## 4 Discussion
Instead, it is likely a product of there being no exhaustive experimental research with sample sizes large enough to overcome the heterogeneity of individual LCR cases [17; 19; 30; 31]. Ultimately, there is considerable qualitative evidence that 3 DPLMs can optimise LCRs and permit more targeted resections, which minimise complications. This should increase the likelihood of postoperative success and reduce the chances of morbidity, implying that 3 DPLMs can directly improve LCR patients' surgical outcomes. A clear theme across the literature included in this review is the demand for methodologically rigorous, multi-institutional clinical trials to prove the clinical utility of 3 DPLMs in LCR surgical planning and intraoperative guidance [13; 15; 16; 17; 19; 30; 34; 35]. These trials must incorporate appropriate control groups and enrol sufficient patients to reach statistically significant conclusions [17; 19]. One such study has been developed by [PERSON] et al. [46] and is scheduled for completion during 2024. This type of research is crucial to progress 3 DPLM technology past its current 'proof-of-concept' phase. 3 DPLMs may also benefit patient outcomes by improving patients' understanding of their pathology and surgical intervention [22; 30; 31; 32; 35]. In a randomised controlled trial, [PERSON] et al. [30] demonstrated statistically significant improvements in LCR patients' surgical education when using 3 DPLMs (vs. education sheets). [PERSON] et al. [35] demonstrated statistically significant improvements in paediatric patients' parents' LCR understanding when consulted using 3 DPLMs (vs. CT images). The latter study's pre-test/post-test methodology likely confounds its results, but together these articles' findings are consistent with other literature examining the patient education value of 3D-printed models [47; 48; 49]. Improving patients' LCR knowledge using 3 DPLMs should enhance their participation in preoperative decision making and ability to provide informed consent [30]. Greater health literacy following 3 DPLM-based education may also improve their postoperative compliance, which then correlates positively with reduced length of hospital stay and decreased postoperative complications [30]. Although limited to gross specimens, 3 DPLMs may also benefit patients' postoperative diagnostic/staging outcomes by improving tumour imaging-pathology matching detection rate [34]. The 3 DPLMs demonstrated by articles in this review can be divided into four categories as demonstrated in Figure 4: (1) single/large-piece 3D-printed parenchyma/tumour model; (2) 3D-printed intrahepatic structures model (with/without 3D-printed parenchyma casing); (3) 3D-printed intrahepatic structures model and parenchyma mould with casted/transparent parenchyma; (4) and simulation-specific hollow models. Construction approach aside, 3 DPLM production begins with a patient's volumetric imaging data (typically CT or MRI) being post-processed (e.g., noise and blur reduction [12] and co-registration of multiphase CT volumes [13])/fusion of CT and MRI volumes [31]) and segmented to produce a 3D virtual liver/ intrahepatic structures model [12]. The current literature aligns with the previous findings of [PERSON] and [PERSON] [20], demonstrating the predominant use of CT imaging data compared to MRI for segmentation of the 3D rendered models. Although MRI provides high soft tissue contrast useful in evaluating focal liver lesions, it is utilised less frequently for 3 DPLM production due to its inferior spatial resolution and the limited availability of high-resolution 3T scanners [34]. CT is preferred, as its superior spatial resolution and ability to rapidly acquire contrast-enhanced images in multiple phases allows highly accurate and detailed delineation of intrahepatic vasculature while minimising patient motion artifacts [10]. This ultimately produces imaging datasets more conducive to accurate 3 DPLM production.