首页> 外文期刊>Journal of digital imaging: the official journal of the Society for Computer Applications in Radiology >Development of an Automated Bone Mineral Density Software Application: Facilitation Radiologic Reporting and Improvement of Accuracy
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Development of an Automated Bone Mineral Density Software Application: Facilitation Radiologic Reporting and Improvement of Accuracy

机译:自动化骨矿物质密度软件应用程序的开发:简化放射学报告并提高准确性

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摘要

The conventional method of bone mineral density (BMD) report production by dictation and transcription is time consuming and prone to error. We developed an automated BMD reporting system based on the raw data from a dual energy X-ray absorptiometry (DXA) scanner for facilitating the report generation. The automated BMD reporting system, a web application, digests the DXA's raw data and automatically generates preliminary reports. In Jan. 2014, 500 examinations were randomized into an automatic group (AG) and a manual group (MG), and the speed of report generation was compared. For evaluation of the accuracy and analysis of errors, 5120 examinations during Jan. 2013 and Dec. 2013 were enrolled retrospectively, and the context of automatically generated reports (AR) was compared with the formal manual reports (MR). The average time spent for report generation in AG and in MG was 264 and 1452 s, respectively (p < 0.001). The accuracy of calculation of T and Z scores in AR is 100 %. The overall accuracy of AR and MR is 98.8 and 93.7 %, respectively (p < 0.001). The mis-categorization rate in AR and MR is 0.039 and 0.273 %, respectively (p = 0.0013). Errors occurred in AR and can be grouped into key-in errors by technicians and need for additional judgements. We constructed an efficient and reliable automated BMD reporting system. It facilitates current clinical service and potentially prevents human errors from technicians, transcriptionists, and radiologists.
机译:通过听写和转录产生骨矿物质密度(BMD)报告的常规方法既费时又容易出错。我们基于双能X射线吸收仪(DXA)扫描仪的原始数据开发了自动BMD报告系统,以促进报告的生成。自动化的BMD报告系统是一个Web应用程序,可消化DXA的原始数据并自动生成初步报告。 2014年1月,将500份考试随机分为自动组(AG)和手动组(MG),比较了报告生成的速度。为了评估准确性和错误分析,回顾性研究了2013年1月和2013年12月的5120项检查,并将自动生成的报告(AR)与正式的手工报告(MR)进行了比较。在AG和MG中,用于生成报告的平均时间分别为264和1452 s(p <0.001)。 AR中T和Z分数的计算准确性为100%。 AR和MR的总体准确度分别为98.8%和93.7%(p <0.001)。 AR和MR中的错误分类率分别为0.039和0.273%(p = 0.0013)。 AR中发生的错误,技术人员可以将其归类为键入错误,并且需要其他判断。我们构建了高效可靠的自动化BMD报告系统。它促进了当前的临床服务,并有可能防止技术人员,转录员和放射科医生的人为错误。

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