α放射性药物疗法（αRPT）在转移性疾病治疗中显示出良好的疗效。然而，α粒子的短程距离需要对近细胞空间进行剂量计算。目前对细胞剂量计算的认识主要基于使用细胞单层的体外实验。这些实验的目的是确定细胞对吸收剂量（AD）的敏感性。然而，AD不能直接测量，需要进行建模。目前的模型通常将细胞理想化为规则网格上的球体（几何模型），简化结合动力学并忽略放射性衰变的随机性质。这种简化的影响尚不清楚，但是过度简化会导致不准确和不可推广的结果，从而阻碍了潜在放射生物学的严格研究。我们使用共聚焦显微镜在典型实验条件下系统地绘制了大量活体细胞的三维细胞几何形态、聚类行为、药物结合、内化和亚细胞运输动力学。这使得我们可以进行基于Monte Carlo的（微）剂量计算。 通过实验确定的HER2+乳腺癌细胞系在使用标记有212Pb的anti-HER2共价物或外部射线疗法处理后的存活分数，采用了严格的统计方法来估计细胞对AD的敏感性和相对生物学效应（RBE）。所有结果均与参考几何模型进行比较，这使我们可以确定哪些方面是适当研究潜在放射生物学的重要模型组成部分。总共测量了567个细胞，延迟孵育时间最长可达26小时。与几何模型相比，实际细胞聚类对AD具有较大的影响（2倍），而细胞几何形态具有较小的影响（16.4%差异）。微剂量计算揭示了大多数测试条件下超过一半的细胞在大部分时间内没有接受任何剂量，这对细胞敏感性的评估产生巨大影响。将这些随机效应纳入模型中，可以显著提高存活分数和RBE的预测准确性（置换测试；p <.01）。这种综合生物和物理方面的完整结合在αRPT实验中提供了更准确的细胞存活模型。具体来说，包括真实的随机辐射效应和细胞聚类行为对获得可推广的放射生物学参数至关重要。 © 2023.作者（们）。

Alpha-emitter radiopharmaceutical therapy (αRPT) has shown promising outcomes in metastatic disease. However, the short range of the alpha particles necessitates dosimetry on a near-cellular spatial scale. Current knowledge on cellular dosimetry is primarily based on in vitro experiments using cell monolayers. The goal of such experiments is to establish cell sensitivity to absorbed dose (AD). However, AD cannot be measured directly and needs to be modeled. Current models, often idealize cells as spheroids in a regular grid (geometric model), simplify binding kinetics and ignore the stochastic nature of radioactive decay. It is unclear what the impact of such simplifications is, but oversimplification results in inaccurate and non-generalizable results, which hampers the rigorous study of the underlying radiobiology.We systematically mapped out 3D cell geometries, clustering behavior, agent binding, internalization, and subcellular trafficking kinetics for a large cohort of live cells under representative experimental conditions using confocal microscopy. This allowed for realistic Monte Carlo-based (micro)dosimetry. Experimentally established surviving fractions of the HER2 + breast cancer cell line treated with a 212Pb-labelled anti-HER2 conjugate or external beam radiotherapy, anchored a rigorous statistical approach to cell sensitivity and relative biological effectiveness (RBE) estimation. All outcomes were compared to a reference geometric model, which allowed us to determine which aspects are crucial model components for the proper study of the underlying radiobiology.In total, 567 cells were measured up to 26 h post-incubation. Realistic cell clustering had a large (2x), and cell geometry a small (16.4% difference) impact on AD, compared to the geometric model. Microdosimetry revealed that more than half of the cells do not receive any dose for most of the tested conditions, greatly impacting cell sensitivity estimates. Including these stochastic effects in the model, resulted in significantly more accurate predictions of surviving fraction and RBE (permutation test; p < .01).This comprehensive integration of the biological and physical aspects resulted in a more accurate method of cell survival modelling in αRPT experiments. Specifically, including realistic stochastic radiation effects and cell clustering behavior is crucial to obtaining generalizable radiobiological parameters.© 2023. The Author(s).