Joint injuries and the resulting posttraumatic osteoarthritis (OA) are a significant problem. There is still a need for tools to evaluate joint injuries, their effect on joint mechanics, and the relationship between altered mechanics and OA. Better understanding of injuries and their relationship to OA may aid in the development or refinement of treatment methods. This may be partially achieved by monitoring changes in joint mechanics that are a direct consequence of injury. Techniques such as image-based finite element modeling can provide in vivo joint mechanics data but can also be laborious and computationally expensive. Alternate modeling techniques that can provide similar results in a computationally efficient manner are an attractive prospect. It is likely possible to estimate risk of OA due to injury from surface contact mechanics data alone. The objective of this study was to compare joint contact mechanics from image-based surface contact modeling (SCM) and finite element modeling (FEM) in normal, injured (scapholunate ligament tear), and surgically repaired radiocarpal joints. Since FEM is accepted as the gold standard to evaluate joint contact stresses, our assumption was that results obtained using this method would accurately represent the true value. Magnetic resonance images (MRI) of the normal, injured, and postoperative wrists of three subjects were acquired when relaxed and during functional grasp. Surface and volumetric models of the radiolunate and radioscaphoid articulations were constructed from the relaxed images for SCM and FEM analyses, respectively. Kinematic boundary conditions were acquired from image registration between the relaxed and grasp images. For the SCM technique, a linear contact relationship was used to estimate contact outcomes based on interactions of the rigid articular surfaces in contact. For FEM, a pressure-overclosure relationship was used to estimate outcomes based on deformable body contact interactions. The SCM technique was able to evaluate variations in contact outcomes arising from scapholunate ligament injury and also the effects of surgical repair, with similar accuracy to the FEM gold standard. At least 80% of contact forces, peak contact pressures, mean contact pressures and contact areas from SCM were within 10 N, 0.5 MPa, 0.2 MPa, and 15 mm2, respectively, of the results from FEM, regardless of the state of the wrist. Depending on the application, the MRI-based SCM technique has the potential to provide clinically relevant subject-specific results in a computationally efficient manner compared to FEM.
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April 2014
Research-Article
Computationally Efficient Magnetic Resonance Imaging Based Surface Contact Modeling as a Tool to Evaluate Joint Injuries and Outcomes of Surgical Interventions Compared to Finite Element Modeling Available to Purchase
Joshua E. Johnson,
Joshua E. Johnson
Department of Mechanical Engineering,
e-mail: [email protected]
University of Kansas
,3138 Learned Hall
,Lawrence, KS 66045
e-mail: [email protected]
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Phil Lee,
Phil Lee
Hoglund Brain Imaging Center,
e-mail: [email protected]
University of Kansas Medical Center
,3901 Rainbow Boulevard
,Kansas City, KS 66160
e-mail: [email protected]
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Terence E. McIff,
Terence E. McIff
Department of Orthopedic Surgery,
e-mail: [email protected]
University of Kansas Medical Center
,3901 Rainbow Boulevard
,Kansas City, KS 66160
e-mail: [email protected]
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E. Bruce Toby,
E. Bruce Toby
Department of Orthopedic Surgery,
e-mail: [email protected]
University of Kansas Medical Center
,3901 Rainbow Boulevard
,Kansas City, KS 66160
e-mail: [email protected]
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Kenneth J. Fischer
Kenneth J. Fischer
1
Department of Mechanical Engineering,
Department of Orthopedic Surgery,
e-mail: [email protected]
Department of Orthopedic Surgery,
1530 W. 15th St.
,3138 Learned Hall
,Lawrence, Kansas 66045
e-mail: [email protected]
1Corresponding author.
Search for other works by this author on:
Joshua E. Johnson
Department of Mechanical Engineering,
e-mail: [email protected]
University of Kansas
,3138 Learned Hall
,Lawrence, KS 66045
e-mail: [email protected]
Phil Lee
Hoglund Brain Imaging Center,
e-mail: [email protected]
University of Kansas Medical Center
,3901 Rainbow Boulevard
,Kansas City, KS 66160
e-mail: [email protected]
Terence E. McIff
Department of Orthopedic Surgery,
e-mail: [email protected]
University of Kansas Medical Center
,3901 Rainbow Boulevard
,Kansas City, KS 66160
e-mail: [email protected]
E. Bruce Toby
Department of Orthopedic Surgery,
e-mail: [email protected]
University of Kansas Medical Center
,3901 Rainbow Boulevard
,Kansas City, KS 66160
e-mail: [email protected]
Kenneth J. Fischer
Department of Mechanical Engineering,
Department of Orthopedic Surgery,
e-mail: [email protected]
Department of Orthopedic Surgery,
1530 W. 15th St.
,3138 Learned Hall
,Lawrence, Kansas 66045
e-mail: [email protected]
1Corresponding author.
Contributed by the Bioengineering Division of ASME for publication in the JOURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received March 22, 2013; final manuscript received January 8, 2014; accepted manuscript posted January 15, 2014; published online March 24, 2014. Assoc. Editor: Zong-Ming Li.
J Biomech Eng. Apr 2014, 136(4): 041002 (9 pages)
Published Online: March 24, 2014
Article history
Received:
March 22, 2013
Revision Received:
January 8, 2014
Accepted:
January 15, 2014
Citation
Johnson, J. E., Lee, P., McIff, T. E., Bruce Toby, E., and Fischer, K. J. (March 24, 2014). "Computationally Efficient Magnetic Resonance Imaging Based Surface Contact Modeling as a Tool to Evaluate Joint Injuries and Outcomes of Surgical Interventions Compared to Finite Element Modeling." ASME. J Biomech Eng. April 2014; 136(4): 041002. https://doi.org/10.1115/1.4026485
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