ArticleJournal of digital imaging2022
Radiomic Quantification for MRI Assessment of Sacroiliac Joints of Patients with Spondyloarthritis.
Article in Journal of digital imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
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Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- The role of deep learning in diagnostic imaging of spondyloarthropathies: a systematic review.European radiology · 2025Pooled it
- Performances of machine learning algorithms in discriminating sacroiliitis features on MRI: a systematic review.RMD open · 2023Pooled it
- Automated grading and diagnosis of sacroiliitis on CT images using a 3D convolutional neural network: a multicenter retrospective study.Scientific reports · 2026Article
- Biomarkers in axial spondyloarthritis diagnosis: from clinical signs to multi-omics integration.Frontiers in immunology · 2026Review
- Multimodal feature fusion model for breast mass malignant risk stratification.Frontiers in oncology · 2026Article
- Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis.Therapeutic advances in musculoskeletal disease · 2025Review
- Dual-energy computed tomography-based radiomics for differentiating patients with and without gout flares.Clinical rheumatology · 2024Article
- Beyond the horizon: Innovations and future directions in axial-spondyloarthritis.Archives of rheumatology · 2023Review
- Assessment of axial spondyloarthritis activity using a magnetic resonance imaging-based multi-region-of-interest fusion model.Arthritis research & therapy · 2023Article
- T1-weighted images-based radiomics for structural lesions evaluation in patients with suspected axial spondyloarthritis.La Radiologia medica · 2023Article
- ASNET: A Novel AI Framework for Accurate Ankylosing Spondylitis Diagnosis from MRI.Biomedicines · 2023Article
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Authors and funding
9 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spondyloarthritis (SpA) is a group of diseases primarily involving chronic inflammation of the spine and peripheral joints, as evaluated by magnetic resonance imaging (MRI). Considering the complexity of SpA, we performed a retrospective study to discover quantitative/radiomic MRI-based features correlated with SpA. We also investigated different fat-suppression MRI techniques to develop detection models for inflammatory sacroiliitis. Finally, these model results were compared with those of experienced musculoskeletal radiologists, and the concordance level was evaluated. Examinations of 46 consecutive patients were obtained using SPAIR (spectral attenuated inversion recovery) and STIR (short tau inversion recovery) MRI sequences. Musculoskeletal radiologists manually segmented the sacroiliac joints for further extraction of 230 MRI features from gray-level histogram/matrices and wavelet filters. These features were associated with sacroiliitis, SpA, and the current biomarkers of ESR (erythrocyte sedimentation rate), CRP (C-reactive protein), BASDAI (Bath Ankylosing Spondylitis Activity Index), BASFI (Bath Ankylosing Spondylitis Functional Index), and MASES (Maastricht Ankylosing Spondylitis Enthesis Score). The Mann-Whitney U test showed that the radiomic markers from both MRI sequences were associated with active sacroiliitis and with SpA and its axial and peripheral subtypes (p < 0.05). Spearman's coefficient also identified a correlation between MRI markers and data from clinical practice (p < 0.05). Fat-suppression MRI models yielded performances that were statistically equivalent to those of specialists and presented strong concordance in identifying inflammatory sacroiliitis. SPAIR and STIR acquisition protocols showed potential for the evaluation of sacroiliac joints and the composition of a radiomic model to support the clinical assessment of SpA.
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