Advanced strategies for the fabrication of multi-material anatomical models of complex pediatric oncologic cases

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Abstract

The printing and manufacturing of anatomical 3D models has gained popularity in complex surgical cases for surgical planning, simulation and training, the evaluation of anatomical relations, medical device testing and patient–professional communication. 3D models provide the haptic feedback that Virtual or Augmented Reality (VR/AR) cannot provide. However, there are many technologies and strategies for the production of 3D models. Therefore, the aim of the present study is to show and compare eight different strategies for the manufacture of surgical planning and training prototypes. The eight strategies for creating complex abdominal oncological anatomical models, based on eight common pediatric oncological cases, were developed using four common technologies (stereolithography (SLA), selectie laser sinterning (SLS), fused filament fabrication (FFF) and material jetting (MJ)) along with indirect and hybrid 3D printing methods. Nine materials were selected for their properties, with the final models assessed for application suitability, production time, viscoelastic mechanical properties (shore hardness and elastic modulus) and cost. The manufacturing and post-processing of each strategy is assessed, with times ranging from 12 h (FFF) to 61 h (hybridization of FFF and SLS), as labor times differ significantly. Cost per model variation is also significant, ranging from EUR 80 (FFF) to EUR 600 (MJ). The main limitation is the mimicry of physiological properties. Viscoelastic properties and the combination of materials, colors and textures are also substantially different according to the strategy and the intended use. It was concluded that MJ is the best overall option, although its use in hospitals is limited due to its cost. Consequently, indirect 3D printing could be a solid and cheaper alternative.

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Valls-Esteve, A. [et al.]. Advanced strategies for the fabrication of multi-material anatomical models of complex pediatric oncologic cases. "Bioengineering", 1 Gener 2024, vol. 11, núm. 31.

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2306-5354

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