TABLE I. Material Properties.

Patient Fat Infiltrative Index	0	1	2	3	4	*	*	*
Steatosis Grade	No-Fat (Liver)	Low (0-6%)	Mild (6-17%)	Moderate (17-22%)	High (>22%)	Tumor	Fat	-
Average Fat Percent (%)	0	4.66 ± 2.80	12.67±2.25	21.20±2.90	29.90±3.7	5.56±2.90	100%	*
Thermal Conductivity [W/(m·K)] (915 MHz)	0.521	0.451	0.364	0.309	0.270	0.44±0.03	0.21	.012
Electrical Conductivity [S/m] (915 MHz)	0.861	0.821	0.757	0.699	0.641	0.81±0.23	0.11	.069
Electrical Conductivity [S/m] (2450 MHz)	1.69	1.62	1.496	1.384	1.273	1.60±0.23	0.268	.069
Permittivity [1] (915 MHz)	46.8	44.9	42.0	39.3	36.5	44.6±1.1	10.8	.067
Permittivity [1] (2450 MHz)	43.0	41.0	37.9	35.0	32.1	40.7±1.1	5.28	.067
Perfusion Mass Flow Rate [] (kg/m3*s)	18	17	15	14	13	—	—	*

Steatosis grade index and the corresponding average percent fat derived from the fat quantification imaging data for each patient. Material properties at a particular steatosis grade were determined using the material characteristic curves established in previous work but with a modified scale based on the human data range [43], [49]. For liver parenchyma, an average fat percentage value across the entirety of the liver was used within (7) to produce a homogenous tissue property. In the case of Tumor Informed Digital Twin, a voxel-by-voxel fat fraction value within the tumor imaging data using (7) was employed for a highly heterogeneous property description. With each tissue type, properties are provided, as well as the exponential factor associated with (7) model.