Dosimetry-based personalized therapy was shown to have clinical benefits e.g. in liver selective internal radiation therapy (SIRT). Yet, there is no consensus about its introduction into clinical practice, mainly as Monte Carlo simulations (gold standard for dosimetry) involve massive computation time. We addressed the problem of computation time and tested a patch-based approach for Monte Carlo simulations for internal dosimetry to improve parallelization. We introduce a physics-inspired cropping layout for patch-based MC dosimetry, and compare it to cropping layouts of the literature as well as dosimetry using organ-S-values, and dose kernels, taking whole-body Monte Carlo simulations as ground truth. This was evaluated in five patients receiving Yttrium-90 liver SIRT. The patch-based Monte Carlo approach yielded the closest results to the ground truth, making it a valid alternative to the conventional approach. Our physics-inspired cropping layout and mosaicking scheme yielded a voxel-wise error of < 2% compared to whole-body Monte Carlo in soft tissue, while requiring only $$\approx$$ 10% of the time. This work demonstrates the feasibility and accuracy of physics-inspired cropping layouts for patch-based Monte Carlo simulations.

中文翻译：

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DosePatch：基于物理的裁剪布局，用于基于补丁的蒙特卡罗模拟，以提供快速、准确的内部剂量测定


基于剂量测定的个性化治疗已被证明具有临床益处，例如在肝脏选择性内部放射治疗（SIRT）中。然而，关于将其引入临床实践尚未达成共识，主要是因为蒙特卡罗模拟（剂量测定的黄金标准）涉及大量计算时间。我们解决了计算时间问题，并测试了基于补丁的内部剂量测定蒙特卡罗模拟方法，以提高并行性。我们为基于补丁的 MC 剂量测定引入了一种受物理启发的裁剪布局，并将其与文献的裁剪布局以及使用器官 S 值和剂量内核的剂量测定进行比较，以全身蒙特卡罗模拟作为基本事实。这是在 5 名接受 Yttrium-90 肝脏 SIRT 的患者中进行评估的。基于补丁的蒙特卡罗方法产生了最接近真实情况的结果，使其成为传统方法的有效替代方案。与软组织中的全身蒙特卡罗相比，我们受物理启发的裁剪布局和镶嵌方案产生的体素误差小于 2%，而仅需要 $$\approx$$ 10% 的时间。这项工作证明了基于补丁的蒙特卡罗模拟的受物理启发的裁剪布局的可行性和准确性。