Evaluating the Application of Tissue-Specific Dose Kernels Instead of Water Dose Kernels in Internal Dosimetry: A...

The aim of this work is to evaluate the application of tissue-specific dose kernels instead of water dose kernels to improve the accuracy of patient-specific dosimetry by taking tissue heterogeneities into consideration.

Tissue-specific dose point kernels (DPKs) and dose voxel kernels (DVKs) for yttrium-90 (⁹⁰Y), lutetium-177 (¹⁷⁷Lu), and phosphorus-32 (³²P) are calculated using the Monte Carlo (MC) simulation code GATE (version 7). The calculated DPKs for bone, lung, adipose, breast, heart, intestine, kidney, liver, and spleen are compared with those of water. The dose distribution in normal and tumorous tissues in lung, liver, and bone of a Zubal phantom is calculated using tissue-specific DVKs instead of those of water in conventional methods. For a tumor defined in a heterogeneous region in the Zubal phantom, the absorbed dose is calculated using a proposed algorithm, taking tissue heterogeneity into account. The algorithm is validated against full MC simulations.

The simulation results indicate that the highest differences between water and other tissue DPKs occur in bone for ⁹⁰Y (12.2% ± 0.6%), ³²P (18.8% ± 1.3%), and ¹⁷⁷Lu (16.9% ± 1.3%). The second highest discrepancy corresponds to the lung for ⁹⁰Y (6.3% ± 0.2%), ³²P (8.9% ± 0.4%), and ¹⁷⁷Lu (7.7% ± 0.3%). For ⁹⁰Y, the mean absorbed dose in tumorous and normal tissues is calculated using tissue-specific DVKs in lung, liver, and bone. The results are compared with doses calculated considering the Zubal phantom water equivalent and the relative differences are 4.50%, 0.73%, and 12.23%, respectively. For the tumor in the heterogeneous region of the Zubal phantom that includes lung, liver, and bone, the relative difference between mean calculated dose in tumorous and normal tissues based on the proposed algorithm and the values obtained from full MC dosimetry is 5.18%.

A novel technique is proposed considering tissue-specific dose kernels in the dose calculation algorithm. This algorithm potentially enables patient-specific dosimetry and improves estimation of the average absorbed dose of ⁹⁰Y in a tumor located in lung, bone, and soft tissue interface by 6.98% compared with the conventional methods.