Accurate estimates of tumor absorbed dose are essential for the evaluation of treatment efficacy in radiopharmaceutical cancer therapy. Although tumor dosimetry via the MIRD schema has been previously investigated, prior studies have been limited to the consideration of soft-tissue tumors. In the present study, specific absorbed fractions (SAFs) for monoenergetic photons, electrons, and alpha particles in tumors of varying compositions were computed using Monte Carlo simulations in MCNPX after which self-irradiation S-values for 22 radionuclides (along with 14 additional alpha-emitter progeny) were generated for tumors of both varying size and tissue composition. The tumors were modeled as spheres with radii ranging from 0.10 cm to 6.0 cm and with compositions varying from 100% soft tissue (ST) to 100% mineral bone (MB). The energies of the photons and electrons were varied on a logarithm energy grid from 10 keV to 10 MeV. The energies of alpha particles were varied along a linear energy grid from 0.5 MeV to 12 MeV. In all cases, a homogenous activity distribution was assumed throughout the tumor volume. Furthermore, to assess the effect of tumor shape, several ellipsoidal tumors of different compositions were modeled and absorbed fractions were computed for monoenergetic electrons and photons. S-values were then generated using detailed decay data from the 2008 MIRD Monograph on Radionuclide Data and Decay Schemes. Our study results demonstrate that a soft-tissue model yields relative errors of 25% and 71% in the absorbed fraction assigned to uniform sources of 1.5 MeV electrons and 100 keV photons, respectively, localized within a 1 cm diameter tumor of MB. The data further show that absorbed fractions for moderate ellipsoids can be well approximated by a spherical shape of equal mass within a relative error of < 8%. S-values for 22 radionuclides (and their daughter progeny) were computed with results demonstrating how relative errors in SAFs could propagate to relative errors in tumor dose estimates as high as 86%. A comprehensive data set of radionuclide S-values by tumor size and tissue composition is provided for application of the MIRD schema for tumor dosimetry in radiopharmaceutical therapy.

准确估计肿瘤吸收剂量对于评估放射性药物癌症治疗的疗效至关重要。尽管之前已经研究过通过 MIRD 模式进行的肿瘤剂量测定，但之前的研究仅限于考虑软组织肿瘤。在本研究中，使用 MCNPX 中的蒙特卡罗模拟计算了不同成分的肿瘤中单能光子、电子和 α 粒子的特定吸收分数 (SAF)，然后计算了 22 种放射性核素的自辐照 S 值（以及 14 种额外的 α发射体后代）针对不同大小和组织组成的肿瘤产生。肿瘤被建模为半径从 0.10 厘米到 6.0 厘米不等的球体，其成分从 100% 软组织 (ST) 到 100% 矿物骨 (MB) 不等。光子和电子的能量在对数能量网格上从 10 keV 到 10 MeV 变化。α 粒子的能量沿线性能量网格从 0.5 MeV 变化到 12 MeV。在所有情况下，都假定在整个肿瘤体积中具有均匀的活性分布。此外，为了评估肿瘤形状的影响，对几个不同成分的椭圆形肿瘤进行了建模，并计算了单能电子和光子的吸收分数。然后使用 2008 MIRD 放射性核素数据和衰变方案专着中的详细衰变数据生成 S 值。我们的研究结果表明，软组织模型在分配给 1.5 MeV 电子和 100 keV 光子的均匀源的吸收分数中产生 25% 和 71% 的相对误差，分别位于直径为 1 cm 的 MB 肿瘤内。数据进一步表明，中等椭圆体的吸收分数可以很好地近似为等质量的球形，相对误差小于 8%。计算了 22 种放射性核素（及其子代）的 S 值，结果表明 SAF 的相对误差如何传播到高达 86% 的肿瘤剂量估计的相对误差。提供了按肿瘤大小和组织组成划分的放射性核素 S 值的综合数据集，用于将 MIRD 模式应用于放射性药物治疗中的肿瘤剂量测定。计算了 22 种放射性核素（及其子代）的 S 值，结果表明 SAF 的相对误差如何传播到高达 86% 的肿瘤剂量估计的相对误差。提供了按肿瘤大小和组织组成划分的放射性核素 S 值的综合数据集，用于将 MIRD 模式应用于放射性药物治疗中的肿瘤剂量测定。计算了 22 种放射性核素（及其子代）的 S 值，结果表明 SAF 的相对误差如何传播到高达 86% 的肿瘤剂量估计的相对误差。提供了按肿瘤大小和组织组成划分的放射性核素 S 值的综合数据集，用于将 MIRD 模式应用于放射性药物治疗中的肿瘤剂量测定。