Objective: Large volume radiological text data have been accumulated since the incorporation of electronic health record (EHR) systems in clinical practice. We aimed to determine whether deep natural language processing algorithms could aid radiologists in improving thyroid cancer diagnosis. Methods: Sonographic EHR data were obtained from the EHR database. Pathological reports were used as the gold standard for diagnosing thyroid cancer. We developed thyroid cancer diagnosis based on natural language processing (THCaDxNLP) to interpret unstructured sonographic text reports for thyroid cancer diagnosis. We used the area under the receiver operating characteristic curve (AUROC) as the primary metric to measure the performance of the THCaDxNLP. We compared the performance of thyroid ultrasound radiologists aided with THCaDxNLP vs. those without THCaDxNLP using 5 independent test sets. Results: We obtained a total number of 788,129 sonographic radiological reports. The number of thyroid sonographic data points was 132,277, 18,400 of which were thyroid cancer patients. Among the 5 test sets, the numbers of patients per set were 439, 186, 82, 343, and 171. THCaDxNLP achieved high performance in identifying thyroid cancer patients (the AUROC ranged from 0.857–0.932). Thyroid ultrasound radiologists aided with THCaDxNLP achieved significantly higher performances than those without THCaDxNLP in terms of accuracy (93.8％ vs. 87.2％; one-sided t-test, adjusted P = 0.003), precision (92.5％ vs. 86.0％; P = 0.018), and F1 metric (94.2％ vs. 86.4％; P = 0.007). Conclusions: THCaDxNLP achieved a high AUROC for the identification of thyroid cancer, and improved the accuracy, sensitivity, and precision of thyroid ultrasound radiologists. This warrants further investigation of THCaDxNLP in prospective clinical trials.

Qiang Zhang;Sheng Zhang;Jianxin Li;Yi Pan;Jing Zhao;Yixing Feng;Yanhui Zhao;Xiaoqing Wang;Zhiming Zheng;Xiangming Yang;Lixia Liu;Chunxin Qin;Ke Zhao;Xiaonan Liu;Caixia Li;Liuyang Zhang;Chunrui Yang;Na Zhuo;Hong Zhang;Jie Liu;Jinglei Gao;Xiaoling Di;Fanbo Meng;Wei Ji;Meng Yang;Xiaojie Xin;Xi Wei;Rui Jin;Lun Zhang;Xudong Wang;Fengju Song;Xiangqian Zheng;Ming Gao;Kexin Chen;Xiangchun Li

Department of Maxillofacial and Otorhinolaryngology Oncology;Department of Diagnostic and Therapeutic Ultrasonography;Department of Ultrasonography;Department of Pathology;Department of Ultrasonography,Affiliated Hospital of Chifeng University,Chifeng 024000,China;Department of Ultrasonography,Integrated Traditional Chinese and Western Medicine Hospital of Jilin city Jilin Province,Jilin 132000,China;Department of Ultrasonography,Dezhou Municipal Hospital,Dezhou 253000,China;Department of Ultrasound Room of Functions Branch,Affiliated Hospital of Hebei University,Baoding 071000,China;Department of Thyroid and Breast Surgery,Weihai Municipal Hospital,Cheeloo College of Medicine,Shandong University,Weihai 262400,China;0Department of General Surgery,Tianjin Medical University General Hospital,Tianjin 300000,China;Department of Thyroid and Breast Surgery,Tianjin 4th Centre Hospital,Tianjin 300000,China;Department of Thyroid Surgery,Affiliated Hospital of Chengde Medical University,Chengde 067000,China;Department of Ultrasonography,The Second Hospital of Tianjin Medical University,Tianjin 300000,China;Department of Thyroid,the Second Hospital of Jilin University,Changchun 130041,China;Department of Head and Neck Thyroid Surgery,Cangzhou Hospital of Integrated Traditional Chinese and Western Medicine of Hebei Province,Cangzhou 061000,China;Department of Surgery of Glands,People's Hospital of Dingzhou,Dingzhou 073000,China;Department of Thyroid and Breast Surgery,Affiliated Hospital of Shaoxing University,Shaoxing 312000,China;Public Laboratory;Department of Epidemiology and Biostatistics;Department of Thyroid and Neck Cancer,National Clinical Research Center for Cancer,Key Laboratory of Molecular Cancer Epidemiology of Tianjin,Key Laboratory of Cancer Prevention and Therapy of Tianjin,Tianjin Medical University Cancer Institute and Hospital,Tianjin Medical University,Tianjin 300060,China

癌症生物学与医学（英文版）

[1]Qiang Zhang;Sheng Zhang;Jianxin Li;Yi Pan;Jing Zhao;Yixing Feng;Yanhui Zhao;Xiaoqing Wang;Zhiming Zheng;Xiangming Yang;Lixia Liu;Chunxin Qin;Ke Zhao;Xiaonan Liu;Caixia Li;Liuyang Zhang;Chunrui Yang;Na Zhuo;Hong Zhang;Jie Liu;Jinglei Gao;Xiaoling Di;Fanbo Meng;Wei Ji;Meng Yang;Xiaojie Xin;Xi Wei;Rui Jin;Lun Zhang;Xudong Wang;Fengju Song;Xiangqian Zheng;Ming Gao;Kexin Chen;Xiangchun Li-.Improved diagnosis of thyroid cancer aided with deep learning applied to sonographic text reports: a retrospective, multi-cohort, diagnostic study)[J].癌症生物学与医学（英文版）,2022(05):733-741

Sonographic,THCaDxNLP

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