Biplanar Videoradiography to Study the Wrist and Distal Radioulnar Joints

Summary

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.

Abstract

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 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 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.

Introduction

Accurate measurement of skeletal kinematics in vivo is essential for understanding healthy and replaced joint function, the influence of pathology, disease progression, and the effects of treatments. Quantifying skeletal kinematics noninvasively at the joint surface (arthrokinematics) is crucial to understand joint pathologies and diseases, such as osteoarthritis, but it is technically challenging. Previously, techniques that use skin surface markers to infer skeletal motion have provided important insight into healthy and pathological kinematics. However, accurate arthrokinematics cannot be attained using these techniques, especially during dynamic acti....

Protocol

This study was approved by the Institutional Review Board (IRB) of Lifespan - Rhode Island Hospital, an AAHRPP accredited IRB. A total of 16 patients provided signed informed consent according to institutional guidelines.

1. Data acquisition

1. Computed Tomography (CT)
   1. Prepare the specimens or subjects for the CT.
      NOTE: For the accuracy evaluation^14,15, 6 intact forearms from four inta.......

Discussion

Biplanar videoradiography (BVR) is an image-based method that can be used to measure bone and implant motion in the wrist and distal radioulnar joint with submillimeter and subdegree accuracy. In the studies we described here, BVR was used to identify an accurate pattern of projected COR for a healthy wrist as well as TWA contact patterns. Such findings may inform the design of next generation total wrist replacements and can provide in vivo data for validation of computational of models. Using BVR, the nonlinea.......

Materials

Name	Company	Catalog Number	Comments
3D Surface Scanner	Artec 3D	Artec Space SpiderTM	Luxembourg
Autoscoper	Brown University	https://simtk.org/projects/autoscoper	https://doi.org/10.1016/j.jbiomech.2019.05.040
CT Scanner	General Electric (GE)	Lightspeed 16	Milwaukee, WI, USA
Geomagic Wrap 3D	3DSystems	Version 2017	Rock Hill, SC, USA
Graphics Processing Unit (GPU)	Nvidia	GeForce GTX 1080	CUDA-enabled GPU
High-speed Video Cameras	Phantom	Version 10	Vision Research, Wayne, NJ, USA
Image Intensifier	Dunlee	40 cm diameter	Aurora, IL, USA
ImageJ	Open-source (Brown University)	https://imagej.net/Fiji	https://doi.org/10.1038/nmeth.2019
Matlab	The MathWorks, Inc.	R2017a to R2020a	Natick, MA, USA
Mimics	Materialise	Version 19.0 to 22.0	Leuven, Belgium
Motion Capture Cameras	Qualisys	Oqus 5+	Gothenburg, Sweden
Pulsed X-ray Generators	EMD Technologies	EPS 45–80	Saint-Eustache, Quebec, QC, Canada
Undistortion Grid	McMaster-Carr	9255T641	Steel Perforated Sheet Staggered Holes, 0.048" Thk, 0.125" Hole Dia, 36" X 40"
Wrist Implant (In-vitro Study)	Integra LifeSciences	Universal 2	Plainsboro, NJ, USA
Wrist Implant (In-vivo Study)	Integra LifeSciences	Freedom	Plainsboro, NJ, USA
WristViz	Open-source (Brown University)	https://github.com/DavidLaidlaw/WristVisualizer/tree/master	Open-source software
X-ray Tubes	Varian Medical Systems	Model G-1086	Palo Alto, CA, USA
XMALab	Open-source (Brown University)	https://www.xromm.org/xmalab/	https://doi.org/10.1242/jeb.145383