The 3D printing of patient-specific kidney models to facilitate pre-surgical planning of renal cell carcinoma using CT datasets

Catalina Lupulescu, Zhonghua Sun

Abstract

Background Three-dimensional (3D) printing in medicine is a rapidly growing field of research. This study endeavoured to investigate the feasibility of using 3D-printed kidney models for pre-surgical planning of renal cell carcinoma (RCC) resection and provide insight into medical 3D printing technologies and materials. Aims To enrich current research on applications of 3D printing for renal disease including training, education and pre-operative planning. Methods Three kidney models were 3D-printed from computed tomography (CT) datasets: two of which were from the same clinical case. The models were CT scanned on a 192-slice scanner using exposure factors for an abdominal CT. Quantitative analysis was performed by measuring and comparing four critical anatomical structures on the model CT, original CT dataset and Standard Tessellation Language (STL) file. Qualitative assessment of the models was achieved through an interactive survey-questionnaire presented to 5 urologists. The models were also ultrasound scanned to generate insight into their uses in radiographic imaging. Results The 3D-printed models displayed no significant differences between the original CT and model CT (p>0.05). The STL file measurements were significantly larger than the original and model CT measurements for models 2 and 3 (p=0.000-0.005). All 5 urologists agreed that the 3D-printed models could facilitate pre-surgical planning and serve educational purposes to clinicians and patients with RCC. The ultrasound scans of the models demonstrate potential for radiographic imaging using realistic 3D-printed models, showing the importance of material considerations. Conclusion 3D-printed kidney models can facilitate pre-operative planning for renal surgery and education. Further studies utilising diverse clinical cases and a cost-benefit analysis of material feasibility are required to better assess the applications envisioned.
Full Text: PDF