利用聚类分析方法辅助核对患者放疗计划  

IClustering analysis：assistance to verification of radiotherapy treatment plans

作　　者：黄鹏[1] 田源[1] 胡志辉[1] 崔伟杰[1] 戴建荣[1] Huang Peng Tian Yuan Hu Zhihui Cui Weijie Dai Jianrong(Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Science ,Peking Union Medical College ,Beijing 10021, China)

机构地区：[1]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疗科,北京100021

出　　处：《中华放射肿瘤学杂志》2016年第11期1218-1222,共5页Chinese Journal of Radiation Oncology

基　　金：国家自然科学基金青年科学基金项目（81502649）

摘　　要：目的：利用聚类分析方法帮助物理师发现参数异常的治疗计划，提高计划核对工作效能。方法从肿瘤信息管理系统数据库中提取2010—2015年间4个野混合IMRT的835例乳腺癌治疗计划。以治疗计划的处方单次剂量、射野角度、机器跳数作为“特征”参数组成数据集。采用基于主成分分析的K.means算法对数据集进行聚类分析，将数据集划分为不同的类簇。根据距离阈值自动检测每个类簇的孤立点。物理师再通过手工核对孤立点对应的治疗计划，判断聚类分析方法发现异常计划的准确性。结果聚类分析程序将乳腺癌治疗计划参数所组成的样本空间分为了4个类簇，其中3个类簇均检测出孤立点。孤立点所对应的乳腺癌治疗计划中，3例治疗计划是由于靶区特殊性而成为孤立点，另外4例治疗计划均存在一定的改进空间。结论聚类分析可有效地帮助物理师进行治疗计划的独立核对。Objective To use clustering analysis to help physicians detect abnormal parameters in radiotherapy treatment plans and improve the efficiency of plan verification. Methods From 2010 to 2015, 835 breast cancer treatment plans for using 4.field hybrid intensity.modulated radiotherapy from MOSAIQ were collectted. Fractional dose, beam angle, and monitor unit were used as featured parameters of a treatment plan to generate a dataset. The K.means clustering algorithm based on principal component analysis was used to perform a clustering analysis of the dataset and divide the dataset into different clusters. The outliers of clusters were automatically detected based on the distance threshold. The outlier.contained treatment plans were manually verified by physicians to determine the accuracy of clustering analysis in detection of abnormal plans. Results In the clustering analysis, the sample space composed by parameters of treatment plans for breast cancer was divided into 4 clusters, 3 of which had outliers detected. In the targeted treatment plans, 3 plans became outliers because of special target volume and the other 4 plans needed improvement. Conclusions Clustering analysis is effective to help physicians to independently verify treatment plans.

关 键 词：聚类分析 孤立点检测 放疗计划 独立核对 

分 类 号：R730.55[医药卫生—肿瘤]