This study was conducted in complete accordance with the Declaration of Helsinki. Before manuscript preparation, written informed consent was provided and signed by the patient. The patient granted permission for data usage for the demonstration of the protocol.
1. Radiographic image processing
<ol>
	<li>Load DICOM files into the software
	<ol>
		<li>Download the newest version of the medical imaging software and open it. 
		NOTE: After opening the software, the home screen will appear.</li>
		<li>Click Load DICOM Data on the sidebar. 
		NOTE: The DICOM database will pop up, showing the previously loaded DICOM datasets.
		<ol>
			<li>Click Import DICOM files in the DICOM database, select the DICOM dataset in the destination folder and click Import. 
			NOTE: The newly added DICOM dataset will appear in the list of studies.</li>
		</ol>
		</li>
		<li>Select the study and click Load at the bottom of the window. 
		NOTE: The DICOM dataset will be opened, and four views (coronal, axial, sagittal, and 3D) of the loaded data will be visible. Nodes are listed on the left-hand side. Theoretically, the described method can be performed on any CT or CBCT regardless of image quality (voxel size, artifacts). However, the segmentation process of higher-quality CBCT/CT scans is more straightforward, and higher-quality 3D models can be acquired. A shown CBCT scan was taken with the following parameters: voxel size: 150 &#181;m, anode voltage: 84 kV, tube current: 40 mA, Field-of-view: 8 x 5 cm. The process can be stopped at any stage; make sure to save the scene before exiting. To save, click the save icon on the left-hand side of the toolbar and save it as a &#34;medical record bundle&#34; (.mrb) by clicking on the box icon in the &#34;save scene&#34; window.</li>
	</ol>
	</li>
	<li>Volume rendering and cropping volume
	<ol>
		<li>Crop the area of interest (upper or lower jaw) to reduce the file size and rendering time. Click the Modules bar visible on the left-hand side of the toolbar to view a scroll-down window showing frequently used modules.</li>
		<li>Select the Volume Rendering module from the dropdown window. To make volume rendering visible, click the eye icon next to the &#34;Volumes&#34; bar.</li>
		<li>Select the desired preset to view the volume render and move the &#34;Shift&#34; slider until the hard tissues can be viewed clearly. 
		NOTE: For CBCT scans, the CT-Bone preset is recommended.</li>
		<li>Check the box next to &#34;Enable&#34; and click the eye icon next to &#34;Display ROI&#34; in the &#34;Crop&#34; section to make the ROI (Region of interest) visible. 
		NOTE: A wireframe box around the dataset in all 2D views and the 3D view will appear. By dragging the sides of the box, the volume will be cropped to the desired area.</li>
		<li>Access the &#34;Crop Volume&#34; module to finalize cropping. Select the original dataset as the input volume. 
		NOTE: Input ROI is automatically set to ROI that was previously created.</li>
		<li>Select Create new volume from the &#34;Output volume&#34; dropdown bar to create a new output volume. Uncheck Interpolated cropping in the advanced settings section and click Apply. 
		NOTE: When returning to the &#34;Data module,&#34; the new cropped volume will appear as a new node.</li>
	</ol>
	</li>
	<li>Segmentation of CBCT dataset
	<ol>
		<li>Access the Segment Editor module for segmentation. 
		NOTE: Segmentation is when 3D reconstructions of anatomical structures are generated based on the CBCT dataset to allow more accessible analysis.</li>
		<li>Select the previously created cropped volume as the Master Volume of the active segmentation. Click +Add to add, and -Remove to remove segments. Rename them according to the anatomical structure they will represent. 
		NOTE: Alveolar bone and all teeth will be separate segments within the segmentation</li>
		<li>Start with the segmentation of the alveolar bone. From the list of effects, select Level Tracing, a semi-automatic tool that outlines the region where pixels have the same background value as the selected pixel.</li>
		<li>Drag the mouse to the perimeter of the bone on one of the 2D views for a yellow line to appear around the selected area and press the left mouse button to generate the segment on the selected slice of the dataset. 
		NOTE: Segmentation can be done in any of the 2D views; however, sagittal and axial orientations work the best.</li>
		<li>Use the Paint and Erase hand tools to modify the segment and correct mistakes if the &#34;Level Tracing&#34; tool did not outline the entire section of the bone or if artifacts present on the slice were also included.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62743/62743fig01.jpg" /> 
Figure 1: Application of &#34;Level Tracing&#34; semi-automatic segmentation tool in sagittal orientation. (A) Outlining the region of pixels with the same background value with a yellow line. (B) Results of &#34;Level Tracing&#34; and subsequent manual segmentation. (C) Refinement of semi-automatic segmentation with the help of manual tools (paint, erase). <a href="https://www.jove.com/files/ftp_upload/62743/62743fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
NOTE: Using number keys to allow fast switching between tools.
<ol start="6" style="margin-left: 40px;">
	<li>Exclude both teeth and implants from the bone segment. Outline teeth and implants using the Erase tool and delete all highlighted pixels representing them.</li>
	<li>Repeat the same process on every 5th slice of the dataset in the selected orientation. 
	NOTE: Click Show 3D to view the segmentation in three dimensions. Set the smoothening factor slider to 0.00.</li>
	<li>Compute the missing segments upon completion of this phase-select Fill between slices from the effects list. 
	NOTE: This tool calculates the missing segments based on those created previously using a morphological contour interpolation algorithm.</li>
	<li>Click Initialize to activate contour interpolation, and if the results are satisfactory, click Apply. Scroll through the dataset upon completion to check and correct occasional mistakes.</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62743/62743fig02.jpg" /> 
Figure 2: Morphological contour interpolation with &#34;Fill Between Slices,&#34; light green areas indicating the automatically reconstructed part of the segment. (A) Axial view. (B) Sagittal view. (C) Coronal view. <a href="https://www.jove.com/files/ftp_upload/62743/62743fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
NOTE: Make sure that only the segment is visible on which the interpolation is applied. The visibility of the segments can be toggled in the segments list.
<ol start="10" style="margin-left: 40px;">
	<li>Make segment boundaries smoother by removing protrusions using the Smoothing effect. Select Median as the smoothing method and set the &#34;Kernel size&#34; to 5 x 5 x 5 pixels by adjusting the mm value in the bracket and clicking Apply.</li>
	<li>Repeat the same steps for the segmentation of teeth once the segmentation of alveolar bone is completed.</li>
</ol>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/62743/62743fig03.jpg" /> 
Figure 3: Finished segmentation, the brown segment representing bone and the blue segment representing teeth. (A) Axial view. (B) Sagittal view. (C) Coronal view. (D) The&#160;3D model is generated automatically from the segments created previously. <a href="https://www.jove.com/files/ftp_upload/62743/62743fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="12" style="margin-left: 40px;">
	<li>Set the &#34;Modify other segments&#34; bar to Allow overlap before tooth segmentation so that the newly created segments will not overwrite the previously created ones.</li>
</ol>
<ol start="4">
	<li>Spatial registration of CBCT dataset and IOS 
	NOTE: Spatial registration is necessary because the coordinate systems for the CBCT dataset and the IOS are different.
	<ol>
		<li>Select Extension Manager From the &#34;View&#34; menu bar and click Install Extensions. Type IGT into the search bar in the right-hand corner, install the SlicerIGT extension and restart the program.</li>
		<li>Load the previously saved .mrb file of the scene by clicking the Data icon and Choose file(s) to add.</li>
		<li>Import the .stl file of IOS by clicking the Data icon in the upper left corner. In the &#34;Add data into the scene&#34; pop-up window, click Choose file(s) to add, go to the destination folder, select the .stl file of the IOS, and click Open.</li>
		<li>Add the .stl file of the intraoral scan as segmentation by selecting Segmentation from the dropdown bar. 
		NOTE: The installed &#34;IGT&#34; module will now appear in the &#34;Modules&#34; dropdown menu.</li>
		<li>Move the cursor over the module, and in the sidebar that appears, select Fiducial Registration Wizard.</li>
		<li>Select Create new Markups Fiducial from the dropdown bar in both the &#34;From fiducials&#34; and the &#34;To fiducials&#34; sections. 
		NOTE: The software will automatically name the two lists &#34;From&#34; and &#34;To.&#34; The &#34;From&#34; list represents the moving volume, which in this case will be the IOS. The &#34;To&#34; list represents the fixed volume, which will be the CBCT dataset.</li>
		<li>Place marker points on well-defined anatomical landmarks on the IOS using the &#34;Place a markup point&#34; icon next to the dropdown bar in the &#34;From&#34; section. Markup points will be numbered in order of placement. 
		NOTE: Place at least 6 points on the cusps and incisal edges of teeth.</li>
		<li>Place markers in the same position to create the &#34;To&#34; list and in the same order on the CBCT dataset. Markup points with the same number must represent the same anatomical landmark.</li>
		<li>Create a transformation by selecting Create new LinearTransform from the dropdown menu in the &#34;Registration result transform&#34; section of the sidebar after the two lists are ready.</li>
		<li>Access the &#34;Transforms&#34; module and select the previously created transformation as the Active transform. In the &#34;Apply transform&#34; section, move the IOS segmentation and the &#34;From&#34; markups list from the &#34;Transformable&#34; box to the &#34;Transformed&#34; box to superimpose the IOS over the CBCT dataset.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/62743/62743fig04.jpg" /> 
Figure 4: Spatial registration of IOS by placing fiducial markers on well-defined anatomical landmarks. <a href="https://www.jove.com/files/ftp_upload/62743/62743fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
NOTE: If necessary, the accuracy of the transformation can be improved by moving the markup points or by adding additional points.
2. Export models as .stl files for free-form surface modeling
<ol>
	<li>Export the matched hard- and soft-tissue models for further surface modeling after segmentation and spatial registration.</li>
	<li>Go to the Segmentations module and select the segmentation with the alveolar bone and teeth models as the active segmentation. Scroll down to the &#34;Export to files&#34; section, choose the destination folder, and select STL as the file format.</li>
	<li>Uncheck the Merge into single file box, set the Coordinate system to RAS, and click Export.</li>
	<li>Repeat the same process for the IOS, visible as a separate segmentation, save the scene, and close the imaging software.</li>
</ol>
3. Free-form surface modeling
<ol>
	<li>Surface smoothing
	<ol>
		<li>Open the CAD software, and on the home screen, click Import. Select the .stl models that were previously exported from the DICOM image processing software. 
		NOTE: Even though smoothing was performed previously, the surface of the models reconstructed from the CBCT dataset will still appear pixelated, so further surface smoothing is necessary.</li>
		<li>Go to Sculpt in the menu bar, and from the brush inventory, select Adaptive reduce. 
		NOTE: Brush size and strength must be adjusted, depending on the amount of smoothing.</li>
	</ol>
	</li>
	<li>Separate crown of the teeth from the IOS 
	NOTE: Crowns of teeth are depicted more accurately on the IOS than on segmented models; therefore, crowns of the segmented teeth models must be replaced with crowns from the IOS.
	<ol>
		<li>Click Select in the sidebar and select Brush as the selection tool. Use Unwrap brush brush mode and adjust the size of the brush. Using the brush, select the crown of each tooth until the marginal gingiva on the IOS. 
		NOTE: Selected surfaces are indicated with an orange color.</li>
		<li>Move the cursor to Modify in the sidebar and select Smooth Boundary. Click Apply if the results are satisfactory. 
		NOTE: Now, the boundary of the selection precisely follows the marginal gingiva.</li>
		<li>Go to Edit in the Select sidebar and click Separate to create an individual object from the selected area.</li>
		<li>Repeat the same process for all teeth.</li>
		<li>Go to Analysis in the menu bar and select Inspect. 
		NOTE: The program will indicate errors in the models. Holes are marked with a blue color.</li>
		<li>Select Flat fill as the &#34;Hole fill mode&#34; and click Auto repair all to create closed models from the IOS model and the separated teeth models.Go to Sculpt and smooth the edges of the filled hole using Shrinksmooth brush.</li>
		<li>Repeat the process for all tooth crowns and the rest of the IOS.</li>
	</ol>
	</li>
	<li>Merge crowns of the teeth with the segmented tooth models. 
	NOTE: If spatial registration was correctly done, the positions of the crowns of teeth on the IOS and the crowns of segmented teeth should match.
	<ol>
		<li>Use the Shrinksmooth brush on the segmented tooth model until they are completely cover by the tooth crowns separated from the IOS. 
		NOTE: Due to imperfections in both the segmentation and the IOS, the crowns don&#39;t always overlap completely.</li>
		<li>Select both the separated crown and the segmented model of the same tooth in the Object Browser. In the sidebar that appears, select Boolean union, and click Accept. 
		NOTE: Now, the crown of the segmented tooth model is replaced by the crown separated from the IOS.</li>
		<li>Use Shrinksmooth to smooth the transition.</li>
	</ol>
	</li>
	<li>Subtractions and model composition
	<ol>
		<li>Subtract the bone model from the soft-tissue model to represent the clinical situation realistically. 
		NOTE: The original IOS without teeth became the model of the soft tissues.</li>
		<li>Select both bone and soft-tissue models in the Object Browser and select Boolean Difference.</li>
		<li>Smooth transitions with the Shrinksmooth brush and remove protrusions from the bottom side of the soft-tissue model.</li>
		<li>Subtract teeth from the soft-tissue model using the same process and smooth transitions.</li>
	</ol>
	</li>
	<li>Color models
	<ol>
		<li>Color the surfaces of the models to give a more realistic look since the model is complete now with the teeth, soft tissues, and alveolar bone being separated from one another, representing the clinical situation in 3D.</li>
		<li>Select Sculpt from the sidebar and switch the little slider from Volume to Surface.</li>
		<li>Select PaintVertex from the brush inventory and select the desired color using the color wheel in the Color section of the sidebar. Color the surface of each model (e.g., bone: brown, soft tissue: pink, teeth: white)</li>
	</ol>
	</li>
</ol>
Animated Figure 1: Animation of the final, colored model, ready for virtual surgical planning. <a href="https://www.jove.com/files/ftp_upload/62743/Animated Figure1.mp4" target="_blank">Please click here to download this Figure.</a>

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The authors declare no conflict of interest.

With the presented protocol, periodontal and alveolar defect morphologies can be visualized in three dimensions (3D), providing a more accurate depiction of the clinical situation than can be achieved by 2D diagnostic methods and 3D models generated with thresholding algorithms. The protocol can be divided into three major phases: (1) semi-automatic segmentation of CBCT datasets, (2) spatial registration of CBCT and IOS, and (3) free-form surface modeling. Technically, segmentation can be performed on any three-dimension...

Technological advancements in dentistry have enabled computer-aided treatment planning and simulation of surgical procedures and prosthetic rehabilitation. Two essential methods for 3D data acquisition in digital dentistry are: (1) cone-beam computed tomography (CBCT)1 and (2) intraoral optical scanning (IOS)2. Digital information of all relevant anatomical structures (alveolar bone, teeth, soft tissues) can be acquired using these tools to plan reconstructive dentoalveolar surgical procedures.
Cone-beam technology was first introduced in 1996 by an Italian research group. Delivering significantly lower radiation dose and higher resolution (compared to conventional computed tomography), CBCT has quickly become the most frequently used 3D imaging modality in dentistry and oral surgery3. CBCT is often used to plan different surgical procedures (e.g., periodontal regenerative surgery, alveolar ridge augmentation, dental implant placement, orthognathic surgery)1. CBCT datasets are viewed and can be processed in radiographic imaging software that provides 2D images, and 3D renders-however, most imaging software use threshold-based algorithms for 3D image reconstruction. Thresholding methods set the upper and lower bounds of a voxel grey value interval. Voxels that fall in between these bounds will be rendered in 3D. This method allows speedy model acquisition; however, since the algorithm cannot differentiate anatomical structures from metal artifacts and scattering, the 3D renders are highly inaccurate and have very little diagnostic value4,5. For the reasons mentioned above, many fields within dentistry still rely on conventional 2D radiographs (intraoral radiographs, panoramic X-ray) or the 2D images of CBCT datasets5. Our research group presented a semi-automatic image segmentation method in a recently published article, using open-source radiographic image processing software6 wherein anatomically based 3D reconstruction of CBCT datasets is performed7. With the help of this method, anatomical structures were differentiated from metal artifacts, and, more importantly, alveolar bone and teeth could be separated. Therefore, a realistic virtual model of hard tissues could be acquired. 3D models were used to evaluate intrabony periodontal defects and for treatment planning before regenerative periodontal surgeries.
Intraoral optical surface scanners provide digital information on clinical conditions (clinical crown of the teeth and soft tissues). The original intended purpose of these devices was to directly acquire digital models of patients for the planning and fabrication of dental prostheses with computer-aided design (CAD) and computer-aided manufacturing (CAM) technologies8. However, due to the wide range of applications, their use was quickly implemented in other fields of dentistry. Maxillo-facial surgeons combine IOS and CBCT into a hybrid setup that can be utilized for virtual osteotomy and digital planning of orthognathic surgeries9,10. Dental implantology is probably the field that uses digital planning and guided execution most commonly. Navigated surgery eliminates most complications related to implant mispositioning. The combination of CBCT datasets and stereolithography (.stl) files of IOS is routinely used to plan the guided implant placement and the fabrication of static implant drilling guides11,12. Intraoral scans superimposed over CBCT datasets have also been used to prepare esthetic crown lengthening13; however, soft tissues were superimposed only over CBCT datasets reconstructed with thresholding algorithms. Yet, to perform accurate 3D virtual planning of regenerative-reconstructive surgical interventions and dental implant placement, realistic 3D hybrid models of patients must be composed of CBCT and IOS data.
Hence, this article aims to present a step-by-step method to acquire realistic hybrid digital models for virtual surgical planning before reconstructive dentoalveolar surgical interventions.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>3DSlicer</td>
			<td>3DSlicer (The software was first developed at Queen&#8217;s University Canada and since it is open source it is constantly developed by it&#8217;s community)</td>
			<td>4.13.0-2021-03-19</td>
			<td>Open source radiographic image processing software platform. Software is primarily intended for general medicine, however the wide range of segmentation an modelling tools allow it&#8217;s use for dental purposes as well</td>
		</tr>
		<tr>
			<td>Meshmixer</td>
			<td>Autodesk Inc.</td>
			<td>3.5</td>
			<td>Open source free form surface modelling software developed for prototype development and basic 3D sculpting. However, due to the usefulness of tools for dental purpose, not just 3D models, but even static guides for navigated surgery can be designed.</td>
		</tr>
	</tbody>
</table>

digital hybrid model preparation for virtual planning of reconstructive dentoalveolar surgical procedures

Virtual, hybrid three-dimensional (3D) model acquisition is presented in this article, utilizing the sequence of radiographic image segmentation, spatial registration, and free-form surface modeling. Firstly cone-beam computed tomography datasets were reconstructed with a semi-automatic segmentation method. Alveolar bone and teeth are separated into different segments, allowing 3D morphology, and localization of periodontal intrabony defects to be assessed. The severity, extent, and morphology of acute and chronic alveolar ridge defects are validated concerning adjacent teeth. On virtual complex tissue models, positions of dental implants can be planned in 3D. Utilizing spatial registration of IOS and CBCT data and subsequent free-form surface modeling, realistic 3D hybrid models can be acquired, visualizing alveolar bone, teeth, and soft tissues. With the superimposition of IOS and CBCT soft tissue, thickness above the edentulous ridge can be assessed about the underlying bone dimensions; therefore, flap design and surgical flap management can be determined, and occasional complications may be avoided.

Virtual allowing three-dimensional (3D) models can be generated using radiographic image segmentation, spatial registration, and free-form modeling. The models digitally depict the clinical situation, making three-dimensional planning of various surgical interventions possible. With separate segmentation of bone and teeth, the boundary between the two anatomical structures is visible, 3D morphology and localization of periodontal intrabony defects are to be assessed. The severity, extent, and morphology of acute and chro...

Watch this Scientific Journal Video about Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures at JoVE.com

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

A workflow for creating three-dimensional (3D) virtual hybrid models has been designed based on cone-beam computed tomography dataset and intraoral optical scans utilizing radiographic image segmentation methods and free-form surface modeling. Digital models are used for the virtual planning of reconstructive dentoalveolar surgical procedures.

Virtual, hybrid three-dimensional (3D) model acquisition is presented in this article, utilizing the sequence of radiographic image segmentation, spatial ...

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1.6K Views.  Department of Periodontology, Semmelweis University. A workflow for creating three-dimensional (3D) virtual hybrid models has been designed based on cone-beam computed tomography dataset and intraoral optical scans utilizing radiographic image segmentation methods and free-form surface modeling. Digital models are used for the virtual planning of reconstructive dentoalveolar surgical procedures.

Video: Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Surgical Procedures for a Rat Model of Partial Orthotopic Liver Transplantation with Hepatic Arterial Reconstruction

Orthotopic liver transplantation (OLT) in rats using a whole or partial graft is an indispensable experimental model for transplantation research, such as studies on graft preservation and ischemia-reperfusion injury 1,2, immunological responses 3,4, hemodynamics 5,6, and small-for-size syndrome 7. The rat OLT is among the most difficult animal models in experimental surgery and demands advanced microsurgical skills that take a long time to learn. Consequently, the use of this model has been limited. Since the reliability and reproducibility of results are key components of the experiments in which such complex animal models are used, it is essential for surgeons who are involved in rat OLT to be trained in well-standardized and sophisticated procedures for this model.
While various techniques and modifications of OLT in rats have been reported 8 since the first model was described by Lee et al. 9 in 1973, the elimination of the hepatic arterial reconstruction 10 and the introduction of the cuff anastomosis technique by Kamada et al. 11 were a major advancement in this model, because they simplified the reconstruction procedures to a great degree. In the model by Kamada et al., the hepatic rearterialization was also eliminated. Since rats could survive without hepatic arterial flow after liver transplantation, there was considerable controversy over the value of hepatic arterialization. However, the physiological superiority of the arterialized model has been increasingly acknowledged, especially in terms of preserving the bile duct system 8,12 and the liver integrity 8,13,14.
In this article, we present detailed surgical procedures for a rat model of OLT with hepatic arterial reconstruction using a 50% partial graft after ex vivo liver resection. The reconstruction procedures for each vessel and the bile duct are performed by the following methods: a 7-0 polypropylene continuous suture for the supra- and infrahepatic vena cava; a cuff technique for the portal vein; and a stent technique for the hepatic artery and the bile duct.

Orthotopic liver transplantation in rats is an indispensable experimental model for biomedical research. Here we present our surgical procedures for orthotopic rat liver transplantation with hepatic arterial reconstruction using a 50% partial graft.

Orthotopic liver transplantation (OLT) in rats using a whole or partial graft is an indispensable experimental model for transplantation research, such as ...

Surgical Fixation of Sternal Fractures: Preoperative Planning and a Safe Surgical Technique Using Locked Titanium Plates and Depth Limited Drilling

Different ways to stabilize a sternal fracture are described in literature. Respecting different mechanisms of trauma such as the direct impact to the anterior chest wall or the flexion-compression injury of the trunk, there is a need to retain each sternal fragment in the correct position while neutralizing shearing forces to the sternum. Anterior sternal plating provides the best stability and is therefore increasingly used in most cases. However, many surgeons are reluctant to perform sternal osteosynthesis due to possible complications such as difficulties in preoperative planning, severe injuries to mediastinal organs, or failure of the performed method.
This manuscript describes one possible safe way to stabilize different types of sternal fractures in a step by step guidance for anterior sternal plating using low profile locking titanium plates. Before surgical treatment, a detailed survey of the patient and a three dimensional reconstructed computed tomography is taken out to get detailed information of the fracture&#8217;s morphology. The surgical approach is usually a midline incision. Its position can be described by measuring the distance from upper sternal edge to the fracture and its length can be approximated by the summation of 60 mm for the basis incision, the thickness of presternal soft tissue and the greatest distance between the fragments in case of multiple fractures.
Performing subperiosteal dissection along the sternum while reducing the fracture, using depth limited drilling, and fixing the plates prevents injuries to mediastinal organs and vessels.
Transverse fractures and oblique fractures at the corpus sterni are plated longitudinally, whereas oblique fractures of manubrium, sternocostal separation and any longitudinally fracture needs to be stabilized by a transverse plate from rib to sternum to rib. Usually the high convenience of a patient is seen during follow up as well as a precise reconstruction of the sternal morphology.

Here we present a method to stabilize sternal fractures by using locked titanium plates in a low profile design. Performing subperiosteal dissection along the sternum while reducing the fracture, using depth limited drilling, and fixing the plates provides a safe surgical way.

Different ways to stabilize a sternal fracture are described in literature. Respecting different mechanisms of trauma such as the direct impact to the ...

Improvement of a Closed Chest Porcine Myocardial Infarction Model by Standardization of Tissue and Blood Sampling Procedures

Myocardial ischemia reperfusion (I/R) injury contributes to almost half of the necrotic area after myocardial infarction. To date there is no approved drug to prevent or reduce myocardial I/R injury. The study and understanding of the pathophysiological mechanisms of myocardial I/R injury is essential to develop successful treatments. Large animal experiments are an important step in translational methods. The porcine model of acute myocardial infarction has been established and described by ourselves and others. We aimed to further improve the value of the model by focusing in detail on the sampling techniques for use in future experiments. Furthermore, we emphasize small but important steps that can affect the quality of the final results. To mimic the clinical situation of myocardial I/R injury, a percutaneous coronary intervention (PCI) catheter was inserted into the left anterior descending coronary artery (LAD) of an anesthetized pig. &#176;&#176;&#176;This model mimics acute myocardial infarction and PCI treatment in humans with the possibility of accurately determining the area at risk as well as the necrotic- and viable ischemic tissue. Here the model was used to investigate the effect of a bicyclic peptide inhibitor of FXIIa. The model can also be modified to allow longer reperfusion times to study later effects of myocardial infarction.

Here we demonstrate a protocol to standardize sampling procedures of an established porcine model of acute myocardial infarction in order to increase its translational value in the understanding of the pathophysiology of myocardial ischemia/reperfusion injury and to test novel drug candidates.

Myocardial ischemia reperfusion (I/R) injury contributes to almost half of the necrotic area after myocardial infarction. To date there is no approved ...

Designing CAD/CAM Surgical Guides for Maxillary Reconstruction Using an In-house Approach

Computer-aided design/computer-assisted manufacturing (CAD/CAM) is now being evaluated as a preparative technique for maxillofacial surgery. Because this technique is expensive and available in only limited areas of the world, we developed a novel CAD/CAM surgical guide using an in-house approach. By using the CAD software, the maxillary resection area and cutting planes and the fibular cutting planes and angles are determined. Once the resection area is decided, the necessary faces are extracted using a Boolean modifier. These superficial faces are united to fit the surface of the bones and thickened to stabilize the solids. Not only the cutting guides for the fibula and maxilla but also the location arrangement of the transferred bone segments is defined by thickening the superficial faces. The CAD design is recorded as .stl files and three-dimensionally (3-D) printed as actual surgical guides. To check the accuracy of the guides, model surgery using 3-D-printed facial and fibular models is performed. These methods may be used to assist surgeons where commercial guides are not available.

Methods for designing a computer-aided design/computer-aided manufacturing (CAD/CAM) surgical guide are shown. Cutting planes are separated, united, and thickened to easily visualize the necessary bone transfer. These designs can be three-dimensional printed and checked for accuracy.

Computer-aided design/computer-assisted manufacturing (CAD/CAM) is now being evaluated as a preparative technique for maxillofacial surgery. Because this ...

Isometric Contractility Measurement of the Mouse Mesenteric Artery Using Wire Myography

The wire myograph technique is used to assess the contractility of vascular smooth muscles in response to depolarization, GPCR agonists/inhibitors and drugs. It is widely used in many studies on the physiological functions of vascular smooth muscle, the pathogenesis of vascular diseases such as hypertension, and the development of smooth muscle relaxant drugs. The mouse is a widely used model animal with a large pool of disease models and genetically modified strains. We introduced this method to measure the isometric contraction of mouse mesenteric artery in detail. A 1.4-mm segment of mouse mesenteric resistance artery was isolated and mounted on a myograph chamber by passing two steel wires through its lumen. After equilibration and normalization steps, the vessel segment was potentiated by a high-K+ solution twice prior to the contraction assay. As an example of the application of this method in drug development, we measured the relaxant effect of a novel natural substance, neoliensinine, isolated from a Chinese herb, embryos of the lotus seed (Nelumbo nucifera Gaertn.) on mouse mesenteric arteries. The vessel segments mounted on the myograph chamber were stimulated with a high-K+ solution. When the force tension reached a stable sustained phase, cumulative doses of neoliensinine were added to the chamber. We found that neoliensinine had a dose-dependent relaxant effect on smooth muscle contraction, thus suggesting that it bears potential activity against hypertension. In addition, as the vessel segment can survive at least 4 hours after mounting and maintain contractility induced by the high-K+ solution for many times, we suggest that the wire myograph system may be used for the time-consuming process of drug screening.

The wire myograph technique is used to investigate vascular smooth muscle functions and screen new drugs. We report a detailed protocol for measuring the isometric contractility of the mouse mesenteric artery and for screening new relaxants of vascular smooth muscle.

The wire myograph technique is used to assess the contractility of vascular smooth muscles in response to depolarization, GPCR agonists/inhibitors and ...

A Pre-clinical Rat Model for the Study of Ischemia-reperfusion Injury in Reconstructive Microsurgery

Ischemia-reperfusion injury is the main cause of flap failure in reconstructive microsurgery. The rat is the preferred preclinical animal model in many areas of biomedical research due to its cost-effectiveness and its translation to humans. This protocol describes a method to create a preclinical free skin flap model in rats with ischemia-reperfusion injury. The described 3 cm x 6 cm rat free skin flap model is easily obtained after the placement of several vascular ligatures and the section of the vascular pedicle. Then, 8 h after the ischemic insult and completion of the microsurgical anastomosis, the free skin flap develops the tissue damage. These ischemia-reperfusion injury-related damages can be studied in this model, making it a suitable model for evaluating therapeutic agents to address this pathophysiological process. Furthermore, two main monitoring techniques are described in the protocol for the assessment of this animal model: transit-time ultrasound technology and laser speckle contrast analysis.

Here, we describe a pre-clinical animal model for studying the pathophysiology of ischemia-reperfusion injury in reconstructive microsurgery. This free skin flap model based on the superficial caudal epigastric vessels in the rat may also allow for the evaluation of different therapies and compounds to counteract ischemia-reperfusion injury-related damage.

Ischemia-reperfusion injury is the main cause of flap failure in reconstructive microsurgery. The rat is the preferred preclinical animal model in many ...

Guided Endodontics: Three-Dimensional Planning and Template-Aided Preparation of Endodontic Access Cavities

Pulp canal obliterations (PCO) are often a consequence of dental trauma, such as luxation injuries. Even though dentin apposition is a sign of vital pulp, pulpitis or apical periodontitis may develop in the long term. Root canal treatment of teeth with severe PCO and pulpal or periapical pathosis is challenging for general practitioners and even for well-equipped endodontic specialists. To ensure detection of the calcified root canal and avoid excessive loss of tooth structure or root perforation, static navigation using templates ("Guided Endodontics") was introduced a few years ago. The general workflow includes three-dimensional imaging using cone-beam computed tomography (CBCT), a digital surface scan, and superimposition of both in a planning software. This is followed by virtual planning of the access cavity and the design of a template that will guide the drill to the desired target point. To do this, a true-to-scale virtual image of the drill must be placed in a way that the tip of the drill reaches the orifice of the calcified root canal. Once the template has been fabricated using computer-aided design and computer-aided manufacturing (CAD/CAM) or a 3D printer, guided preparation of the access cavity can be performed clinically. For research purposes, a postoperative CBCT image can be used to quantify the accuracy of the access cavity performed. This work aims to present the technique of static guided endodontics from imaging to clinical implementation.

Guided endodontics describes a template-aided approach for access cavity preparation. The procedure requires cone-beam computed tomography and a surface scan to produce a template. An incorporated sleeve guides the drill to the target point. This allows the preparation of minimally invasive endodontic access cavities in calcified teeth.

Pulp canal obliterations (PCO) are often a consequence of dental trauma, such as luxation injuries. Even though dentin apposition is a sign of vital pulp, ...

Three-Dimensional Preoperative Virtual Planning in Derotational Proximal Femoral Osteotomy

Anterior knee pain (AKP) is a common pathology among adolescents and adults. Increased femoral anteversion (FAV) has many clinical manifestations, including AKP. There is growing evidence that increased FAV plays a major role in the genesis of AKP. Furthermore, this same evidence suggests that derotational femoral osteotomy is beneficial for these patients, as good clinical results have been reported. However, this type of surgery is not widely used among orthopedic surgeons.
The first step in attracting orthopedic surgeons to the field of rotational osteotomy is to give them a methodology that simplifies preoperative surgical planning and allows for the previsualization of the results of surgical interventions on computers. To that end, our working group uses 3D technology. The imaging dataset used for surgical planning is based on a CT scan of the patient. This 3D method is open access (OA), meaning it is accessible to any orthopedic surgeon at no economic cost. Furthermore, it not only allows for the quantification of femoral torsion but also for carrying out virtual surgical planning. Interestingly, this 3D technology shows that the magnitude of the intertrochanteric rotational femoral osteotomy does not present a 1:1 relationship with the correction of the deformity. Additionally, this technology allows for the adjustment of the osteotomy so that the relationship between the magnitude of the osteotomy and the correction of the deformity is 1:1. This paper outlines this 3D protocol.

This work presents a detailed surgical planning protocol using 3D technology with free open-source software. This protocol can be used to correctly quantify femoral anteversion and simulate derotational proximal femoral osteotomy for the treatment of anterior knee pain.

Anterior knee pain (AKP) is a common pathology among adolescents and adults. Increased femoral anteversion (FAV) has many clinical manifestations, ...

3D Reconstruction for the Diagnosis and Treatment of Pulmonary Nodules

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

The three-dimensional (3D) reconstruction of pulmonary nodules using medical images has introduced new technical approaches for diagnosing and treating pulmonary nodules, and these approaches are progressively being acknowledged and adopted by physicians and patients. Nonetheless, constructing a relatively universal 3D digital model of pulmonary nodules for diagnosis and treatment is challenging due to device differences, shooting times, and nodule types. The objective of this study is to propose a new 3D digital model of pulmonary nodules that serves as a bridge between physicians and patients and is also a cutting-edge tool for pre-diagnosis and prognostic evaluation. Many AI-driven pulmonary nodule detection and recognition methods employ deep learning techniques to capture the radiological features of pulmonary nodules, and these methods can achieve a good area under-the-curve (AUC) performance. However, false positives and false negatives remain a challenge for radiologists and clinicians. The interpretation and expression of features from the perspective of pulmonary nodule classification and examination are still unsatisfactory. In this study, a method of continuous 3D reconstruction of the whole lung in horizontal and coronal positions is proposed by combining existing medical image processing technologies. Compared with other applicable methods, this method allows users to rapidly locate pulmonary nodules and identify their fundamental properties while also observing pulmonary nodules from multiple perspectives, thereby providing a more effective clinical tool for diagnosing and treating pulmonary nodules.

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules  

The objective of this study is to develop a novel 3D digital model of pulmonary nodules that serves as a communication bridge between physicians and patients and is also a cutting-edge tool for pre-diagnosis and prognostic evaluation.

The three-dimensional (3D) reconstruction of pulmonary nodules using medical images has introduced new technical approaches for diagnosing and treating ...