## 2 Materials and Methods
### Region-of-Interest Definition and Radiomic Feature Extraction  
Three phantom inserts corresponding to three different textures were chosen for the analysis (Figure 1). An example of the phantom imaged on each of the three scanners is shown in Figure 2.  
To assess the texture-discriminative power of each radiomic feature as a function of the VOI size, six concentric cylindrical VOIs of different radii were drawn in each insert, as shown in Figure 1, on three consecutive slices placed in correspondence with the middle of the insert along the \(z\)-axis (see Supplementary Material Figure S1). For each scanner, these VOIs were used to extract radiomic features from both the test and retest scans. Before feature extraction, intensity normalization was performed by rescaling the intensities of the different images to have a mean value of 300 and a standard deviation (s.d.) of 100. Then, for each VOI, radiomic features from the classes first-order, gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), gray level size zone matrix (GLSZM), neighboring gray-tone difference matrix (NGTDM), and gray level dependence matrix (GLDM) were extracted in 2D from both original and filtered images (Laplacian of Gaussian, LoG, with \(\sigma\) = 6 mm; wavelet; square; square root; logarithm; exponential) using PyRadiomics 3.0.1 package (available at [[https://github.com/AIM-Harvard/pyradiomics/releases/tag/v3.0.1](https://github.com/AIM-Harvard/pyradiomics/releases/tag/v3.0.1)]([https://github.com/AIM-Harvard/pyradiomics/releases/tag/v3.0.1](https://github.com/AIM-Harvard/pyradiomics/releases/tag/v3.0.1)), accessed on 5 January 2021) [10]. A total of 944 radiomic features were extracted for each VOI. Parameter files used for the feature extraction are provided at [[https://github.com/ReliabilityRadiomicsIEOFC/PhantomStudy](https://github.com/ReliabilityRadiomicsIEOFC/PhantomStudy)]([https://github.com/ReliabilityRadiomicsIEOFC/PhantomStudy](https://github.com/ReliabilityRadiomicsIEOFC/PhantomStudy)), accessed on 5 January 2021. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Scanner**} & \multicolumn{2}{c}{**Field**} & \multirow{2}{*}{**Vendor**} & \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Sequence**} & \multicolumn{2}{c}{**TR**} & \multicolumn{2}{c}{**TE**} & \multicolumn{2}{c}{**Slice**} & \multicolumn{2}{c}{**Slice**} & \multicolumn{2}{c}{**Pixel**} & \multirow{2}{*}{**FoV** (mm \(\times\) mm)} \\  & & **(T)** & & & & **(ms)** & & **(mm)** & & **(mm)** & **(mm)** \\ \hline A & 1.5 & GE & Optima & \multirow{2}{*}{FRSE} & \multirow{2}{*}{4763} & \multirow{2}{*}{109} & \multirow{2}{*}{5} & \multirow{2}{*}{5.5} & \multirow{2}{*}{0.6 \(\times\) 0.6} & \multirow{2}{*}{320 \(\times\) 320} \\ B & 1.5 & Philips & Ingenia & & & & & & & & \\ C & 3 & Philips & Ingenia & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Scanner properties and imaging parameters. TR = repetition time; TE = echo time; FoV = field of view; FRSE = fast recovery fast spin echo; FSE = fast spin echo. Figure 1: MR representation of the inserts embedded in the phantom, with corresponding textures and VOIs placement. Three phantom inserts were chosen as representative of three textures, from a finer texture (1) to a coarser one (3) through a medium texture (2). The volumes of the selected VOIs were: 29.8 cm\({}^{3}\) (red), 20.7 cm\({}^{3}\) (green), 13.3 cm\({}^{3}\) (blue), 7.4 cm\({}^{3}\) (yellow), 3.3 cm\({}^{3}\) (pink), and 0.8 cm\({}^{3}\) (cyan). Window width/window level for the image: 1970/1165. Figure 2: MR representation of the inserts embedded in the phantom on different scanners. On top left, the representation obtained on scanner A is shown. The representation obtained on scanner B is shown on top right, while the representation obtained on scanner C is shown at the bottom.