ArticleJournal of magnetic resonance imaging : JMRI2018
Tool for osteoarthritis risk prediction (TOARP) over 8 years using baseline clinical data, X-ray, and MRI: Data from the osteoarthritis initiative.
Article in Journal of magnetic resonance imaging : JMRI, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.
- Defining and predicting radiographic knee osteoarthritis progression: a systematic review of findings from the osteoarthritis initiative.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2022Pooled it
- Osteoarthritis: Epidemiology, Diagnosis, and Treatment.MedComm · 2026Review
- Deep learning-enhanced, accelerated cartilage TSkeletal radiology · 2026Article
- Usefulness of 3D joint space width on weight-bearing CT in comparison with 2D joint space width on radiographs for predicting 24-month worsening of knee osteoarthritis pain and function in the MOST study.Osteoarthritis and cartilage · 2026Article
- NOTUM Enhances Cartilage Repair via Wnt/β-Catenin Modulation in a Rabbit Osteochondral Defect Model.International journal of molecular sciences · 2026Article
- Healthy knee asymmetry is a potential risk factor for knee osteoarthritis: Data from the osteoarthritis initiative.Osteoarthritis imaging · 2025Article
- Simplifying Knee OA Prognosis: A Deep Learning Approach Using Radiographs and Minimal Clinical Inputs.Diagnostics (Basel, Switzerland) · 2025Article
- Machine learning models for clinical and structural knee osteoarthritis prediction: Recent advancements and future directions.Osteoarthritis and cartilage open · 2025Article
- Biomarker-Guided Imaging and AI-Augmented Diagnosis of Degenerative Joint Disease.Diagnostics (Basel, Switzerland) · 2025Review
- [Predictors of Knee Replacement Following Meniscal Tear Arthroscopy: a 7-Year Risk Prediction Model].Acta chirurgiae orthopaedicae et traumatologiae Cechoslovaca · 2025Article
- Reproducibility of Quantitative Double-Echo Steady-State TJournal of magnetic resonance imaging : JMRI · 2025Article
- Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications.Magma (New York, N.Y.) · 2024Review
- Short-term variations in trabecular bone texture parameters associated to radio-clinical biomarkers improve the prediction of radiographic knee osteoarthritis progression.Scientific reports · 2023Article
- Prediction of total knee replacement using deep learning analysis of knee MRI.Scientific reports · 2023Article
- A joint multi-modal learning method for early-stage knee osteoarthritis disease classification.Heliyon · 2023Article
- Development and evaluation of nomograms for predicting osteoarthritis progression based on MRI cartilage parameters: data from the FNIH OA biomarkers Consortium.BMC medical imaging · 2023Article
- Article
- Radiographic Biomarkers for Knee Osteoarthritis: A Narrative Review.Life (Basel, Switzerland) · 2023Review
- The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI and X-ray images.Osteoarthritis and cartilage · 2023Article
- Prediction Models for Knee Osteoarthritis: Review of Current Models and Future Directions.The archives of bone and joint surgery · 2023Review
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundOsteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA development. PURPOSE: To develop a risk prediction tool for moderate-severe OA (TOARP) over 8 years based on subject characteristics, knee radiographs, and MRI data at baseline using data from the Osteoarthritis Initiative (OAI). STUDY TYPE: Retrospective. SUBJECTS: 641 subjects with no/mild radiographic OA (Kellgren-Lawrence [KL] 0-2) and no clinically significant symptoms (Western Ontario and McMaster Universities Arthritis Index [WOMAC] 0-1) were selected from the OAI. FIELD STRENGTH/SEQUENCE: MR images were obtained using 3.0T. ASSESSMENT: Compartment-specific cartilage and meniscus morphology and cartilage T STATISTICAL TESTS: Best subsets variable selection followed by cross-validation were used to assess which combinations of variables best predict moderate/severe OA.
resultsModel 1 included KL score, previous knee injury in the last 12 months, age, gender, and BMI. Model 2 included all variables in Model 1 plus presence of cartilage defects in the lateral femur and patella, and presence of a meniscal tear. Model 3 included all variables in Models 1 and 2, plus cartilage T DATA
conclusionWe established a risk calculator for the development of moderate/severe knee OA over 8 years that includes radiographic and MRI data. The inclusion of MRI-based morphological abnormalities and cartilage T LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1517-1526.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.