实用医学杂志2024，Vol.40Issue(2)：153-157,5.DOI:10.3969/j.issn.1006-5725.2024.02.005
AccuLearning自动勾画临床靶区和危及器官用于宫颈癌术后放疗的可行性研究
Feasibility of automatic segmentation of CTV and OARs in postoperative radiotherapy for cervical cancer using AccuLearning
摘要
Abstract
Objective To explore the feasibility of automatic segmentation of clinical target volume(CTV)and organs at risk(OARs)for cervical cancer using AccuLearning(AL)based on geometric and dosimetric indices.Methods Seventy-five CT localization images with manual contouring data of postoperative cervical cancer were enrolled in this study.Sixty cases were randomly selected to trained to generate automatic segmentation model by AL,and the CTV and OARs of the remaining 15 cases were automatically contoured.Radiotherapy plans on the automatic segmentation contours were imported on the CT images of manual contours.The efficiency,Dice similarity coefficient(DSC),Hausdorff distance(HD)and dosimetric parameters were compared between the two methods.Results The time of automatic segmentation was significantly shorter than that of the manual contour(P<0.05).The DSC of all structures were≥0.87.The HD of bowel bag and rectum were about 10 mm,and that of the rest of OARs were less than 5 mm.CTV(D98,V90% ,V95% ,Dmean,HI),bowel bag(V50)and bladder(V50)had significant differences in dosimetric comparison(P<0.05).Conclusion The automatic segmentation model based on AL can improve the efficiency of radiotherapy.Automatic segmentation of OARs has the potential of clinical application,while that of CTV still needs to be further modified.关键词
自动勾画/宫颈癌/临床靶区/危及器官/剂量学Key words
automatic segmentation/cervical cancer/clinical target volume/organs at risk/dosimetry分类
医药卫生引用本文复制引用
陈飞,龚筱钦,余云鹏,游涛,王旭,戴春华,胡静..AccuLearning自动勾画临床靶区和危及器官用于宫颈癌术后放疗的可行性研究[J].实用医学杂志,2024,40(2):153-157,5.基金项目
江苏省卫生健康委员会医学科研重点项目(编号:ZDB2020022) （编号:ZDB2020022）
镇江市重点研发计划(社会发展)项目(编号:SH2023002) （社会发展）
镇江市社会发展指导性科技计划项目(编号:FZ2020031) （编号:FZ2020031）
