This work was funded by Key Discipline Construction Project of Pudong Health Bureau of Shanghai (PWZxk2017-08) and the National Natural Science Foundation of China (81672199). The authors would like to thank Wang Lei for his help in proofreading an earlier version and Li Zhaoyang for his help in developing the parametric model.

This study was approved by the health research ethics board of the authors&#8217; institute. As cervical vertebral bones have more intricate shapes19, the protocol uses the cervical vertebrae as an illustration to facilitate relevant research.
1. Preparation of materials, scanning, and image processing
<ol>
	<li>Collect a dry cervical vertebra without pathologic deformation or broken parts.</li>
	<li>Place the vertebra vertically in the platform of the scanner (Figure 1, see Table of Materials), with the endplate facing the camera lens. Use the active light source of the scanner. Then, start the scanning process to obtain point cloud data (.ASC format). 
	NOTE: According to the pre-scan images, adjust the scanner and position of the vertebra to capture as much surface morphology information as possible.</li>
	<li>Open the software specially used for processing point clouds (see Table of Materials). Click Import to import the point cloud data and generate the digital graphic of the vertebra. Set the sample rate to 100%, select Keep Full Data On Sampling, select the unit of data as millimeters, and click Shade Points. Use the Lasso Selection Tool to select redundant points on the graphic, then click Delete to remove them. Click Reduce Noise and set the smoothness level to its maximum to reduce noise and spikes (Figure 2A,B). 
	NOTE: There are basic software operation instructions at the bottom of the GUI (graphical user interface). Noise points with obvious sharp spurs laterally or vertically should be removed to reduce error.</li>
	<li>Click Wrap to package the imaging data into .stl format file to transform the point cloud into mesh, which will convert a point object into a polygon object. 
	NOTE: Reverse engineering software usually accepts .stl-style 3D format.</li>
	<li>Open the software specially used for 3D reconstruction and data processing (see Table of Materials). Click File then New in the submenu. Select Part in the List of Types. Click Start, then Shape in the submenu, then Digitized Shape Editor. Click the Import icon in the toolbar at the right-hand side of the GUI. In the Import window, select the .stl format file, then click Apply &#62; OK. Click Fit All in the icon in the toolbar at the bottom to load the reconstructed image to the main window of the presentation software. 
	NOTE: Steps 1.5&#8211;2.3.3 are performed with the same software.</li>
	<li>Click Activate in the toolbar at the right-hand side. In the Activate window, select Trap Mode &#62; Polygonal Type &#62; Inside Trap. Then, select the vertebral endplate on the 3D image to remove unneeded vertebral components, such as the posterior elements and osteophytes (Figure 2C).</li>
</ol>
2. Quantification of 3D morphology of the endplate
<ol>
	<li>Defining the endplate 3D coordinate system
	<ol>
		<li>Click Start &#62; Shape in the submenu, then Generative Shape Design. Click the Point icon in the toolbar at the right-hand side. Mark three anatomic landmarks on the epiphyseal rim: the first two are the left and right endpoints of the endplate trailing edge, respectively; the third is the anterior median point.</li>
		<li>Click the Line icon in the toolbar at the right-hand side and select the two trailing edge endpoints to define a posterior frontal line. Click the Plane icon, select the plane type to be normal to curve, then select the posterior frontal line and anterior median point to define the mid-sagittal plane.</li>
		<li>Click Start &#62; Shape &#62; Quick Surface Reconstruction. Click the Planar Section icon, enter 1 in the number option, then select the endplate image and mid-sagittal plane to generate an intersecting curve. Click Curve from the Scan icon and select the intersection of the intersecting curve and posterior epiphyseal rim. Define the intersection as the posterior median point.</li>
		<li>Click Start &#62; Shape &#62; Generative Shape Design. Click the Line icon and select the anterior median point and posterior median point to define a mid-sagittal diameter. Click the Point icon, then Points and Planes Repetition in the submenu. Then, select the mid-sagittal diameter and enter 1 in the Instance(s) option to define the midpoint of the mid-sagittal diameter.</li>
		<li>Click the Axis System icon in the toolbar at the bottom. Then, select the midpoint of the mid-sagittal diameter as the origin, the line parallel to the posterior frontal line as the x-axis, the mid-sagittal diameter as the y-axis, and the line pointing forward and perpendicular to the x-y plane as the z-axis (Figure 3). 
		NOTE: The two trailing edge endpoints are chosen as reference points because they are consistent and show minimum variation in the presence of osteophytes10.</li>
	</ol>
	</li>
	<li>Fitting characteristic curves and points on the endplate surface (Figure 4A&#8211;D)
	<ol>
		<li>Click the Point icon, then Points and Planes Repetition in the submenu. Select the mid-sagittal diameter and enter 3 in the Instance(s) option to divide the mid-sagittal diameter equally into four parts.</li>
		<li>Click Start &#62; Shape &#62; Quick Surface Reconstruction. Click the Planar Section icon, enter 1 in the Number option, then select the endplate image and x-z plane to generate an intersecting curve. Click Curve from the Scan icon and select the two intersections of the x-z plane and epiphyseal rim.</li>
		<li>Define the line between the two intersections as the mid-frontal diameter. In the same way, divide the mid-frontal diameter equally into four parts. 
		NOTE: When the endplate is not symmetrical relative to the med-sagittal plane, choose one of the two endpoints of the mid-frontal curve that has a shorter vertical distance to the z-y plane. Then, define the mid-frontal diameter as 2x the length of the shorter, and divide it equally into four parts.</li>
		<li>Click the Measure Between icon in the toolbar at the bottom to measure the length of a quarter of the mid-sagittal diameter. Click the Planar Section icon, enter 2 in the Number option, enter the measured value in the Step option, then select the endplate image and x-z plane to generate two fitting curves on one side of the frontal part. Click Swap to generate two fitting curves on the other side. In the same way, obtain the other three fitting curves in the sagittal plane. 
		NOTE: The two mid-frontal fitting curves overlap with the two mid-sagittal fitting curves.</li>
		<li>Select 11 equidistant points in each curve for subsequent measurements. Specific method is as follows:
		<ol>
			<li>Taking the mid-sagittal curve as an example, divide the mid-sagittal diameter equally into 10 parts, resulting in a sum of 11 points, including nine intermediate points and two endpoints (refer to steps 2.1.3 and 2.2.1).</li>
			<li>Go through each equidistant point, obtain nine fitting curves on the endplate surface (refer to step 2.2.2). Click Curve from the Scan icon and select the intersection of the fitting curves and the mid-sagittal curve. Finally, obtain a total of 66 points on each endplate (11 points per curve multiplied by six curves). Click the Measure Item icon in the toolbar at the bottom to measure the coordinates of each point.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Measurement of endplate morphological parameters
	<ol>
		<li>Line parameter:
		<ol>
			<li>Click the Measure Between icon to measure the length of line parameter that is the distance between two measured points.</li>
		</ol>
		</li>
		<li>Concavity parameters:
		<ol>
			<li>Create a plane parallel to the x-y plane (Figure 5A): click Start &#62; Shape &#62; Generative Shape Design. Click the Sketch icon in the toolbar at the right-hand side, then click the x-y plane. Click the Circle icon, click Origin on the endplate surface, drag the cursor of the mouse to an appropriate distance, then click. Click the Exit Workbench icon, then the Fill icon, and then click.</li>
			<li>Click the Offset icon, select the filled plane, and enter an appropriate value in the offset option until it is tangent to the most concave part, and zoom in. Click Start &#62; Shape &#62; Quick Surface Reconstruction. Then, click the 3D curve icon to find and create the most concave point. Click the Measure Item icon to measure the coordinates of the most concave point (Figure 5B).</li>
			<li>Click the Measure Between icon, then select the most concave point and x-y plane to measure the whole endplate concavity depth. Similarly, find and create the most concave depth on a particular plane and measure its coordinates.</li>
			<li>Click the Projection icon in the toolbar at the right-hand side, then select the most concave point and x-y plane to obtain the projective point. Click the Measure Item icon to measure the coordinates of the projective point, and determine its distribution based on the coordinates.</li>
		</ol>
		</li>
		<li>Surface area parameters:
		<ol>
			<li>Click the Measure Inertia icon in the toolbar at the bottom and click endplate surface to measure its area. Click the Activate icon and select the central endplate along the inner margins of the epiphyseal ring (refer to step 1.6), then click the Measure Inertia icon to measure its area (Figure 5C). Click the Activate icon, then the central endplate, and finally the Swap icon in the Activate window to obtain an epiphyseal rim. Then, measure its area.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
3. Development of endplate surface mathematical model
<ol>
	<li>Determining the fit order of the parametric equation
	<ol>
		<li>Open the data analysis and visualization software (see Table of Materials). Input x = [corresponding data] in the command window. Click Enter. 
		NOTE: The &#8220;corresponding data&#8221; refers to x-coordinate data of the 11 characteristic points in one curve that has been measured in the previous steps. Click Enter after inputting each command, with the same applying to subsequent operations. Steps 3.1&#8211;5.5 are performed uniformly with the same software.</li>
		<li>In the same way, input z = [corresponding data].</li>
		<li>Input the code for i=1:5 z2=polyfit(x,z,i); Z=polyval(z2,x); if sum((Z-z).^2)&#60;0.01 C=i break; end; end&#8203;. 
		NOTE: The protocol sets the error sum of squares below 0.01 to obtain higher precision, the value of which can be readjusted to satisfy various demands.</li>
		<li>Click Enter to obtain a C value that is the desired fit order.</li>
	</ol>
	</li>
	<li>Parameter equation fitting
	<ol>
		<li>Input cftool and click Enter to bring up the Curve Fitting Tool.</li>
		<li>Input the coordinates of a curve in the command window (refer to steps 3.1.1 and 3.1.2). In the Curve Fitting Tool, select x-coordinate data when fitting frontal plane curves and y-coordinate data when fitting sagittal plane curves in the x data option, select z-coordinate data in the y data option, select polynomial, and enter the fit order obtained. Then, the software will output the parametric equation and goodness of fit automatically. 
		NOTE: As the curve is a 2D image, the default work option is the x and y options in the Curve Fitting Tool when fitting a curve.</li>
		<li>In the similar way, input the 3D coordinates of the 66 points and match the coordinate data to the corresponding axis options. Select polynomial and enter the fit order to gain the parametric equation of the endplate surface (Figure 6B).</li>
	</ol>
	</li>
</ol>
4. Acquisition of geometric data based on parametric equation
<ol>
	<li>Input x- and y-coordinate values of any point on the endplate in the command window.</li>
	<li>Input PX1, PX2, PX3.... 
	NOTE: Px is the parameters of the parametric equation that have been fitted using polynomial in the steps above.</li>
	<li>Input the equation and click Enter to obtain the result (i.e., input format: z = P00 + P10*x + P01*y + P20*x^2 + P11*x*y + P02*y^2 + P30*x^3 + P21*x^2*y + P12*x*y^2 + P03*y^3 + P40*x^4 + P31*x^3*y + P22*x^2*y^2 + P13*x*y^3 + P04*y^4).</li>
</ol>
5. Representation of the endplate based on parametric equation
<ol>
	<li>Input PX1, PX2, PX3....in the command window.</li>
	<li>Input the code X=N1:0.01:N2;. 
	NOTE: N1&#8211;N2 is the range of X-axis data (i.e., the values of the two endpoints of the themid-coronal curve).</li>
	<li>Input the code &#8220;Y=N3:0.01:N4;&#8221;.</li>
	<li>Input the equation (i.e., z=@(x,y)P00 + P10.*x + P01.*y + P20.*x.^2 + P11.*x.*y + P02.*y.^2 + P30.*x.^3 + P21.*x.^2.*y+ P12.*x.*y.^2 + P03.*y.^3 + P40.*x.^4 + P31.*x.^3.*y + P22.*x.^2.*y.^2+ P13.*x.*y.^3 + P04.*y.^4;).</li>
	<li>Input the code ezmesh(z, [N1,N2,N3,N4]) to obtain 3D simulation graphics (Figure 6C).</li>
</ol>

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The authors declare no competing financial interests.

Reverse engineering has been increasingly and successfully applied to the field of medicine, such as cranioplasty20, oral21, and maxillofacial implants21. Reverse engineering measurements, namely product surface digitization, refers to the conversion of surface information into point cloud data employing specific measuring equipment and methods. On the basis of such data, complex surface modeling, evaluation, improvements, and manufacturing can be pe...

A vertebral endplate is the superior or inferior shell of the vertebral body and serves as a mechanical interface to transfer stress between the disc and vertebral body1. It consists of the epiphyseal rim, which is a strong and solid bony labrum surrounding the outer rim of the vertebral body, and the central endplate, which is thin and porous2.
The spine is subject to a wide array of degenerative, traumatic, and neoplastic disorders, which may warrant surgical intervention. Recently, spinal devices such as artificial discs and cages have been widely used. Accurate and detailed morphometric parameters of endplates are necessary for the design and amelioration of spinal implants with effective prosthesis-vertebra contact and bone ingrowth potential3. Furthermore, information on the exact shape and geometry of vertebral endplates is important for understanding the biomechanics. Although the finite element modeling allows for simulation of the real vertebrae and has been widely used to study physiological responses of the spine to various loading conditions4, this technique is patient-specific and not generalizable to all vertebrae. It has been suggested that the intrinsic variability of vertebrae geometry among the general population should be considered when developing the finite element model5. Therefore, the geometric parameters of endplates are conducive to the mesh generation and fidelity enhancement in finite element modeling.
Although the importance of the matching of endplate geometry and implant surface has been discussed in previous studies6,7,8, data on the morphology of vertebral endplates is scarce. Most previous studies have failed to reveal the 3D nature of the endplate9,10,11. A spatial analysis is required to better and fully depict endplate morphology12,13,14. In addition, most studies have employed lower precision measurement techniques10,15,16. Moreover, significant magnification has been reported when geometry parameters are measured by employing radiography or computed tomography (CT)17,18. Though magnetic resonance imaging (MRI) is considered non-invasive, it is less accurate in defining the precise margins of osseous structures11. Due to a lack of a standardized measurement protocol, there are large differences among existing geometric data.
In recent years, reverse engineering, which can digitize the existing physical parts into computerized solid models, has been increasingly applied to the field of medicine. The technique makes it feasible to develop an accurate representation of the anatomical character of sophisticated vertebrae surfaces. The reverse engineering system includes two subsystems: the instrumentation system and software system. The instrumentation system adopted in this protocol has a non-contact optical 3D range flatbed scanner, which is high-speed and highly accurate (precision 0.02 mm, 1,628 x 1,236 pixels). The scanner can efficiently (input time 3 s) capture surface morphology information of the target object and convert it into digital point cloud. The software system (i.e., reverse engineering software) is a computer application for point cloud data processing (see Table of Materials), 3D surface model reconstruction, free curve and surface editing, and data processing (see Table of Materials).
The purposes of the present report are to (1) devise a measurement protocol and algorithm to obtain quantitative parameters of vertebral endplates based on a reverse engineering technique, (2) develop a mathematical model that allows for a realistic representation of vertebral endplates without digitizing too many landmarks. These methods will be beneficial to surgical act planning and finite element modeling.

<table><tbody><tr><td>Catia</td><td>Dassault Systemes, Paris, France</td><td>https://www.3ds.com/products-services/catia/</td><td>3D surface model reconstruction, free curve and surface editing and data processing</td></tr><tr><td>Geomagic Studio</td><td>Geomagic Inc., Morrisville, NC</td><td>https://cn.3dsystems.com/software?utm_source=geomagic.com&amp;amp;utm_medium=301</td><td>point cloud data processing</td></tr><tr><td>MATLAB</td><td>The MathWorks Inc., Natick,USA</td><td>https://www.mathworks.com/</td><td>analyze data, develop algorithms, and create models</td></tr><tr><td>Optical 3D range flatbed scanner</td><td>Xi&amp;rsquo;an XinTuo 3D Optical Measurement Technology Co.Ltd., Xi&amp;rsquo;an, Shaanxi, China</td><td>http://www.xtop3d.com/</td><td>acquire surface geometric parameters and convert into digital points</td></tr></tbody></table>

precision measurements and parametric models of vertebral endplates

Detailed and comprehensive geometric data of vertebrae endplates is important and necessary to improve the fidelity of finite element models of the spine, design and ameliorate spinal implants, and understand degenerative changes and biomechanics. In this protocol, a high-speed and highly accurate scanner is employed to convert morphology data of endplate surfaces into a digital point cloud. In the software system, the point cloud is further processed and reconstructed into three dimensions. Then, a measurement protocol is performed, involving a 3D coordinate system defined to make each point a 3D coordinate, three sagittal and three frontal surface curves that are symmetrically fitted on the endplate surface, and 11 equidistant points that are selected in each curve. Measurement and spatial analyses are finally performed to obtain geometric data of the endplates. Parametric equations representing the morphology of curves and surfaces are fitted based on the characteristic points. The suggested protocol, which is modular, provides an accurate and reproducible method to obtain geometric data of vertebral endplates and may assist in more sophisticated morphological studies in the future. It will also contribute to designing personalized spinal implants, planning surgical acts, making clinical diagnoses, and developing accurate finite element models.

Using the highly accurate optical 3D range flatbed scanner, the endplates were converted into more than 45,000 digital points, which adequately characterize the morphology (Figure 2A,B).
In the measurement protocol, the spatial analysis of endplate surfaces was conducted. Representative curves were fitted and quantified on the surface to characterize morphology (Figure 4B). The line...

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Precision Measurements and Parametric Models of Vertebral Endplates

A reverse engineering system is employed to record and obtain detailed and comprehensive geometry data of vertebral endplates. Parametric models of vertebral endplate are then developed, which are beneficial to designing personalized spinal implants, making clinical diagnoses, and developing accurate finite element models.

Detailed and comprehensive geometric data of vertebrae endplates is important and necessary to improve the fidelity of finite element models of the spine, ...

precision-measurements-and-parametric-models-of-vertebral-endplates

Research

JoVE Journal

Medicine

6.4K Views.  Tongji University School of Medicine. A reverse engineering system is employed to record and obtain detailed and comprehensive geometry data of vertebral endplates. Parametric models of vertebral endplate are then developed, which are beneficial to designing personalized spinal implants, making clinical diagnoses, and developing accurate finite element models.

Video: Precision Measurements and Parametric Models of Vertebral Endplates

Three and Four-Dimensional Visualization and Analysis Approaches to Study Vertebrate Axial Elongation and Segmentation

Somitogenesis is a hallmark of vertebrate embryonic development. For years, researchers have been studying this process in a variety of organisms using a wide range of techniques encompassing ex vivo and in vitro approaches. However, most studies still rely on the analysis of two-dimensional (2D) imaging data, which limits proper evaluation of a developmental process like axial extension and somitogenesis involving highly dynamic interactions in a complex 3D space. Here we describe techniques that allow mouse live imaging acquisition, dataset processing, visualization and analysis in 3D and 4D to study the cells (e.g., neuromesodermal progenitors) involved in these developmental processes. We also provide a step-by-step protocol for optical projection tomography and whole-mount immunofluorescence microscopy in mouse embryos (from sample preparation to image acquisition) and show a pipeline that we developed to process and visualize 3D image data. We extend the use of some of these techniques and highlight specific features of different available software (e.g., Fiji/ImageJ, Drishti, Amira and Imaris) that can be used to improve our current understanding of axial extension and somite formation (e.g., 3D reconstructions). Altogether, the techniques here described emphasize the importance of 3D data visualization and analysis in developmental biology, and might help other researchers to better address 3D and 4D image data in the context of vertebrate axial extension and segmentation. Finally, the work also employs novel tools to facilitate teaching vertebrate embryonic development.

Here, we describe computational tools and methods that allow visualization and analysis of three and four-dimensional image data of mouse embryos in the context of axial elongation and segmentation, obtained by in toto optical projection tomography, and by live imaging and whole-mount immunofluorescence staining using multiphoton microscopy.

Somitogenesis is a hallmark of vertebrate embryonic development. For years, researchers have been studying this process in a variety of organisms using a ...

Developmental Biology

Semiautomated Longitudinal Microcomputed Tomography-based Quantitative Structural Analysis of a Nude Rat Osteoporosis-related Vertebral Fracture Model

Osteoporosis-related vertebral compression fractures (OVCFs) are a common and clinically unmet need with increasing prevalence as the world population ages. Animal OVCF models are essential to the preclinical development of translational tissue engineering strategies. While a number of models currently exist, this protocol describes an optimized method for inducing multiple highly reproducible vertebral defects in a single nude rat. A novel longitudinal semiautomated microcomputed tomography (&#181;CT)-based quantitative structural analysis of the vertebral defects is also detailed. Briefly, rats were imaged at multiple time points post-op. The day 1 scan was reoriented to a standard position, and a standard volume of interest was defined. Subsequent &#181;CT scans of each rat were automatically registered to the day 1 scan so the same volume of interest was then analyzed to assess for new bone formation. This versatile approach can be adapted to a variety of other models where longitudinal imaging-based analysis could benefit from precise 3D semiautomated alignment. Taken together, this protocol describes a readily quantifiable and easily reproducible system for osteoporosis and bone research. The suggested protocol takes 4 months to induce osteoporosis in nude ovariectomized rats and between 2.7 and 4 h to generate, image, and analyze two vertebral defects, depending on tissue size and equipment.

The goal of this protocol is to generate a nude rat osteoporosis-related vertebral compression fracture model that can be longitudinally evaluated in vivo using a semiautomated microcomputed tomography-based quantitative structural analysis.

Osteoporosis-related vertebral compression fractures (OVCFs) are a common and clinically unmet need with increasing prevalence as the world population ...

Bioengineering

An Anesthesia, Surgery, and Harvest Method for the Evaluation of Transpedicular Screws Using an In Vivo Porcine Lumbar Spine Model

Pedicle screw fixation is the gold standard for the treatment of spinal diseases. However, many studies have reported the issue of loosening pedicle screws after spinal surgery, which is a serious concern. To address this problem, diverse types of pedicle screws have been examined to identify those with good fixation strength and osseointegration in spine bone. The porcine spine is a good alternative for the human spine in the evaluation of pedicle screws due to the anatomical size, mechanical characteristics, and cost. Although several studies have reported that pedicle screws are efficient in the porcine model, no study has described detailed protocols for the evaluation of a pedicle screw using the porcine model. Here, we describe a detailed method for evaluating transpedicular screws using an in vivo porcine lumbar spine model. The technical details for anesthesia, spine surgery, and harvest provided here will facilitate with the evaluation of the transpedicular screw fixation model.

An Anesthesia, Surgery, and Harvest Method for the Evaluation of Transpedicular Screws Using an In Vivo Porcine Lumbar Spine Model

Here, we introduce a method to evaluate transpedicular screws by using an in vivo porcine lumbar spine model.

Pedicle screw fixation is the gold standard for the treatment of spinal diseases. However, many studies have reported the issue of loosening pedicle ...

Evaluation of Patients' Posture and Gait Profile After Lumbar Fusion Surgery by Video Rasterstereography and Treadmill Gait Analysis

This protocol provides guidance on how to perform high resolution video rasterstereography and treadmill gait analysis on patients after lumbar fusion surgery to obtain results about altered variables of gait and posture. These observed changes can then be correlated with the patient-reported outcome measure of pain relief. The rasterstereographic device projects lines of parallel light onto the surface of the tested subject&#39;s back. The deformation of these lines is recognized by the device. From these data, a special software then generates a 3-D profile based on the principle of triangulation. With an inaccuracy of only 0.2 mm it can measure changes in posture at very high precision. Gait and stance parameters are recorded using a treadmill equipped with an electric sensor mat that contains 10,200 miniature force sensors in the registering zone under the belt. Initial walking speed on the treadmill is 0.5 km/h. Speed is then gradually increased by increments of 0.1 km/h until each subject reaches his or her individual maximum well tolerable walking speed. At this speed, parameters are recorded during a 20 s measurement interval. Subjects are tested barefoot and without holding a handrail. Among various other parameters, stride width, step length, stance phase and foot rotation are measured. Both methods used reportedly have a high intra- and inter-observer reliability. The advantage of these highly accurate techniques is that they offer an objective and very detailed perspective on changes in the patient&#39;s posture and gait. Due to the amount of data generated, these techniques are, however, not so much suitable for everyday routine use, but rather interesting to scientifically evaluate long term alterations in posture and gait in patients like for example after lumbar fusion surgery.

Here, we present a protocol to analyze the posture and the gait of patients after lumbar fusion surgery by means of high-resolution video rasterstereography and a treadmill equipped with an integrated sensor mat. Allowing critical functional postoperative evaluation on a less subjective level may enhance accuracy and reliability of indication for surgery.

This protocol provides guidance on how to perform high resolution video rasterstereography and treadmill gait analysis on patients after lumbar fusion ...

Three-Dimensional Printing Guide Template Assisted Percutaneous Vertebroplasty (PVP)

Percutaneous vertebroplasty (PVP) is considered an effective treatment for the back pain caused by osteoporotic vertebral compression fracture. The accuracy of PVP mainly depends on the surgeons&#39; experience and multiple fluoroscopes during a traditional procedure. Puncture related complications were reported all over the world. To make the surgical procedure more precise and decrease the rate of puncture-related complications, our team applied a three-dimensional printing guide template to PVP to modify the traditional procedure. This protocol introduces how to model target vertebrae DICOM imaging data into three-dimensions in the software, how to simulate operation in this 3-D model, and how to use all of the surgical data to reconstruct a patient specific template for application. Using this template, surgeons can identify suitable puncture points accurately to improve the accuracy of the operation. The whole protocol includes: 1) diagnosis of the osteoporotic vertebral compression fracture; 2) acquisition of CT imaging of the target vertebra; 3) simulation of the operation in the software; 4) design and fabrication of the 3-D printing guide template; and 5) application of the template into an operation procedure.

Three-Dimensional Printing Guide Template Assisted Percutaneous Vertebroplasty PVP

Herein, we present a three-dimensional printing guide template for percutaneous vertebraplasty. A patient with a T11 vertebral compression fracture was selected as a case study.

Percutaneous vertebroplasty (PVP) is considered an effective treatment for the back pain caused by osteoporotic vertebral compression fracture. The ...

3D Printing Model of a Patient's Specific Lumbar Vertebra

Selective dorsal rhizotomy (SDR) is a difficult, risky, and sophisticated operation, in which a laminectomy should not only expose an adequate surgical field of view but also protect the patient&#39;s spinal nerves from injury. Digital models play an important role in the pre-and intra-operation of SDR, because they can not only make doctors more familiar with the anatomical structure of the surgical site, but also provide precise surgical navigation coordinates for the manipulator. This study aims to create a 3D digital model of a patient-specific lumbar vertebra that can be used for planning, surgical navigation, and training of the SDR operation. The 3D printing model is also manufactured for more effective work during these processes.
Traditional orthopedic digital models rely almost entirely on computed tomography (CT) data, which is less sensitive to soft tissues. Fusion of the bone structure from CT and the neural structure from magnetic resonance imaging (MRI) is the key element for the model reconstruction in this study. The patient&#39;s specific 3D digital model is reconstructed for the real appearance of the surgical area and shows the accurate measurement of inter-structural distances and regional segmentation, which can effectively help in the preoperative planning and training of SDR. The transparent bone structure material of the 3D-printed model allows surgeons to clearly distinguish the relative relationship between the spinal nerve and the vertebral plate of the operated segment, enhancing their anatomical understanding and spatial sense of the structure. The advantages of the individualized 3D digital model and its accurate relationship between spinal nerve and bone structures make this method a good choice for preoperative planning of SDR surgery.

This study aims to create a 3D-printed model of a patient-specific lumbar vertebra, which contains both the vertebra and spinal nerve models fused from high-resolution computed tomography (HRCT) and MRI-Dixon data.

Selective dorsal rhizotomy (SDR) is a difficult, risky, and sophisticated operation, in which a laminectomy should not only expose an adequate surgical ...

Biomechanical Analysis of Adjacent Segments after Spinal Fusion Surgery Using a Geometrically Parametric Patient-Specific Finite Element Model

This study aimed to perform a mechanical analysis of adjacent segments after spinal fusion surgery using a geometrically parametric patient-specific finite element model to elucidate the mechanism of adjacent segment degeneration (ASD), thereby providing theoretical evidence for early disease prevention. Fourteen parameters based on patient-specific spinal geometry were extracted from a patient's preoperative computed tomography (CT) scan, and the relative positions of each spinal segment were determined using the image match method. A preoperative patient-specific model of the spine was established through the above method. The postoperative model after L4-L5 posterior lumbar interbody fusion (PLIF) surgery was constructed using the same method except that the lamina and intervertebral disc were removed, and a cage, 4 pedicle screws, and 2 connecting rods were inserted. Range of motion (ROM) and stress changes were determined by comparing the values of each anatomical structure between the preoperative and postoperative models. The overall ROM of the lumbar spine decreased after fusion, while the ROM, stress in the facet joints, and stress in the intervertebral disc of adjacent segments all increased. An analysis of the stress distribution in the annulus fibrosus, nucleus pulposus, and facet joints also showed that not only was the maximum stress in these tissues elevated, but the areas of moderate-to-high stress were also expanded. During torsion, the stress in the facet joints and annulus fibrosus of the proximal adjacent segment (L3-L4) increased to a larger extent than that in the distal adjacent segment (L5-S1). While fusion surgery causes an overall restriction of motion in the lumbar spine, it also causes more load sharing by the adjacent segments to compensate for the fused segment, thus increasing the risk of ASD. The proximal adjacent segment is more prone to degeneration than the distal adjacent segment after spinal fusion due to the significant increase in stress.

Here, we used a patient-specific finite element model to analyze the mechanical changes in adjacent segments after spinal fusion surgery. The results showed that fusion surgery reduced the overall motion of the lumbar spine but increased the load on and stress in adjacent segments, especially the proximal segment.

This study aimed to perform a mechanical analysis of adjacent segments after spinal fusion surgery using a geometrically parametric patient-specific ...

A Mouse Model of Lumbar Spine Instability

Intervertebral disc degeneration (IDD) is a common pathological change leading to low back pain. Appropriate animal models are desired for understanding the pathological processes and evaluating new drugs. Here, we introduced a surgically induced lumbar spine instability (LSI) mouse model that develops IDD starting from 1 week post operation. In detail, the mouse under anesthesia was operated by low back skin incision, L3&#8211;L5 spinous processes exposure, detachment of paraspinous muscles, resection of processes and ligaments, and skin closure. L4&#8211;L5 IVDs were chosen for the observation. The LSI model develops lumbar IDD by porosity and hypertrophy in endplates at an early stage, decrease in intervertebral disc volume, shrinkage in nucleus pulposus at an intermediate stage, and bone loss in lumbar vertebrae (L5) at a later stage. The LSI mouse model has the advantages of strong operability, no requirement of special equipment, reproducibility, inexpensive, and relatively short period of IDD development. However, LSI operation is still a trauma that causes inflammation within the first week post operation. Thus, this animal model is suitable for study of lumbar IDD.

We developed a lumbar intervertebral disc degeneration mouse model by resection of L3&#8211;L5 spinous processes along with supra- and inter-spinous ligaments and detachment of paraspinous muscles.

Intervertebral disc degeneration (IDD) is a common pathological change leading to low back pain. Appropriate animal models are desired for understanding ...

Biology

Pedicle Screw Placement Using an Augmented Reality Head-Mounted Display in a Porcine Model

This protocol helps assess the accuracy and workflow of an augmented reality (AR) hybrid navigation system using the Magic Leap head-mounted display (HMD) for minimally invasive pedicle screw placement. The cadaveric porcine specimens were placed on a surgical table and draped with sterile covers. The levels of interest were identified using fluoroscopy, and a dynamic reference frame was attached to the spinous process of a vertebra in the region of interest. Cone beam computerized tomography (CBCT) was performed, and a 3D rendering was automatically generated, which was used for the subsequent planning of the pedicle screw placements. Each surgeon was fitted with an HMD that was individually eye-calibrated and connected to the spinal navigation system.
Navigated instruments, tracked by the navigation system and displayed in 2D and 3D in the HMD, were used for 33 pedicle cannulations, each with a diameter of 4.5 mm. Postprocedural CBCT scans were assessed by an independent reviewer to measure the technical (deviation from the planned path) and clinical (Gertzbein grade) accuracy of each cannulation. The navigation time for each cannulation was measured. The technical accuracy was 1.0 mm &#177; 0.5 mm at the entry point and 0.8 mm &#177; 0.1 mm at the target. The angular deviation was 1.5&#176; &#177; 0.6&#176;, and the mean insertion time per cannulation was 141 s &#177; 71 s. The clinical accuracy was 100% according to the Gertzbein grading scale (32 grade 0; 1 grade 1). When used for minimally invasive pedicle cannulations in a porcine model, submillimeter technical accuracy and 100% clinical accuracy could be achieved with this protocol.

The augmented reality head-mounted display, Magic Leap, was used in combination with a conventional navigation system to place pedicle screws in a porcine model by adhering to a novel workflow. With a median insertion time of &lt;2.5 min, submillimeter technical accuracy and 100% clinical accuracy were achieved according to Gertzbein.

This protocol helps assess the accuracy and workflow of an augmented reality (AR) hybrid navigation system using the Magic Leap head-mounted display (HMD) ...

Enhancing Pedicle Puncture Precision with 3D Modeling and a Nine-Grid Method

Nine-Grid Area Division Method: A New Ideal Bone Puncture Region for Percutaneous Vertebroplasty in Lumbar Spine

Percutaneous vertebroplasty (PVP) is widely recognized as an efficacious intervention for alleviating low back pain resulting from osteoporotic vertebral compression fractures. The ideal bone puncture point is conventionally situated at the projection "left 10 points, right 2 points" of the pedicle in the lumbar spine. Determining the optimal bone puncture point represents a critical and complex challenge. The accuracy of percutaneous vertebroplasty (PVP) is primarily influenced by the proficiency of the operating surgeons and the utilization of multiple fluoroscopes during the conventional procedure. Incidences of puncture-related complications have been documented globally. In an effort to enhance the precision of the surgical technique and reduce the occurrence of puncture-related complications, our team applied the "Nine-grid Area Division Method" for PVP in the lumbar spine to modify the traditional procedure. There is potential to decrease the number of puncture times, the radiation exposure dosage, and the duration of surgical procedures.
This protocol introduces the definition of the "Nine-grid Area Division Method" and describes the process of modeling target vertebrae DICOM imaging data within medical imaging processing software, simulating operations within a 3-D model, refining the 3-D model using reverse engineering production software, reconstructing the vertebral engineering model within 3-D modeling design software, and utilizing surgical data to determine safe entry regions for pedicle projection. By employing this methodology, surgeons can effectively identify appropriate puncture points with precision and ease, thereby reducing the intricacies associated with puncturing and enhancing the overall accuracy of surgical procedures.

Author Spotlight: Improving Percutaneous Vertebroplasty Surgical Accuracy and Efficiency Through Advanced Puncture Techniques

Herein, we present a "Nine-grid Area Division Method" for percutaneous vertebroplasty. A patient with an L1 vertebral compression fracture was selected as a case study.

Percutaneous vertebroplasty (PVP) is widely recognized as an efficacious intervention for alleviating low back pain resulting from osteoporotic vertebral ...

Precision Measurements and Parametric Models of Vertebral Endplates

Summary

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Chapters in this video

Three and Four-Dimensional Visualization and Analysis Approaches to Study Vertebrate Axial Elongation and Segmentation

Semiautomated Longitudinal Microcomputed Tomography-based Quantitative Structural Analysis of a Nude Rat Osteoporosis-related Vertebral Fracture Model

An Anesthesia, Surgery, and Harvest Method for the Evaluation of Transpedicular Screws Using an In Vivo Porcine Lumbar Spine Model

Evaluation of Patients' Posture and Gait Profile After Lumbar Fusion Surgery by Video Rasterstereography and Treadmill Gait Analysis

Three-Dimensional Printing Guide Template Assisted Percutaneous Vertebroplasty (PVP)

3D Printing Model of a Patient's Specific Lumbar Vertebra

Biomechanical Analysis of Adjacent Segments after Spinal Fusion Surgery Using a Geometrically Parametric Patient-Specific Finite Element Model

A Mouse Model of Lumbar Spine Instability

Pedicle Screw Placement Using an Augmented Reality Head-Mounted Display in a Porcine Model

Nine-Grid Area Division Method: A New Ideal Bone Puncture Region for Percutaneous Vertebroplasty in Lumbar Spine