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Research Papers

Accuracy of 3D Cartilage Models Generated From MR Images Is Dependent on Cartilage Thickness: Laser Scanner Based Validation of In Vivo Cartilage

[+] Author and Article Information
Seungbum Koo1

School of Mechanical Engineering, Chung-Ang University, Seoul 156-756, South Koreaskoo@cau.ac.kr

Nicholas J. Giori

Department of Orthopedic Surgery, Stanford University, 450 Broadway Street, Pavilion C, 4th Floor Redwood City, CA 94063-6342; VA Palo Alto Healthcare System, 3801 Miranda Avenue, Palo Alto, CA 94304-1290

Garry E. Gold

Department of Radiology, Stanford University, Stanford, CA 94305

Chris O. Dyrby

 VA Palo Alto Healthcare System, 3801 Miranda Avenue, Palo Alto, CA 94304-1290; Department of Mechanical Engineering, Stanford University, 496 Lomita Mall, Durand Building, Room 061, Stanford, CA 94305-4038

Thomas P. Andriacchi

Department of Orthopedic Surgery, Stanford University, 450 Broadway Street, Pavilion C, 4th Floor, Redwood City, CA 94063-6342; VA Palo Alto Healthcare System, 3801 Miranda Avenue, Palo Alto, CA 94304-1290; Department of Mechanical Engineering, Stanford University, 496 Lomita Mall, Durand Building, Room 061, Stanford, CA 94305-4038

1

Corresponding author.

J Biomech Eng 131(12), 121004 (Oct 29, 2009) (5 pages) doi:10.1115/1.4000087 History: Received December 31, 2007; Revised June 03, 2009; Posted September 01, 2009; Published October 29, 2009

Cartilage morphology change is an important biomarker for the progression of osteoarthritis. The purpose of this study was to assess the accuracy of in vivo cartilage thickness measurements from MR image-based 3D cartilage models using a laser scanning method and to test if the accuracy changes with cartilage thickness. Three-dimensional tibial cartilage models were created from MR images (in-plane resolution of 0.55 mm and thickness of 1.5 mm) of osteoarthritic knees of ten patients prior to total knee replacement surgery using a semi-automated B-spline segmentation algorithm. Following surgery, the resected tibial plateaus were laser scanned and made into 3D models. The MR image and laser-scan based models were registered to each other using a shape matching technique. The thicknesses were compared point wise for the overall surface. The linear mixed-effects model was used for statistical test. On average, taking account of individual variations, the thickness measurements in MRI were overestimated in thinner (<2.5mm) regions. The cartilage thicker than 2.5 mm was accurately predicted in MRI, though the thick cartilage in the central regions was underestimated. The accuracy of thickness measurements in the MRI-derived cartilage models systemically varied according to native cartilage thickness.

FIGURES IN THIS ARTICLE
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Copyright © 2009 by American Society of Mechanical Engineers
Topics: Lasers , Thickness , Cartilage
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Figures

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Figure 2

(a) Thickness maps calculated from a MR image-based 3D model and a laser-scan based 3D models. Dark blue represents the thickest cartilage and dark red represents the thinnest cartilage as shown in the color bar. (b) Difference maps were calculated by subtracting the thickness maps from the laser-scan based 3D model from the MR image-based 3D model. Thus blue regions represent thickness overestimation in MR image-based 3D models, green regions show the same estimation, and red regions represent underestimation. The letters A, P, M, and L in boxes represent anterior, posterior, medial, and lateral, respectively.

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Figure 3

Differences in thickness measurement between MRI based 3D models and laser-scan based 3D models were calculated point by point for each of the specimens. This graph is from one of the tested specimens. Positive values represent thickness overestimation in MR image-based measurements. The median of the difference was drawn as solid lines, and 25% and 75% quartiles were drawn as dotted lines.

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Figure 4

Variations of individual specimens are shown for ten specimens with gray lines. Positive and negative values represent thickness overestimation and underestimation in MR image-based 3D models, respectively. The linear mixed-effects model was used to find a fitting line of the data from ten specimens. The black lines represent the fitted line from the linear mixed-effects model and the 95% confidence interval.

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Figure 1

The schematic description of creating 3D cartilage models from two laser-scan data sets. Cartilage surface and bone surface were scanned along with features on platform and registered to each other using the platform features to obtain actual shape of cartilage.

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