Dose optimisation in paediatric radiography – Using regression models to investigate the relative impact of acquisition factors on image quality and radiation dose

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Abstract

Objective: To investigate the optimum pelvis X-ray acquisition factors for a 10-year-old child. Secondly, to evaluate the impact of each acquisition factor on image quality (IQ) and radiation dose. Method: Images were acquired using a pelvis phantom and a range of acquisition parameters; e.g. tube potential, additional filtration and source-to-image distance (SID). Automatic exposure control (AEC) was used with two orientations (head towards/away from two outer chambers) and three different chamber selections. Visual IQ was evaluated using relative and absolute-VGA methods. Radiation doses were measured by placing a dosimeter on the anterior surface of the phantom. Regression analysis was used to determine optimum parameters. Results: The optimised technique (178.8 µGy), with diagnostic IQ, was with 89kVp, 130 cm SID and with 1 mm Al + 0.1 mm Cu filtration. This technique was with the head towards the two outer AEC chambers. Regression analysis showed that SID had the lowest impact on IQ (β = 0.002 95% CI −0.001 to 0.005) and dose (β = −0.96 95% CI −0.40 to −1.53). The impact of filtration on dose (β = −76.24 95% CI −86.76 to −85.72) was higher than tube potential (β = −13.44 95% CI −14.34 to −12.53). The following impact ratios were higher on IQ than radiation dose: filtration/kVp; 11.28 times, filtration/SID; 7.01 times and kVp/SID; 0.62 times. Conclusion: Optimised parameters were identified as 89 kVp, 130 cm SID and with 1 mm Al + 0.1 mm Cu additional filtration. Regression analysis demonstrated that filtration and tube potential had the greatest effect on radiation dose and IQ, respectively.

Original languageEnglish
Pages (from-to)61-68
Number of pages8
JournalPhysica Medica
Volume68
DOIs
Publication statusPublished - Dec 2019
Externally publishedYes

Keywords

  • Digital radiography
  • Exposure factor impact
  • Paediatric dose reduction
  • Pelvis radiography
  • Regression analysis

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