Radioembolization (RE) with ⁹⁰Y-microspheres has gained widespread acceptance as a safe and effective technique for treating liver malignancies. Accurate quantification in RE is a key step in treatment planning optimization and is becoming a pressing issue in light of the Directive 2013/59/EURATOM. The aim of this study was to develop a SPECT/CT imaging protocol for quantitative imaging optimization in RE based on cutting edge imaging technology (Symbia IntevoTM system provided with the innovative xSPECT software) and a novel anthropomorphic 3D-printed phantom. In the present study, ^99mTc-labeled macroaggregated albumin was used as a surrogate radiopharmaceutical for treatment planning. Gamma camera calibration factors and recovery coefficients were determined performing preliminary SPECT/CT acquisitions of a point source, a cylindrical homogeneous phantom and the NEMA/IEC phantom. Data reconstruction was performed using the built-in xSPECT package, using both the Ordered Subset Expectation–Maximization (OSEM) and the Ordered Subset Conjugated Gradient (OSCG) algorithm. Specific regions of interest (ROIs) were drawn on the MIM 6.1.7 system according to the physical volume. The quantification procedure was validated using the anthropomorphic phantom provided with a fillable liver section and spheres of different diameters (20 mm, 40 mm and a 40 mm spherical shell). The measured activity concentration in all geometries is consistent within 4%, demonstrating that the xSPECT software permit an absolute quantification in anthropomorphic geometry largely within the 10% recommended from the manufacturer. Caution is advised in the presence of spherical objects with a necrotic core, as underestimations in the order of 20% were obtained.

This study compares dosimetric approaches for lung dosimetry in ¹⁶⁶ radioembolization (Ho-TARE) with direct Monte Carlo (MC) simulations on a voxelized anthropomorphic phantom derived from a real patient’s CT scan, preserving the patient’s lung density distribution. Lung dosimetry was assessed for five lung shunt (LS) scenarios with conventional methods: the mono-compartmental organ-level approach (MIRD), voxel S-value convolution for soft tissue (kST, ICRU soft tissue with 1.04 g/cm³) and lung tissue (kLT, ICRU lung tissue with 0.296 g/cm³), local density rescaling (kST_L and kLT_L, respectively, for soft tissue and lung tissue), or global rescaling for a lung mean density of 0.221 g/cm³ (kLT₂₂₁). Significant underestimations in the mean absorbed dose (AD) were observed, with relative differences with respect to the reference (MC) of −64% for MIRD, −93% for kST, −56% for kST_L, −76% for kLT, −68% for kLT₂₂₁, and −60% for kLT_L. Given the high heterogeneity of lung tissue, standard dosimetric approaches cannot accurately estimate the AD. Additionally, MC results for ¹⁶⁶Ho showed notable spatial absorbed dose inhomogeneity, highlighting the need for tailored lung dosimetry in Ho-TARE accounting for the patient-specific lung density distribution. MC-based dosimetry thus proves to be essential for safe and effective radioembolization treatment planning in the presence of LS.