基于人群的统计模型，用于研究放射性毒性后 I 种子植入后前列腺内不均匀敏感性。
A Population-based Statistical Model for Investigating Heterogeneous Intraprostatic Sensitivity to Radiation Toxicity After I Seed Implantation.
机构信息
Division of Molecular Modification and Cancer Biology, National Cancer Center Research Institute, Tokyo, Japan
Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
出版信息
In Vivo. 2019 Nov-Dec;33(6):2103-2111. doi: 10.21873/invivo.11710.
Abstract
AIM
To develop a population-based statistical model in order to find a spatial pattern of dose distribution which is related to lower urinary tract symptoms (LUTS) after iodine-125 (I) seed implantation for prostate cancer.
PATIENTS AND METHODS
A total of 75 patients underwent I seed implantation for prostate cancer. Principal component analysis was applied to the standardized dose array and for each patient dose distribution was uniquely characterized by a combination of weighted eigenvectors. The correlation between eigenvectors and the severity of LUTS was investigated with linear regression analysis.
RESULTS
Eight eigenvectors were identified as being significantly associated with the severity of LUTS (p<0.05). Multivariate regression model identified that intraprostatic parameters, which were positively associated with the severity of LUTS, were distributed around a portion of the urethral base and a peripheral region of the prostate.
CONCLUSION
We established a population-based statistical model that may indicate a significant dose pattern associated with the severity of radiation toxicity.
摘要
目的
建立一个基于人群的统计模型，以寻找与前列腺癌碘-125（I）种子植入后下尿路症状（LUTS）相关的剂量分布空间模式。
患者和方法
共有 75 例患者接受了前列腺癌 I 种子植入。对标准化剂量数组应用主成分分析，为每位患者的剂量分布通过加权特征向量的组合进行独特描述。用线性回归分析研究特征向量与 LUTS 严重程度之间的相关性。
结果
确定了 8 个特征向量与 LUTS 的严重程度显著相关（p<0.05）。多变量回归模型确定，与 LUTS 严重程度呈正相关的前列腺内参数分布在尿道基底的一部分和前列腺的外周区域周围。
结论
我们建立了一个基于人群的统计模型，该模型可能表明与放射毒性严重程度相关的显著剂量模式。
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