Kleefeld Christoph, Castillo Lopez Jorge Patricio, Costa Paulo R, Fitton Isabelle, Mohamed Ahmed, Pesznyak Csilla, Ruggeri Ricardo, Tsalafoutas Ioannis, Tsougos Ioannis, Wong Jeannie Hsiu Ding, Zdesar Urban, Ciraj-Bjelac Olivera, Tsapaki Virginia
Department of Medical Physics and Clinical Engineering, University Hospital Galway and Physics, School of Natural Sciences, University of Galway, H91 TK33 Galway, Ireland.
National Cancer Institute, Mexico City 07760, Mexico.
J Clin Med. 2024 Aug 22;13(16):4967. doi: 10.3390/jcm13164967.
: Radiography is an essential and low-cost diagnostic method in pulmonary medicine that is used for the early detection and monitoring of lung diseases. An adequate and consistent image quality (IQ) is crucial to ensure accurate diagnosis and effective patient management. This pilot study evaluates the feasibility and effectiveness of the International Atomic Energy Agency (IAEA)'s remote and automated quality control (QC) methodology, which has been tested in multiple imaging centers. : The data, collected between April and December 2022, included 47 longitudinal data sets from 22 digital radiographic units. Participants submitted metadata on the radiography setup, exposure parameters, and imaging modes. The database comprised 968 exposures, each representing multiple image quality parameters and metadata of image acquisition parameters. Python scripts were developed to collate, analyze, and visualize image quality data. : The pilot survey identified several critical issues affecting the future implementation of the IAEA method, as follows: (1) difficulty in accessing raw images due to manufacturer restrictions, (2) variability in IQ parameters even among identical X-ray systems and image acquisitions, (3) inconsistencies in phantom construction affecting IQ values, (4) vendor-dependent DICOM tag reporting, and (5) large variability in SNR values compared to other IQ metrics, making SNR less reliable for image quality assessment. : Cross-comparisons among radiography systems must be taken with cautious because of the dependence on phantom construction and acquisition mode variations. Awareness of these factors will generate reliable and standardized quality control programs, which are crucial for accurate and fair evaluations, especially in high-frequency chest imaging.
放射摄影是肺部医学中一种重要且低成本的诊断方法，用于肺部疾病的早期检测和监测。足够且一致的图像质量对于确保准确诊断和有效的患者管理至关重要。本试点研究评估了国际原子能机构（IAEA）远程自动化质量控制（QC）方法的可行性和有效性，该方法已在多个成像中心进行了测试。2022年4月至12月收集的数据包括来自22个数字放射摄影设备的47个纵向数据集。参与者提交了关于放射摄影设置、曝光参数和成像模式的元数据。该数据库包含968次曝光，每次曝光代表多个图像质量参数和图像采集参数的元数据。开发了Python脚本以整理、分析和可视化图像质量数据。试点调查确定了影响IAEA方法未来实施的几个关键问题，如下：（1）由于制造商限制，获取原始图像存在困难；（2）即使在相同的X射线系统和图像采集中，图像质量参数也存在差异；（3）模体构建不一致影响图像质量值；（4）依赖供应商的DICOM标签报告；（5）与其他图像质量指标相比，信噪比（SNR）值变化较大，使得SNR在图像质量评估中不太可靠。由于对模体构建和采集模式变化的依赖，放射摄影系统之间的交叉比较必须谨慎进行。了解这些因素将产生可靠且标准化的质量控制程序，这对于准确和公平的评估至关重要，尤其是在高频胸部成像中。
