The authors acknowledge Mr. Jean Luc Cornille, Science of Motion, for his input into modeling accuracy; Dr. Martha Littlefield and Mr. James Ray (LSU SVM), and Dr. Steve Holladay, Dr. Carla Jarrett, and Mr. Brent Norwood (UGA CVM) for access to anatomical specimens; Dr. Ajay Sharma (UGACVM) and Dr. L. Abbigail Granger and Mr. Mark Hunter (LSUSVM) for conducting CT scans; and undergraduate researchers Jeremy Baker, Joshua Maciejewski, Sarah Langlois and Daniel Pazooki (LSU School of Veterinary Medicine Functional and Evolutionary Anatomy Lab) for their work related to this research. Funding was procured from the Louisiana State University School of Veterinary Medicine&#39;s Equine Health Studies Program via a Charles V. Cusimano grant.

1. Forelimb rigging
<ol>
	<li>Place graphic joints inside the forelimb in all areas of movement. 
	NOTE: The resulting joint placement is a joint chain from the scapula to the distal end of the coffin bone (Figure 2A). In the area of the carpal bones, 3 joints in close proximity are used to increase the bending radius.
	<ol>
		<li>Press the F3 key to enable the Rigging Menu set. In the menus, select Skeleton | Create Joints to select the Create Joints tool.</li>
		<li>In the View panel of the software, click in the approximate areas of the joints found in Figure 2A in the order of 1 to 10, and press the ENTER key.</li>
		<li>Adjust the position of the joints by clicking on the desired joint and use&#160;the Move Tool&#160;by&#160;pressing the W key to translate the joint into the desired position. Alternatively, adjust a joint by clicking on the desired joint and altering the Translate X, Translate Y, and Translate Z values found in the Channel Box/Layer Editor panel.</li>
	</ol>
	</li>
	<li>Create 5 separate Inverse Kinematic handles (IK handles) (joints will be referred to by the numbers found in Figure 2A).
	<ol>
		<li>In the menus, select Skeleton | Create IK Handle to select the Create IK Handle tool. Using the Create IK Handle tool, select joint 1, then joint 3; name this IK handle Front Leg IK in the Outliner panel. Using the Create IK Handle tool, select joint 3, then joint 7; name this IK handle Front Lower IK.</li>
		<li>Using the Create IK Handle tool, select joint 7, then joint 8; name this IK handle Front Toe 1 IK in the Outliner panel. Using the Create IK Handle tool, select joint 8, then joint 9; name this IK handle Front Toe 2 IK in the Outliner panel. Using the Create IK Handle tool, select joint 9, then joint 10; name this IK handle Front Toe 3 IK in the Outliner panel.</li>
	</ol>
	</li>
	<li>Create forelimb controls
	<ol>
		<li>Create a Non-Uniform Rational B-Splines (NURBS) circle by using the Circle tool in the menu Create | NURBS Primitives | Circle.</li>
		<li>Create two NURBS Circles and move them using the Move Tool to encircle joint 3 and joint 10, and name them Front Ctrl and Front Lower Ctrl, respectively, in the Outliner panel.</li>
		<li>Create a NURBS Circle; select the circle, and in the Channel Box/Layer Editor Panel, change the Rotate Z value to 90. Using the Move tool, place it at the tip of joint 10, and name it Front Flick Ctrl in the Outliner panel.</li>
	</ol>
	</li>
	<li>Group Front Toe 1 IK, Front Toe 2 IK, and Front Toe 3 IK by selecting all three and pressing the CTRL + G keys. Name this group Front Toe Group in the Outliner panel. Parent the IK handles and Front Toe Group to the controls. 
	NOTE: It is important to Shift + select in the exact order described below to ensure a proper parent tree.
	<ol>
		<li>Select Front Leg IK, then Front Ctrl in the Outliner panel, and press the P key.</li>
		<li>Select Front Lower Ctrl, then Front Ctrl in the Outliner panel, and press the P key.</li>
		<li>Select Front Lower IK, then Front Lower Ctrl in the Outliner panel, and press the P key.</li>
		<li>Select Front Flick Ctrl, then Front Lower Ctrl in the Outliner panel and press the P key.</li>
		<li>Select Front Toe Group, then Front Flick Ctrl in the Outliner panel, and press the P key.</li>
	</ol>
	</li>
	<li>Use the Bind Skin tool to bind the bone meshes, except sesamoid bones, including navicular bones to the most proximal joint. Ensure that each bone mesh is only bound to one joint.
	<ol>
		<li>Click on the bone mesh, Shift + click on the most proximal joint, and select the Bind Skin tool under Skin | Bind Skin.</li>
	</ol>
	</li>
	<li>Rigging sesamoid bones and the navicular bone
	<ol>
		<li>Create a joint, place it in the middle of sesamoid bone, and press the Enter key. In the View panel, select the sesamoid bone mesh, and Shift + click the joint in the middle of the bone. Use the Bind Skin tool to bind the mesh to the joint. 
		&#8203;NOTE: The sesamoid bone can now be manipulated using the Move and Rotate tools for adjustment when changing the leg position.</li>
		<li>In the View panel, select the joint in the sesamoid bone, Shift + click the nearest joint in the forelimb, and press the P key. 
		NOTE: This parents the joint in the sesamoid bone to the forelimb.</li>
		<li>Repeat steps 1.6.1 to 1.6.2 for other sesamoid bones and the navicular bone.</li>
	</ol>
	</li>
	<li>Repeat steps 1.1 through 1.6 for the other forelimb. 
	NOTE: The joint at the scapula can be selected and translated in all 3 directions (6 degrees of freedom) using the Move tool.</li>
</ol>
2. Hindlimb rigging
<ol>
	<li>Place joints inside the hindlimb in all areas of movement to obtain a joint chain from the head of the demur to the distal end of the coffin bone (Figure 2B).</li>
	<li>Create 5 separate IK handles (joints will be referred to the numbers found in Figure 2B).
	<ol>
		<li>Using the Create IK handle tool, select joint 11, then joint 12; name this IK handle Hind IK in the Outliner panel. Using the Create IK handle tool, select joint 12, then joint 14; name this IK handle Hind Lower IK in the Outliner panel.</li>
		<li>Using the Create IK handle tool, select joint 14, then joint 15; name this IK handle Hind Toe 1 IK in the Outliner panel. Using the Create IK handle tool, select joint 15, then joint 16; name this IK handle Hind Toe 2 IK in the Outliner panel.</li>
		<li>Using the Create IK handle tool, select joint 16, then joint 17; name this IK handle Hind Toe 3 IK in the Outliner panel.</li>
	</ol>
	</li>
	<li>Create hindlimb controls
	<ol>
		<li>Create two NURBS Circles named Hind Ctrl and Hind Lower Ctrl and move them to encircle joint 12 and joint 17, respectively.</li>
		<li>Create a NURBS Circle named Hind Flick Ctrl. Make this circle vertical, and place it at the tip of joint 10.</li>
	</ol>
	</li>
	<li>Group Hind Toe 1 IK, Hind Toe 2 IK, and Hind Toe 3 IK by selecting all three and pressing CTRL + G. Name this group Hind Toe Group.</li>
	<li>Parent the IK handles and Hind Toe Group to the controls. Be sure to Shift + select in the exact order described below to ensure a proper parent tree.
	<ol>
		<li>Select Hind IK, then Hind Ctrl, and press the P key.</li>
		<li>Select Hind Lower Ctrl, then Hind Ctrl, and press the P key.</li>
		<li>Select Hind Lower IK, then Hind Lower Ctrl, and press the P key.</li>
		<li>Select Hind Flick Ctrl, then Hind Lower Ctrl, and press the P key.</li>
		<li>Select Hind Toe Group, then Hind Flick Ctrl, and press the P key.</li>
	</ol>
	</li>
	<li>Use the Bind Skin tool to bind the bone meshes to the most proximal joint. Ensure that each bone mesh is bound to only one joint.
	<ol>
		<li>Click on the bone mesh, Shift + click the most proximal joint, and select the Bind Skin tool under Skin | Bind Skin.</li>
	</ol>
	</li>
	<li>Rigging patella, sesamoid bones, and navicular bone
	<ol>
		<li>Create a joint, place it in the middle of the patella, and press the Enter key. In the View panel, select the patella mesh, and Shift + click on the joint in the patella. Use the Bind Skin tool to bind the mesh to the joint. 
		NOTE: The patella can now be manipulated using the Move and Rotate tools for adjustment when changing the leg position.</li>
		<li>In the View panel, select the joint in the patella, Shift + click on the nearest joint in the forelimb, and press the P key to parent the joint in the patella to the forelimb.</li>
		<li>Repeat steps 2.7.1 and 2.7.2 for the sesamoid bones and the navicular bone.</li>
	</ol>
	</li>
	<li>Repeat steps 2.1 through 2.7 for the other hindlimb.</li>
</ol>
3. Ribbon spine rigging
<ol>
	<li>Create a NURBS Plane with altered options with the length roughly equal to the length of the spine with 1 U-patch and # V-patches, where # is the number of thoracic and lumbar vertebrae. 
	&#8203;NOTE: For this paper, the length is 20 with 22 V patches.
	<ol>
		<li>Select the square found next to the Create Plane tool under Create | NURBS Primitives | Plane.</li>
	</ol>
	</li>
	<li>Rebuild the plane with altered options.
	<ol>
		<li>Press the F2 key to enter the modeling menu set. Select the plane in the view panel, and select the Rebuild tool settings by selecting the square next to the Rebuild tool under Surfaces | Rebuild. Use the following options: number of spans U = 1; number of spans V = # (22 in this case); select &#34;1 Linear&#34; for both the Degree U and Degree V options; keep the other settings to default; and press the Rebuild button.</li>
	</ol>
	</li>
	<li>Create nhairs with altered options.
	<ol>
		<li>Press the F5 key to enter the FX menu set. &#8220;Select the plane in the view panel, and use the Create Hair tool with altered options by selecting the square next to nHair | Create Hairs. Use the following options: output set to NURBS curves; U count =1; V count = # (22 in this case); keep the other options to default; and press the Create Hairs button.</li>
	</ol>
	</li>
	<li>Delete the following in the outliner panel: nucleus1, hairSystem1OutputCurves group, and hairSystem1. Fully expand the group labeled hairSystem1Follicles, and delete all the items labeled with curve__. 
	NOTE: The result should leave a group labeled hairSystem1Follicles that contains a list of items labeled nurbsPlane_Follicle____.</li>
	<li>Select the plane, and move and orient it so that it is roughly overlapping with the spine by using the Move tool and Rotate tool. Select the plane, hold the right mouse button, and select Control Vertex to make all the vertices of the plane visible.</li>
	<li>Move the vertices to orient the follicles to be between the vertebrae at the height where the spinal cord would be. Create # number of separate joints (22 in this case) at any place in the View panel as the position of these joints will be corrected in later steps.</li>
	<li>Parent a joint with a nurbsPlane_Follicle____ so that each has a single joint under its tree.
	<ol>
		<li>In the Outliner panel, select a joint created in step 3.6, then Ctrl + click on a nurbsPlane_Follicle____, and press the P key. Repeat 3.7.1 with the other joints created in step 3.6 and the other nurbsPlane_Follicle____ objects.</li>
	</ol>
	</li>
	<li>In the Outliner panel, Ctrl + select all the joints; in the Chanel Box/Layer Box panel, set the Translate X, Y, and Z to 0. Duplicate all the joints by Ctrl + selecting all the joints in the Outliner panel and pressing the Ctrl + D keys. Un-parent all the duplicate joints by Ctrl + selecting all the duplicate joints in the Outliner panel and pressing the Shift + P keys</li>
	<li>Bind the joints under nurbsPlane_Follicle____ with their respective vertebra mesh.
	<ol>
		<li>Press the F3 key to enter the Rigging menu set. Click on the original joint (not the duplicate joint) under nurbsPlane_Follicle____, Shift + click on the respective vertebra mesh, and then use the Bind Skin tool under Skin | Bind Skin. Repeat these actions in step 3.9.1 for each joint and vertebrae mesh.</li>
	</ol>
	</li>
	<li>CTRL + click all duplicate joints and the plane, and use the Bind Skin tool to bind all the duplicate joints to the plane. 
	&#8203;NOTE: The duplicate joints can now be manipulated to control the vertebrae.</li>
	<li>Repeat steps 3.1 through 3.10 for the cervical and caudal vertebrae.</li>
</ol>
4. Rib and sternum rigging
<ol>
	<li>Place separate joints at the rib head, at the proximal end of the costal cartilage, and at the distal end of the costal cartilage. Parent the joint at the proximal end of the costal cartilage to the joint at its rib head.</li>
	<li>Parent the joint at the distal end of the costal cartilage to the closest joint at the proximal end of the costal cartilage. Parent the joint at the rib head to the spine joint that controls the vertebrae caudal to the rib.</li>
	<li>In the Rigging menu set under the Skin tab, use the Bind Skin tool to bind the rib to the joint at its head and the costal cartilage to both the joints at its proximal end and the distal end.</li>
	<li>Repeat steps 4.1 through 4.3 for each rib.</li>
	<li>Place separate joints at the most cranial end of each sternal segment. Parent each sternal segment joint to the spinal joint most dorsal to each sternal segment joint. In the Rigging menu set under the Skin tab, use the Bind Skin tool to bind the sternal segment to its joint.</li>
</ol>
5. Positioning and animation
<ol>
	<li>Select a frame in the timeline.</li>
	<li>Position the model and controls. Import an image to use as a reference by creating a Free Image Plane. 
	NOTE: The images from Muybridge13&#160;of the horse at the walk were used as proof of concept.
	<ol>
		<li>While the Free Image Plane is selected, select the image file under the Attribute Editor tab and under the Image Plane Attributes dropdown menu.</li>
	</ol>
	</li>
	<li>Select all controls and the spine control joints, and press the S key to save them as a key frame.</li>
	<li>Along different frames along the timeline, move and rotate the controls and spine control joints, and press S. 
	NOTE: Repositioning controls and spine control joints and saving them as key frames along different points of the timeline creates an animation. There need not be a key frame set along each frame of the timeline; only critical positions or timings need to be key-framed. The 3D animation and modeling software will interpolate between the key-framed positions of each control and spine control joint, creating a smooth animation.</li>
</ol>

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Part 1: Navicular bone and related structures.</a> Equine Veterinary Journal. 38 (1), 15-22 (2006).</li><li>Dyson, S., Murray, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Magnetic+resonance+imaging+evaluation+of+264+horses+with+foot+pain:+the+podotrochlear+apparatus,+deep+digital+flexor+tendon+and+collateral+ligaments+of+the+interphalangeal+joint.">Magnetic resonance imaging evaluation of 264 horses with foot pain: the podotrochlear apparatus, deep digital flexor tendon and collateral ligaments of the interphalangeal joint.</a> Equine Veterinary Joint. 39 (4), 340-343 (2007).</li><li>Dyson, S., Murray, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+concurrent+scintigraphic+and+magnetic+resonance+imaging+evaluation+to+improve+understanding+of+the+pathogenesis+of+injury+of+the+podotrochlear+apparatus.">Use of concurrent scintigraphic and magnetic resonance imaging evaluation to improve understanding of the pathogenesis of injury of the podotrochlear apparatus.</a> Equine Veterinary Journal. 39 (4), 365-369 (2007).</li><li>Egenvall, A., Lonnell, C., Roepstorff, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+morbidity+and+mortality+data+in+riding+school+horses,+with+special+regard+to+locomotor+problems.">Analysis of morbidity and mortality data in riding school horses, with special regard to locomotor problems.</a> Preventive Veterinary Medicine. 88 (3), 193-204 (2009).</li><li>Waguespack, R., Hanson, R. 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The authors have declared no conflicts of interest.

This protocol demonstrates how to create a 3D whole-body skeletal model of an organism and demonstrates how to use the whole-body equine skeletal model described in this paper. The model is currently in a format that requires a specific 3D animation and modeling software, which has quite a learning curve for new users. However, a version of this software is freely available for those who are affiliated with a university. Although modeling whole-body posture and movement is used to assess human athletes and to identify causes of mechanically induced chronic injuries11, it is less commonly done with equine athletes. To use this approach for the assessment of the potential causes of equine athletic injuries and performance issues, a realistic whole-body skeletal equine model was created from CT data using the 3D visualization software and 3D animation and modeling software. This model is different from other equine models that are either artistic graphic recreations of the skeleton (https://www.youtube.com/watch?v=YncZtLaZ6kQ) or that only depict the limbs14,15,16,17.&#160;In this whole-body model, forelimbs, hindlimbs, spine, and ribcage were all rigged and had controls attached that allow for easy manipulation of the model for realistic and accurate positioning and animation.
The protocol used to rig the model allows for repeatability and future alterations to suit the needs of the specific horse being rigged, enabling individualized analysis. Thus, the equine model is a tool to be used by researchers as they analyze movement. However, it is not an automated program that provides answers without the input of parameters specific to the animal being modeled and the question being addressed, as the accuracy of the model is directly related to the strength of a particular analysis. The ability to input parameters also allows the model to be continually updated with data from future research studies. Additionally, this graphic rigging protocol can be applied and/or adjusted to reflect the anatomical differences between individuals. It can also be adapted to effectively model other animals. The 3D equine model can be easily manipulated and positioned to simulate positions and movements. This is especially evident with the limbs as their movements are relatively simple to see and model.
Graphic joint positioning in the model was determined by a similar approach to that used in other studies18,19. The bone meshes were placed in a neutral position. Graphic joints were positioned so that the bones were able to rotate freely without causing any collision with other bone meshes. In the digits, the graphic joint was placed at the point where a sphere coincided with the surfaces of movement. The graphic joint of the scapula was placed in the approximate center of the scapula blade. This positioning of the graphic joint allows it to be moved in 6 degrees of freedom to orient the scapula into the desired position. Unlike the limbs, the movement of the spine is not easily seen, is more complex than often realized, and thus is more difficult to model. Although the model has the flexibility to be used to investigate movements and issues at specific spinal joints, it also needed to be able to represent the often hard-to-distinguish movements of the whole spine. The use of the &#34;ribbon spine&#34; allows for more realistic movement of the spine during animations.
This is important as the spine in horses, as has been found in humans, is often the origin of issues that are potentially related to aberrant biomechanical movements and injury to the limbs. A strength of this model is the ability to accurately demonstrate spine positions, like transversal vertebral rotations20 (Figure 4). How these postures impact the limbs in three dimensions during various gaits can be determined by using the model in combination with kinematic and force analysis (e.g., pressure plate studies to confirm increased loading of the limbs and static force analysis). Soft tissue musculofascial components are currently being added to the whole-body skeletal model. Future goals are to expand the use of the model in 3D biomechanical analysis for studies of equine lameness. Such expansion would include using the model to complete 3D force analyses that compare healthy and unhealthy postures and registering the model with 3D data points collected in motion capture studies to provide a more effective visual representation of movement.

Chronic lameness in horses is often associated with progressive degenerative tissue lesions similar to those of osteoarthritis (OA), a major public health problem in humans1,2,3,4,5,6,7,8,9. In human medicine, because therapeutic approaches focused on treating specific lesions (e.g., pharmacotherapy and direct chondral repair) have mostly failed, pathomechanical forces are now recognized as the root cause of tissue damage in OA. Aberrant or pathomechanical forces impact both bone and cartilage cells directly, inducing the release of inflammatory mediators and progressive tissue degeneration9. These observations indicate that unless the causative mechanical forces are corrected, many chronic degenerative bone and joint diseases will continue to progress. Hence, the therapeutic focus in human medicine is shifting to approaches that &#34;unload&#34; the affected joints through targeted exercise10,11. However, this shift has not yet been made in equine medicine, partly because models for equine motion that can be adapted to show an individual&#39;s movements are needed.
Comprehensive, whole-body biomechanical analysis is common in designing training programs to optimize athletic performance and facilitate injury recovery in human athletes11 (see also e.g., the journal &#34;Sports Biomechanics&#34;), but is less commonly done for equine athletes (but see12). Thus, the overarching goal here is to establish pathomechanical models of equine lameness that can be used to develop individualized preventative and rehabilitative therapies to improve the health of equine athletes. Such pathomechanical models can characterize differences in the functional anatomy of regions (i.e., the spine) that are not as easily discernible to the naked eye as others (i.e., the lower limb). To achieve this goal, the first objective was to develop an anatomically accurate, manipulatable, whole-body, equine&#160;skeletal model that can be used as a template by researchers interested in functional anatomical, kinematic, and kinetic analyses. To be useful to equine clinicians and researchers, this model must (1) be biologically realistic to enable accurate anatomical positioning, (2) allow for easy and accurate adjustments for modeling various postures of healthy and non-healthy horses, (3) be able to be animated to study the effects of various gaits, and (4) facilitate repeatable re-creations of positions and movements.
A 3D graphic&#160;whole-body equine&#160;skeletal model was built from CT data in which the positions of bones relative to each other could be manipulated and then animated to match movements from pictures or videos of a horse in motion, thus creating a 4D equine skeletal model. Depending upon what best fits the question to be addressed, the model can be used in 2D, 3D, and 4D versions or in various combinations to illustrate and characterize the pathomechanical effects of specific positions or postures. Because of its basic and flexible design, the model serves as a template that can be modified by researchers to reflect their specific questions and data parameters. Such parameters include, for example, anatomical information based on sex and animal size, 3D motion analysis data, soft tissue force estimations, and inertial properties. Thus, the model allows for more detailed analysis of specific areas or joints, while also providing the basis to set up experiments that are unable to be performed on living horses. Due to practical limitations related to specimen availability (e.g., the ribs cut) and the scanner, the whole-body equine model is the result of merging data from three equine specimens. Thus, the model is not a perfect representation of a single individual, but has been standardized to represent individual variability more broadly. In short, it is a template to be used and modified to suit the needs of researchers. CT scans of the trunk, head and neck, and limbs were acquired from two equine specimens of approximately the same size with a 64-slice CT scanner using a bone algorithm, pitch of 0.9, 1 mm slice. CT scans of a set of ribs were acquired with a 64-slice CT scanner using a bone algorithm, pitch of 0.9, 0.64 mm slices.
Anatomic integrity of the bony joints (e.g., within the limb) was maintained. The soft tissues available in the CT scans were also used to confirm the placement of the bones. As some whole ribs and the proximal portions of all the ribs were available and scanned on the thorax specimen, the separately scanned ribs could be accurately sized and placed within the whole-body skeletal model. The resulting CT Digital Imaging and Communications in Medicine (DICOM) data were imported into the 3D visualization software (see the Table of Materials), and individual bones were segmented into individual data sets (i.e., bone meshes). The individual 3D bone meshes were then imported into the 3D animation and modeling software (Table of Materials) where they were sized, if necessary, and assembled into a complete equine skeleton in preparation for rigging-a graphic method of connecting the bone meshes so that their movements are linked (Figure 1).

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Avizo</td>
			<td>VSG, Visualization Science Group, Inc., Burlington, MA</td>
			<td>N/A</td>
			<td>cited in text as &#34;3D visualization software&#34;</td>
		</tr>
		<tr>
			<td>Maya</td>
			<td>Autodesk, Inc., San Rafael, CA</td>
			<td>N/A</td>
			<td>cited in text as &#34;3D animation and modeling software&#34;; Free student version</td>
		</tr>
	</tbody>
</table>

construction of a realistic, whole-body, three-dimensional equine skeletal model using computed tomography data

Therapies based upon whole-body biomechanical assessments are successful for injury prevention and rehabilitation in human athletes. Similar approaches have rarely been used to study equine athletic injury. Degenerative osteoarthritis caused by mechanical stress can originate from chronic postural dysfunction, which, because the primary dysfunction is often distant from the site of tissue injury, is best identified through modeling whole-body biomechanics. To characterize whole-body equine kinematics, a realistic skeletal model of a horse was created from equine computed tomography (CT) data that can be used for functional anatomical and biomechanical modeling. Equine CT data were reconstructed into individual three-dimensional (3D) data sets (i.e., bones) using 3D visualization software and assembled into a complete 3D skeletal model. The model was then rigged and animated using 3D animation and modeling software. The resulting 3D skeletal model can be used to characterize equine postures associated with degenerative tissue changes as well as to identify postures that reduce mechanical stress at the sites of tissue injury. In addition, when animated into 4D, the model can be used to demonstrate unhealthy and healthy skeletal movements and can be used to develop preventative and rehabilitative individualized therapies for horses with degenerative lamenesses. Although the model will soon be available for download, it is currently in a format that requires access to the 3D animation and modeling software, which has quite a learning curve for new users. This protocol will guide users in (1) developing such a model for any organism of interest and (2) using this specific equine model for their own research questions.

The result of the method was a 3D full equine skeletal model inside the 3D animation and modeling software that allows for accurate anatomical positioning and movement simulations. The model itself has a graphic rigging system delegated to the forelimbs, hindlimbs, spine, neck, and ribcage. The 3D model could be placed into different postures (Figure 3 and Figure 4) by multiple individuals. The movements of the 4D model (in motion) have been compared to videos from the side, back, and front, as well as with overhead drone footage to more accurately depict the motion of the spine and video of horses at the walk (Video), canter, and trot to create animations of those gaits.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62276/62276fig01.jpg" /> 
Figure 1: The 3D equine model can be moved into various postures and animated to demonstrate whole-body movements in various gaits in the 3D animation and modeling software. (A,C) Graphic rigging systems for the horse. The graphic ribbon spine that enables natural movement of the bony spine is illustrated by the green plane. The controls used to move the various graphic rigs and the attached bone meshes are illustrated by the yellow ovals and cross arrows on the model. (A) Standing position. (C) Rearing position. (B, D) The model with the bone meshes attached to the graphic rigging system. The positions of the controls change the position of the skeleton of the horse. (B) Standing horse. (D) Rearing horse. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62276/62276fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62276/62276fig02.jpg" /> 
Figure 2: The rigging of each limb with joints allows for positioning and the creation of movement. (A) Forelimb with graphic joints indicated with numbers 1-10. (B) Hindlimb with graphic joints indicated with numbers 11-17. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62276/62276fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/62276/62276fig03.jpg" /> 
Figure 3: The 3D equine model was matched to classic Muybridge13&#160;photos as proof of concept and to create the first animations. (A) Muybridge photographs of a horse at the walk. (B) The 3D equine model superimposed over the photographs to be used as key frames in the animation. (C) The 3D equine model. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62276/62276fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/62276/62276fig04.jpg" /> 
Figure 4: The 3D equine model can be moved into various postures (e.g., the transversal rotation of the spine demonstrated here) to understand the relationship of such postures to pathomechanical force regimes and the resulting degeneration of the affected skeletal elements, joints, and soft tissues. (A) A graphic 2D representation of a normal posture of a horse (with rider) using graphically manipulated photographs of an equine skeleton compared to a still image of the 3D equine model with the head and cervical vertebrae hidden to enable the visualization of the thorax. (B) A graphic 2D representation of a horse (with rider) with a transversal rotation of the spine using graphically manipulated photographs of an equine skeleton compared to a still image of the 3D equine model with the head and cervical vertebrae hidden to enable the visualization of the thorax. Note here the effect of the transversal rotation on the skeleton and the limbs of the body. The depicted position would overload the left forelimb, which was supported by the compression and cracking of the left front hoof wall in the living horse. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62276/62276fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Video. The 4D Horse. Key positions of the skeleton, as matched to the Muybridge13&#160;photos of the horse, have been interpolated to create an animation of the horse at a walk. The movement can be seen from the front, side, top, and back. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62276/4D Horse.mp4" target="_blank">Please click here to download this Video.</a>

Watch this Scientific Journal Video about Construction of a Realistic, Whole-Body, Three-Dimensional Equine Skeletal Model using Computed Tomography Data at JoVE.com

Construction of a Realistic, Whole-Body, Three-Dimensional Equine Skeletal Model using Computed Tomography Data

The purpose of this protocol is to describe the method of creation of a realistic, whole-body, skeletal model of a horse that can be used for functional anatomical and biomechanical modeling to characterize whole-body mechanics.

Therapies based upon whole-body biomechanical assessments are successful for injury prevention and rehabilitation in human athletes. Similar approaches ...

construction-realistic-whole-body-three-dimensional-equine-skeletal

Research

JoVE Journal

Biology

3.0K Views.  Louisiana State University School of Veterinary Medicine. The purpose of this protocol is to describe the method of creation of a realistic, whole-body, skeletal model of a horse that can be used for functional anatomical and biomechanical modeling to characterize whole-body mechanics.

Video: Construction of a Realistic, Whole-Body, Three-Dimensional Equine Skeletal Model using Computed Tomography Data

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique with sub-micron resolution capability that is now being used to evaluate the structure and function of plant xylem network in three dimensions (3D) (e.g. Brodersen et al. 2010; 2011; 2012a,b). HRCT imaging is based on the same principles as medical CT systems, but a high intensity synchrotron x-ray source results in higher spatial resolution and decreased image acquisition time. Here, we demonstrate in detail how synchrotron-based HRCT (performed at the Advanced Light Source-LBNL Berkeley, CA, USA) in combination with Avizo software (VSG Inc., Burlington, MA, USA) is being used to explore plant xylem in excised tissue and living plants. This new imaging tool allows users to move beyond traditional static, 2D light or electron micrographs and study samples using virtual serial sections in any plane. An infinite number of slices in any orientation can be made on the same sample, a feature that is physically impossible using traditional microscopy methods.
Results demonstrate that HRCT can be applied to both herbaceous and woody plant species, and a range of plant organs (i.e. leaves, petioles, stems, trunks, roots). Figures presented here help demonstrate both a range of representative plant vascular anatomy and the type of detail extracted from HRCT datasets, including scans for coast redwood (Sequoia sempervirens), walnut (Juglans spp.), oak (Quercus spp.), and maple (Acer spp.) tree saplings to sunflowers (Helianthus annuus), grapevines (Vitis spp.), and ferns (Pteridium aquilinum and Woodwardia fimbriata). Excised and dried samples from woody species are easiest to scan and typically yield the best images. However, recent improvements (i.e. more rapid scans and sample stabilization) have made it possible to use this visualization technique on green tissues (e.g. petioles) and in living plants. On occasion some shrinkage of hydrated green plant tissues will cause images to blur and methods to avoid these issues are described. These recent advances with HRCT provide promising new insights into plant vascular function.

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique that can be used to study the structure and function of plant vasculature in 3D. We demonstrate how HRCT facilitates exploration of xylem networks across a wide range of plant tissues and species.

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique with sub-micron resolution capability that is now being ...

3D Printing of Preclinical X-ray Computed Tomographic Data Sets

Three-dimensional printing allows for the production of highly detailed objects through a process known as additive manufacturing. Traditional, mold-injection methods to create models or parts have several limitations, the most important of which is a difficulty in making highly complex products in a timely, cost-effective manner.1 However, gradual improvements in three-dimensional printing technology have resulted in both high-end and economy instruments that are now available for the facile production of customized models.2 These printers have the ability to extrude high-resolution objects with enough detail to accurately represent in vivo images generated from a preclinical X-ray CT scanner. With proper data collection, surface rendering, and stereolithographic editing, it is now possible and inexpensive to rapidly produce detailed skeletal and soft tissue structures from X-ray CT data. Even in the early stages of development, the anatomical models produced by three-dimensional printing appeal to both educators and researchers who can utilize the technology to improve visualization proficiency. 3, 4 The real benefits of this method result from the tangible experience a researcher can have with data that cannot be adequately conveyed through a computer screen. The translation of pre-clinical 3D data to a physical object that is an exact copy of the test subject is a powerful tool for visualization and communication, especially for relating imaging research to students, or those in other fields. Here, we provide a detailed method for printing plastic models of bone and organ structures derived from X-ray CT scans utilizing an Albira X-ray CT system in conjunction with PMOD, ImageJ, Meshlab, Netfabb, and ReplicatorG software packages.

Using modern plastic extrusion and printing technologies, it is now possible to quickly and inexpensively produce physical models of X-ray CT data taken in a laboratory. The three -dimensional printing of tomographic data is a powerful visualization, research, and educational tool that may now be accessed by the preclinical imaging community.

Three-dimensional printing allows for the production of highly detailed objects through a process known as additive manufacturing.  Traditional, ...

Whole-Body Nanoparticle Aerosol Inhalation Exposures

Inhalation is the most likely exposure route for individuals working with aerosolizable engineered nano-materials (ENM). To properly perform nanoparticle inhalation toxicology studies, the aerosols in a chamber housing the experimental animals must have: 1) a steady concentration maintained at a desired level for the entire exposure period; 2) a homogenous composition free of contaminants; and 3) a stable size distribution with a geometric mean diameter &lt; 200 nm and a geometric standard deviation &sigma;g &lt; 2.5 5. The generation of aerosols containing nanoparticles is quite challenging because nanoparticles easily agglomerate. This is largely due to very strong inter-particle forces and the formation of large fractal structures in tens or hundreds of microns in size 6, which are difficult to be broken up. Several common aerosol generators, including nebulizers, fluidized beds, Venturi aspirators and the Wright dust feed, were tested; however, none were able to produce nanoparticle aerosols which satisfy all criteria 5.
A whole-body nanoparticle aerosol inhalation exposure system was fabricated, validated and utilized for nano-TiO2 inhalation toxicology studies. Critical components: 1) novel nano-TiO2 aerosol generator; 2) 0.5 m3 whole-body inhalation exposure chamber; and 3) monitor and control system. Nano-TiO2 aerosols generated from bulk dry nano-TiO2 powders (primary diameter of 21 nm, bulk density of 3.8 g/cm3) were delivered into the exposure chamber at a flow rate of 90 LPM (10.8 air changes/hr). Particle size distribution and mass concentration profiles were measured continuously with a scanning mobility particle sizer (SMPS), and an electric low pressure impactor (ELPI). The aerosol mass concentration (C) was verified gravimetrically (mg/m3). The mass (M) of the collected particles was determined as M = (Mpost-Mpre), where Mpre and Mpost are masses of the filter before and after sampling (mg). The mass concentration was calculated as C = M/(Q*t), where Q is sampling flowrate (m3/min), and t is the sampling time (minute). The chamber pressure, temperature, relative humidity (RH), O2 and CO2 concentrations were monitored and controlled continuously. Nano-TiO2 aerosols collected on Nuclepore filters were analyzed with a scanning electron microscope (SEM) and energy dispersive X-ray (EDX) analysis.
In summary, we report that the nano-particle aerosols generated and delivered to our exposure chamber have: 1) steady mass concentration; 2) homogenous composition free of contaminants; 3) stable particle size distributions with a count-median aerodynamic diameter of 157 nm during aerosol generation. This system reliably and repeatedly creates test atmospheres that simulate occupational, environmental or domestic ENM aerosol exposures.

A whole-body nanoparticle aerosol inhalation exposure facility was constructed for nano-sized titanium dioxide (TiO2) inhalation toxicology studies. This system provides nano-TiO2 aerosol test atmospheres that have: 1) a steady mass concentration; 2) a homogenous composition free of contaminants; and 3) a stable particle size distribution during aerosol generation.

Inhalation is the most likely exposure route for individuals working with aerosolizable engineered nano-materials (ENM). To properly perform nanoparticle ...

Measuring Respiratory Function in Mice Using Unrestrained Whole-body Plethysmography

Respiratory dysfunction is one of the leading causes of morbidity and mortality in the world and the rates of mortality continue to rise. Quantitative assessment of lung function in rodent models is an important tool in the development of future therapies. Commonly used techniques for assessing respiratory function including invasive plethysmography and forced oscillation. While these techniques provide valuable information, data collection can be fraught with artefacts and experimental variability due to the need for anesthesia and/or invasive instrumentation of the animal. In contrast, unrestrained whole-body plethysmography (UWBP) offers a precise, non-invasive, quantitative way by which to analyze respiratory parameters. This technique avoids the use of anesthesia and restraints, which is common to traditional plethysmography techniques. This video will demonstrate the UWBP procedure including the equipment set up, calibration and lung function recording. It will explain how to analyze the collected data, as well as identify experimental outliers and artefacts that results from animal movement. The respiratory parameters obtained using this technique include tidal volume, minute volume, inspiratory duty cycle, inspiratory flow rate and the ratio of inspiration time to expiration time. UWBP does not rely on specialized skills and is inexpensive to perform. A key feature of UWBP, and most appealing to potential users, is the ability to perform repeated measures of lung function on the same animal.

The assessment of respiratory physiology has traditionally relied upon techniques, which require restraint or sedation of the animal. Unrestrained whole-body plethysmography, however, provides precise, non-invasive, quantitative analysis of respiratory physiology in animal models. In addition, the technique allows repeated respiratory assessment of mice allowing for longitudinal studies.

Respiratory dysfunction is one of the leading causes of morbidity and mortality in the world and the rates of mortality continue to rise. Quantitative ...

FRET Imaging in Three-dimensional Hydrogels

Imaging of F&#246;rster resonance energy transfer (FRET)&#160;is a powerful tool for examining cell biology in real-time. Studies utilizing FRET commonly employ two-dimensional (2D) culture, which does not mimic the three-dimensional (3D) cellular microenvironment. A method to perform quenched emission FRET imaging using conventional widefield epifluorescence microscopy of cells within a 3D hydrogel environment is presented. Here an analysis method for ratiometric FRET probes that yields linear ratios over the probe activation range is described. Measurement of intracellular cyclic adenosine monophosphate (cAMP) levels is demonstrated in chondrocytes under forskolin stimulation using a probe for EPAC1 activation (ICUE1) and the ability to detect differences in cAMP signaling dependent on hydrogel material type, herein a photocrosslinking hydrogel (PC-gel, polyethylene glycol dimethacrylate) and a thermoresponsive hydrogel (TR-gel). Compared with 2D FRET methods, this method requires little additional work. Laboratories already utilizing FRET imaging in 2D can easily adopt this method to perform cellular studies in a 3D microenvironment. It can further be applied to high throughput drug screening in engineered 3D microtissues. Additionally, it is compatible with other forms of FRET imaging, such as anisotropy measurement and fluorescence lifetime imaging (FLIM), and with advanced microscopy platforms using confocal, pulsed, or modulated illumination.

F&#246;rster resonance energy transfer (FRET) imaging is a powerful tool for real-time cell biology studies. Here a method for FRET imaging cells in physiologic three-dimensional (3D) hydrogel microenvironments using conventional epifluorescence microscopy is presented. An analysis for ratiometric FRET probes that yields linear ratios over the activation range is described.

Imaging of F&#246;rster resonance energy transfer (FRET)&#160;is a powerful tool for examining cell biology in real-time. Studies utilizing FRET commonly ...

Assessment of Global Ocular Structure Following Spaceflight Using a Micro-Computed Tomography (Micro-CT) Imaging Method

Reports show that prolonged exposure to a spaceflight environment produces morphologic and functional ophthalmic changes in astronauts during and after an International Space Station (ISS) mission. However, the underlying mechanisms of these spaceflight-induced changes are currently unknown. The purpose of the present study was to determine the impact of the spaceflight environment on ocular structures by evaluating the thickness of the mouse retina, the retinal pigment epithelium (RPE), the choroid and the sclera layer using micro-CT imaging. Ten-week-old C57BL/6 male mice were housed aboard the ISS for a 35-day mission and then returned to Earth alive for tissue analysis. For comparison, ground control (GC) mice on Earth were maintained in identical environmental conditions and hardware. Ocular tissue samples were collected for micro-CT analysis within 38(&#177;4) hours after splashdown. The images of the cross-section of the retina, the RPE, the choroid, and the sclera layer of the fixed eye was recorded in an axial and sagittal view using a micro-CT imaging acquisition method. The micro-CT analysis showed that the cross-section areas of the retina, RPE, and choroid layer thickness were changed in spaceflight samples compared to GC, with spaceflight samples showing significantly thinner cross-sections and layers compared to controls. The findings from this study indicate that micro-CT evaluation is a sensitive and reliable method to characterize ocular structure changes. These results are expected to improve the understanding of the impact of environmental stress on global ocular structures.

Assessment of Global Ocular Structure Following Spaceflight Using a Micro-Computed Tomography Micro-CT Imaging Method

We present a protocol using high-resolution micro-computed tomography imaging to determine whether spaceflight induced damage on ocular structures. The protocol shows the micro-CT-derived measurement of ex vivo rodent ocular structures. We demonstrate the ability to assess ocular morphological changes following spaceflight using a non-destructive tridimensional technique to evaluate ocular damage.

Reports show that prolonged exposure to a spaceflight environment produces morphologic and functional ophthalmic changes in astronauts during and after an ...

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current state-of-the-art cryoET combined with subtomogram averaging analysis enables the high-resolution structural determination of macromolecular complexes that are present in multiple copies within tomographic reconstructions. Tomographic experiments usually require a vast amount of tilt series to be acquired by means of high-end transmission electron microscopes with important operational running-costs. Although the throughput and reliability of automated data acquisition routines have constantly improved over the recent years, the process of selecting regions of interest at which a tilt series will be acquired cannot be easily automated and it still relies on the user's manual input. Therefore, the set-up of a large-scale data collection session is a time-consuming procedure that can considerably reduce the remaining microscope time available for tilt series acquisition. Here, the protocol describes the recently developed implementations based on the SerialEM package and the PyEM software that significantly improve the time-efficiency of grid screening and large-scale tilt series data collection. The presented protocol illustrates how to use SerialEM scripting functionalities to fully automate grid mapping, grid square mapping, and tilt series acquisition. Furthermore, the protocol describes how to use PyEM to select additional acquisition targets in off-line mode after automated data collection is initiated. To illustrate this protocol, its application in the context of high-end data collection of Sars-Cov-2 tilt series is described. The presented pipeline is particularly suited to maximizing the time-efficiency of tomography experiments that require a careful selection of acquisition targets and at the same time a large amount of tilt series to be collected.

The increasing demand for large-scale data collection in cryogenic electron tomography requires high-throughput image acquisition routines. Described here is a protocol that implements the recent developments of advanced acquisition strategies aimed at maximizing the time-efficiency and throughput of tomographic data collection.

Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current ...

Three-dimensional Characterization of Interorganelle Contact Sites in Hepatocytes using Serial Section Electron Microscopy

Transmission electron microscopy has been long considered to be the gold standard for the visualization of cellular ultrastructure. However, analysis is often limited to two dimensions, hampering the ability to fully describe the three-dimensional (3D) ultrastructure and functional relationship between organelles. Volume electron microscopy (vEM) describes a collection of techniques that enable the interrogation of cellular ultrastructure in 3D at mesoscale, microscale, and nanoscale resolutions. 
This protocol provides an accessible and robust method to acquire vEM data using serial section transmission EM (TEM) and covers the technical aspects of sample processing through to digital 3D reconstruction in a single, straightforward workflow. To demonstrate the usefulness of this technique, the 3D ultrastructural relationship between the endoplasmic reticulum and mitochondria and their contact sites in liver hepatocytes is presented. Interorganelle contacts serve vital roles in the transfer of ions, lipids, nutrients, and other small molecules between organelles. However, despite their initial discovery in hepatocytes, there is still much to learn about their physical features, dynamics, and functions. 
Interorganelle contacts can display a range of morphologies, varying in the proximity of the two organelles to one another (typically ~10-30 nm) and the extent of the contact site (from punctate contacts to larger 3D cisternal-like contacts). The examination of close contacts requires high-resolution imaging, and serial section TEM is well suited to visualize the 3D ultrastructural of interorganelle contacts during hepatocyte differentiation, as well as alterations in hepatocyte architecture associated with metabolic diseases.

A simple and comprehensive protocol to acquire three-dimensional details of membrane contact sites between organelles in hepatocytes from the liver or cells in other tissues.

Transmission electron microscopy has been long considered to be the gold standard for the visualization of cellular ultrastructure. However, analysis is ...

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Cryo-electron tomography (cryo-ET) has been gaining momentum in recent years, especially since the introduction of direct electron detectors, improved automated acquisition strategies, preparative techniques that expand the possibilities of what the electron microscope can image at high-resolution using cryo-ET and new subtomogram averaging software. Additionally, data acquisition has become increasingly streamlined, making it more accessible to many users. The SARS-CoV-2 pandemic has further accelerated remote cryo-electron microscopy (cryo-EM) data collection, especially for single-particle cryo-EM, in many facilities globally, providing uninterrupted user access to state-of-the-art instruments during the pandemic. With the recent advances in Tomo5 (software for 3D electron tomography), remote cryo-ET data collection has become robust and easy to handle from anywhere in the world. This article aims to provide a detailed walk-through, starting from the data collection setup in the tomography software for the process of a (remote) cryo-ET data collection session with detailed troubleshooting. The (remote) data collection protocol is further complemented with the workflow for structure determination at near-atomic resolution by subtomogram averaging with emClarity, using apoferritin as an example.

The present protocol describes high-resolution cryo-electron tomography remote data acquisition using Tomo5 and subsequent data processing and subtomogram averaging using emClarity. Apoferritin is used as an example to illustrate detailed step-by-step processes to achieve a cryo-ET structure at 2.86 &#197; resolution.

Cryo-electron tomography (cryo-ET) has been gaining momentum in recent years, especially since the introduction of direct electron detectors, improved ...

Assessment of Bone Fracture Healing Using Micro-Computed Tomography

Micro-computed tomography (&#181;CT) is the most common imaging modality to characterize the three-dimensional (3D) morphology of bone and newly formed bone during fracture healing in translational science investigations. Studies of long bone fracture healing in rodents typically involve secondary healing and the formation of a mineralized callus. The shape of the callus formed and the density of the newly formed bone may vary substantially between timepoints and treatments. Whereas standard methodologies for quantifying parameters of intact cortical and trabecular bone are widely used and embedded in commercially available software, there is a lack of consensus on procedures for analyzing the healing callus. The purpose of this work is to describe a standardized protocol that quantitates bone volume fraction and callus mineral density in the healing callus. The protocol describes different parameters that should be considered during imaging and analysis, including sample alignment during imaging, the size of the volume of interest, and the number of slices that are contoured to define the callus.

Micro-computed tomography (&#181;CT) is a non-destructive imaging tool that is instrumental in assessing bone structure in preclinical studies, however there is a lack of consensus on &#181;CT procedures for analyzing the bone healing callus. This study provides a step-by-step &#181;CT protocol that allows the monitoring of fracture healing.

Micro-computed tomography (&#181;CT) is the most common imaging modality to characterize the three-dimensional (3D) morphology of bone and newly formed ...