12 H. Sekkat et al.: Radioprotection 2025, 60( 1), 9 – 19 The team starts by identifying critical exams and clinical tasks, establishing a baseline for patient doses. This includes precise dose measurements and image quality assessments based on set of reference criteria( IAEA, 2007). Radiologists evaluate image quality, while medical physicists measure patient doses using standard metrics and procedures. The results are compared with local or national DRLs or benchmarks, considering image quality evaluations( ICRP, 2017; IAEA, 2018). This analysis identifies exams needing optimization. Reviewing all protocols at one institution can be resource-intensive, requiring dedicated efforts of many person-day( IAEA, 2007, ICRP, 2017).
Misinterpretations of DRLs are common, with some assuming optimization is achieved if doses are below DRLs, potentially ignoring other important factors( Rehani, 2015). The optimization team must navigate these complexities when establishing DRLs for each procedure. Reference Levels( RLs) follow this rationale, allowing practitioners to compare patient doses for specific procedures to national or local RLs. This comparison helps assess and optimize radiation practices. The French Society of Medical Physics advocates using dose reference levels for systematic assessment and optimization( Greffier et al., 2017).
3.3.4 Computed tomography
Numerous articles in current literature propose a myriad of strategies for optimizing CT protocols, as evidenced by the wealth of advanced techniques discussed. These encompass tube modulation to dynamically adjust tube current based on anatomy, kV modulation customized to smaller size and younger patients, z-axis overscan for comprehensive coverage with minimized radiation exposure, scan length limitation to focus on clinically relevant anatomy, and the utilization of iterative reconstruction algorithms for improved image quality and potential dose reduction. Additionally, the incorporation of dual-energy imaging is outlined, particularly for contrastenhanced exams in patients with renal function concerns, offering diagnostic advantages while potentially lowering radiation dose. Furthermore, the integration of machine learning and artificial intelligence algorithms emerges as a promising avenue for personalizing CT protocols to individual patient characteristics and specific clinical scenarios. Collectively, these strategies represent cutting-edge developments in CT imaging, reflecting a commitment to achieving an optimal balance between diagnostic accuracy and patient safety( Eberhard et al., 2020; Greffier et al., 2020; El Mansouri et al., 2022, 2024; Nhila et al., 2023; Khallouqi et al., 2024; Sekkat et al., 2024).
3.3.5 Radiography
Traditional methods for optimizing radiographic imaging doses per examination involve techniques such as increasing kV, decreasing mAs by using AEC( automatic exposure control), reducing exposure time, ensuring appropriate positioning, and using collimation to focus on the specific body region clinically required( Körner et al., 2007; Talbi et al., 2022). The advent of digital radiology has expanded the potential for dose reduction due to the dynamic range of digital detectors. Digital images can be assessed using manufacturer-provided software or free tools like ImageJ, offering functions such as panning, zooming, grayscale inversion, distance and angle measurement, and windowing to enhance image appearance( Schindelin et al., 2015). Image processing, a key feature of digital radiography, significantly influences the visual representation of the image. However, during the transition to the digital environment, there is a potential for increased radiation dose, often attributed to a perceived lack of visual control( IAEA, 2015). Current advancements include image processing techniques and noise reduction algorithms, complementing traditional optimization strategies for achieving optimal radiographic imaging. Monitoring patient doses, using exposure indices or relevant dose quantities like the Kerma-Area Product( KAP), contributes to the optimization of radiographic procedures.
3.3.6 Mammography
Optimization is particularly important in mammography, especially for the early detection of breast cancer in asymptomatic women. Recent advancements, including breast tomosynthesis and contrast-enhanced mammography, have contributed to the expanded utilization of mammographic imaging. However, accurately estimating breast dose in the context of these emerging technologies remains a challenge. Notably, the introduction of ultra-low-dose craniocaudal images in digital mammography holds promise for the screening of a predominantly young and asymptomatic population. These ultra-low-dose images don’ t only meet the screening needs of this demographic but also serve as a foundational basis for further research in optimizing a lowdose approach, thereby contributing to the ongoing evolution of mammographic imaging practices( Bluekens et al., 2015; Talbi et al., 2022; Tahiri et al., 2024).
3.3.7 Fluoroscopy and interventional radiology
Even if contemporary X-ray angiography machines incorporate advanced technological features that hold potential for dose optimization, their utilization and impact on radiation dose necessitate clear comprehension by the users( Chambers et al., 2018).
A consistent theme across literature studies focusing on radiation protection in fluoroscopy is the acknowledgment that optimizing patient dose in interventional procedures results from an interconnection between modifying equipment protocols and influencing operator behavior, rather than merely altering protocol characteristics. Recommendations include the active utilization of digital processing, customizing examination protocols, selectively removing the antiscatter grid in specific clinical scenarios( e. g., spinal digital subtraction angiography), reducing pulse rate and frame rate, defaulting to low-level fluoroscopy mode, and implementing continuous dose monitoring alongside patient follow-up( Jones et al., 2014; Greffier et al., 2017; Chambers et al., 2018; Panick et al., 2018; Liu et al., 2019).
3.3.8 Aligning protocols with equipment functionality
Optimizing radiation dose through the modification of examination protocols is a complex task, requiring the expertise of a medical physicist. This process is undertaken collaboratively