Systematic Review: Development of Computed Tomography Technology to Reduce X-ray Exposure (2020-2025)
Article Information
Publication Timeline
- Received05 October 2025
- Accepted11 November 2025
- Published
Abstract
Background: Radiation exposure from computed tomography (CT) remains a significant concern in medical imaging, prompting continuous technological innovation to optimize dose reduction while maintaining diagnostic image quality. This systematic review synthesizes recent developments in CT technology for radiation dose reduction from 2020 to 2025.
Objective: To systematically review and analyze technological advancements in CT imaging that reduce X-ray radiation exposure, evaluate their clinical effectiveness, and identify future research directions.
Methods: A comprehensive literature search was conducted across four major databases (SciSpace, PubMed, Google Scholar, and full-text repositories) for publications from January 2020 to November 2025. Search terms included combinations of “computed tomography,” “CT,” “radiation dose reduction,” “dose optimization,” “low dose,” and related technological terms. Studies were included if they reported on technological innovations for CT dose reduction with quantitative outcomes. A total of 99 unique papers were identified, combined, and reranked by relevance.
Results: Three primary technological tracks emerged: (1) Advanced reconstruction algorithms (iterative reconstruction and deep learning-based methods) achieving 36-89% dose reductions; (2) Photon-counting detector CT (PCCT) providing superior image quality at significantly lower doses compared to conventional energy-integrating detectors; (3) Optimized acquisition techniques including automatic exposure control, tube current modulation, and spectral shaping with tin filters achieving up to 89% dose reduction in specific protocols. Real-world clinical implementations demonstrated CTDIvol reductions up to 82% and DLP reductions up to 83.9% while maintaining or improving diagnostic accuracy.
Conclusions: Substantial progress has been made in CT dose reduction through convergent advances in reconstruction algorithms, detector hardware, and acquisition strategies. Deep learning reconstruction and photon-counting detectors represent paradigm shifts with proven clinical benefits. However, challenges remain in external validation, standardization across vendors, and task-specific optimization. Future research should focus on prospective multicenter trials, standardized benchmarking protocols, and integrated AI-driven dose optimization systems.
Keywords
Computed tomographyradiation dose reductioniterative reconstructiondeep learningphoton-counting detectordose optimizationmedical imaging technologyReferences
- Ungania S, Solivetti FM, D’Arienzo M, et al. Reducing radiation dose in computed tomography imaging of adolescent idiopathic scoliosis using spectral shaping technique with tin filter. Tomography. 2023;11(10):110. doi:10.3390/tomography11100110. [Google Scholar][Crossref]
- Alagic Z. New developments in computed tomography: low dose techniques, image reconstruction, and spectral imaging. 2024. doi:10.69622/25975000.v1. [Google Scholar][Crossref]
- Theek B, Nolte T, et al. Emerging methods in radiology. Radiologe. 2020;60(11). doi:10.1007/S00117-020-00696-0. [Google Scholar][Crossref]
- Russo E, Stucchi E, Carlucci E, et al. Clinical implementation of AI for CT dose optimization and diagnostic reliability in oncology: a real-world evaluation. J Adv Health Care. 2025;7. doi:10.36017/jahc202574469. [Google Scholar][Crossref]
- Kang Z, Li X, Zhou S. Recommendation of low-dose CT in the detection and management of COVID-2019. Eur Radiol. 2020;30. doi:10.1007/S00330-020-06809-6. [Google Scholar][Crossref]
- Ng CKC. Artificial intelligence for radiation dose optimization in pediatric radiology: a systematic review. Children (Basel). 2022;9(7):1044. doi:10.3390/children9071044. [Google Scholar][Crossref]
- Ungania S, Solivetti FM, D’Arienzo M, et al. New-generation ASiR-V for dose reduction while maintaining image quality in CT: a phantom study. Appl Sci. 2023;13(9):5639. doi:10.3390/app13095639. [Google Scholar][Crossref]
- Woeltjen MM, Niehoff J, Michael AE, et al. Low-dose high-resolution photon-counting CT of the lung: radiation dose and image quality in the clinical routine. Diagnostics. 2022;12(6):1441. doi:10.3390/diagnostics12061441. [Google Scholar][Crossref]
- Dieckmeyer M, Sollmann N, Kupfer K, et al. Computed tomography of the head. Clin Neuroradiol. 2023;33. doi:10.1007/s00062-023-01271-5. [Google Scholar][Crossref]
- Adelodun MO, Anyanwu EC. Environmental and patient safety: advances in radiological techniques to reduce radiation exposure. Int J Front Med Surg Res. 2024;6(1). doi:10.53294/ijfmsr.2024.6.1.0040. [Google Scholar][Crossref]
- Lin X, Zhuo W, Liu H, et al. Potential of fluid dynamic bowtie filter for dose reduction and image quality improvement of cone-beam CT. Appl Sci. 2022;12(18):9346. doi:10.3390/app12189346. [Google Scholar][Crossref]
- Russo E, Stucchi E, Carlucci E, et al. Clinical implementation of AI for CT dose optimization and diagnostic reliability in oncology: a real-world evaluation. J Adv Health Care. 2025;7. doi:10.36017/jahc202574469. [Google Scholar][Crossref]
How to Cite
Saeed, R. R. (2025). Systematic Review: Development of Computed Tomography Technology to Reduce X-ray Exposure (2020-2025). International Journal of Medical and All Body Health Research, 6(4), 137-150. https://doi.org/10.54660/IJMBHR.2025.6.4.137-150
Saeed, Rana Riyadh. "Systematic Review: Development of Computed Tomography Technology to Reduce X-ray Exposure (2020-2025)." International Journal of Medical and All Body Health Research, vol. 6, no. 4, 2025, pp. 137-150. https://doi.org/10.54660/IJMBHR.2025.6.4.137-150.
Saeed, R. R. (2025) 'Systematic Review: Development of Computed Tomography Technology to Reduce X-ray Exposure (2020-2025)', International Journal of Medical and All Body Health Research, 6(4), pp. 137-150. doi: 10.54660/IJMBHR.2025.6.4.137-150.
Saeed RR. Systematic Review: Development of Computed Tomography Technology to Reduce X-ray Exposure (2020-2025). International Journal of Medical and All Body Health Research. 2025;6(4):137-150. doi:10.54660/IJMBHR.2025.6.4.137-150
Similar Articles
- Morphometry of the Lumbar Pedicle: A Computed Tomography-Based Study with Implications for Pedicle Screw Fixation Vol 7, Issue 3 (2026)
- HRCT Findings in Pulmonary Tuberculosis: Predicting Disease Activity Through Radiological Assessment Vol 7, Issue 1 (2026)
- Role of Computed Tomography of the Chest in Differentiating Cardiogenic and Non-Cardiogenic Pulmonary Edema Vol 7, Issue 1 (2026)
- Comparative Analysis of Thoracic Ultrasound and Contrast-Enhanced CT in Diagnosing Pleural Empyema: A Cross Sectional Study Vol 6, Issue 3 (2025)
- Evaluation of Role of Computed Tomography in Acute Abdomen: A Comprehensive Clinical Analysis Vol 6, Issue 3 (2025)
Find this Article on
Google Scholar Semantic Scholar OpenAlex Scilit Crossref ResearchGate BASEA newly published article may take a few days to appear on these services.