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Peer-reviewed veterinary case report

Semi-automated International Cartilage Repair Society scoring of equine articular cartilage lesions in optical coherence tomography images.

Journal:
Equine veterinary journal
Year:
2017
Authors:
Te Moller, N C R et al.
Affiliation:
Department of Equine Sciences · Netherlands
Species:
horse

Abstract

BACKGROUND: Arthroscopic optical coherence tomography (OCT) is a promising tool for the detailed evaluation of articular cartilage injuries. However, OCT-based articular cartilage scoring still relies on the operator's visual estimation. OBJECTIVES: To test the hypothesis that semi-automated International Cartilage Repair Society (ICRS) scoring of chondral lesions seen in OCT images could enhance intra- and interobserver agreement of scoring and its accuracy. STUDY DESIGN: Validation study using equine cadaver tissue. METHODS: Osteochondral samples (n = 99) were prepared from 18 equine metacarpophalangeal joints and imaged using OCT. Custom-made software was developed for semi-automated ICRS scoring of cartilage lesions on OCT images. Scoring was performed visually and semi-automatically by five observers, and levels of inter- and intraobserver agreement were calculated. Subsequently, OCT-based scores were compared with ICRS scores based on light microscopy images of the histological sections of matching locations (n = 82). RESULTS: When semi-automated scoring of the OCT images was performed by multiple observers, mean levels of intraobserver and interobserver agreement were higher than those achieved with visual OCT scoring (83% vs. 77% and 74% vs. 33%, respectively). Histology-based scores from matching regions of interest agreed better with visual OCT-based scoring than with semi-automated OCT scoring; however, the accuracy of the software was improved by optimising the threshold combinations used to determine the ICRS score. MAIN LIMITATIONS: Images were obtained from cadavers. CONCLUSIONS: Semi-automated scoring software improved the reproducibility of ICRS scoring of chondral lesions in OCT images and made scoring less observer-dependent. The image analysis and segmentation techniques adopted in this study warrant further optimisation to achieve better accuracy with semi-automated ICRS scoring. In addition, studies on in vivo applications are required.

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Original publication: https://pubmed.ncbi.nlm.nih.gov/27592527/