ArticleOsteoarthritis and cartilage open2022
Fast quantitative bone marrow lesion measurement on knee MRI for the assessment of osteoarthritis.
Article in Osteoarthritis and cartilage open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- Multi-label Ensemble Model for Knee Joint Anatomy and Lesion Segmentation: Segmentation of Clinical Images With Ensembling, Morphology, and Attention (SCEMA).Magnetic resonance in medicine · 2026Article
- Analysis of multiple MRI-based quantitative structural measurements of knee osteoarthritis in a case control study - association with pain and structural progression and comparison to semi-quantitative scoring.Osteoarthritis and cartilage open · 2025Article
- Machine learning models for clinical and structural knee osteoarthritis prediction: Recent advancements and future directions.Osteoarthritis and cartilage open · 2025Article
- Imaging of osteoarthritis-related bone marrow lesions in clinical trials.Osteoarthritis imaging · 2025Article
- Bone marrow lesions in osteoarthritis: biomarker or treatment target? A narrative review.Skeletal radiology · 2025Review
- Progression of Bone Marrow Lesions and the Development of Knee Osteoarthritis: Osteoarthritis Initiative Data.Radiology · 2024Article
- Unsupervised Segmentation of Knee Bone Marrow Edema-like Lesions Using Conditional Generative Models.Bioengineering (Basel, Switzerland) · 2024Article
- Automatic Segmentation of Bone Marrow Lesions on MRI Using a Deep Learning Method.Bioengineering (Basel, Switzerland) · 2024Article
- Knowledge mapping and bibliometric analysis of medical knee magnetic resonance imaging for knee osteoarthritis (2004-2023).Frontiers in surgery · 2024Article
- A synoptic literature review of animal models for investigating the biomechanics of knee osteoarthritis.Frontiers in bioengineering and biotechnology · 2024Review
- Quantitative bone marrow lesion, meniscus, and synovitis measurement: current status.Skeletal radiology · 2023Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Objective: Knee osteoarthritis (KOA) is a prevalent disease with a high economic and social cost. Magnetic resonance imaging (MRI) can be used to visualize many KOA-related structures including bone marrow lesions (BMLs), which are associated with OA pain. Several semi-automated software methods have been developed to segment BMLs, using manual, labor-intensive methods, which can be costly for large clinical trials and other studies of KOA. The goal of our study was to develop and validate a more efficient method to quantify BML volume on knee MRI scans. Materials and methods: We have applied a deep learning approach using a patch-based convolutional neural network (CNN) which was trained using 673 MRI data sets and the segmented BML masks obtained from a trained reader. Given the location of a BML provided by the reader, the network performed a fully automated segmentation of the BML, removing the need for tedious manual delineation. Accuracy was quantified using the Pearson's correlation coefficient, by a comparison to a second expert reader, and using the Dice Similarity Score (DSC). Results: The Pearson's R Conclusions: We developed and validated a deep learning-based method to segment BMLs on knee MRI data sets. This has the potential to be a valuable tool for future large studies of KOA.
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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.