# Assessment of a Patient Dose Monitoring System for Average
## 4 Discussion
The heterogeneous distribution of glandular tissue is crucial to consider in AGD estimates, as regions with different levels of glandular density can lead to significant variations in results. Specifically, the normalized glandular dose coefficients (DgN) obtained using homogeneous breast models may not accurately reflect the reality of glandular tissue distribution, potentially causing dose overestimation or underestimation in different areas of the breast [38]. The use of heterogeneous mammographic phantoms, such as the three-layer heterogeneous phantoms (THEPs), could address this issue. The THEPs are designed to mimic the heterogeneous distribution of glandular tissue, with glandular fractions ranging from 25% to 75%. Monte Carlo simulations on these phantoms show that heterogeneous glandular distribution can alter DgN coefficients by 30-40%, depending on breast thickness and glandular tissue distribution [38]. Differences between uniform and heterogeneous glandular distributions were observed to be as much as 29% higher or lower, depending on the glandular tissue position in the breast. Therefore, adopting models that consider heterogeneous glandular distribution could improve dose estimates. Alternatively, a more precise determination of AGD could be achieved using experimental methods to derive glandular dose coefficients, such as by measuring spectral differences between incident and transmitted X-rays through breast phantoms with varying proportions of glandular and adipose tissue and different thicknesses [25]. This approach would allow the use of experimental X-ray spectra specific to the mammography system, rather than relying on theoretical models or simulations. However, implementing such experimental methodologies in clinical practice is challenging due to the complexity, costs, and advanced instrumentation required. Despite these challenges, using realistic models of glandular distribution derived from anthropomorphic phantoms or Monte Carlo simulations could significantly improve AGD estimates in mammography and other breast imaging techniques, such as digital breast tomosynthesis (DBT) or breast-dedicated CT (BCT) [39]. These models could help reduce AGD estimation errors, which have been shown to be overestimated by up to 21% when using homogeneous models [39]. However, experimental methodologies remain difficult to implement in clinical practice. As seen, current mean glandular dose calculation models have limitations due to oversimplified models of breast composition and imaging systems. In the past, simplifications were necessary to reduce the computational cost of obtaining dose conversion coefficients. However, with technological advances, a new breast dosimetry method based on new breast models has recently been developed and tested by the American Associationof Physicists in Medicine (AAPM TG282) and the European Federation for Organizations of Medical Physics (EFOMP) [40]. These models were derived from large patient datasets of fibroglandular density percentiles across the real population. Although the current study has limitations--mainly related to the analysis of mammographic images from a single manufacturer at one institution and the subdivision into two limited subgroups--it allows the conclusion that the AGD displayed by mammography systems and downloaded from DoseWatch is consistent when compared to independent AGD calculations using the Dance or Boone methods. In this regard, DoseWatch is a valuable tool for evaluating radiation doses received by patients, collecting AGD values from many images in just a few seconds, and enabling quick and easy comparisons and analyses.