Purpose: The safety and clinical efficacy of 125I seed-loaded stent for the treatment of portal vein tumor thrombosis have been shown. However, the dosimetry characteristics of the seed-loaded stents remain unclear and there is no fast dose calculation technique available for seed-loaded stent. This paper aims to explore a fast and accurate analytical dose calculation method which takes into account the effect of stent and tissue inhomogeneity.
Methods: An accurate model of the seed-loaded stent was established using 3D modeling software and subsequently used in the MC simulation to calculate the dose distribution around stent. The dose perturbation caused by the presence of the stent was analyzed and dose perturbation kernels (DPKs) were derived. Then, the dose calculation method from AAPM TG43 was adapted and integrated with the DPK and inhomogeneity correction factor (ICF) correction to calculate dose distributions analytically. To validate the proposed method, extensive comparisons were performed with other methods in water phantom and voxelized CT phantoms of three patients.
Results: The stent has a large effect on the dose distributions and reduces the dose up to 47% for single seed stent and 13% for 16-seed stent. In water phantom, dose distributions from MC simulations and the proposed method showed a good agreement with the relative error less than 3.3%. In voxelized CT phantoms, the relative errors of TG43 method can be up to 33% while those of the proposed method were less than 5%. For a dose matrix with 256×256×46 grid for 16 seeds-loaded stent, it only takes 17 seconds compared with 25 hours for MC simulation.
Conclusion: With its good agreement with MC calculation and computational efficiency, the proposed method is adequate for dose evaluation and optimization in seed-loaded stent implantation treatment planning.
Funding Support, Disclosures, and Conflict of Interest: This work was supported by the National Key R&D Program of China under Grant No. 2018YFA0704100 and 2018YFA0704101, the National Natural Science Foundation of China under Grant No. 61601012.
Not Applicable / None Entered.