## 1 Introduction  
Lung cancer is the leading cause of cancer-related deaths worldwide [1]. Its notoriety can be attributed to the delayed presentation of symptoms, with early manifestations of lung nodules being undetected [2]. Lung cancer screening trials have revealed that annual low-dose CT (LDCT) can improve early detection rates and hence survival from lung cancer by 20-30% compared to planar chest X-rays in high-risk individuals [2; 3; 4]. However, some countries are hesitant to adopt national lung cancer screening programs using LDCT due to the risks associated with repetitive exposure to higher levels of ionising radiation in a screening forum [5]. Although LDCT delivers approximately 1.5 mSv per examination, which is lower than the 8 mSv range of regular CT scans, the cumulative dose from annual screenings may equate to or even exceed typical CT radiation levels, elevating the risk of carcinogenic effects [6]. With the recent advancements in CT technology [7], studies have explored the potential to reduce dose to levels comparable to that of conventional chest X-rays, in the range of 0.06-0.10 mSv [8], whilst maintaining adequate image quality for the detection of lung nodules [5; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18]. These submillisievert scans are termed \"ultra-low-dose-CT\" (ULDCT). For example, [PERSON] et al. [5] utilised a porcine phantom with artificial lung nodules to investigate low-dose and ULDCT protocols. They reduced tube voltage by capitalising on using advanced-modelled iterative reconstruction (ADMIRE), an algorithm which retrospectively modifies data to suppress noise. Additionally, tin filtering was used to shape high energy spectra for an efficient, lower-dose beam. Consequently, they suggested that an ULDCT protocol is feasible for lung nodule detection by applying 100 kVp with tin filtering, delivering a mere 0.1 mSv effective dose. Similarly, [PERSON] et al. [11] used iterative reconstruction (IRIS, Siemens, Healthineers, Germany) on a commercial N1-LUNGMAN phantom and concluded that 80 kVp with 6 mAs was adequate for nodule visualisation. Likewise, by manipulating tube voltage and current, [PERSON] et al. [13] concluded that an ULDCT protocol of 80 kVp and 30 mAs in a commercial Alderson Rando phantom was viable for nodule detection, giving an effective dose of 0.072 mSv. The indication that lung nodule detection is possible with radiation exposures equivalent to chest X-rays justifies the potential benefits of participating in LDCT screening programs, where the advantages may outweigh the risks. However, these studies predominantly investigated low-dose protocols using commercial phantoms or simplistic block slabs, which have been criticised for being unrealistic, too generic, not patient-specific, and exorbitantly expensive, costing in the range of AUD 30,000-40,000 [19; 20]. Furthermore, their homogeneous composition of lung parenchyma, without inclusion of lung vessels, creates enhanced contrast that makes lung nodules easier to visualise compared to what would be their appearance within realistic, heterogeneous, multi-cellular human anatomy. Therefore, a more realistic representation of a human chest is warranted to more reliably study low-dose protocols for lung nodule detection. Three-dimensional (3D) printed phantoms are increasingly utilised as more realistic alternatives for representing human anatomy [21], with many researchers creating chest phantoms for radiological applications [22]. In their study, [PERSON] et al. [19] 3D printed a thoracic model using fused-deposition modelling (FDM), whereby thermoplastic filament is melted through a heated nozzle and deposited layer-by-layer on a printing bed. Despite replicating the human lungs, nodules, vessels, bones, muscle, and fat, their model was not radiation-equivalent. Currently, [PERSON] et al.