[1]柳炫宇,陈舒影,郭飞宝,等.定制化与通用模型在宫颈癌危及器官勾画准确性中的比较[J].中国医学物理学杂志,2024,41(11):1337-1342.[doi:DOI:10.3969/j.issn.1005-202X.2024.11.003]
　LIU Xuanyu,CHEN Shuying,et al.Comparative study on the accuracies of customized and universal models for organs-at-risk segmentation in cervical cancer[J].Chinese Journal of Medical Physics,2024,41(11):1337-1342.[doi:DOI:10.3969/j.issn.1005-202X.2024.11.003]
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定制化与通用模型在宫颈癌危及器官勾画准确性中的比较()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
41卷
期数:
2024年第11期
页码:
1337-1342
栏目:
医学放射物理
出版日期:
2024-11-26

文章信息/Info

Title:
Comparative study on the accuracies of customized and universal models for organs-at-risk segmentation in cervical cancer
文章编号:
1005-202X（2024）11-1337-06
作者:
柳炫宇1; 2; 陈舒影1; 2; 郭飞宝1; 2; 3; 4; 陈燕彬1; 2; 4; 何清1; 2; 4; 吕文龙1; 2; 3; 4; 陈颀5; 张倚萌5; 王少彬5; 6; 蔡传书1; 2; 3; 4
1. 福建医科大学附属第一医院肿瘤中心放疗科， 福建 福州 350005； 2.福建医科大学附属第一医院滨海院区国家区域医疗中心， 福建 福州 350212； 3.放射生物福建省高等学校重点实验室， 福建 福州 350005； 4.福建医科大学医学影像学院， 福建 福州 350122； 5.北京医智影科技有限公司， 北京 100083； 6.清华大学医学院， 北京 100084
Author(s):
LIU Xuanyu1;  2;  CHEN Shuying1;  2;  GUO Feibao1;  2;  3;  4;  CHEN Yanbin1;  2;  4;  HE Qing1;  2;  4;  L?Wenlong1;  2;  3;  4;  CHEN Qi5;  ZHANG Yimeng5;  WANG Shaobin5;  6;  CAI Chuanshu1;  2;  3;  4
1. Department of Radiotherapy, Cancer Center, the First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China 2. National Regional Medical Center, Binhai Branch of the First Affiliated Hospital of Fujian Medical University, Fuzhou 350212, China 3. Key Laboratory of Radiation Biology of Fujian Higher Education Institutions, Fuzhou 350005, China 4. School of Medical Imaging, Fujian Medical University, Fuzhou 350122, China 5. MedMind Technology Co., Ltd., Beijing 100083, China 6. Tsinghua Medicine, Tsinghua University, Beijing 100084, China
关键词:
宫颈癌; 自动勾画; RT-Mind; 定制化模型
Keywords:
Keywords: cervical cancer automatic segmentation RT-Mind customized model
分类号:
R318；R811.1
DOI:
DOI:10.3969/j.issn.1005-202X.2024.11.003
文献标志码:
A
摘要:
目的：对比分析定制化自动勾画模型和商品化通用勾画模型在宫颈癌危及器官勾画中的差异，探讨定制化模型的可行性。方法：回顾性选取270例宫颈癌患者，由资深临床医生勾画其膀胱、直肠、小肠、骨盆骨髓、股骨头及肾脏等器官。随机选取病例构建定制化勾画模型，其中202例作为训练集，30例作为验证集，38例作为测试集。在测试集上，使用定制化模型和通用模型进行勾画预测。对比测试集在两种模型下的结果与手动勾画的结果，评估定制化模型的性能。结果：从DSC值上分析，定制化模型/通用模型与手动勾画相近，均表现出良好的勾画效果（DSC值：0.7~0.9）。然而，在质心偏差和95%豪斯多夫距离这两个关键指标上，定制化模型优于通用模型。结论：与通用模型相比，定制化模型能更准确地勾画宫颈癌危及器官的结构。定制化模型根据特定数据集优化，为临床决策提供精准支持，展现其在宫颈癌治疗中的广阔应用前景。
Abstract:
Abstract: Objective To compare and analyze the differences between customized models and commercial universal models in the segmentation of organs-at-risk in cervical cancer, and to investigate the feasibility of customized models. Methods A retrospective analysis was conducted on 270 cervical cancer patients. Senior clinicians manually delineated organs-at-risk, including the bladder, rectum, small intestine, pelvic bone marrow, femoral heads, and kidneys. The cases were randomly selected to develop customized models, with 202 cases allocated to the training set, 38 cases to the test set, and 30 cases to the validation set. The universal and customized models were used for segmentation on the test set, and the automatic segmentation results obtained by the two models were compared with manual segmentation results to assess the performance of the customized model. Results Both customized model and universal model had comparable DSC values to manual segmentation, demonstrating satisfactory delineation outcomes (DSC values ranging from 0.7 to 0.9). However, in terms of deviation of centroid and 95% Hausdorff distance, the customized model surpassed the universal model. Conclusion Compared with the universal model, the customized model offers superior accuracy in delineating the structures of organs-at-risk in cervical cancer. As the customized model is optimized based on specific datasets, it provides precise support for clinical decision-making and holds promising applications in the treatment of cervical cancer.

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备注/Memo

备注/Memo:
【收稿日期】2024-05-20 【基金项目】福建省科技计划项目（2021Y0101）；福建医科大学启航基金（2020QH1057） 【作者简介】柳炫宇，技师，研究方向：医学物理，E-mail: 792953672@qq.com 【通信作者】蔡传书，教授，主任医师，研究方向：肿瘤学，E-mail: 857269804@qq.com
更新日期/Last Update: 2024-11-26