[1]耿继武,刘浩,李子尧,等. 基于三维生物学有效剂量的肺纤维化分层与预测模型[J].中国医学物理学杂志,2018,35(7):749-752.[doi:DOI:10.3969/j.issn.1005-202X.2018.07.002]
　GENG Jiwu,LIU Hao,LI Ziyao,et al. Three-dimensional biologically effective dose model for stratification and prediction of lung fibrosis[J].Chinese Journal of Medical Physics,2018,35(7):749-752.[doi:DOI:10.3969/j.issn.1005-202X.2018.07.002]
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 基于三维生物学有效剂量的肺纤维化分层与预测模型()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
35卷
期数:
2018年第7期
页码:
749-752
栏目:
医学放射物理
出版日期:
2018-07-20

文章信息/Info

Title:
 Three-dimensional biologically effective dose model for stratification and prediction of lung fibrosis
文章编号:
1005-202X（2018）07-0749-04
作者:
 耿继武1; 刘浩2; 李子尧3; 路顺4; 文磊5; 任骅6; 周兆明7; 陈明8; 陈龙华9; 周成8; 9
 1.广东省职业病防治院， 广东 广州 510300；2.南方医科大学南方医院普外科， 广东 广州 510515；3.大连医科大学附属第一医院泌尿外科， 辽宁 大连 116011；4.电子科技大学医学院附属四川省肿瘤医院（研究所）放疗科， 四川 成都 610041；5.第四军医大学西京医院肿瘤科， 陕西 西安 710032；6.国家癌症中心/中国医学科学院北京协和医学院肿瘤医院放射治疗科， 北京 100021；7.德国海德堡大学医院， 海德堡 69120；8.浙江省肿瘤医院放射肿瘤学重点实验室， 浙江 杭州 3100229； 9.南方医科大学南方医院放疗科，广东 广州 510515.
Author(s):
 GENG Jiwu1;  LIU Hao2;  LI Ziyao3;  LU Shun4;  WEN Lei5;  REN Hua6;  ZHOU Zhaoming7;  CHEN Ming8;  CHEN Longhua9;  ZHOU Cheng8;  9
 1. Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; 2. Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; 3. Department of Urology, the First Affiliated Hospital of Dalian Medical University, Dalian 116011, China; 4. Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu 610041, China; 5. Department of Clinical Oncology, Xijing Hospital, the Fourth Military Medical University, Xi’an 710032, China;
关键词:
 ; 雌性小鼠; 生物学有效剂量; 放射性肺纤维化; 剂量-效应曲线; 放射生物学
Keywords:
 ; Keywords: female mice;  biologically effective dose;  radiation-induced lung fibrosis;  dose-response curve;  radiobiology
分类号:
R811.5
DOI:
DOI:10.3969/j.issn.1005-202X.2018.07.002
文献标志码:
A
摘要:
 目的：拟建立基于小鼠放射性肺损伤影像学改变的三维生物学有效剂量（BED）预测模型。 方法：对研究纳入单次与分次照射的实验结果进行BED与数学建模。采用8~10周龄C57BL6雌性小鼠随机分组进行X线全肺野照射，分别给予单次照射组0.0、10.5、12.5、14.5、17.5、20.0 Gy梯度剂量照射；分割照射组单次0.0、2.0、4.0、6.0、7.0、8.5 Gy，共5次分割照射。照射后24周行CT扫描成像、经三维分割算法获得肺部平均密度与肺部体积值。 结果：根据BED分别建立基于CT肺密度、肺体积的剂量-效应关系，其中位剂量（半数有效剂量）分别为（68.17±10.53） Gy （adjusted R2=0.89）、（84.12±19.70） Gy （adjusted R2=0.94）。进一步对CT肺密度与肺体积进行线性回归分析后发现两者存在显著线性相关性（R2=0.96, P<0.000 1）。根据这一重要动态关联，最终建立了BED剂量与肺纤维化基于双影像学参数的三维剂量-效应评估模型。 结论：首次提出了辐射诱导小鼠肺纤维化的三维BED模型。该模型可以对不同分割剂量组的纤维化程度进行准确地分层与预测，为开展部分肺野照射、抗肺纤维化新药测试等研究奠定放射生物学基础。
Abstract:
 Abstract: Objective To establish a three-dimensional (3D) biologically effective dose (BED) prediction model based on lung fibrosis-related radiological parameters. Methods BED and mathematical modeling were performed on the results of 1-fraction and multi-fraction irradiation. C57BL6 female mice aged from 8 to 10 weeks which were randomly divided into 1-fraction group and 5-fraction group received X-ray whole lung irradiation. The dose gradients for 1-fraction group were 0.0, 10.5, 12.5, 14.5, 17.5 and 20.0 Gy, respectively; the 5-fraction group was delivered with 0.0, 2.0, 4.0, 6.0, 7.0 and 8.5 Gy per fraction, with a total of 5 fractions. Computed tomography (CT) imaging was performed at 24 weeks after irradiation. The average lung density and volume changes were obtained by 3D segmentation algorithm. Results BED dose-response relationships based on CT lung density as well as CT lung volume were investigated. The median dose (half effective dose, ED50) for radiation-induced lung density changes was (68.17±10.53) Gy (adjusted R2=0.89); whereas the median dose (ED50) for radiation-induced lung volume reduction was (84.12±19.70) Gy (adjusted R2=0.94). A good linear correlation between CT lung density and CT lung volume was demonstrated with the use of linear regression analysis (R2 = 0.96, P<0.000 1). According to this important finding, a dual CT parameters based 3D-BED model was established for stratification and prediction of pulmonary fibrosis. Conclusion A 3D-BED model is firstly proposed to achieve a precise stratification and prediction of lung fibrosis after exposing with different radiation doses, establishing a radiobiological basis for future radiobiological studies on partial lung field irradiation and the development of novel anti-fibrotic agents.

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备注/Memo

备注/Memo:
 【收稿日期】2018-04-21
【基金项目】国家自然科学青年科学基金（81703166）
【作者简介】耿继武，副主任医师，从事辐射卫生防护工作，E-mail: 1044161@qq.com
【通信作者】周成，博士，从事放射治疗工作，E-mail: czhou.rob@gmail.com
更新日期/Last Update: 2018-07-24