Technical Brief

Prediction of In Vivo Knee Joint Kinematics Using a Combined Dual Fluoroscopy Imaging and Statistical Shape Modeling Technique

[+] Author and Article Information
Jing-Sheng Li

Bioengineering Laboratory,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
College of Health and Rehabilitation
Sciences: Sargent College,
Boston University,
Boston, MA 02215

Tsung-Yuan Tsai, Shaobai Wang, Pingyue Li

Bioengineering Laboratory,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114

Young-Min Kwon, Andrew Freiberg, Harry E. Rubash

Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114

Guoan Li

Bioengineering Laboratory,
Department of Orthopaedic Surgery,
Massachusetts General Hospital
and Harvard Medical School,
Boston, MA 02114
e-mail: gli1@mgh.harvard.edu

1Corresponding author.

Manuscript received February 13, 2014; final manuscript received September 16, 2014; accepted manuscript posted October 16, 2014; published online October 30, 2014. Assoc. Editor: Kenneth Fischer.

J Biomech Eng 136(12), 124503 (Oct 30, 2014) (6 pages) Paper No: BIO-14-1074; doi: 10.1115/1.4028819 History: Received February 13, 2014; Revised September 16, 2014; Accepted October 16, 2014

Using computed tomography (CT) or magnetic resonance (MR) images to construct 3D knee models has been widely used in biomedical engineering research. Statistical shape modeling (SSM) method is an alternative way to provide a fast, cost-efficient, and subject-specific knee modeling technique. This study was aimed to evaluate the feasibility of using a combined dual-fluoroscopic imaging system (DFIS) and SSM method to investigate in vivo knee kinematics. Three subjects were studied during a treadmill walking. The data were compared with the kinematics obtained using a CT-based modeling technique. Geometric root-mean-square (RMS) errors between the knee models constructed using the SSM and CT-based modeling techniques were 1.16 mm and 1.40 mm for the femur and tibia, respectively. For the kinematics of the knee during the treadmill gait, the SSM model can predict the knee kinematics with RMS errors within 3.3 deg for rotation and within 2.4 mm for translation throughout the stance phase of the gait cycle compared with those obtained using the CT-based knee models. The data indicated that the combined DFIS and SSM technique could be used for quick evaluation of knee joint kinematics.

Copyright © 2014 by ASME
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Fig. 3

Coordinate system setup for 6DOF kinematics measurement. Flexion angle was defined as the angle between the two long axes in sagittal plane. Internal/external rotation angle was defined as the angle of TEA and the tibial medial-lateral axis on the transverse plane of the tibia. Valgus/varus rotation was defined as the angle between the TEA and tibial medial-lateral axis in the coronal plane of the tibia. The position of the midpoint of the TEA in the tibial coordinate system was used to calculate the translations along the anteroposterior, mediolateral, and superoinferior directions.

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Fig. 2

Environment setup for the SSM in a virtual dual fluoroscope imaging system. Avg models, including the femur and tibia, were imported and positioned to match the silhouettes on the dual fluoroscopic images. Corresponding SSM would deform to fit the outlines of dual-fluoroscopic images.

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Fig. 1

Flowchart of combined DFIS and SSM to calculate the knee joint kinematics through a 2D–3D registration

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Fig. 4

3D surface rendering of differences between the 3D SSM model compared with 3D CT model. The warm and cold colors denote the differences inside and outside the CT-based model surface.

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Fig. 5

Rotational kinematic comparison between SSM model and CT model during stance of gait cycle. The positive values denote flexion, internal tibial rotation (ITR), and Varus rotation (VAR) of the knee joint motion.

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Fig. 6

Translational kinematic comparison between SSM model and CT model. The positive values denote anterior tibial translation (ATT), medial tibial translation (MTT), and superior femoral translation (SUP) of the knee joint motion.




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