ArticleProceedings of the National Academy of Sciences of the United States of America2020
Enabling early detection of osteoarthritis from presymptomatic cartilage texture maps via transport-based learning.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Evaluation of Pre-Operative Cartilage and Meniscus Ultrashort Echo Time T2* as Biomarkers of Long-Term Clinical Outcomes Following Anterior Cruciate Ligament Reconstruction.Journal of magnetic resonance imaging : JMRI · 2026Article
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- Development of a multimodal vision transformer model for predicting traumatic versus degenerative rotator cuff tears on magnetic resonance imaging: A single-centre retrospective study.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
- Plasma Glycated and Oxidized Amino Acid-Based Screening Test for Clinical Early-Stage Osteoarthritis.Antioxidants (Basel, Switzerland) · 2025Article
- Predictive modeling of hematoma expansion from non-contrast computed tomography in spontaneous intracerebral hemorrhage patients.medRxiv : the preprint server for health sciences · 2025Article
- Linear Optimal Transport Subspaces for Point Set Classification.Journal of mathematical imaging and vision · 2025Article
- Artificial intelligence-assisted analysis of musculoskeletal imaging-A narrative review of the current state of machine learning models.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Review
- Integration of longitudinal load-bearing tissue MRI radiomics and neural network to predict knee osteoarthritis incidence.Journal of orthopaedic translation · 2025Article
- Quantifying Nuclear Structures of Digital Pathology Images Across Cancers Using Transport-Based Morphometry.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2025Article
- Spatiotemperal Dynamics of Osteoarthritis: Bridging Insights from Bench to Bedside.Aging and disease · 2024Review
- Discovering the gene-brain-behavior link in autism via generative machine learning.Science advances · 2024Article
- Glenohumeral Osteoarthritis: A Biological Advantage or a Missed Diagnosis?Journal of clinical medicine · 2024Review
- Identification of sulfur metabolism-related gene signature in osteoarthritis and TM9SF2's sustenance effect on M2 macrophages' phagocytic activity.Journal of orthopaedic surgery and research · 2024Article
- 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
- Knee Osteoarthritis Detection and Severity Classification Using Residual Neural Networks on Preprocessed X-ray Images.Diagnostics (Basel, Switzerland) · 2023Article
- The application of machine learning in early diagnosis of osteoarthritis: a narrative review.Therapeutic advances in musculoskeletal disease · 2023Review
- Cutting-Edge Approaches in Arthroplasty: Before, during and after Surgery.Journal of personalized medicine · 2022Article
- Optimization of spin-lock times for TScientific reports · 2022Article
- Article
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9 authors.
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Abstract
Many diseases have no visual cues in the early stages, eluding image-based detection. Today, osteoarthritis (OA) is detected after bone damage has occurred, at an irreversible stage of the disease. Currently no reliable method exists for OA detection at a reversible stage. We present an approach that enables sensitive OA detection in presymptomatic individuals. Our approach combines optimal mass transport theory with statistical pattern recognition. Eighty-six healthy individuals were selected from the Osteoarthritis Initiative, with no symptoms or visual signs of disease on imaging. On 3-y follow-up, a subset of these individuals had progressed to symptomatic OA. We trained a classifier to differentiate progressors and nonprogressors on baseline cartilage texture maps, which achieved a robust test accuracy of 78% in detecting future symptomatic OA progression 3 y prior to symptoms. This work demonstrates that OA detection may be possible at a potentially reversible stage. A key contribution of our work is direct visualization of the cartilage phenotype defining predictive ability as our technique is generative. We observe early biochemical patterns of fissuring in cartilage that define future onset of OA. In the future, coupling presymptomatic OA detection with emergent clinical therapies could modify the outcome of a disease that costs the United States healthcare system $16.5 billion annually. Furthermore, our technique is broadly applicable to earlier image-based detection of many diseases currently diagnosed at advanced stages today.
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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.