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Updated: Feb 1, 2026

Tissue Collection and RNA Extraction from the Human Osteoarthritic Knee Joint
Published on: July 22, 2021
Spatially matching morphometric assessment of cartilage and subchondral bone in osteoarthritic human knee joint with
Birgitta Gatenholm1, Carl Lindahl2, Mats Brittberg3
1Department of Orthopaedics, Institute of Clinical Sciences, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Department of Orthopaedics, Sahlgrenska University Hospital, Mölndal, Sweden.
Objective:
The objective of this study was to develop a reproducible and semi-automatic method based on micro computed tomography (microCT) to analyze cartilage and bone morphology of human osteoarthritic knee joints in spatially matching regions of interest.
Materials And Methods:
Tibial plateaus from randomly selected patients with advanced osteoarthritis (OA) who underwent total knee arthroplasty surgery were microCT scanned once fresh and once after staining with Hexabrix. The articular surface was determined manually in the first scan. Total articular surface, defect surface and cartilage surface were computed by triangulation of the cartilage surface and the spatially corresponding subchondral bone regions were automatically generated and the standard cortical bone and trabecular bone morphometric indices were computed.
Results:
The method to identify cartilage surface and defects was successfully validated against photographic examinations. The microCT measurements of the cartilage defect were also verified by conventional histopathology using safranin O-stained sections. Cartilage thickness and volume was significantly lower for OA condyle compared with healthy condyle. Bone fraction, bone tissue mineral density, cortical density and trabecular thickness differed significantly depending on the level of cartilage damage.
Conclusion:
This new microCT imaging workflow can be used for reproducible quantitative evaluation of articular cartilage damage and the associated changes in subchondral bone morphology in osteoarthritic joints with a relatively high throughput compared to manual contouring. This methodology can be applied to gain better understanding of the OA disease progress in large cohorts.
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