Computer-Assisted Reporting and Decision Support in Standardized Radiology Reporting for Cancer Imaging

被引:5
作者
Bizzo, Bernardo C. [1 ,2 ,3 ]
Almeida, Renata R. [1 ,4 ]
Alkasab, Tarik K. [1 ,2 ]
机构
[1] Harvard Med Sch, Boston, MA 02115 USA
[2] Massachusetts Gen Hosp, Dept Radiol, 55 Fruit St,Founders 210, Boston, MA 02114 USA
[3] Univ Fed Rio de Janeiro, Dept Radiol, Rio De Janeiro, Brazil
[4] Brigham & Womens Hosp, Dept Radiol, 75 Francis St, Boston, MA 02115 USA
来源
JCO CLINICAL CANCER INFORMATICS | 2021年 / 5卷
关键词
ACR INCIDENTAL FINDINGS; WHITE PAPER; MANAGEMENT; CT; CYSTS; MRI;
D O I
10.1200/CCI.20.00129
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
PURPOSE Recent advances in structured reporting are providing an opportunity to enhance cancer imaging assessment to drive value-based care and improve patient safety. METHODS The computer-assisted reporting and decision support (CAR/DS) framework has been developed to enable systematic ingestion of guidelines as clinical decision structured reporting tools embedded within the radiologist's workflow. RESULTS CAR/DS tools can reduce the radiology reporting variability and increase compliance with clinical guidelines. The lung cancer use-case is used to describe various scenarios of a cancer imaging structured reporting pathway, including incidental findings, screening, staging, and restaging or continued care. Various aspects of these tools are also described using cancer-related examples for different imaging modalities and applications such as calculators. Such systems can leverage artificial intelligence (AI) algorithms to assist with the generation of structured reports and there are opportunities for new AI applications to be created using the structured data associated with CAR/DS tools. CONCLUSION These AI-enabled systems are starting to allow information from multiple sources to be integrated and inserted into structured reports to drive improvements in clinical decision support and patient care.
引用
收藏
页码:426 / 434
页数:9
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