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Manual or auto-mode: Does this affect radiation dose in digital mammography without compromising image quality?

journal contribution
posted on 2023-07-06, 15:38 authored by D. Patidar, L. B. C. Yap, Hajmath Begum Mohamed Sali, Bao Lin Pauline SohBao Lin Pauline Soh

Introduction: In current practice, auto-filter exposure mode is used for most screening mammography examinations. However, with better understanding of the side effects of radiation, it is important to examine exposure parameters and practises to minimise radiation dose to patients. The purpose of this phantom study is to investigate the impact that different exposure modes (manual, auto-time and auto-filter) have on radiation dose, while maintaining images of diagnostic quality.

Methods: This study was conducted in three stages. In the first stage, 125 images were taken using a Gammex 156 phantom with polymethyl methacrylate blocks to reflect varying thicknesses (4.5, 5.0, 5.5, 6.0 and 6.5 cm). In the second stage, three mammographers independently assessed image quality and assigned scores based on the number of distinct fibers, masses and speck groups visible. Images with acceptable quality were further investigated in the third stage by comparing their average glandular dose (AGD) using the Kruskal–Wallis H test and Dunn's post-hoc pairwise analysis.

Results: Significant differences in AGD were shown between the auto-filter mode and manual mode techniques for 6.0 cm, and between auto-time mode and manual mode techniques for 6.5 cm (p < 0.05).

Conclusion: For 4.5, 5.0 and 5.5 cm phantoms, as AGD was not significantly different among the different modes, the auto-filter may remain the most practical option. However, significant reductions in AGD were obtained for the 6.0 and 6.5 cm phantoms when manual mode techniques were used.

Implications for practice: Manual mode techniques can potentially provide dose-saving opportunity in 6.0 and 6.5 cm breast thickness though future work on human breast should be done to confirm this. Results from this study will support future research based on patient data.


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