Surface roughness and thickness analysis of contrast-enhanced articular cartilage using mesh parameterization

T Maerz; M D Newton; H W T Matthew; K C Baker

doi:10.1016/j.joca.2015.09.006

Surface roughness and thickness analysis of contrast-enhanced articular cartilage using mesh parameterization

Osteoarthritis Cartilage. 2016 Feb;24(2):290-8. doi: 10.1016/j.joca.2015.09.006. Epub 2015 Oct 9.

Authors

T Maerz¹, M D Newton², H W T Matthew³, K C Baker⁴

Affiliations

¹ Orthopaedic Research Laboratories, Beaumont Health System, Royal Oak, MI, USA; Department of Orthopaedic Surgery, Oakland University - William Beaumont Oakland University School of Medicine, Rochester, MI, USA; Department of Biomedical Engineering, Wayne State University, Detroit, MI, USA.
² Orthopaedic Research Laboratories, Beaumont Health System, Royal Oak, MI, USA.
³ Department of Biomedical Engineering, Wayne State University, Detroit, MI, USA; Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, MI, USA.
⁴ Orthopaedic Research Laboratories, Beaumont Health System, Royal Oak, MI, USA; Department of Orthopaedic Surgery, Oakland University - William Beaumont Oakland University School of Medicine, Rochester, MI, USA. Electronic address: kevin.baker@beaumont.edu.

PMID: 26455998
DOI: 10.1016/j.joca.2015.09.006

Abstract

Objective: Articular cartilage (AC) morphology is an important metric for characterizing degeneration. We propose a novel morphologic analysis using mesh parameterization, enabling the use of surface roughness and thickness metrics to characterize degeneration in a rodent model of post-traumatic osteoarthritis.

Methods: Six rats underwent anterior cruciate ligament transection (ACL-T) and six were controls (Control). At 4-weeks, femora and tibiae were harvested and imaged using contrast-enhanced micro-computed tomography (μCT). Cartilage surfaces were manually outlined, and 2-dimensional thickness maps were generated using mesh parameterization and analyzed by thickness and surface roughness (Sa). The parameterization technique was validated against the direct distance transform (DDT) and histologic AC thickness from sagittal Safranin-O/Fast-Green sections. Parameterization and DDT measurements were also validated using known, virtual shapes with zero, one, and two planes of curvature.

Results: Parameterization had 0.00-6.26% error and DDT had 5.06-12.02% error in determining thicknesses of known shapes. Parameterization thickness correlated highly to DDT thickness (femur: r = 0.978, P < 0.001; tibia: r = 0.992, P < 0.001) and histologic thickness (femur: r = 0.952, P < 0.001; tibia: r = 0.959, P < 0.001). Thickness maps enabled visualization and quantification of AC degeneration. ACL-T samples displayed general thickening of cartilage, with adjacent regions of thickening and thinning on the medial femoral condyle. Compared to Control, ACL-T thickness was higher in the whole femur, whole tibia, and all compartments and sub-compartments. Sa was higher in the whole femur and medial and lateral condyle, and the whole tibia and medial and lateral plateau. The largest increases in Sa were observed on the medial femoral condyle.

Conclusions: Cartilage analysis using parameterization effectively characterized early degeneration in AC, including sub-compartmental thickening/thinning, and is a powerful tool for assessing degeneration in preclinical osteoarthritis.

Keywords: Cartilage morphology; Contrast-enhanced μCT; Image analysis; Mesh parameterization; Post-traumatic osteoarthritis; Surface roughness.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Anterior Cruciate Ligament Injuries*
Cartilage, Articular / diagnostic imaging*
Case-Control Studies
Contrast Media
Femur / diagnostic imaging*
Knee Injuries / diagnostic imaging*
Organ Size
Rats
Stifle / diagnostic imaging*
Tibia / diagnostic imaging*
X-Ray Microtomography

Substances

Contrast Media