Contemporary Strategies for Radiation Dose Optimization in Computed Tomography: Balancing Diagnostic Image Quality and Radiation Exposure

Background: Computed tomography (CT) is an essential imaging modality because of its rapid data acquisition, high spatial resolution, and broad clinical applications. However, increasing utilization has raised concerns regarding radiation exposure and its potential risks. Radiation dose optimization is therefore essential to achieve diagnostically adequate image quality while minimizing patient exposure. This review critically synthesizes current strategies for optimizing radiation dose in CT, focusing on acquisition parameters, patient-size-based dose adjustment, image reconstruction, artificial intelligence (AI), photon-counting CT (PCCT), pediatric imaging, image quality, and dose quantification.  

Methodology: A literature review was conducted using PubMed, Scopus, ScienceDirect, and Google Scholar, covering publications from January 2010 to August 2026. Of 300 identified articles, 42 duplicates were removed. Following title and abstract screening, 258 articles remained, of which 84 underwent full-text assessment. Ultimately, 70 articles were included in the review.

Conclusion: CT radiation dose optimization requires protocol optimization, appropriate patient-size adjustment, advanced reconstruction techniques, and clinical awareness. AI-based reconstruction and PCCT offer promising opportunities to improve dose efficiency while maintaining diagnostically acceptable image quality.