摘要
目的评价基于深度学习(DL)的乳腺X线摄影钙化检测系统对乳腺可疑钙化的检出效能。方法回顾分析932例接受乳腺X线检查患者的头足位(CC)和内外斜位(MLO)资料,由2名低年资医师和DL系统盲法独立阅片,一名高年资医师审核结果。比较DL系统与低年资医师检出敏感度差异,结合双向表χ2检验,评价不同BI-RADS分类、钙化形态和分布影响。结果针对3728幅影像(932例),标记可疑钙化274例。2名低年资医师和DL系统的检出敏感度分别是76.64%(210/274)、82.12%(225/274)和99.64%(273/274)。DL系统检出敏感度不受钙化形态、分布、BI-RADS分类等因素的影响(P均>0.05),而低年资医师对无定形钙化和团簇分布钙化的敏感度明显降低(P均<0.05)。结论基于DL的乳腺X线影像钙化检出系统检出对可疑形态钙化的敏感度高且稳定,可辅助临床医师减少漏检。
Objective To observe the efficiency of mammography detection system based on deep learning(DL)for breast suspicious calcifications.Methods Standard cranio-caudal(CC)and medio-lateral oblique(MLO)view breast images of 932 women were interpreted by two junior radiologists and the DL system,respectively.Then the results were reviewed by a senior radiologist.The sensitivities of the two junior radiologists and DL model were compared.Then two-way tests were used to annalyze differences under different BI-RADS categories,morphologies and distributions.Results There were 274 suspicious calcifications in the ground truth from 932 cases(3728 images).The sensitivity of two junior radiologists and DL system was 76.64%(210/274),82.12%(225/274)and 99.64%(273/274),respectively.No significant difference of the DL system was found under different morphologies,distributions and BI-RADS categories(all P>0.05),while for the junior radiologists,the sensitivities of amorphous or grouped calcifications were significantly lower than of the others(both P<0.05).Conclusion The automatic mammography suspicious calcification detection system based on DL show promising sensitivities and robustness,which may help radiologists to reduce the missing of suspicious calcifications.
作者
王小琦
刘鹏
陈赜
张番栋
WANG Xiaoqi;LIU Peng;CHEN Ze;ZHANG Fandong(Department of Radiology,Gansu Provincial Cancer Hospital,Lanzhou 730050,China;Deepwise AI Lab,Beijing 100080,China)
出处
《中国医学影像技术》
CSCD
北大核心
2019年第12期1784-1788,共5页
Chinese Journal of Medical Imaging Technology
