Research reported in this publication was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases under award number R01AR051912. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (NIH).

The authors have no conflicts of interest.

The technique described here overcomes several disadvantages associated with conventional techniques for assessing shoulder motion (i.e., cadaveric simulations, 2D imaging, static 3D imaging, video-based motion capture systems, wearable sensors, etc.) by providing accurate measures of 3D joint motion during dynamic activities. The accuracy of the protocol described herein was established for the glenohumeral joint against the gold standard of radiostereometric analysis (RSA) to be &#177;0.5&#176; and &#177;0.4 mm67,68. Similar protocols have been developed for other joints such as the knee69, spine70, and foot/ankle71. Importantly, without a system that is sufficiently accurate, the sample size necessary to detect statistically significant and clinically potential meaningful differences in joint motion could be prohibitive. Furthermore, this level of accuracy affords the ability to describe potentially important outcome measures such as joint positions and/or translations62,72, arthrokinematics72,73,74,75, subacromial distances61,72,75, and instantaneous axes of motion76. Ultimately, accurately measuring in-vivo joint motion is essential for providing a mechanistic understanding of shoulder function under normal and pathologic conditions, and for assessing the effects of non-surgical and surgical clinical interventions.
The accuracy afforded by quantifying shoulder kinematics using biplane videoradiography comes with many challenges and limitations. The primary limitation associated with this technique is the radiation exposure to the participant as a result of the CT scan and biplane x-ray imaging. Consequently, the number of motion trials that can be acquired or follow-up sessions over time is limited. The effective dose corresponding with the protocol described here is approximately 10.5 mSv, with the majority (approximately 10 mSv) coming from the CT scan, which includes imaging of the distal humerus so that the epicondyles can be used to construct the humeral anatomical coordinate system64. For context, this dose corresponds to approximately 3 years of exposure to natural background sources of radiation. Recent recommendations of the National Council on Radiation Protection and Measurements suggest this dose can be classified as &#34;minor&#34; assuming a moderate expected benefit to the individual or society77. Consequently, it is imperative that motion analysis using biplane videoradiography be used in a well-designed study based on a solid scientific premise that has the potential to have an significant impact on public health.
Reducing the dose associated with biplane videoradiography is crucial to facilitate the broader use of this technology in research and clinical settings. Fortunately, recent advances in CT and MR imaging may substantially reduce the dose to the participant. For example, humeral and scapular bone models derived using MRI78,79 or lower dose CT80 have been shown to have acceptable accuracy for many research applications. Furthermore, redefining the humeral coordinate system in a manner that does not require the humeral epicondyles81 will decrease the dose by reducing the CT imaging volume. Careful practice of motion trials before acquiring any images is also crucial to ensure that each collected trial has value and does not unnecessarily add to the participant&#39;s total dose. Ultimately, carefully considering these factors, and many others, is critical when responsibly using biplane videoradiography to quantify 3D kinematics in human research participants.
The participant&#39;s body habitus and differences in tissue density (and therefore image brightness) between the central torso and the lateral aspect of the shoulder presents additional challenges when quantifying shoulder motion using biplane videoradiography. In particular, clear visualization of the scapula and ribs is often challenging using the radiographic technique described in this protocol (i.e., ~70 kVp, 320 mA, 2 ms pulsed exposure) in individuals with high BMI (&#62;30 kg/m2) and women with large or dense breast tissue. Kinematic tracking accuracy likely deteriorates without clear visualization of bone edges. Consequently, careful selection of participants by restricting BMI can ameliorate many of these challenging imaging considerations. However, &#34;washout&#34; of the lateral acromion at lower angles of humeral elevation is common even in participants of healthy body habitus (Figure 2A, green system at Frame 1). This is because there is little tissue (and thus density) around the acromion when the humerus is at lower angles of elevation, and visibility of this region is conceded in order to visualize the scapula and ribs. However, once the humerus elevates and the bulk of the shoulder in projected onto itself (thus increasing radiographic density), the acromion becomes well-visualized. Therefore, the optimal radiographic technique for a motion trial does not necessarily guarantee visualization of all bones at all times, but allows for the clear visualization of enough bony anatomy to conduct markerless tracking.
Another challenge when using biplane videoradiography is the relatively small 3D imaging volume, which is predominantly defined by the image receptor size, the orientation of the two imaging systems, and the SID. Although limiting the 3D imaging volume helps control the radiation dose (i.e., through collimation), a small imaging volume may restrict the range over which joint motion can be acquired and/or the types of tasks being assessed. For example, tasks that require trunk motion (e.g., throwing) may be incompatible with biplane videoradiography motion analysis because the participant will likely move outside of the 3D imaging volume while performing the task. Patient movement outside the imaging volume is common even in simpler tasks such as raising the arm, especially in individuals whose humeral elevation range of motion is significantly impaired (e.g., due to massive rotator cuff tears, adhesive capsulitis, OA), because these individuals often compensate by leaning to the contralateral side. Consequently, careful positioning of the participant within the imaging volume and verbal cues to avoid leaning are crucial steps in the data collection process (section 2.4).
The small 3D imaging volume also limits the visualization of other segments that may be of interest. For example, tracking the torso is necessary to quantify scapulothoracic and humerothoracic kinematics. The protocol described in this article addresses this challenge by tracking the third and fourth ribs. However, other investigators have tracked the torso using an external surface-based tracking system synced with the radiographic system49,50,62. Each of these approaches has unique limitations. For example, tracking the ribs requires good visualization of the central torso, which is challenging in individuals with larger body habitus without washing out the lateral shoulder, as previously described. Furthermore, tracking the ribs may be challenging with a smaller image intensifier (i.e., less than 40 cm). In contrast, tracking torso motion using surface sensors introduces skin motion artifact. Regardless of the approach used, the limited 3D imaging volume remains a challenge when quantifying shoulder kinematics using biplane videoradiography.
In summary, biplane videoradiography allows for highly accurate quantification of shoulder kinematics. Variations in the protocol described herein has been used for numerous studies within the lab58,59,72,73,82, with each protocol variation carefully constructed based on the specific research aims in order to minimize dose, maximize image quality, and maximize segment visibility. Ultimately, accurately measuring in-vivo joint motion is important for providing a mechanistic understanding of shoulder function under normal and pathologic conditions, and for assessing the effects of non-surgical and surgical clinical interventions.

The shoulder is one of the human body&#39;s most complex joint systems, with motion occurring through the coordinated actions of four individual joints, multiple ligaments, and approximately 20 muscles. The shoulder also has the greatest range of motion of the body&#39;s major joints and is often described as a compromise between mobility and stability. Unfortunately, shoulder pathologies are common, resulting in substantial pain, disability, and decreased quality of life. For example, rotator cuff tears affect about 40% of the population over age 601,2,3, with approximately 250,000 rotator cuff repairs performed annually4, and an estimated economic burden of $3-5 billion per year in the United States5. Additionally, shoulder dislocations are common and are often associated with chronic dysfunction6. Lastly, glenohumeral joint osteoarthritis (OA) is another significant clinical problem involving the shoulder, with population studies indicating that roughly 15%-20% of adults over the age of 65 have radiographic evidence of glenohumeral OA7,8. These conditions are painful, impair activity levels, and decrease quality of life.
Although the pathogeneses of these conditions are not fully understood, it is generally accepted that altered shoulder motion is associated with many shoulder pathologies9,10,11. Specifically, abnormal joint motion may contribute to the pathology9,12, or that the pathology may lead to abnormal joint motion13,14. Relationships between joint motion and pathology are likely complex, and subtle alterations in joint motion may be important in the shoulder. For example, although angular motion is the predominant motion occurring at the glenohumeral joint, joint translations also occur during shoulder motion. Under normal conditions these translations likely do not exceed several millimeters15,16,17,18,19, and therefore may be below the level of in-vivo accuracy for some measurement techniques. While it may be tempting to assume that small deviations in joint motion may have little clinical impact, it is important to also recognize that the cumulative effect of subtle deviations over years of shoulder activity may exceed the individual&#39;s threshold for tissue healing and repair. Furthermore, in-vivo forces at the glenohumeral joint are not inconsequential. Using custom instrumented glenohumeral joint implants, previous studies have shown that raising a 2 kg weight to head height with an outstretched arm can result in glenohumeral joint forces that can range from 70% to 238% of body weight20,21,22. Consequently, the combination of subtle changes in joint motion and high forces concentrated over the glenoid&#39;s small load-bearing surface area may contribute to the development of degenerative shoulder pathologies.
Historically, the measurement of shoulder motion has been accomplished through a variety of experimental approaches. These approaches have included the use of complex cadaveric testing systems designed to simulate shoulder motion23,24,25,26,27, video-based motion capture systems with surface markers28,29,31, surface-mounted electromagnetic sensors32,33,34,35, bone pins with reflective markers or other sensors attached36,37,38, static two-dimensional medical imaging (i.e., fluoroscopy39,40,41 and radiographs17,42,43,44,45), static three-dimensional (3D) medical imaging using MRI46,47, computed tomography48, and dynamic, 3D single plane fluoroscopic imaging49,50,51. More recently, wearable sensors (e.g., inertial measurement units) have gained popularity for measuring shoulder motion outside the laboratory setting and in free-living conditions52,53,54,55,56,57.
In recent years, there has been a proliferation of biplane radiographic or fluoroscopic systems designed to accurately measure dynamic, 3D in-vivo motions of the shoulder58,59,60,61,62. The purpose of this article is to describe the authors&#39; approach for measuring shoulder motion using a custom biplanar videoradiography system. The specific objectives of this article are to describe the protocols to acquire biplanar videoradiographic images of the shoulder complex, acquire CT scans, develop 3D bone models, locate anatomical landmarks, track the position and orientation of the humerus, scapula, and torso from the biplanar radiographic images, and calculate kinematic outcome measures.

<table><tbody><tr><td>Calibration cube</td><td>Built in-house</td><td>N/A</td><td>10 cm Lucite box with a tantalum bead in each corner and four additional beads midway along the box&amp;rsquo;s vertical edges (12 beads total). The positions of each bead are precisely known relative to a corner of the box that serves as the origin of the laboratory coordinate system.</td></tr><tr><td>Distortion correction grid</td><td>Built in-house</td><td>N/A</td><td>Lucite sheet that covers the entire face of the 16 inch image intensifier and contains an orthogonal array of tantalum beads spaced at 1 cm.</td></tr><tr><td>ImageJ</td><td>National Institutes of Health</td><td>N/A</td><td>Image processing software used to prepare TIFF stack of bone volumes.</td></tr><tr><td>Markerless Tracking Workbench</td><td>Custom, in house software</td><td>N/A</td><td>A workbench of custom software used to digitize anatomical landmarks on 3D bone models, constructs anatomical coordinate systems, uses intensity-based image registration to perform markerless tracking, and calculates and visualize kinematic outcomes measures.</td></tr><tr><td>MATLAB</td><td>Mathworks, Inc</td><td>N/A</td><td>Computer programming software. For used to perform data processing and analysis.</td></tr><tr><td>Mimics (version 20)</td><td>Materialise, Inc</td><td>N/A</td><td>Image processing software used to segment humerus, scapula, and ribs from CT scan.</td></tr><tr><td>Open Inventor</td><td>Thermo Fisher Scientific</td><td>N/A</td><td>3D graphics program used to visualize bones</td></tr><tr><td>Phantom Camera Control (PCC) software (version 3.4)</td><td></td><td>N/A</td><td>Software for specifying camera parameters, and acquiring and saving radiographic images</td></tr><tr><td>Pulse generator (Model 9514)</td><td>Quantum Composers, Inc.</td><td>N/A</td><td>Syncs the x-ray and camera systems and specifies the exposure time</td></tr><tr><td>Two 100 kW pulsed x-ray generators (Model CPX 3100CV)</td><td>EMD Technologies</td><td>N/A</td><td>Generates the x-rays used to produce radiographic images</td></tr><tr><td>Two 40 cm image intensifiers (Model P9447H110)</td><td>North American Imaging</td><td>N/A</td><td>Converts x-rays into photons to produce visible image</td></tr><tr><td>Two Phantom VEO 340 cameras</td><td>Vision Research</td><td>N/A</td><td>High speed cameras record the visible image created by the x-ray system</td></tr></tbody></table>

measuring 3d in-vivo shoulder kinematics using biplanar videoradiography

The shoulder is one of the human body's most complex joint systems, with motion occurring through the coordinated actions of four individual joints, multiple ligaments, and approximately 20 muscles. Unfortunately, shoulder pathologies (e.g., rotator cuff tears, joint dislocations, arthritis) are common, resulting in substantial pain, disability, and decreased quality of life. The specific etiology for many of these pathologic conditions is not fully understood, but it is generally accepted that shoulder pathology is often associated with altered joint motion. Unfortunately, measuring shoulder motion with the necessary level of accuracy to investigate motion-based hypotheses is not trivial. However, radiographic-based motion measurement techniques have provided the advancement necessary to investigate motion-based hypotheses and provide a mechanistic understanding of shoulder function. Thus, the purpose of this article is to describe the approaches for measuring shoulder motion using a custom biplanar videoradiography system. The specific objectives of this article are to describe the protocols to acquire biplanar videoradiographic images of the shoulder complex, acquire CT scans, develop 3D bone models, locate anatomical landmarks, track the position and orientation of the humerus, scapula, and torso from the biplanar radiographic images, and calculate the kinematic outcome measures. In addition, the article will describe special considerations unique to the shoulder when measuring joint kinematics using this approach.

A 52-year-old asymptomatic female (BMI = 23.6 kg/m2) was recruited as part of a previous investigation and underwent motion testing (coronal plane abduction) on her dominant (right) shoulder65. Prior to data collection, the participant provided written informed consent. The investigation was approved by Henry Ford Health System&#39;s Institutional Review Board. Data collection was performed using the protocol previously described (Figure 3).
The participant&#39;s glenohumeral, scapulothoracic, and humerothoracic kinematics are presented in Figure 7, Figure 8, and Figure 9, respectively. Visual inspection of glenohumeral and scapulothoracic kinematics suggests the participant&#39;s shoulder motion was consistent with what is generally expected during coronal plane abduction66. Specifically, glenohumeral motion consisted of elevation and slight external rotation, and was generally in a plane posterior to the scapula (Figure 7), while scapulothoracic motion consisted of upward rotation, posterior tilt, and slight internal/external rotation (Figure 8).
During the motion trial, the minimum subacromial distance (i.e., narrowest width of the subacromial outlet for a given frame) ranged from 1.8 mm at 74.0&#176; humerothoracic elevation (frame 45) to 8.3 mm at 134.0&#176; humerothoracic elevation (frame 89) (Figure 10A, Figure 11A). The average subacromial distance (i.e., average width of the subacromial outlet within the specified 200 mm2 measurement area) tended to follow a similar trajectory as the minimum distance metric. For example, the average subacromial distance ranged from 4.2 mm at 75.4&#176; humerothoracic elevation (frame 46) to 9.2 mm at 134.0&#176; humerothoracic elevation (frame 89). Finally, the minimum subacromial distance tended to follow a complementary trajectory to the surface area metric (Figure 10B) such that the minimum distance tended to be smaller when the surface area is larger. Plotting the location of the minimum distance on the humeral head suggests the location closest to the acromion shifts laterally across the rotator cuff footprint as the humerothoracic elevation angle increases (Figure 11A). Across the motion trial, the contact path length measured 40.5 mm on the humeral head and 28.8 mm on the acromion.
During the motion trial, the minimum glenohumeral distance (i.e., narrowest width of the glenohumeral joint space) ranged from 1.0 mm at 137.9&#176; humerothoracic elevation (frame 92) to 2.1 mm at 34.2&#176; humerothoracic elevation (frame 21) (Figure 12A, Figure 11B). As with the subacromial distances, the average glenohumeral distance tended to follow a similar trajectory as the minimum distance metric, and these distances followed a complementary trajectory with the surface area metric (Figure 12B). For example, the average glenohumeral distance ranged from 1.4 mm at 137.9&#176; humerothoracic elevation (frame 92) to 2.6 mm at 23.5&#176; humerothoracic elevation (frame 12). Plotting the location of the glenohumeral contact center relative to the glenoid edge contours suggest that the participant&#39;s arthrokinematics included moderate surface interactions. Specifically, the humerus stayed relatively centered in the glenoid in the anterior/posterior direction but shifted superiorly and then inferiorly during the motion trial (Figure 11B). Across the motion trial, the contact path length measured 30.0 mm on the glenoid and 45.4 mm on the humeral head.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62210/62210fig01.jpg" /> 
Figure 1: The CT field of view. (A) coronal, (B) sagittal, and (C) transverse planes. During acquisition, the CT technologist ensures the field of view includes the clavicle (superiorly), the distal humeral epicondyles (inferiorly), the entire glenohumeral joint (laterally), and the costovertebral and sternocostal joints (medially). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig01large.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/62210/62210fig02.jpg" /> 
Figure 2:&#160;Schematic of the biplane videoradiographic system. The x-ray systems are positioned with a 50&#176; inter-beam angle and a source-to-image distance (SID) of 183 cm. Participants are positioned in the biplane volume such that their glenohumeral joint is located approximately at the intersection of the x-ray beams. Systems are termed &#34;green&#34; and &#34;red&#34; to distinguish the control panels and the filenames of the images. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig02large.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/62210/62210fig03.jpg" /> 
Figure 3: Biplane radiographic images from a representative subject during coronal plane abduction. Although the jaw appears in the images of the green system, care should be taken to avoid including the head in the field of view to minimize dose to this area. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig03large.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/62210/62210fig04.jpg" /> 
Figure 4:&#160;Definition of anatomical coordinate systems. (A) Humeral coordinate system defined by digitizing the geometric center of the humeral head, medial epicondyle, and lateral epicondyle. (B) Scapular coordinate system defined by digitizing the medial spine, inferior angle, and posterior aspect of the acromioclavicular joint. (C) Rib coordinate system defined by digitizing the posterior aspect of the costovertebral facet, the lateral-most aspect of the rib, and the lateral sternum at the level of the rib. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/62210/62210fig05.jpg" /> 
Figure 5:&#160;Definition of regions of interest (ROI) for proximity statistics. (A) humeral head ROI, which is used to calculate acromiohumeral distance and glenohumeral joint contact patterns, (B) acromial and glenoid ROIs, which are used to calculate acromiohumeral distance and glenohumeral joint contact patterns, respectively. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/62210/62210fig06.jpg" /> 
Figure 6:&#160;Screenshots of the proprietary markerless tracking software. The screenshot illustrates the optimized solutions of the humerus and scapula from a representative subject during coronal plane abduction. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/62210/62210fig07.jpg" /> 
Figure 7:&#160;Glenohumeral kinematics from a representative subject during a single trial of coronal plane abduction. Note: Anterior position has been transformed to be a positive value. Abbreviations: med. = medial; lat. = lateral; sup. = superior; inf. = inferior; ant. = anterior; post. = posterior. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/62210/62210fig08.jpg" /> 
Figure 8: Scapulothoracic kinematics from a representative subject during a single trial of coronal plane abduction. Note: Anterior position has been transformed to be a positive value. Abbreviations: IR = internal rotation; ER = external rotation; UR = upward rotation; DR = downward rotation; AT = anterior tilt; PT = posterior tilt; med. = medial; lat. = lateral; sup. = superior; inf. = inferior; ant. = anterior; post. = posterior. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/62210/62210fig09.jpg" /> 
Figure 9: Humerothoracic kinematics from a representative subject during a single trial of coronal plane abduction. Note: Anterior position has been transformed to be a positive value. Abbreviations: med. = medial; lat. = lateral; sup. = superior; inf. = inferior; ant. = anterior; post. = posterior. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig09large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/62210/62210fig10.jpg" /> 
Figure 10: Assessment of the subacromial space during a trial of coronal plane abduction in a representative subject. (A) Measures of acromiohumeral distance are displayed across frames along with the corresponding humerothoracic elevation angles. The minimum distance is calculated as the smallest distance between the centroids of the nearest-neighbor triangle between the humeral head and acromial ROIs. The average distance represents the area-weighted mean of the minimum distance, calculated over the triangles in the humeral head ROI that have the smallest gap to their nearest neighbor on the acromial ROI. (B) The surface area of the humeral head ROI that is within 10 mm of the acromial ROI is displayed across frames along with the corresponding humerothoracic elevation angles. Abbreviation: HT = humerothoracic. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 11" class="xfigimg" src="/files/ftp_upload/62210/62210fig11.jpg" /> 
Figure 11: Proximity mapping. (A) subacromial space, (B) glenohumeral joint space. The subacromial proximity is mapped on the humeral head ROI using the minimum distance metric for the frame of data in which the minimum distance was smallest (i.e., frame #45). The contact path (black) represents the minimum distance trajectory between frames #1-45. The glenohumeral joint proximity is mapped using the weighted-average contact center for the frame of data in which the joint space was smallest (i.e., frame #92). The contact path (black) represents the centroid trajectory between frames #1-92. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig11large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 12" class="xfigimg" src="/files/ftp_upload/62210/62210fig12.jpg" /> 
Figure 12: Assessment of the glenohumeral joint space during a trial of coronal plane abduction in a representative subject. (A) Measures of glenohumeral joint space are displayed across frames along with the corresponding humerothoracic elevation angles. The minimum distance is calculated as the smallest distance between the centroids of the nearest-neighbor triangle between the glenoid and humeral head ROIs. The average distance represents the area-weighted mean of the minimum distance, calculated over the triangles in the glenoid ROI that have the smallest gap to their nearest neighbor on the humeral head ROI. (B) The surface area of the glenoid ROI that is within 10 mm of the humeral head ROI is displayed across frames along with the corresponding humerothoracic elevation angles. Abbreviation: HT = humerothoracic.&#160;<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62210/62210fig12large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

Biplane videoradiography can quantify shoulder kinematics with a high degree of accuracy. The protocol described herein was specifically designed to track the scapula, humerus, and the ribs during planar humeral elevation, and outlines the procedures for data collection, processing, and analysis. Unique considerations for data collection are also described.

The shoulder is one of the human body's most complex joint systems, with motion occurring through the coordinated actions of four individual joints, ...

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3.0K Views.  Henry Ford Health System. We geloven dat het belangrijk is om ons protocol en wat we hebben geleerd met behulp van deze technologie in ons onderzoek te delen, omdat de deelnemers aan deze studies worden blootgesteld aan straling en daarom is de foutmarge erg klein. Het grote voordeel van deze techniek is de nauwkeurigheid waarmee de gezamenlijke beweging kan worden gekwantificeerd, waardoor onderzoekers vragen kunnen stellen die anders niet mogelijk zouden zijn. Voordat u met een analyse begint, plaatst u de stoel in ...

Video: Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

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This paper demonstrates a protocol to characterize the mechanical properties of living cells by means of microindentation using an Atomic Force Microscope (AFM).

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Fabrication and Implantation of Miniature Dual-element Strain Gages for Measuring In Vivo Gastrointestinal Contractions in Rodents.

Gastrointestinal dysfunction remains a major cause of morbidity and mortality. Indeed, gastrointestinal (GI) motility in health and disease remains an area of productive research with over 1,400 published animal studies in just the last 5 years. Numerous techniques have been developed for quantifying smooth muscle activity of the stomach, small intestine, and colon. In vitro and ex vivo techniques offer powerful tools for mechanistic studies of GI function, but outside the context of the integrated systems inherent to an intact organism. Typically, measuring in vivo smooth muscle contractions of the stomach has involved an anesthetized preparation coupled with the introduction of a surgically placed pressure sensor, a static pressure load such as a mildly inflated balloon or by distending the stomach with fluid under barostatically-controlled feedback. Yet many of these approaches present unique disadvantages regarding both the interpretation of results as well as applicability for in vivo use in conscious experimental animal models. The use of dual element strain gages that have been affixed to the serosal surface of the GI tract has offered numerous experimental advantages, which may continue to outweigh the disadvantages. Since these gages are not commercially available, this video presentation provides a detailed, step-by-step guide to the fabrication of the current design of these gages. The strain gage described in this protocol is a design for recording gastric motility in rats. This design has been modified for recording smooth muscle activity along the entire GI tract and requires only subtle variation in the overall fabrication. Representative data from the entire GI tract are included as well as discussion of analysis methods, data interpretation and presentation.

Fabrication and Implantation of Miniature Dual-element Strain Gages for Measuring In Vivo Gastrointestinal Contractions in Rodents.

The in vivo measurement of smooth muscle contractions along the gastrointestinal tract of laboratory animals remains a powerful, though underutilized, technique. Flexible, dual element strain gages are not commercially available and require fabrication. This protocol describes the construction of reliable, inexpensive strain gages for acute or chronic implantation in rodents.

Gastrointestinal dysfunction remains a major cause of morbidity and mortality. Indeed, gastrointestinal (GI) motility in health and disease remains an ...

Using Adhesive Patterning to Construct 3D Paper Microfluidic Devices

We demonstrate the use of patterned aerosol adhesives to construct both planar and nonplanar 3D paper microfluidic devices. By spraying an aerosol adhesive through a metal stencil, the overall amount of adhesive used in assembling paper microfluidic devices can be significantly reduced. We show on a simple 4-layer planar paper microfluidic device that the optimal adhesive application technique and device construction style depends heavily on desired performance characteristics. By moderately increasing the overall area of a device, it is possible to dramatically decrease the wicking time and increase device success rates while also reducing the amount of adhesive required to keep the device together. Such adhesive application also causes the adhesive to form semi-permanent bonds instead of permanent bonds between paper layers, enabling single-use devices to be non-destructively disassembled after use. Nonplanar 3D origami devices also benefit from the semi-permanent bonds during folding, as it reduces the likelihood that unrelated faces may accidently stick together. Like planar devices, nonplanar structures see reduced wicking times with patterned adhesive application vs uniformly applied adhesive.

We demonstrate the use of patterned aerosol adhesives to construct 3D paper microfluidic devices. This method of adhesive application forms semi-permanent bonds between layers, enabling single-use devices to be non-destructively disassembled after use and to ease folding complex nonplanar structures.

We demonstrate the use of patterned aerosol adhesives to construct both planar and nonplanar 3D paper microfluidic devices. By spraying an aerosol ...

Preparation of 3D Collagen Gels and Microchannels for the Study of 3D Interactions In Vivo

Historically, most cellular processes have been studied in only 2 dimensions. While these studies have been informative about general cell signaling mechanisms, they neglect important cellular cues received from the structural and mechanical properties of the local microenvironment and extracellular matrix (ECM). To understand how cells interact within a physiological ECM, it is important to study them in the context of 3 dimensional assays. Cell migration, cell differentiation, and cell proliferation are only a few processes that have been shown to be impacted by local changes in the mechanical properties of a 3-dimensional ECM. Collagen I, a core fibrillar component of the ECM, is more than a simple structural element of a tissue. Under normal conditions, mechanical cues from the collagen network direct morphogenesis and maintain cellular structures. In diseased microenvironments, such as the tumor microenvironment, the collagen network is often dramatically remodeled, demonstrating altered composition, enhanced deposition and altered fiber organization. In breast cancer, the degree of fiber alignment is important, as an increase in aligned fibers perpendicular to the tumor boundary has been correlated to poorer patient prognosis1. Aligned collagen matrices result in increased dissemination of tumor cells via persistent migration2,3. The following is a simple protocol for embedding cells within a 3-dimensional, fibrillar collagen hydrogel. This protocol is readily adaptable to many platforms, and can reproducibly generate both aligned and random collagen matrices for investigation of cell migration, cell division, and other cellular processes in a tunable, 3-dimensional, physiological microenvironment.

Preparation of 3D Collagen Gels and Microchannels for the Study of 3D Interactions In Vivo

Collagen is a core component of the ECM, and provides essential cues for several cellular processes ranging from migration to differentiation and proliferation. Provided here is a protocol for embedding cells within 3D collagen hydrogels, and a more advanced technique for generating randomized or aligned collagen matrices using PDMS microchannels.

Historically, most cellular processes have been studied in only 2 dimensions.  While these studies have been informative about general cell signaling ...

Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact

The measurement of dynamic scapular kinematics is complex due to the sliding nature of the scapula beneath the skin surface. The aim of the study was to clearly describe the acromion marker cluster (AMC) method of determining scapular kinematics when using a passive marker motion capture system, with consideration for the sources of error which could affect the validity and reliability of measurements. The AMC method involves placing a cluster of markers over the posterior acromion, and through calibration of anatomical landmarks with respect to the marker cluster it is possible to obtain valid measurements of scapular kinematics. The reliability of the method was examined between two days in a group of 15 healthy individuals (aged 19-38 years, eight males) as they performed arm elevation, to 120&#176;, and lowering in the frontal, scapular and sagittal planes. Results showed that between-day reliability was good for upward scapular rotation (Coefficient of Multiple Correlation; CMC = 0.92) and posterior tilt (CMC = 0.70) but fair for internal rotation (CMC = 0.53) during the arm elevation phase. The waveform error was lower for upward rotation (2.7&#176; to 4.4&#176;) and posterior tilt (1.3&#176; to 2.8&#176;), compared to internal rotation (5.4&#176; to 7.3&#176;). The reliability during the lowering phase was comparable to results observed during the elevation phase. If the protocol outlined in this study is adhered to, the AMC provides a reliable measurement of upward rotation and posterior tilt during the elevation and lowering phases of arm movement.

This report presents details of how to adopt the acromion marker cluster method of obtaining scapular kinematics when using a passive marker motion capture device. As has been described in the literature, this method provides a robust, non-invasive, three-dimensional, dynamic and valid measurement of scapular kinematics, minimizing skin movement artifact.

The measurement of dynamic scapular kinematics is complex due to the sliding nature of the scapula beneath the skin surface. The aim of the study was to ...

Medicine

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

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.

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 ...

Biplanar Videoradiography Dataset for Model-based Pose Estimation Development and New User Training

Measuring the motion of the small foot bones is critical for understanding pathological loss of function. Biplanar videoradiography is well-suited to measure in vivo bone motion, but challenges arise when estimating the rotation and translation (pose) of each bone. The bone's pose is typically estimated with marker- or model-based methods. Marker-based methods are highly accurate but uncommon in vivo due to their invasiveness. Model-based methods are more common but are currently less accurate as they rely on user input and lab-specific algorithms. This work presents a rare in vivo dataset of the calcaneus, talus, and tibia poses, as measured with marker-based methods during running and hopping. A method is included to train users to improve their initial guesses into model-based pose estimation software, using marker-based visual feedback. New operators were able to estimate bone poses within 2&#176; of rotation and 1 mm of translation of the marker-based pose, similar to an expert user of the model-based software, and representing a substantial improvement over previously reported inter-operator variability. Further, this dataset can be used to validate other model-based pose estimation software. Ultimately, sharing this dataset will improve the speed and accuracy with which users can measure bone poses from biplanar videoradiography.

This work presents an in vivo dataset with bone poses estimated with marker-based methods. A method is included here to train operators in improving their initial estimates for model-based pose estimation and reducing inter-operator variability.

Measuring the motion of the small foot bones is critical for understanding pathological loss of function. Biplanar videoradiography is well-suited to ...

Engineering

Bioprinting of Cartilage and Skin Tissue Analogs Utilizing a Novel Passive Mixing Unit Technique for Bioink Precellularization

Bioprinting is a powerful technique for the rapid and reproducible fabrication of constructs for tissue engineering applications. In this study, both cartilage and skin analogs were fabricated after bioink pre-cellularization utilizing a novel passive mixing unit technique. This technique was developed with the aim to simplify the steps involved in the mixing of a cell suspension into a highly viscous bioink. The resolution of filaments deposited through bioprinting necessitates the assurance of uniformity in cell distribution prior to printing to avoid the deposition of regions without cells or retention of large cell clumps that can clog the needle. We demonstrate the ability to rapidly blend a cell suspension with a bioink prior to bioprinting of both cartilage and skin analogs. Both tissue analogs could be cultured for up to 4 weeks. Histological analysis demonstrated both cell viability and deposition of tissue specific extracellular matrix (ECM) markers such as glycosaminoglycans (GAGs) and collagen I respectively.

Cartilage and skin analogs were bioprinted using a nanocellulose-alginate based bioink. The bioinks were cellularized prior to printing via a single step passive mixing unit. The constructs were demonstrated to be uniformly cellularized, have high viability, and exhibit favorable markers of differentiation.

Bioprinting is a powerful technique for the rapid and reproducible fabrication of constructs for tissue engineering applications. In this study, both ...

Biplanar Videoradiography to Study the Wrist and Distal Radioulnar Joints

Accurate measurement of skeletal kinematics in vivo is essential for understanding normal joint function, the influence of pathology, disease progression, and the effects of treatments. Measurement systems that use skin surface markers to infer skeletal motion have provided important insight into normal and pathological kinematics, however, accurate arthrokinematics cannot be attained using these systems, especially during dynamic activities. In the past two decades, biplanar videoradiography (BVR) systems have enabled many researchers to directly study the skeletal kinematics of the joints during activities of daily living. To implement BVR systems for the distal upper extremity, videoradiographs of the distal radius and the hand are acquired from two calibrated X-ray sources while a subject performs a designated task. Three-dimensional (3D) rigid-body positions are computed from the videoradiographs via a best-fit registrations of 3D model projections onto&#160;to each BVR view. The 3D models are density-based image volumes of the specific bone derived from independently acquired computed-tomography data. Utilizing graphics processor units and high-performance computing systems, this model-based tracking approach is shown to be fast and accurate in evaluating the wrist and distal radioulnar joint biomechanics. In this study, we first summarized the previous studies that have established the submillimeter and subdegree agreement of BVR with an in vitro&#160;optical motion capture system in evaluating the wrist and distal radioulnar joint kinematics. Furthermore, we used BVR to compute the center of rotation behavior of the wrist joint, to evaluate the articulation pattern of the components of the implant upon one another, and to assess the dynamic change of ulnar variance during pronosupination of the forearm. In the future, carpal bones may be captured in greater detail with the addition of flat panel X-ray detectors, more X-ray sources (i.e., multiplanar videoradiography), or advanced computer vision algorithms.

Biplanar videoradiography (BVR) is an advanced imaging technique for understanding the three-dimensional movement of skeletal bones and implants. Combining density-based image volumes and videoradiographs of the distal upper extremity, BVR is used to study the in vivo motion of the wrist and distal radioulnar joint, as well as joint arthroplasties.

Accurate measurement of skeletal kinematics in vivo is essential for understanding normal joint function, the influence of pathology, disease progression, ...

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Several hip pathologies have been attributed to abnormal morphology with an underlying assumption of aberrant biomechanics. However, structure-function relationships at the joint level remain challenging to quantify due to difficulties in accurately measuring dynamic joint motion. The soft tissue artifact errors inherent in optical skin marker motion capture are exacerbated by the depth of the hip joint within the body and the large mass of soft tissue surrounding the joint. Thus, the complex relationship between bone shape and hip joint kinematics is more difficult to study accurately than in other joints. Herein, a protocol incorporating computed tomography (CT) arthrography, three-dimensional (3D) reconstruction of volumetric images, dual fluoroscopy, and optical motion capture to accurately measure the dynamic motion of the hip joint is presented. The technical and clinical studies that have applied dual fluoroscopy to study form-function relationships of the hip using this protocol are summarized, and the specific steps and future considerations for data acquisition, processing, and analysis are described.

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Dual fluoroscopy accurately captures in vivo dynamic motion of human joints, which can be visualized relative to reconstructed anatomy (e.g., arthrokinematics). Herein, a detailed protocol to quantify hip arthrokinematics during weight-bearing activities of daily living is presented, including the integration of dual fluoroscopy with traditional skin marker motion capture.

Several hip pathologies have been attributed to abnormal morphology with an underlying assumption of aberrant biomechanics. However, structure-function ...

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

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