This protocol uses multi-view stereo to generate three-dimensional (3D) models out of uncalibrated sequences of photographs, making it affordable and adjustable to a surgical setting. Strain maps between the 3D models are quantified with spline-based isogeometric kinematics, which facilitate representation of smooth surfaces over coarse meshes sharing the same parameterization.
Tissue expansion is a popular technique in plastic and reconstructive surgery that grows skin in vivo for correction of large defects such as burns and giant congenital nevi. Despite its widespread use, planning and executing an expansion protocol is challenging due to the difficulty in measuring the deformation imposed at each inflation step and over the length of the procedure. Quantifying the deformation fields is crucial, as the distribution of stretch over time determines the rate and amount of skin grown at the end of the treatment. In this manuscript, we present a method to study tissue expansion in order to gain quantitative knowledge of the deformations induced during an expansion process. This experimental protocol incorporates multi-view stereo and isogeometric kinematic analysis in a porcine model of tissue expansion. Multi-view stereo allows three-dimensional geometric reconstruction from uncalibrated sequences of images. The isogeometric kinematic analysis uses splines to describe the regional deformations between smooth surfaces with few mesh points. Our protocol has the potential to bridge the gap between basic scientific inquiry regarding the mechanics of skin expansion and the clinical setting. Eventually, we expect that the knowledge gained with our methodology will enable treatment planning using computational simulations of skin deformation in a personalized manner.
Tissue expansion is a common technique in plastic and reconstructive surgery that grows skin in vivo for the correction of large cutaneous defects 1. Neumann, in 1957, was the first surgeon to document this procedure. He implanted a balloon below the skin of a patient and inflated it gradually over a period of several weeks to grow new tissue and resurface an ear 2. Skin, like most biological tissues, adapts to applied forces and deformations in order to reach mechanical homeostasis. When stretched beyond the physiological regime, skin grows 3,4. One of the central advantages of tissue expansion is the production of skin with proper vascularization and the same hair bearing, mechanical properties, color, and texture as the surrounding tissue 5.
After its introduction six decades ago, skin expansion has been widely adopted by plastic and reconstructive surgeons and is presently used to correct burns, large congenital defects, and for breast reconstruction after mastectomy 6,7. Yet, despite its widespread use, skin expansion procedures can lead to complications 8. This is partly due to the lack of sufficient quantitative evidence needed to understand the fundamental mechanobiology of the procedure and to guide the surgeon during preoperative planning 9,10. Key parameters in this technique are the filling rate, filling volume per inflation, the selection of the shape and size of the expander, and the placement of the device 11,12. Current preoperative planning relies largely on the physician's experience, resulting in a wide variety of arbitrary protocols that often differ greatly 13,14,15.
To address the current knowledge gaps, we present an experimental protocol to quantify expansion-induced deformation in a porcine animal model of tissue expansion. The protocol relies on the use of multi-view stereo (MVS) to reconstruct three-dimensional (3D) geometries out of sequences of two-dimensional (2D) images with unknown camera positions. Employing splines, representation of smooth surfaces leads to the calculation of the corresponding deformation maps by means of an isogeometric (IGA) description. The analysis of the geometry is based on the theoretical framework of continuum mechanics of membranes having an explicit parameterization 16.
Characterizing physiologically relevant deformations of living materials over long periods of time still remains a challenging problem. Common strategies for imaging of biological tissues include stereoscopic digital image correlation, commercial motion capture systems with reflective markers, and biplane video fluoroscopy 17,18,19. However, these techniques require a restrictive experimental setup, are generally expensive, and have been primarily used for ex vivo or acute in vivo settings. Skin has the advantage of being a thin structure. Even though it consists of several layers, the dermis is largely responsible for the mechanical properties of the tissue and thus the surface deformation is of primary importance 20; reasonable kinematical assumptions can be made regarding the out of plane deformation 21,22. Moreover, skin is already exposed to the outside environment, making it possible to use conventional imaging tools to capture its geometry. Here we propose the use of MVS as an affordable and flexible approach to monitor in vivo deformations of skin over several weeks without interfering majorly with a tissue expansion protocol. MVS is a technique that extracts 3D representations of objects or scenes from a collection of 2D images with unknown camera angles 23. Only in the last three years, several commercial codes have appeared (see list of materials for examples). The high accuracy of the model reconstruction with MVS, with errors as low as 2% 24, makes this approach suitable for the kinematic characterization of skin in vivo over long periods of time.
To obtain the corresponding deformation maps of skin during tissue expansion, points between any two geometric configurations are matched. Conventionally, researchers in computational biomechanics have used finite element meshes and inverse analysis to retrieve the deformation map 25,26. The IGA approach employed here uses spline basis functions which offer several advantages for the analysis of thin membranes 27,28. Namely, the availability of high degree polynomials facilitates representations of smooth geometries even with very coarse meshes 29,30. Additionally, it is possible to fit the same underlying parameterization to all the surface patches, which circumvents the need for an inverse problem to account for non-matching discretizations.
The method described here opens new avenues to study skin mechanics in relevant in vivo settings over long periods of time. In addition, we are hopeful that our methodology is an enabling step towards the ultimate goal of developing computational tools for personalized treatment planning in the clinical setting.
This protocol involves animal experiments. The protocol was approved by the IRB of Ann and Robert H. Lurie Children's Hospital of Chicago Research Center Animal Care and Use Committee to guarantee humane treatment of animals. The results for two expansion studies using this protocol have been published elsewhere 16,31.
Execution of this protocol requires a team with complementary expertise. The first part of the protocol describes the surgical procedure on the animal model, requiring personnel with the appropriate medical training. The subsequent analysis, particularly sections 4 and 5, involve basic computer programming skills in C++ and Python, and use of a command line shell.
1. Surgical Procedure for Expander Placement
NOTE: Personnel involved in the operation must be scrubbed and gowned in a sterile fashion. Sterile towels and drapes are applied around the surgical field to maintain sterility. All instruments, sutures, and tissue expanders are received in sterile packaging and handled only by sterile personnel. Sterility of the operative site must not be violated until the procedure is complete.
2. Inflation Protocol
NOTE: The timing of the inflations and amount of solution used in each expander depends on the specific question being studied. To characterize the effect of different expander geometries, a suitable protocol is to perform five inflation steps at 0, 2, 7, 10, and 15 days to achieve filling volumes of 50, 75, 105, 165, and 225 cc respectively.
3. Multi-view Stereo Reconstruction
4. Spline Surface Fit
5. Quantification of Expansion-induced Deformation
This methodology has been successfully employed to study the deformation induced by different expander geometries: rectangle, sphere and crescent expanders 31,32. The results corresponding to the sphere and crescent expanders are discussed next. Figure 2 illustrates the three steps of MVS model reconstruction. The starting point is a collection of photographs from a static scene. The animal with the tattooed grids and the tape measures was lying still as the photographs were taken from different angles. The MVS algorithm matched features between the photographs to extract 3D coordinates. As a result, a geometric model consisting of a triangular mesh with texture was generated.
The protocol described here can be used to investigate different aspects of the tissue expansion process. The variations in regional strains induced by sphere and crescent expanders is one important aspect of the expansion process since it leads to regional variations in the amount of skin grown. Both devices were filled to the same volume at every time point. Five inflation steps were performed at 0, 2, 7, 10, and 15 days to generate filling volumes of 50, 75, 105, 165, and 225 cc. Figure 3 shows photographs of the expanded skin grids at the end of each inflation step. The expanders stretched the skin and the deformation was apparent by the distortion of the grid over time.
For every configuration of the grid a spline surface was generated as described in the Protocol section. Deformations were calculated by choosing a reference and a deformed grid as illustrated in Figure 1. The results of two different types of analyses are discussed here. To study the chronic deformation, the pig at day 0 was selected as the reference configuration and compared to all other time points. Comparing the end of every inflation step to the reference configuration results in the contour plots shown in Figure 4. The methodology presented here extracts three measures of deformation. The area change is denoted θ, the stretch in the longitudinal direction is termed λG1, and λG2 is the stretch in the transverse direction, as shown in Figure 1. The progression of the area changes and stretches in the two orthogonal directions for sphere and crescent expanders are depicted in Figure 4. Spline surfaces are generally smooth and therefore the corresponding contour plots were smooth. Nonetheless, the coarseness of the mesh was evidenced by the contours which showed spot features. A finer grid would increase the fidelity of the deformation maps. Nevertheless, the differences between different expander geometries was immediately apparent and quantifiable. Even though both expanders were filled to the same volume, the spherical expander induced a larger deformation. The spatial variation of the contour plots revealed that skin was stretched more at the center of the expander compared to the periphery of the grid. Results are summarized in Table 1.
A second analysis consisted of determining the acute deformation at every inflation step. In this case, the reference configuration was the grid just prior to expansion, and the deformed grid was that immediately after the inflation step. The deformations induced at every inflation step were remarkably similar on average between the different time points. The summary is contained in Table 2. On average, the deformation was close to 1 (where 1 would be the absence of deformation). Inspection of the contour maps shown in Figure 5 showcased evident spatial variations. Even though there was almost no deformation on average, some zones of the grid were stretched while others were shrunk with respect to the reference. Similar to the analysis of the chronic deformation, the center regions were the ones being stretched the most.
In both the acute and chronic cases, longitudinal and transverse stretches showed a clear trend indicative of anisotropy. Skin, as most collagenous tissues, shows a preferred fiber orientation contributing to an anisotropic mechanical response 25. In the case of skin in the back of a pig, fibers are thought to be aligned transversely 33. Our experiments showed that during skin expansion, the stretches in the longitudinal directions were always greater than those along the transverse direction. This was true for both the sphere and the crescent expanders, at all time points, and for the acute and chronic deformation contours. This result supports the hypothesis that skin anisotropy can impact the deformations induced during a tissue expansion procedure.
Figure 1: Grid Configurations and Parameter Space. Grids are tattooed on the back of the animals and photographed with tape measures in place in order to scale the geometric models (top). Deformation between a reference and a deformed configuration is characterized by three variables: area change θ, longitudinal stretch λG1, and transverse stretch λG2 (top). The grid is consistently parameterized by numbering the points always from caudal to rostral and from dorsal to ventral directions (bottom left). The output of the analysis is a contour plot over the parameter space. The contours are marked at the corners with one pixel which takes the color black, red, green, and blue, to facilitate identification of caudal, rostral, dorsal, and ventral sides (bottom right). Please click here to view a larger version of this figure.
Figure 2: Multi-view Stereo Reconstruction of an Expansion Process. MVS is an algorithm from computer vision that takes as input photographs from different angles with unknown camera positions (left). The algorithm matches features across the images to find 3D coordinates (center). The output of the algorithm is a triangular mesh with the texture overlaid (right). (Figure adapted with permission from 31) Please click here to view a larger version of this figure.
Figure 3: Expansion of Sphere and Crescent Expanders. Sphere (top row) and crescent (bottom row) expanders were placed below the tattooed skin on the back of a pig and inflated at days 0, 2, 7, 10, and 15 days to generate filling volumes of 50, 75, 105, 165, and 225 cc. (Figure adapted with permission from 31). Please click here to view a larger version of this figure.
Figure 4: Chronic Deformation Induced by Sphere and Crescent Expanders. The tattooed grids were converted to spline surfaces for analysis (rows 1 and 2). Taking the reference to be the grid at day 0, three measures of deformation were calculated. Area change showed progressively higher values over time, with higher deformation in the center region of the expander, and higher deformation in the sphere compared to the crescent (rows 3 and 4). Longitudinal stretches (rows 5 and 6) resembled area stretches while transverse stretches (rows 7 and 8) showed bands of deformation and less stretch compared to the longitudinal direction. (Figure adapted with permission from 31) Please click here to view a larger version of this figure.
Figure 5: Acute Deformation Induced by Sphere and Crescent Expanders. Taking as reference the configuration just prior to an inflation step, and as deformed the configuration immediately after injection of solution into an expander, acute deformations were calculated. Deformation maps were smooth, however, some edge effects were noticeable and the coarseness of the discretization was reflected in spot-like patterns of deformation. Area changes (rows 1 and 2) showed regional variation, with higher stretch in the region corresponding to the expander. Stretches were similar across the different time points. The same trend could be seen for longitudinal stretches (rows 3 and 4). Transverse stretches (rows 5 and 6) showed more uniform distributions and lower values compared to the longitudinal case. (Figure adapted with permission from 31) Please click here to view a larger version of this figure.
Time [days] | Expander | Volume [cc] | Area change θ | Longitudinal stretch λG1 | Transverse stretch λG2 | ||||||
max | min | avg | max | min | avg | max | min | avg | |||
0 | sphere | 50 | 1.44 | 0.71 | 0.98 | 1.37 | 0.76 | 1 | 1.17 | 0.84 | 0.97 |
0 | crescent | 50 | 1.46 | 0.76 | 0.98 | 1.24 | 0.79 | 1 | 1.17 | 0.84 | 0.98 |
2 | sphere | 75 | 1.74 | 0.68 | 1.08 | 1.51 | 0.73 | 1.08 | 1.19 | 0.75 | 1 |
2 | crescent | 75 | 1.43 | 0.66 | 1 | 1.31 | 0.65 | 1 | 1.26 | 0.77 | 1 |
7 | sphere | 105 | 0.01 | 0.69 | 1.21 | 1.7 | 0.75 | 1.13 | 1.32 | 0.84 | 1.07 |
7 | crescent | 105 | 1.66 | 0.83 | 1.15 | 1.4 | 0.87 | 1.11 | 1.33 | 0.86 | 1.03 |
10 | sphere | 165 | 2.26 | 0.74 | 1.36 | 1.76 | 0.77 | 1.21 | 1.39 | 0.83 | 1.11 |
10 | crescent | 165 | 1.86 | 0.87 | 1.26 | 1.58 | 0.8 | 1.15 | 1.45 | 0.83 | 1.09 |
15 | sphere | 225 | 2.77 | 0.72 | 1.52 | 2.01 | 0.69 | 1.29 | 1.47 | 0.89 | 1.18 |
15 | crescent | 225 | 1.87 | 0.83 | 1.32 | 1.46 | 0.84 | 1.17 | 1.44 | 0.92 | 1.14 |
21 | sphere | 225 | 3.09 | 0.93 | 1.7 | 2.13 | 0.9 | 1.33 | 1.62 | 0.98 | 1.27 |
21 | crescent | 225 | 2.25 | 0.87 | 1.49 | 1.66 | 0.85 | 1.25 | 1.67 | 0.96 | 1.2 |
Table 1: Summary of Chronic Deformation. Strains were calculated taking the initial configuration as the reference and comparing the patches at the end of each inflation step with respect to it. The average of the deformation attributed to the sphere expander reached 1.70 at day 21 while the crescent expander deformed 1.49 in area by the end of expansion. There was significant spatial variation and maximum and minimum values varied with respect to the average. The longitudinal stretches reached 1.33 and 1.25 for the sphere and crescent expanders respectively, while transverse stretches were lower, with values of 1.27 and 1.20. (Table adapted with permission from 31)
Time [days] | Expander | Volume [cc] | Area change θ | Longitudinal stretch λG1 | Transverse stretch λG2 | ||||||
max | min | avg | max | min | avg | max | min | avg | |||
0 | sphere | 50 | 1.32 | 0.72 | 0.98 | 1.44 | 0.75 | 1 | 1.23 | 0.83 | 0.97 |
0 | crescent | 50 | 1.5 | 0.71 | 0.98 | 1.3 | 0.8 | 1 | 1.21 | 0.84 | 0.98 |
2 | sphere | 75 | 1.36 | 0.69 | 0.98 | 1.26 | 0.66 | 1 | 1.2 | 0.8 | 0.98 |
2 | crescent | 75 | 1.31 | 0.61 | 0.98 | 1.24 | 0.8 | 1.01 | 1.34 | 0.68 | 0.97 |
7 | sphere | 105 | 1.4 | 0.79 | 0.98 | 1.3 | 0.57 | 1 | 1.2 | 0.77 | 0.98 |
7 | crescent | 105 | 1.37 | 0.59 | 1 | 1.6 | 0.83 | 1.02 | 1.16 | 0.77 | 0.98 |
10 | sphere | 165 | 1.6 | 0.73 | 1.01 | 1.35 | 0.6 | 1.02 | 1.25 | 0.75 | 0.99 |
10 | crescent | 165 | 1.48 | 0.58 | 1.01 | 1.42 | 0.75 | 1.02 | 1.22 | 0.77 | 1 |
15 | sphere | 225 | 1.27 | 0.73 | 1.01 | 1.35 | 0.55 | 1.02 | 1.22 | 0.79 | 0.98 |
15 | crescent | 225 | 1.34 | 0.54 | 1.02 | 1.37 | 0.8 | 1.02 | 1.32 | 0.81 | 1 |
Table 2: Summary of Acute Deformation. Strains were calculated taking the configuration prior to expansion as the reference and the configuration immediately after the inflation step as the deformed grid. On average, both the sphere and crescent expanders showed similar trends, with values close to 1 which would indicate no deformation. However, due to spatial variations, we measured maximum area changes were as high as 1.60 for the sphere and 1.50 for the crescent. The stretches in the longitudinal and transverse directions were anisotropic, with the maximum values of longitudinal stretches almost always higher than the transverse stretches. (Table adapted with permission from 31)
Here we presented a protocol to characterize the deformations induced during a tissue expansion procedure in a porcine model using multi-view stereo (MVS) and isogeometric kinematics (IGA kinematics). During tissue expansion, skin undergoes large deformations going from a smooth and relatively flat surface to a dome-like 3D shape. Skin, like other biological membranes 34, responds to stretch by producing new material, increasing in area that can be then used for reconstructive purposes 35. Therefore, accurate determination of the stretch produced by an expander is crucial to understand the mechanisms that regulate the adaptation of skin. Planning an expansion procedure is challenging because tissue expanders come in different sizes and shapes, the stretch distribution is not uniform over the entire expanded area and it depends on the location and rate of inflation 11,36. Having a protocol to accurately estimate expansion-induced deformation and capable of resolving large strains, 3D shapes, and regional variations, opens new avenues to study the mechanical regulation of skin growth, and can eventually lead to quantitative preoperative planning tools. Towards that goal, we developed a non-invasive, affordable, and flexible methodology to measure deformation in a porcine model of skin expansion 32.
Critical Steps
Animal models for tissue expansion have been well characterized for more than two decades 37. Porcine skin shows comparable properties to human integument. Furthermore, skin expansion in pigs follows a similar procedure as it would be done in humans 38. The tissue expansion procedure is the cornerstone for the success of this protocol. Experienced surgeons, experts in tissue expansion, performed the technique in the animal model presented here.
Skin is conveniently exposed to the outside environment and it is a thin membrane, therefore its deformation can be characterized by tracking points on its surface 17. MVS offers a flexible and affordable technique to study 3D skin deformations in vivo over long periods of time. This algorithm takes as input a set of photographs from a static scene and uses feature matching across the photographs to extract 3D coordinates. MVS reconstruction and the subsequent kinematic analysis critically depend on the photo acquisition steps of this protocol.
Modifications and Troubleshooting
During tissue expansion, the device can migrate away from the grid due to animal movement and loosening of the pocket in which the expander was originally placed. If the expanded area moves outside of the grid, the expander should be deflated and removed. This problem has been encountered using the protocol in one out of eight grids 31,32. Expanders can also leak if they are defective or punctured during the inflation protocol. This also compromises the validity of the experiment and the safety of the animal, therefore the expander should be removed. This problem has been encountered using this protocol in one out of eight grids 31,32.
MVS reconstruction can be challenging for some sets of photographs due to lighting effects, lack of focus, and background noise 23. Even though the commercial tools for MVS are powerful, if the results are not accurate enough at first, the following troubleshooting steps have always corrected the problem in on our experience: manually remove the background in the photographs; select a subset of photographs with sharper focus and discard blurry images; manually select matching points across photographs in the commercial software interface.
Limitations of the Technique
As discussed above, porcine integument is similar to human 38, nevertheless, there are still differences. Therefore, a porcine model is not expected to be fully predictive of human tissue expansion protocols 37. Another limitation of the protocol is the lack of commercial tools or user-friendly software to analyze the geometric models. Currently, once the geometry is generated through MVS, the analysis is performed with in-house code which consists of C++ and Python scripts. While on the one hand, the proposed method is creative and offers an affordable, convenient way to study the mechanics of soft tissue over long periods of time, the data analysis is dependent on technologies which have only been popular for the past decade 27. To circumvent this limitation, we provide our implementation of spline subroutines with this submission. One more limitation is the restriction of a tattooed grid in order to track chronic deformations. The need for a tattooed grid hinders the translation of the protocol to clinical settings.
Significance of the Technique with Respect to Existing/Alternative Methods
Currently, physicians rely mostly on their experience during preoperative planning of tissue expansion procedures, which has led to a wide variety of arbitrary protocols that often differ greatly 13,14,15. The protocol presented here addresses existing knowledge gaps by quantifying expansion-induced deformation in a porcine animal model of tissue expansion. To the author's knowledge, this is the first protocol to quantify continuous deformation maps on sizable patches of skin tissue 31,32.
The protocol is innovative, non-invasive, affordable and flexible; it relies on recent developments in computer vision algorithms such as MVS, and numerical analysis such as IGA kinematics. MVS has advanced intensely in the past decade, reaching reconstruction errors as low as 2% 24. The rise in commercially available software as well as open source code showcases the high popularity of this method 41. MVS is affordable because it requires only a digital camera and photographs are taken without calibration of the camera position. In contrast, other techniques such as stereo reconstruction require additional hardware to control the location of the camera 17. MVS is flexible because it can be performed in a variety of scenarios as long as photographs can be taken from different angles. This is a feature that becomes more relevant when considering a potential clinical application. In contrast, other techniques such as motion tracking require a specific setup and cannot be performed in an arbitrary location 18. One more feature of MVS is the production of 3D geometries. Other techniques, such as digital image correlation (DIC), are preferred for 2D motion tracking 39. The results presented here showcased the ability of commercial algorithms to faithfully reconstruct the 3D shapes induced during tissue expansion.
From the 3D geometries, deformations have to be calculated. This protocol relies on the use of spline surface IGA kinematics. Splines are useful because a few control points parameterize smooth geometries with high continuity which are needed for analysis of thin membranes 40. The greatest advantage of splines in this application is the notion of a parametric space. Other techniques, such as finite elements, lack a global parameter domain. While this is convenient for certain problems such as simulation of irregular patches (for example patches with holes), having an explicit parameterization allows determination of stretches between any two configurations in a straightforward manner. For instance, two different analyses were shown here: chronic and acute deformations. To calculate the strains in the grids with this protocol it is enough to provide the splines of the two surfaces of interest since all the surfaces have the same parameter domain.
During tissue expansion, skin responds to the applied deformation by growing in surface area, producing new integument that can then be employed for reconstructive surgery. Characterizing clinically relevant deformations of skin over long periods of time can improve our understanding of the mechanobiology of this organ as well as enable the development of quantitative preoperative tools. The protocol described here specifically addresses the need of an experimental design with potential translation to the clinical setting.
Future Applications or Directions after Mastering this Technique
The source code that is used in this protocol could easily be adjusted to other applications and could be incorporated into more user-friendly implementations. Provided with this paper are routines to evaluate spline basis functions, parameterize continuous fields over spline surfaces, integrate those continuous fields, and calculate deformation gradients, membrane and bending strains. We expect that this source code will continue to evolve towards a tool that can be eventually used in real clinical applications of tissue expansion as well as enable other applications. Another future area of work is the refinement of this protocol to take into consideration mechanical properties and stresses in the tissue and not only kinematics.
From a clinically relevant perspective, this protocol is able to quantify regional variations of tissue deformation, as well as differences between different expander shapes and inflation rates 31,32. Further work is needed to continue to evaluate the effect of different expansion parameters on the tissue response. Moreover, further refinement of the porcine model with emphasis on the biological mechanisms of adaptation can help elucidate fundamental mechanisms regulating skin adaptation to overstretch. The ultimate goal is to validate the protocol in a porcine model in order to translate it to the clinical setting.
The authors have nothing to disclose.
This work was supported by NIH grant 1R21EB021590-01A1 to Arun Gosain and Ellen Kuhl.
Yucatan miniature swine | Sinclair Bioresources, Windham, ME | N/A | |
Antibiotics | Santa Cruz Animal Health, Paso Robles, CA | sc-362931Rx | Ceftiofur, dosage 5mg/kg intramuscular |
Chlorhexidine-based surgical soap | Cardinal Health, Dublin, OH | AS-4CHGL(4-32) | 4% chlorhexidine gluconate surgical hand scrub |
Tattoo transfer medium | Hildbrandt Tattoo Supply, Point Roberts, WA | TRANSF | Stencil thermal tattoo transfer paper |
Lidocaine with epinephrine | ACE Surgical Supply Co, Brockton, MA | 001-1423 | Lidocaine Hcl 1% (Xylocaine) – Epinephrine 1:100,000, 20ml |
Buprenorphine | ZooPharm, Windsor, CO | 1 mg/ml sustained release, dosage 0.01 mg/kg intramuscular | |
Digital camera | Sony | Alpha33 | Standard digital camera with 18-35mm lens, 3.5-5.6 aperture. Used in automatic mode, no flash |
Tape measure | Medline, Mundelein, Illinois | NON171330 | Retractable tape measure, cloth, plastic case, 72inches |
Tissue expanders | PMT, Chanhassen, MN | 03610-06-02 | 4cm x 6cm, rectangular, 120cc, 3610 series 2 stage tissue expander with standard port |
ReCap360 | Autodesk | N/A | MVS Software, Web application: recap360.autodesk.com |
Blender | Blender Foundation | N/A | Computer Graphics Software, open source: blender.org |
SISL | SINTEF | N/A | C++ spline libraries, open source: https://www.sintef.no/projectweb/geometry-toolkits/sisl/ |