A common protocol of FE model generation was used as previously described.26 (link) In summary, DICOM data sets of 3 CT scans were segmented in MIMICS (MIMICS 16.0, Materialise; Leuven, Belgium) to export 3-dimensional (3D) models (Table 1 ). The available CT scans of 3 healthy neonates were taken at 3 different time stages adapted to the conventional initiation and treatment duration of presurgical period of NAM therapy: at date of birth, at 4 weeks, and at 3.5 months of age. On the basis of the 3D models of the healthy neonates (= original CT scan), 2 additional models each were virtually created, 1 with a small (~ 4.5 mm width) and 1 with a large (~ 12 mm width) cleft of the alveolar crest and hard palate in the models at 4 weeks and 3.5 months of age. In the newborn model, only a small cleft was simulated. Subsequently, the 3D models were exported to 3-MATIC (3-MATIC 8.0, Materialise; Leuven, Belgium) and smoothed, the area of applied forces was defined for each model separately and the applicable models were then meshed in ANSYS ICEM CFD (ANSYS 16.0, ANSYS Inc.; Pa.; Table 1 ). The virtual mesh of each model was again imported to MIMICS, and the bone density–dependent material properties were allocated. Finally, the 3D geometries were exported to ANSYS APDL (ANSYS APDL 16.0, ANSYS Inc.; Pa.) for FEA (Fig. 1 ).
3 matic 8
Manufactured by Materialise
Sourced in Belgium
3-matic 8.0 is a software product developed by Materialise for 3D modeling and engineering applications. It provides tools for mesh processing, design optimization, and additive manufacturing preparation. The core function of 3-matic 8.0 is to assist users in creating, modifying, and preparing 3D models for various manufacturing processes.
Automatically generated - may contain errors
Lab products found in correlation
3 protocols using 3 matic 8
1
Finite Element Modeling of Cleft Palate
2
Accuracy Assessment of Surgical Resection Planes
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Following the TKA resections, 3D scans were repeated on each knee insert. The digitized postresection bone surfaces were registered with the corresponding whole bone surfaces. In Unigraphics, 3D model of the instrument used for intraoperative bone resection check was virtually placed on each resected tibia and femur. Surgical resection planes were recreated from the bone-contacting plane of the checker instrument. The same set of surgical resection parameters (actual surgical parameters) were measured in the predefined anatomical referencing system using Geomagic software platform (Fig. 2B ). To assess the accuracy of the surface registration workflow, one tibia and one femur were selected from each deformity groups (neutral, varus, and valus). The surface distance error between each registered preoperative and postoperative bone surface pair was computed (3-matic 8.0, Materialise, Leuven, Belgium) and averaged across the 6 sampled bones. Both the mean surface distance (0.0007 mm) and its associated standard deviation (SD, 0.0037 mm) were found to be lower than the level of accuracy reported in this study (0.01 mm) (Fig. 3 ). The workflow was therefore confirmed to be sufficiently accurate.
3
Aortic Root Segmentation and Finite Element Mesh
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To extract the patient specific geometries, segmentation of the aortic root was performed on the pre-operative scans using Mimics 16.0 (Materialise N.V., Leuven, Belgium). The left ventricle and aorta were extracted from the CT images using a threshold on the contrast agent, as depicted in panel A of figure 1. The left ventricle and aorta were separated from connected structures and each other using a graph cut algorithm [Boykov and Kolmogorov, 2004] . 3-dimensional (3D) triangulated parts were created using a marching cubes triangulation (figure 1B). Smoothing was performed to remove noise and small substructures. Three leaflets were created starting from the left ventricle by smoothing and disconnecting the valve surface. Finally, the calcifications were extracted using a threshold above the intensity of the contrast agent and a region grow in the aortic root, followed by a marching cubes triangulation.
Based on the 3D triangulated surfaces, a finite element mesh was generated using 3-matic 8.0 (Materialise N.V., Leuven, Belgium). Triangular shell elements were used to model the aortic root and the leaflets (figure 1C). Four node linear tetrahedral elements were used to model the calcifications.
The calcifications were divided into separate volumes along the leaflet boundaries, as an approximation of the damage resulting from the balloon pre-dilation.
Based on the 3D triangulated surfaces, a finite element mesh was generated using 3-matic 8.0 (Materialise N.V., Leuven, Belgium). Triangular shell elements were used to model the aortic root and the leaflets (figure 1C). Four node linear tetrahedral elements were used to model the calcifications.
The calcifications were divided into separate volumes along the leaflet boundaries, as an approximation of the damage resulting from the balloon pre-dilation.
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