ArticleJournal of orthopaedic surgery and research2022
Radiomics analysis using MR imaging of subchondral bone for identification of knee osteoarthritis.
Article in Journal of orthopaedic surgery and research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- The use of radiomic analysis of magnetic resonance imaging findings in predicting features of early osteoarthritis of the knee-a systematic review and meta-analysis.Irish journal of medical science · 2024Pooled it
- Construction of a radiomics-based diagnostic nomogram for patellofemoral osteoarthritis-using lateral knee X-ray images from a South China population.Quantitative imaging in medicine and surgery · 2026Article
- Radiomics-based MRI model for predicting the severity of rotator cuff tears.Orthopadie (Heidelberg, Germany) · 2026Article
- Quantitative Imaging of the Mandibular Condyle: Radiomics and Microarchitectural Biomarkers.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2026Review
- Progress in machine learning-assisted medical imaging for osteoarthritis and osteoporosis diagnosis: a narrative review.Quantitative imaging in medicine and surgery · 2026Review
- CT-based subchondral bone microstructural analysis in knee osteoarthritis via MR-guided distillation learning.Frontiers in radiology · 2026Article
- Artificial intelligence and big data for precision regenerative medicine in knee osteoarthritis: endotyping, responder prediction, and clinical translation.Frontiers in bioengineering and biotechnology · 2026Review
- An MRI-based radiomics framework for early identification and progression stratification in knee osteoarthritis: data from the osteoarthritis initiative.BMC musculoskeletal disorders · 2025Article
- Using magnetic resonance imaging-based subregional texture analysis models to classify knee osteoarthritis severity by compartment.Scientific reports · 2025Article
- Radiomic features of infrapatellar fat pad are associated with knee symptoms and radiographic post-traumatic osteoarthritis at 10+ years after anterior cruciate ligament reconstruction.Osteoarthritis imaging · 2025Article
- Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value.European journal of radiology open · 2025Article
- Progress in multi-omics studies of osteoarthritis.Biomarker research · 2025Review
- Computed tomography radiomics in predicting patient satisfaction after robotic-assisted total knee arthroplasty.International journal of computer assisted radiology and surgery · 2025Article
- Texture analysis combined with machine learning in radiographs of the knee joint: potential to identify tibial plateau occult fractures.Quantitative imaging in medicine and surgery · 2025Article
- MRI-based radiomic analysis of soft tissue reactions near total hip arthroplasty.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025Article
- Interpretable machine learning and radiomics in hip MRI diagnostics: comparing ONFH and OA predictions to experts.Frontiers in immunology · 2025Article
- Radiomics signature of osteoarthritis: Current status and perspective.Journal of orthopaedic translation · 2024Review
- Radiomics analysis using magnetic resonance imaging of bone marrow edema for diagnosing knee osteoarthritis.Frontiers in bioengineering and biotechnology · 2024Article
- MRI texture analysis of acetabular cancellous bone can discriminate between normal, cam positive, and cam-FAI hips.European radiology · 2023Article
- Radiomics in Spine Surgery.International journal of spine surgery · 2023Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundTo develop a magnetic resonance imaging (MRI)-based radiomics predictive model for the identification of knee osteoarthritis (OA), based on the tibial and femoral subchondral bone, and compare with the trabecular structural parameter-based model.
methodsEighty-eight consecutive knees were scanned with 3T MRI and scored using MRI osteoarthritis Knee Scores (MOAKS), in which 56 knees were diagnosed to have OA. The modality of sagittal three-dimensional balanced fast-field echo sequence (3D BFFE) was used to image the subchondral bone. Four trabecular structural parameters (bone volume fraction [BV/TV], trabecular thickness [Tb.Th], trabecular separation [Tb.Sp], and trabecular number) and 93 radiomics features were extracted from four regions of the lateral and medial aspects of the femur condyle and tibial plateau. Least absolute shrinkage and selection operator (LASSO) was used for feature selection. Machine learning-based support vector machine models were constructed to identify knee OA. The performance of the models was assessed by area under the curve (AUC) of the receiver operator characteristic (ROC). The correlation between radiomics features and trabecular structural parameters was analyzed using Pearson's correlation coefficient.
resultsOur radiomics-based classification model achieved the AUC score of 0.961 (95% confidence interval [CI], 0.912-1.000) when distinguishing between normal and knee OA, which was higher than that of the trabecular parameter-based model (AUC, 0.873; 95% CI, 0.788-0.957). The first-order, texture, and Laplacian of Gaussian-based radiomics features correlated positively with Tb.Th and BV/TV, but negatively with Tb.Sp (P < 0.05).
conclusionsOur results suggested that our MRI-based radiomics models can be used as biomarkers for the classification of OA and are superior to the conventional structural parameter-based model.
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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.