# Enhancing Soft Tissue Differentiation with Different Dual-Energy CT Systems: A Phantom Study
## 2 Materials and Methods
### Image Analysis and Statistics  
Images were analyzed using an in-house MATLAB R2018a script (MathWorks, Natick, MA, USA). Once the central slice was identified along the longitudinal axis, a threshold mask of the phantom was created and its center was identified. A set of regions of interest (ROIs) of 10 mm diameter was placed at known distances from the phantom center in correspondence with the various equivalent soft-tissue inserts (30 mm diameter), sufficiently inside the outer edges to avoid the blurring effect on the boundaries. Mean values and standard deviations (SD) of CT numbers were extracted from each ROI on nine consecutive central slices (i.e., the central slice, plus the first four slices above and the first four slices below the central slice along the longitudinal axis). Data extraction was performed for each VMI reconstruction, each of the six acquisitions, and each of the nine slices. We calculated that, with six acquisitions and nine slices (therefore a total of 54 measurements for each equivalent soft-tissue insert), we reached a statistical power of 80% to detect significant differences assuming to observe a \"medium\" effect size d = 0.4 and setting the probability of a type-I error to 5%. To confirm the consistency of the measurements, a repeatability analysis was performed. The methods and results of this part can be viewed in Supplementary Section S1 and Supplementary Table S1. As a first analysis, the accuracy of the CT numbers (CTm) measured on VMI at different energies was assessed. The elemental compositions of the soft-tissue (accuracy of 1% certified by the manufacturer) inserts were entered in the NIST XCOM online database [40] to determine the mass attenuation coefficients in the range of 40-140 keV. The mass attenuation coefficients were then multiplied by the mass densities to determine the linear attenuation coefficients. A density of 0.9982 \(\pm\) 0.002 g/cm\({}^{3}\) was used for water at 20 \({}^{\circ}\)C. Next, the nominal CT numbers (CTNIST) corresponding to the various inserts were calculated using the definition of the Hounsfield Unit (HU). The CTm \begin{table}
\begin{tabular}{c c c c c} \hline
**SECT** & **GE** & **Siemens Confidence** & **Siemens** & **Siemens** \\
**PROTOCOL** & **Revolution GSI** & **Siemens Confidence** & **Edge** & **Force** \\ \hline Pitch & 0.96 & 0.95 & 0.95 & 0.95 \\ Slice Thickness (mm) & 1.25 & 1.50 & 1.50 & 1.50 \\ Reconstruction algorithm (strength) & FBP, & FBP, & FBP, & FBP, \\  & ASIR (30\%) & SAFIRE (3) & ADMIRE (3) & ADMIRE (3) \\ Reconstruction kernel & Medium smooth & B30 & Br40 & Br40 \\ CTDIrol (mGy) & 34 & 31 & 30 & 35 \\  & GE & Siemens Confidence & Siemens & Siemens \\  & Revolution GSI & & Edge & Force \\  & & kVp switching & sequential scan & split filter & dual source \\  & kVp & 80–140 & 80–140 & 120 & 80–140 \\  & No & No & Au, Sn & No \\  & 600 & 600–142 & 1450 & 600–109 \\ Rotation time (s) & 1 & 1 & 1 & 1 \\  & Collimation (mm) & 20 \(\times\) 1.25 & 16 \(\times\) 1.2 & 64 \(\times\) 0.6 & 96 \(\times\) 0.6 \\   FOV (cm) & 50 & 50 & 50 & 50 \\  & Pitch & 0.96 & 0.95 & 0.25 & 0.95 \\  & Slice Thickness (mm) & 1.25 & 1.50 & 1.00 & 1.50 \\  & FBP, & FBP, & FBP, & FBP, \\  & ASIR (30\%) & SAFIRE (3) & ADMIRE (3) & ADMIRE (3) \\ Reconstruction kernel & Medium smooth & D30 & Qr40 & Qr40 \\  & VMI energy & 40–140 keV & 40–140 keV & 40–140 keV \\ CTDlvol (mGy) & 36 & 31 & 31 & 32 \\ \hline \end{tabular} Abbreviations: SECT = single-energy CT, FOV = field of view, FBP = filtered back projection, DECT = dual-energy CT.  
\end{table} 
Table 1: _Cont._and CTNIST were finally compared, and the root mean square errors (RMSE [41]) were calculated as:  
\[RMSE=\sqrt{\sum_{i,j}^{N}\frac{\left(CT_{m\ ij}-CT_{NIST}\right)^{2}}{N}}\]  
where the indices \(i\) and \(j\) represent acquisitions (6) and slices (9), respectively, and N is the total number of measurements for each type of insert (2 \(\times\) 6 \(\times\) 9 = 108).