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33 protocols using mimics innovation suite

1

Computed Tomography-Guided Maxillectomy Planning

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Computed tomography (CT) scans of all cadaver heads were performed via a 64-slice CT scanner (Siemens 64 slice; Siemens Medical Solutions, Malvern, Pennsylvania) and imported into a DICOM image processing software (Mimics Innovation Suite, Materialise, Leuven, Belgium). Following the procedure described by Lascelles et al. (19 (link)), five osteotomy cuts were defined to complete a caudal maxillectomy with ventral orbitectomy, (1) zygomatic cut, (2) rostrolateral cut, (3) dorsolateral cut, (4) palatine cut, and (5) orbital rim cut. The skulls were thresholded, segmented, and virtual osteotomy cuts were planned in 3-Matics software (Mimics Innovation Suite, Materialise, Leuven, Belgium) (see Figure 1).
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2

Preoperative MRI and CT Imaging for Personalized Total Knee Arthroplasty

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Preoperatively, MRI scans were obtained for all patients according to the standard Signature scanning protocols and sent to the manufacturing company (Materialise NV, Leuven, Belgium) for further processing. Standard procedures were followed according to the Signature MRI total knee system (Biomet, Inc., Warsaw, Indiana, United States). MRI images were converted to virtual 3D models (Mimics, Materialise NV, Leuven, Belgium), anatomical landmarks were selected for definition of the coordinate system and a virtual planning was developed and proposed to the surgeon (Biomet Signature Planner, Materialize NV, Leuven, Belgium). The Signature software allows modifications of implant size, resection level and component orientation in the coronal, sagittal and axial planes. A default planning was proposed to the surgeon who made changes where needed and gave his final approval.
Additionally, each patient had a pre-operative full leg CT-scan. CT-images were segmented (RMS (root mean square) error of 0.55 mm [22] (link)) using the Mimics Innovation Suite (Materialise NV, Leuven, Belgium). The CT-scans were not used for surgical planning, but were required additional measurements for the post-processing of the data, to be able to link the post-operative CT-based model more reliable to the pre-operative MRI-based model for the accuracy assessment of component positioning.
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3

Postoperative Assessment of Implant Alignment

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Postoperatively (average 46 days, range 31-81 days), a full leg CT scan was obtained for all patients using the same scanning protocol as preoperatively to calculate the differences between the preoperative plan and postoperative measurements. Three dimensional virtual bone models were derived from the Signature planning and postoperative CT images using the Mimics Innovation Suite (Materialise NV, Leuven, Belgium). First, CAD (computer aided design) models of the implanted components were superposed on their segmented postoperative counterparts. Second, the postoperative CT bone models were registered on the preoperative CT bone models using an iterative closest point (ICP) algorithm. Similarly, the pre-operative CT bone models were registered on the Signature planning models using the same method and manually transformed to the same coordinate system as used preoperatively to perform the planning. The same transformation was applied to the CAD models of the components. Thirdly, we measured the orientation of the CAD models in the post-operative 3D model and calculate the difference with the planned orientation in the coronal, sagittal and axial planes (Figure 2). Femoral varus angle deviation was defined as the angle between the intersection lines of the pre-and postoperative distal cut planes with the femoral coronal plane.
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4

Clavicle Fracture Orientation Analysis

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To examine the effect of fracture orientation, three different midshaft fracture orientations (transversal, superomedial to inferolateral and inferomedial to superolateral ) were created in a 3D clavicle bone mesh obtained through segmenting a CT-scan of a clavicle composite bone (Mimics Innovation Suite, Materialise, Leuven) (Sawbones, Sweden). These fractures are all classified as diaphyseal simple or oblique fracture in the AO/ OTA classification. To identify the worst case fracture orientation, first, for each patient, the mean load case was calculated by taking the mean of the trapezius, deltoid, pectoralis major, and sternocleidomastoided (SCM)
force over all ADL, as overall estimation of the clavicle loading. Then, the net joint moments in the AC and SC joints about the 3 axis were calculated using equations 1 and 2:
𝑁𝑒𝑑_𝐴𝐢_π‘šπ‘œπ‘šπ‘’π‘›π‘‘ π‘Žπ‘₯𝑖𝑠 = π‘€π‘’π‘Žπ‘›_π‘šπ‘œπ‘šπ‘’π‘›π‘‘_π‘‡π‘Ÿπ‘Žπ‘ π‘Žπ‘₯𝑖𝑠 + π‘€π‘’π‘Žπ‘›_π‘šπ‘œπ‘šπ‘’π‘›π‘‘_𝐷𝑒𝑙𝑑 π‘Žπ‘₯𝑖𝑠 (1)
These net moments are indicative of the rotation direction of the fragment with respect to the joint centres. The rotation directions thus show whether the fracture gap is closed or opened due to muscle action, and therefore allows determining the least self-stabilising fracture orientation.
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5

CT-based Rotator Cuff Pathology Assessment

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The training dataset for the SSM consisted of 110 CT scan images (Siemens Definition Flash, Erlangen, Germany; matrix 512 x512, full body field of view, slice spacing 0.9mm and Brightspeed, GE Healthcare, Chicago, IL, USA, matrix 512 x 512, 50cm field of view and slice spacing of 1.25mm) from a mixed population of pathologic (n= 66, patients with different amounts of degenerative rotator cuff pathology) and presumably non-pathologic patients (n= 44, full body CT scan images from post-mortem investigation at the anatomical pathology department of our hospital) without observable signs of acquired bony anatomical abnormalities or arthropathy as judged by an experienced shoulder surgeon (FV) on the 2D CT-scan images.
The CT images were segmented using Mimics Innovation Suite (v21.0; Materialise, Leuven,
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6

CT-Guided Fabrication of Temporal Bone Prostheses

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Imaging of the cadaver temporal bones was obtained using a standard CT protocol on a Brilliance CT 64 Channel (Philips Healthcare, Amsterdam, The Netherlands). Imaging parameters were as follows: slice thickness 0.67Β mm with 0.33Β mm overlap; tube rotation time 0.75Β s; filter set to Detail; tube voltage 140 kVp and current 300 mAs; collumation 64Β Γ—Β 0.625; matrix 768; resolution set to HI; and scan field of view 200Β mm. The printer for fabrication of the prostheses was a Form2 3D printer (FormLabs, Somerville, Massachusetts). The printer uses stereolithographic (SLA) technology on an optically cured resin. Print parameters were a layer thickness of 25Β ΞΌm using the black photoreactive resin. Digital prosthesis design was accomplished with the Mimics Innovation Suite (Materialise, Belgium).
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7

Evaluation of Customized 3D-Printed Biopsy Models

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The data of the postoperative CT scans were segmented and loaded into Mimics Innovation Suite (Materialise, Leuven, Belgium) (Fig. 5). A fusion of these postoperative data with the preoperative planning data was performed. For determining the axis deviation, the maximum distance between the planned biopsy channel and the true biopsy channel was measured according to the ISO 1101 standard [24 ], a method which has also been applied in previous studies [5 (link), 25 (link), 26 (link)]. Further parameters were determined, such as the angle between the planned and the true biopsy axis as well as the depth of the drilled biopsy channels which was compared to the planned depth.

The figure shows certain steps of the biopsy of a customized 3D-printed models of the lower jaw (control group)

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8

Micro-CT Analysis of Bone Density

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Samples harvested at 12 w were scanned with micro-CT (ΞΌCT40, Scanco Medical, Bassersdorf, Switzerland). The parameters were set at a resolution of 18 ΞΌm, I = 114 ΞΌA, E = 70 kVp, with integration time of 300 ms. The image analysis was carried out using the Mimics innovation suite (Version 16.0, Materialise, Plymouth, MI). A three-dimensional region of interest (ROI) was defined as a cylindrical area covering the defect to reconstruct and analyze each specimen. The function of β€œProfile Lines” of the Mimics innovation suite was used to evaluate the bone mineral density of the area of focus for each sample. A profile line was drawn from the peripheral host bone, across the defect area to the other side of the defect boundary. The gray values on the profile line were shown in a curve diagram, which were in proportional to the bone mineral density (in a scale from 0 to 255) [52 ]. The percentage of the increase of bone density in the scaffold comparing to host bone was calculated as: (gray value in scaffold - gray value in host bone)/gray value in host bone (technical replicates n = 6).
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9

CBCT Image Acquisition Protocol

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All CBCT images were acquired by NewTom VG or NewTom VGi (QR srl, Verona, Italy). Exposure conditions were 110Β kV, 5Β mA, 0.125-mm voxel size, 140 × 140 × 150Β mm image size, and were performed according to the manufacturer's instructions. The sagittal plane of the patient's head was perpendicular to the ground; the orbito-auricular plane was parallel to the ground; the tongue was in the resting position; and the upper and lower jaws were in the cusp staggered position. Subjects were asked to keep their head steady, breathe calmly, not chew or swallow during filming.
All CBCT data were exported as Digital Imaging and Communications in Medicine (DICOM) files and reconstructed using the Materialise Interactive Medical Image Control System (Mimics Innovation Suite, Materialise, Belgium) for the measurements.
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10

Mandible and Nerve Canal Segmentation

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The DICOMs for the training and validation were imported into Mimics Innovation Suite (Version 24.0, Materialise NV, Leuven, Belgium), whereas the test samples were imported later into Mimics Innovation Suite Version 25.0. A semi-automatic segmentation workflow was applied using the Threshold, Split Mask, Region Grow, Edit Mask, Multiple Slice Edit, Smart Fill, and Smooth Mask tools. The teeth were included in the segmentation, and the masks were filled (i.e., they do not contain any voids). The mandible and the inferior nerve canal were labeled as a single mask and exported as a Standard Tessellation Language (STL) file.
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