Toward Emulating Human Movement: Adopting a Data-Driven Bitmap-Based "Voxel" Multimaterial Workflow to Create a Flexible 3D Printed Neonatal Lower Limb

• Published in: 3D printing and additive manufacturing Vol. 9; no. 5; pp. 349 - 364
• Main Authors: Guy, Bernard Joseph, Morris, Ana, Mirjalili, Seyed Ali
• Format: Journal Article
• Language: English
• Published: United States Mary Ann Liebert, Inc., publishers 01.10.2022
• Subjects: Original; workflow; additive manufacture; voxel; bitmap; medical 3D printing
• ISSN: 2329-7662; 2329-7670
• DOI: 10.1089/3dp.2021.0256

It is increasingly common to produce physical anatomical medical models using high-fidelity multiproperty 3D printing to assist doctor-patient communication, presurgical planning, and surgical simulation. Currently, most medical models are created using image thresholding and traditional mesh-based segmentation techniques to produce mono-material boundaries (STL file formats) of anatomical features. Existing medical modeling manufacturing methods restrict shape specification to one material or density, which result in anatomically simple 3D printed medical models with no gradated material qualities. Currently, available high-resolution functionally graded multimaterial 3D printed medical models are rigid and do not represent biomechanical movement. To bypass the identified limitations of current 3D printing medical modeling workflows, we present a bitmap-based "voxel" multimaterial additive manufacturing workflow for the production of highly realistic and flexible anatomical models of the neonatal lower limb using computed tomographic ("CT") data. By interpolating and re-slicing a biomedical volumetric data set at the native 3D printer resolution of 27 μm and using CT scan attenuation properties (Hounsfield units) to guide material mixing ratios, producing highly realistic models of the neonatal lower limb at a significantly faster rate than other manufacturing methods. The presented medical modeling workflow has considerable potential to improve medical modeling manufacturing methods by translating medical data directly into 3D printing files aiding in anatomical education and surgical simulation practices, especially in neonatal research and clinical training.