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Region partitioning of articular cartilage with...
Journal article

Region partitioning of articular cartilage with streaming-potential-based parameters and indentation maps

Abstract

Articular cartilage exhibits site-specific tissue inhomogeneity, for which the tissue properties may continuously vary across the articular surface. To facilitate practical applications such as studying site-specific cartilage degeneration, the inhomogeneity may be approximated with several distinct region-wise variations, with one set of tissue properties for one region. A clustering method was previously developed to partition such regions using cartilage indentation-relaxation and thickness mapping instead of simply using surface geometry. In the present study, a quantitative parameter based on streaming potential measurement was introduced as an additional feature to assess the applicability of the methodology with independent datasets. Experimental data were collected from 24 sets of femoral condyles, extracted from fresh porcine stifle joints, through streaming potential mapping, automated indentation, and needle penetration tests. K-means clustering and Elbow method were used to find optimal region partitions. Consistent with previous findings, three regions were suggested for either lateral or medial condyle regardless of left or right joint. The region shapes were approximately triangular or trapezoidal, which was similar to what was found previously. Streaming potentials were confirmed to be region-dependent, but not significantly different among joints. The cartilage was significantly thicker in the medial than lateral condyles. The region areas were consistent among joints, and comparable to that found in a previous study. The present study demonstrated the capability of region partitioning methods with different variables, which may facilitate new applications whenever site-specific tissue properties must be considered.

Authors

Niasar EHA; Wilson ECB; Quenneville CE; Maly MR; Li LP

Journal

Journal of the Mechanical Behavior of Biomedical Materials, Vol. 154, ,

Publisher

Elsevier

Publication Date

June 1, 2024

DOI

10.1016/j.jmbbm.2024.106534

ISSN

1751-6161

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