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Comparison of Virtual Dose Simulator and K-Factor Methods for Effective Dose Assessment in Thoracic CT
1Groupe Biomédical Montérégie, Centre Intégré de Santé et des Services Sociaux de la Montérégie-Centre, Brossard, QC J4W 3J8, Canada.
None:
Rationale and Objective: Medical imaging, particularly computed tomography (CT), is the largest man-made contributor to collective radiation exposure. This study compares methods for assessing CT radiation dose, focusing on thoracic examinations. Population investigated: We retrospectively analyzed 3956 non-contrast thoracic CT exams from 1553 females (mean age 70 ± 12 years) and 2403 males (mean age 69 ± 12 years). Methods: Data were acquired using a Siemens Somatom Force CT-Scanner (installed in 2015). Exposure parameters and patient somatic data were recorded and used as inputs for the Virtual Dose Simulator (VDS), which served as the gold standard for effective dose (EDref) measurement. Additionally, ED was calculated using two ICRP-103 K-factor methods: Shrimpton et al. (EDshr) and Romanyukha et al. (EDrom). Results: Regression analysis demonstrated strong linear relationships between EDref and both weight and BMI (R2 ≥ 0.84), with EDref values ranging from 1.55 to 4.59 mSv. Even stronger linear relationships were observed between EDref and CT scanner tube current, particularly for women (R2 = 0.93) and men (R2 = 0.90). Similar trends emerged for dose-length product (DLP), which showed high correlations for both women (R2 = 0.95) and men (R2 = 0.94). Compared to VDS, EDrom underestimated women's doses by 10% and slightly overestimated men's doses by 1%, while EDshr underestimated the effective dose by 18% for women and 9% for men. Conclusion: This study demonstrates that K-factor methods provide a simple, efficient, and clinically practical approach for both individual cumulative dose monitoring (critical for patients requiring repeated imaging) and population-level dose assessment (essential for epidemiological risk evaluation). The high reliability of K-factor-based estimates, as demonstrated in this work, underscores their potential for integration into clinical practice to enhance dose optimization and patient safety.
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