ArticleJournal of orthopaedic research : official publication of the Orthopaedic Research Society2015
Classification of histologically scored human knee osteochondral plugs by quantitative analysis of magnetic resonance images at 3T.
Article in Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 15 citations in OpenAlex.
- Progress in machine learning-assisted medical imaging for osteoarthritis and osteoporosis diagnosis: a narrative review.Quantitative imaging in medicine and surgery · 2026Review
- Histological analysis of age-related degeneration in human female and male knee cartilage and meniscus.Osteoarthritis and cartilage open · 2026Article
- Articular Cartilage-From Basic Science Structural Imaging to Non-Invasive Clinical Quantitative Molecular Functional Information for AI Classification and Prediction.International journal of molecular sciences · 2023Review
- Evaluation of cartilage degeneration using multiparametric quantitative ultrashort echo time-based MRI: anQuantitative imaging in medicine and surgery · 2022Article
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- Functional MRI for evaluation of hyaline cartilage extracelullar matrix, a physiopathological-based approach.The British journal of radiology · 2019Review
- Associations of three-dimensional T1 rho MR mapping and three-dimensional T2 mapping with macroscopic and histologic grading as a biomarker for early articular degeneration of knee cartilage.Clinical rheumatology · 2017Article
- Ex vivo quantitative multiparametric MRI mapping of human meniscus degeneration.Skeletal radiology · 2016Observational
- Quantitative OCT and MRI biomarkers for the differentiation of cartilage degeneration.Skeletal radiology · 2016Article
- Article
- Article
- Machine learning classification of OARSI-scored human articular cartilage using magnetic resonance imaging.Osteoarthritis and cartilage · 2015Article
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 1 country.
Funding
Abstract
This work evaluates the ability of quantitative MRI to discriminate between normal and pathological human osteochondral plugs characterized by the Osteoarthritis Research Society International (OARSI) histological system. Normal and osteoarthritic human osteochondral plugs were scored using the OARSI histological system and imaged at 3 T using MRI sequences producing T1 and T2 contrast and measuring T1, T2, and T2* relaxation times, magnetization transfer, and diffusion. The classification accuracies of quantitative MRI parameters and corresponding weighted image intensities were evaluated. Classification models based on the Mahalanobis distance metric for each MRI measurement were trained and validated using leave-one-out cross-validation with plugs grouped according to OARSI histological grade and score. MRI measurements used for classification were performed using a region-of-interest analysis which included superficial, deep, and full-thickness cartilage. The best classifiers based on OARSI grade and score were T1- and T2-weighted image intensities, which yielded accuracies of 0.68 and 0.75, respectively. Classification accuracies using OARSI score-based group membership were generally higher when compared with grade-based group membership. MRI-based classification--either using quantitative MRI parameters or weighted image intensities--is able to detect early osteoarthritic tissue changes as classified by the OARSI histological system. These findings suggest the benefit of incorporating quantitative MRI acquisitions in a comprehensive clinical evaluation of OA.
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