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International Journal of Bioprinting Flexible 3D printing in cardiovascular medicine

and clinical purposes , and their suitability for numerous high grade of detail and to prevent the formation of steps
1-4
clinical scenarios has been graded in several guidelines . when reconstructing the 3D model. The Digital Imaging
5-7
In contrast to two-dimensional (2D) images and and Communications in Medicine (DICOM) images were
digital volumetric renderings from computed tomography exported from our picture archiving and communication
(CT) and magnetic resonance imaging (MRI) datasets system (PACS), and all patient identifiers were irreversibly
displayed on 2D computer screens, 3D-printed models removed. A positive ethics vote was obtained from the
that are fabricated from the same data are able to provide institutional review board (IRB-No.: 1004/2020).
a patient-specific understanding of anatomy and spatial 2.2. Segmentation and post-processing
relationships, and they are a step closer toward better When 3D printing based on medical image data, a
personalized medicine and individualized patient care . software is required for segmentation and 3D post-
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In the field of cardiovascular surgery and interventional processing to create a printable stereolithography (STL)
radiology (IR), vascular 3D printing is a technical file. In this study, segmentation was done cost-effectively
challenge, especially when considering the complexity of with a freely available open-source software, ImageJ
vascular anatomy in addition to a large variety of available (version 1.53, Laboratory for Optical and Computational
10
3D printing technologies and materials . Finding a 3D Instrumentation, University of Wisconsin) , while 3D
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printing material with properties similar to biological post-processing was done with Blender (version 3.0,
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tissues, which is ideally elastic and transparent, to simulate Blender Foundation) . The CTA data were imported in
interventional procedures without the use of radiation ImageJ, and the inner lumen of the contrast-enhanced
is one of the greatest challenges thus far. Silicone or arteries was segmented using the “Window/Level” tool.
silicone-like materials seem to be ideal for this purpose, Structures with similar Hounsfield units, like bones, were
but they are not available for direct model fabrication with still included at this time point. In order to clear the stack
end-user 3D printers. Therefore, creating such models from surrounding bones, the “Region of Interest (ROI)
was managed amid complex, time- and cost-intensive Manager” tool was used. Instead of defining the ROIs
workarounds, particularly silicone molding. However, slice by slice, ROI interpolation was done to accelerate
with the introduction of novel liquid resins, this issue has and simplify the segmentation workflow. All structures
been solved, enabling direct production of complex hollow outside the borders of the defined ROIs, including the
vascular structures with low-cost stereolithography (SLA) surrounding structures, such as bones, were removed by
3D printing based on the imaging data of individual patients using a simple macro as defined in Table 1. Based on the
with high level of detail and accuracy. SLA technology segmented DICOM stack, the STL file was generated using
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allows the fabrication of models without internal support the integrated and freely available 3D-Viewer plugin .
structures at printing resolutions of 50 to 100 μm, which is After being imported into Blender, the STL object was
essential for printing vessels with small luminal diameter. cleared from residual non-vascular structures. Modifiers
In an appropriate simulation setting, these vascular models were used to smooth the vessels and generate vessel walls
can be connected to a circulatory system with a peristaltic with wall thickness of 1 mm. The endings of the aorta
water pump for patient-specific, endovascular procedure and procedure-relevant arteries were digitally cut open.
simulations for both, training purpose and interventional The segmentation and 3D post-processing workflow is
procedure planning. summarized step-by-step in Table 2.
In this study, we present our manufacturing workflow
of case-specific vascular 3D printing with flexible Table 1. Simple ImageJ macro for removing non-vascular
structures using the ROI Manager
and transparent resin as well as demonstrate various
applications in an illustrative case series. n = roiManager(“count”);
for (i=0; i<n; i++)
2. Materials and methods {
roiManager(“select”, i);
2.1. Image acquisition setBackgroundColor(0, 0, 0);
Vascular models were fabricated from preprocedural CT run(“Clear Outside”, “No”);
angiography (CTA) scans (Somatom Definition Edge }
Plus, Siemens, Germany) using a bolus of 120 mL non- Especially in the abdomen, the spine can be in direct contact with the
ionic contrast media at an injection rate of 3.5 to 5mL/s. aorta via lumbar arteries, which causes difficulties in segmentation,
as vascular structures and bones might fuse to one object. Using the
An arterial phase was acquired with a delay of 30 s ROI Manager in ImageJ, this macro automatically removes everything
following contrast injection. Axial reconstructions with outside the ROI on each slice of the stack. The macro can be saved as
thin slices of 1-mm thickness were generated to ensure a ClearOutsideMacro.ijm and installed via Plugins → Macro → Install.

Volume 9 Issue 2 (2023) 307 https://doi.org/10.18063/ijb.v9i2.669