A high-quality volume dataset with high resolution and no artefacts is required to allow for 3D printing. This can be acquired by common modern radiological imaging techniques provided that the proper reconstructions and protocols are applied. Computed tomography (CT) is the most common imaging modality providing image data for 3D printing in cardiac valve diseases (18 of 29 papers, 62%) [6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23], followed by US (8 papers, 28%) [9, 24,25,26,27,28,29,30], computer-generated models (computer-aided design) (2 papers, 7%) [31, 32], and magnetic resonance imaging (MRI) (1 paper, 3%) [34] (Fig. 2).
The quality of printed models is highly depending on the quality of the imaging dataset used. Cardiac motion and breathing artefacts have a negative impact on the segmentation and thus the printed volume. Typically, high-resolution scans are used in combination with electrocardiography gating, breath-hold, and/or respiratory gating [35]. In order to allow 3D printing of structures, they must have distinct tissue contrast in the imaging data [4].
In CT, commonly 0.75- to 1-mm slice thickness with a smoother kernel is used [4, 6, 35]. Scans with a higher resolution are less favourable since they introduce higher noise levels and require a more cumbersome segmentation process [35]. Some studies reported the use of multiphase acquisition during the cardiac cycle to ensure that the right phase can be reconstructed [20]. In MRI, standard cardiac imaging sequences can be used. However, the lower resolution of MRI in comparison with CT can hamper the production of good-quality 3D prints [35]. In US, the use of 3D scanning is required to obtain a proper 3D volume for segmenting the anatomical structures [24].
Regardless of the modality used to acquire the 3D datasets, structures of interest have to be segmented and translated into a surface model to enable 3D printing. Segmentation is the key process herein [33]. In some cases, the vessel wall is too thin to segment; extra thickness then should be added to the model since 3D printers have minimum thickness requirements [20].
The most commonly described tool for segmentation and creation of the STL file required for 3D printing is the Mimics/3-Matic software combination (Materialise, Leuven, Belgium). Secondly, SolidWorks (Dassault Systèmes SolidWorks Corporation, Vélizy-Villacoublay Cedex, France) is also used frequently. Less common are the 3D Slicer (Open source software package), AutoDesk Meshmixer (Autodesk, San Rafael, CA), and Vascular Modeling Toolkit (VMTK, Orobix, Bergamo, Italy).
All used packages have in common is that they allow to import the imaging data (according to the Digital Imaging and COmmunications in Medicine (DICOM) standard) from modalities such as CT, US, and MRI and transfer them to a 3D model. This model is realised by the segmentation of the structures of interest after which a surface representation is constructed. This surface reconstruction is commonly exported in STL format from the modeling software and loaded into the software of the 3D printer. This software allows to create and correct the model in order to ensure that it is printable and enables inclusion of required structures such as additional support material. After completion of the model, the data are resliced into print levels after which they can be sent to the printer to be manufactured.