## 4 Discussion
### Optimising CT Protocols for Lung Nodule Detection  
This study reveals that a low-dose CT protocol of 80 kVp, 30 mAs with ADMIRE 3 (0.23 mSv effective dose) is a potentially viable option for the good diagnostic ability of lung nodules on CT scans. These findings are in agreement with [PERSON] et al. 's study \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Author/Study** & **Phantom** & **Cost (AUD)** & **Time (h)** &
\begin{tabular}{c} **Radiation Equivalence Relative to** \\ **Patient/Human Norms** \\ \end{tabular} \\ \hline
[71] & Heart & 110 & 12.1 & Maximum error of 8\% (27 HU) \\ \hline
[72] & Coronary arteries & 70 & 7 & Maximum error of 15\% (61 HU) \\ \hline
[73] & Skeletal thorax & N/P & 120 & \(-8.8\%\) to 1.6\% error (maximum 19 HU) \\ \hline
[19] & Lung, fat, muscle, bone, vessels, nodules & 450 & 72 & \(-7\%\) to \(-1772\%\) error (maximum 505 HU) \\ \hline
[74] & Lung shell, bone, airway, lung vessels, nodules & 5450 & N/P & \(-28.6\%\) to 124\% error (maximum 221 HU) \\ \hline
[75] & Lung and vessels & few hundred & N/P &
\begin{tabular}{c} 11.43\% to 2000\% \\ (maximum 99 HU) \\ \end{tabular} \\ \hline
[49] &
\begin{tabular}{c} 3D-printed replica of an axial slice \\ from a commercial phantom \\ \end{tabular} & 64 & 58 & Maximum error 160 HU \\ \hline
[58] & Axial slice of skeletal thorax, lung, soft tissue, heart, oesophagus & 250 & 120 & 22.5-63\% error (maximum 451 HU) \\ \hline  & This study & 527 & 1178.5 & \(-331\%\) to 8\% error (maximum \(-196\) HU) \\ \hline \hline \end{tabular} Abbreviations: N/P, not provided.  
\end{table} 
Table 6: Comparisons of 3D-printed chest phantoms. that concluded that 80 kVp, 30 mAs (0.072 mSv) provides sufficient diagnostic capability for detection of lung nodules in an Alderson Rando phantom [13]. However, our study provides more weight to these findings due to the incorporation of pulmonary vessels that are absent from commercial phantoms. Nevertheless, the relatively high contrast of nodules to lung background is still considered a limitation of this study due to the inability to reproduce the smaller peripheral lung vessels (Figure 6). Thus, there appears less \"anatomical noise\" within the constructed phantom compared to the patient. The small branched peripheral vessels were not able to be printed due to limitations of the resin material. The flexible and flimsy material could not withstand the pressures of the printing process and forces involved from removing the support material. Future studies can use more robust material or, alternatively, use traditional moulding techniques to create the lung vessels. The correlation between objective image quality and dose reduction was strong (Figures 10 and 12). This reveals a trade-off between radiation protection and image quality, causing reduced SNR and CNR. However, despite the reduction in SNR and CNR associated with the reduced effective dose, this did not affect the subjective visual perception of lung nodules by the radiologists, with median radiologist scores averaging 4, indicating good diagnostic confidence. Despite the interrater agreement being very low (\(\kappa=-0.398\), 95% CI [\(-0.644\) to \(-0.152\)], \(p<0.002\). ), all radiologists scored at least 3 for all scans, which indicates acceptable diagnostic confidence. The disagreement between scoring may be due to differences in subjective interpretation of the Likert scale, lack of clarity in understanding the scale, or differences in expertise between the radiologists. Objective changes in image quality of SNR and CNR may not be perceptible by the human eye [76]. This affirms the ability and responsibility of radiographers to reduce radiation exposures in order to limit dose to patients, regardless of degradation to image quality, as long as the diagnostic capacity is maintained [77]. Lowering radiation dose is feasible for lung cancer screening due to the high intrinsic contrast between air and pulmonary structures [15]. Nevertheless, [PERSON] et al.