摘要
Objective:This study aims to develop a deep multiscale image learning system(DMILS)to differentiate malignant from benign thyroid follicular neoplasms on multiscale whole-slide images(WSIs)of intraoperative frozen pathological images.Methods:A total of 1,213 patients were divided into training and validation sets,an internal test set,a pooled external test set,and a pooled prospective test set at three centers.DMILS was constructed using a deep learningbased weakly supervised method based on multiscale WSIs at 10×,20×,and 40×magnifications.The performance of the DMILS was compared with that of a single magnification and validated in two pathologist-unidentified subsets.Results:The DMILS yielded good performance,with areas under the receiver operating characteristic curves(AUCs)of 0.848,0.857,0.810,and 0.787 in the training and validation sets,internal test set,pooled external test set,and pooled prospective test set,respectively.The AUC of the DMILS was higher than that of a single magnification,with 0.788 of 10×,0.824 of 20×,and 0.775 of 40×in the internal test set.Moreover,DMILS yielded satisfactory performance on the two pathologist-unidentified subsets.Furthermore,the most indicative region predicted by DMILS is the follicular epithelium.Conclusions:DMILS has good performance in differentiating thyroid follicular neoplasms on multiscale WSIs of intraoperative frozen pathological images.
基金
supported by the Taishan Scholar Project(No.ts20190991,tsqn202211378)
the Key R&D Project of Shandong Province(No.2022CXPT023)
the General Program of National Natural Science Foundation of China(No.82371933)。
作者简介
authors contributed equally:Jiahui Liu;authors contributed equally:Chuanguang Xiao;Correspondence to:Xicheng Song,MD.Department of Otorhinolaryngology,Head and Neck Surgery,Yantai Yuhuangding Hospital,Qingdao University,Yantai 264000,China.Email:drxchsong@163.com;Correspondence to:Ning Mao,MD.Department of Radiology,Yantai Yuhuangding Hospital,Qingdao University,Yantai 264000,China.Email:maoning@pku.edu.cn;Correspondence to:Hongxia Cheng,MD.Department of Pathology,Shandong Provincial Hospital Affiliated to Shandong First Medical University,Jinan 250014,China.Email:hongxiacheng322@hotmail.com.
