowed the operator to refine one or more interpolated ROIs. After a single slice refinement, the modification was propagated to the ROIs next to the selected slice with a further automatic interpolation. This step ensured shape and spatial continuity among refined and unrefined ROIs.
* **Epicardial Adipose Tissue Segmentation**: Segmentation was applied only to the volume inside the ROI using an efficient double-threshold algorithm, analyzing the voxels having HU values in the selected range. In general, this range is kept fixed,  
Figure 1: Overall flow diagram of the proposed semi-automatic computer-assisted approach for epicardial adipose tissue segmentation.  
but it can be modified according to the different CT scanners or acquisition thickness protocols.
* **Quartiles and Volume Computation**: the fat quartiles were computed considering the range of interest in terms of Hounsfield Units (HU) and volume. In addition, the mean HU value, the percentage, and the volume (overall and of each quartile) were calculated.  
The output provided the overall EAT volume (in cm\({}^{3}\)) as well as the area/volume for each single image. The voxels representing EAT were used for calculation only when they had HU values within a pre-specified range [16]. The HU range of interest was set between \(-175\) HU and \(-15\) HU, and the quartiles (Q) of attenuation (i.e., Q1, Q2, Q3, Q4) considering the selected interval of density, were computed accordingly [12; 13]. In addition, the mean HU value, and the percentages of distribution with respect to the whole EAT volume were calculated. Figure 2 shows an example of segmented fat with the corresponding quartiles, which are represented in different colors and overlapped on the native CCT image.  
The attenuation values (HU) were also measured in the antero-superior mediastum, near the coronary arteries (proximal right coronary artery, left main trunk, left descending coronary artery, circumflex artery), and in the posterior mediastum, both in the first and in the second CCT. The epicardial and subcutaneous thoracic fat thicknesses were also measured.