Systematic Review: Development of Computed Tomography Technology to Reduce X-ray Exposure (2020-2025)
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…
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Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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