Background/Aim: We established a data-driven method for extracting spatial patterns of dose distribution associated with radiation injuries, based on patients with prostate cancer who underwent iodine-125 (I-125) seed implantation. Patients and Methods: Seventy-five patients underwent I-125 seed implantation for prostate cancer. We modeled the severity of lower urinary tract symptoms (LUTS) to be estimated using a linear model, which is formulated as an inner product between the dose distribution D and voxel-wise radiosensitivity B inside the prostate. For the estimation, tensor regression based on a low-rank decomposition with generalized fused lasso penalty was applied. Results: The spatial distribution of B was visually assessed. Positive parameters appeared dominantly in the region close to the urethra and the prostate base. Conclusion: Our tensor regression-based model can predict intra-organ radiosensitivity in a data-driven manner, providing a compelling parameter distribution associated with the development of LUTS after I-125 seed implantation for prostate cancer.

中文翻译：

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基于张量回归的模型研究前列腺癌 I-125 种子植入后的异质空间放射敏感性

背景/目的：基于接受碘 125 (I-125) 种子植入的前列腺癌患者，我们建立了一种数据驱动的方法，用于提取与辐射损伤相关的剂量分布的空间模式。患者和方法：75 名患者因前列腺癌接受了 I-125 种子植入。我们对下尿路症状 (LUTS) 的严重程度进行建模，以使用线性模型进行估计，该模型被表述为剂量分布 D 和前列腺内体素放射敏感性 B 之间的内积。对于估计，应用了基于具有广义融合套索惩罚的低秩分解的张量回归。结果：B 的空间分布通过视觉评估。阳性参数主要出现在靠近尿道和前列腺底部的区域。结论：