英国乳腺影像系统设置差异大,影响AI与医生判读结果。
Survey of image processing settings used for mammography systems in the United Kingdom: how variable is it?
- 通过提取DICOM头信息,调研497台设备的图像处理设置。
- 同一型号设备有2至7个不同软件版本,图像外观差异显著。
- 适合关注AI部署、设备标准化及乳腺筛查质量的人员阅读。
本研究开展英国全国性调查,分析乳腺影像系统的配置情况,重点关注图像处理参数与软件版本。我们开发程序从DICOM头中提取特定标签,28个医学物理部门对2023年后采集的TORMAM幻影图像使用该程序,获得497台设备数据。涉及7种不同型号的乳腺摄影系统。结果显示,每种型号均存在2至7个不同的工作站软件版本,且各系统配备多种图像处理设置。初步使用TORMAM幻影验证发现,相同X射线设备下图像外观存在明显差异。富士、通用电气和西门子系统在剂量设置上也存在差异。此外,探测器板和滤线栅类型亦不一致。本次快照显示,设备配置差异可能导致图像表现不同,进而影响人工智能分析与人工阅片结果。因此,引入AI时必须考虑这些差异,并应对未来设置变化。相关责任方包括AI供应商、医学物理人员、设备制造商及乳腺筛查单位,需协同管理,确保筛查效果不受设备配置影响。
原文摘要 · Abstract (English)
The aim was to undertake a national survey of the setup of mammography imaging systems in the UK, we were particularly interested in image processing and software version. We created a program that can extract selected tags from the DICOM header. 28 medical physics departments used the program on processed images of the TORMAM phantom acquired since 2023 and this produced data for 497 systems. We received data for 7 different models of mammography systems. We found that currently in use each model had between 2 and 7 different versions of software for the acquisition workstation. Each of the systems had multiple versions of image processing settings, a preliminary investigation with TORMAM demonstrated large differences in the appearance of the image for the same X-ray model. The Fujifilm, GE and Siemens systems showed differences in the setup of the dose levels. In addition to these settings there were differences in the paddles used and grid type. Our snapshot of system set up showed that there is a potential for the images to appear differently according to the settings seen in the headers. These differences may affect the outcomes of AI and also human readers. Thus the introduction of AI must take these differences into consideration and the inevitably changes of settings in the future. There are responsibilities on AI suppliers, physics, mammographic equipment manufacturers, and breast-screening units to manage the use of AI and ensure the outcomes of breast screening are not adversely affected by the set-up of equipment.
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