## 4 Discussion
### Optimising CT Protocols for Lung Nodule Detection
[78] suggest that clinicians may be hesitant to reduce exposure parameters to ultra-low levels, despite the feasibility of producing acceptable image quality with such low radiation levels. However, it is possible that a reduction of image quality may interfere with the diagnostic potential of smaller sub-solid lung nodules, which have lower contrast detectability [76]. Future studies should explore further reductions in kVp and mAs and detection of smaller subsolid nodules to establish the threshold where noise begins to interfere with diagnostic ability. Our findings suggest that it is potentially feasible to achieve accurate lung nodule detection using radiation doses lower than those currently applied in national lung cancer screening programs [79]. For instance, the American National Lung Cancer Screening Program uses 120-140 kVp with 40-80 mAs, delivering approximately 1.5 mSv per scan [3], which is 85% higher than the dose proposed in this phantom study. This demonstrates the potential to reduce patient exposure by 85% in clinical settings using our optimised protocol. However, these significant dose reductions may lead to some smaller nodules being undetected, although, if these nodules are benign, this could decrease false positive rates, alleviating associated stress and the need for follow-up testing. As Australia plans to implement its own lung cancer screening program in 2025 [80], these results, along with similar research, could provide valuable guidance in selecting optimal CT protocols for lung nodule detection. However, a more accurate phantom with all tissues validated to match the patient's HU, is essential before applying it reliably in clinical settings. This study has several limitations. First, the alveoli and lung parenchyma were not replicated. Currently, no material exists in the literature that can accurately mimic the delicate structure of lung parenchyma whilst maintaining low HU for aerated lungs [22]. Secondly, large air gaps were present between phantom tissue layers, resulting from the poor adhesion of the superglue. However, replicating the extensive connective tissue network that binds human tissues at the cellular level would be a significant challenge. Additionally, some discrepancies in the size of printed anatomical parts were evident. For instance, the ribs were too short to connect to adjacent structures, and the skin was undersized, leaving large gaps between sections. These issues stem from the inherent limitations of FDM printing, such as material shrinkage and warping after cooling [22]. To address these shortcomings, future studies could explore printing with more flexible materials, allowing for better moulding to the anatomy. Another challenge was the labour-intensive manual removal of support materials and assembly of individual parts, which may have introduced slight positional variations that accumulated during each attachment. Printing larger anatomical components in a single print may help reduce these inconsistencies. However, in certain instances, dividing the printed objects into smaller constituents is necessary in order to integrate different tissues together. For example, the scapulae were excluded from the phantom due to difficulties inserting their complicated shapes within the surrounding muscle layers. Had they been printed in multiple parts, compilation with the muscle layer may have been possible. Alternatively, multi-nozzle, multi-material printers can integrate heterogeneous material layers in a single print, albeit at a significant cost [81]. Furthermore, we acknowledge the limited external validity of the proposed optimum protocols, as they are primarily applicable to patients with similar body weight and habitus to the one used in developing the phantom. Finally, as a phantom-based study, this model could not replicate the intricate complexities of a living human subject. For example, the functional dynamics of a beating heart or the respiratory motion of the diaphragm and lungs were not simulated.