Enhancing X-ray quality and dose reduction: Evaluation with additional filters, Contrast-Detail Phantom and Monte Carlo simulation

Abstract

Purpose:

In radiology, achieving high image quality while minimizing radiation dose exposure is essential. For these purpose, understanding the technical parameters affecting both dose and image quality is crucial.

Methods:

This study aimed to evaluate, through both experimental and computational approaches, different combinations of additional filters of 0.1, 0.2, and 0.3 mm Cu and equipment voltage (96 to 133 kVp) for one of the most commonly performed radiological examinations, the Posteroanterior (PA) chest X-ray. The objective was to determine the optimal trade-off between dose and image quality and define the best radiographic technique for this examination. This balance was achieved through Figures of Merit (FOM). Experimentally, image quality was quantified and evaluated using a method called the Image Quality Figure Inverse (IQFinv), obtained with the Contrast-Detail Phantom from the brand Artinis (CDRAD Phantom), and the dose was measured using the air kerma-area product ($P_{KA}$). The $P_{KA}$ values obtained were corrected through Monte Carlo simulations to estimate the patient dose. This was done for each combination of filter and kVp. Furthermore, these spectra were used to simulate the experimental setup to determine the energy deposited at the skin (0.07 mm) and at various depths within the phantom.

Results:

The experimental results demonstrated that the optimal trade-offs between image quality and radiation dose were achieved with the combinations of 96 kVp and 0.3 mm Cu and 102 kVp with 0.2 mm Cu. Compared to the routine protocol (109 kVp, 0 mm Cu), these techniques reduced $P_{KA}$ by approximately 13% and 12%, respectively, while improving IQF${}_{inv}$ by about 8% and 9%. Computational simulations reproduced the experimental results, showing that the best relationships between patient dose and image quality were achieved with the same techniques in both cases.

Conclusion:

Our results show that CDRAD Phantom and Monte Carlo simulations can be explored as a method that enables dosimetry in patients by representing real situations, thus allowing the selection of the correct radiographic technique (kVp and additional filtration). The correct selection of these technical parameters significantly reduces the patient’s dose while increasing image quality.