利用基于图像配准的深度学习方法提高磁共振引导前列腺癌放疗自动勾画精度  

Improving auto-segmentation accuracy for online magnetic resonance imaging-guided prostate radiotherapy by registration-based deep learning method

作　　者：王云祥 杨碧凝 刘宇翔 朱冀 卢宁宁 戴建荣 门阔 WANG Yunxiang;YANG Bining;LIU Yuxiang;ZHU Ji;LU Ning-Ning;DAI Jianrong;MEN Kuo(National Cancer Center/National Clinical Research Center for Cancer/Department of Radiation Oncology,Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100021,China)

机构地区：[1]国家癌症中心/国家肿瘤临床医学研究中心/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

出　　处：《中国医学物理学杂志》2024年第6期667-672,共6页Chinese Journal of Medical Physics

基　　金：国家自然科学基金(11975313);中国医学科学院中央级公益性科研院所基本科研业务费健康长寿专项(2021-JKCS-003)。

摘　　要：目的:改进在线磁共振图像中前列腺靶区和危及器官的自动勾画性能,提高磁共振引导前列腺癌在线自适应放射治疗的效率。方法:对40例接受磁共振引导在线自适应放射治疗的前列腺癌患者进行回顾性研究,其中训练集25例、验证集5例、测试集10例。将模拟定位图像与相应勾画信息和在线磁共振图像进行配准后输入深度学习网络,实现对磁共振图像的自动勾画,并与形变配准方法和单MR输入的深度学习方法进行比较。结果:本文方法的自动勾画准确性整体优于形变配准方法和单MR输入的深度学习方法,临床靶区、膀胱、直肠和左、右侧股骨头的平均Dice相似性指数分别达0.896、0.941、0.840、0.943和0.940。结论:本文方法能有效提高磁共振引导前列腺癌在线自适应放射治疗中自动勾画的准确性和效率。Objective To improve the performance of auto-segmentation of prostate target area and organs-at-risk in online magnetic resonance image and enhance the efficiency of magnetic resonance imaging-guided adaptive radiotherapy(MRIgART)for prostate cancer.Methods A retrospective study was conducted on 40 patients who underwent MRIgART for prostate cancer,including 25 in the training set,5 in the validation set,and 10 in the test set.The planning CT images and corresponding contours,along with online MR images,were registered and input into a deep learning network for online MR image auto-segmentation.The proposed method was compared with deformable image registration(DIR)method and single-MR-input deep learning(SIDL)method.Results The overall accuracy of the proposed method for auto-segmentation was superior to those of DIR and SIDL methods,with average Dice similarity coefficients of 0.896 for clinical target volume,0.941 for bladder,0.840 for rectum,0.943 for left femoral head and 0.940 for right femoral head,respectively.Conclusion The proposed method can effectively improve the accuracy and efficiency of auto-segmentation in MRIgART for prostate cancer.

关 键 词：前列腺癌 磁共振引导在线自适应放射治疗 图像配准 深度学习 自动勾画 

分 类 号：R318[医药卫生—生物医学工程] TP391[医药卫生—基础医学] R811.1[自动化与计算机技术—计算机应用技术]