Automated Identification and Measurement Extraction of Pancreatic Cystic Lesions from Free-Text Radiology Reports Using Natural Language Processing

作者：Rikiya Yamashita, Kristen N. Bird, P. Cheung, Johannes H. Decker, Marta Flory, Daniel Goff, Linda Nayeli Morimoto, Andy Shon, Andrew L. Wentland, Daniel L. Rubin, Terry S. Desser · 发表于：Radiology Artificial Intelligence · 年份：2021 · DOI：10.1148/ryai.210092 · 被引用次数：37 · 研究领域：Pancreatic and Hepatic Oncology Research、Artificial Intelligence in Healthcare and Education、Radiomics and Machine Learning in Medical Imaging

Purpose To automatically identify a cohort of patients with pancreatic cystic lesions (PCLs) and extract PCL measurements from historical CT and MRI reports using natural language processing (NLP) and a question answering system. Materials and Methods Institutional review board approval was obtained for this retrospective Health Insurance Portability and Accountability Act–compliant study, and the requirement to obtain informed consent was waived. A cohort of free-text CT and MRI reports generated between January 1991 and July 2019 that covered the pancreatic region were identified. A PCL identification model was developed by modifying a rule-based information extraction model; measurement extraction was performed using a state-of-the-art question answering system. The system's performance was evaluated against radiologists’ annotations. Results For this study, 430 426 free-text radiology reports from 199 783 unique patients were identified. The NLP model for identifying PCL was applied to 1000 test samples. The interobserver agreement between the model and two radiologists was almost perfect (Fleiss κ = 0.951), and the false-positive rate and true-positive rate were 3.0% and 98.2%, respectively, against consensus of radiologists’ annotations as ground truths. The overall accuracy and Lin concordance correlation coefficient for measurement extraction were 0.958 and 0.874, respectively, against radiologists’ annotations as ground truths. Conclusion An NLP-based system was deve...