ArticleClinics (Sao Paulo, Brazil)2020
Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging.
Article in Clinics (Sao Paulo, Brazil), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 21 citations in OpenAlex.
- An Anatomically Guided and Optimization-Refined Radiomics Framework for Opportunistic Osteoporosis Assessment from Lumbar Spine MRI.Diagnostics (Basel, Switzerland) · 2026Article
- Integrating deep learning and machine learning for improved CKD-related cortical bone assessment in HRpQCT images: A pilot study.Bone reports · 2025Article
- MRI-based radiomics assessment of the imminent new vertebral fracture after vertebral augmentation.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2023Article
- Development and validation of a machine learning model to predict imminent new vertebral fractures after vertebral augmentation.BMC musculoskeletal disorders · 2023Article
- Features of lumbar spine texture extracted from routine MRI correlate with bone mineral density and can potentially differentiate patients with and without fragility fractures in the spine.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2023Article
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Authors and funding
7 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveDual-energy X-ray absorptiometry (DXA)-derived bone mineral density (BMD) often fails to predict fragility fractures. Quantitative textural analysis using magnetic resonance imaging (MRI) may potentially yield useful radiomic features to predict fractures. We aimed to investigate the correlation between BMD and texture attributes (TAs) extracted from MRI scans and the interobserver reproducibility of the analysis.
methodsForty-nine volunteers underwent lumbar spine 1.5-T MRI and DXA. Three-dimensional (3-D) gray-level co-occurrence matrices were measured from routine sagittal T2 fast spin-echo images using the IBEX software. Twenty-two TAs were extracted from 3-D segmented L3 vertebrae. The estimated concordance coefficient was calculated using linear regression analysis. A Pearson correlation coefficient analysis was performed to evaluate the correlation between BMD and the TAs. Interobserver reproducibility was assessed with the concordance coefficient described by Lin.
resultsThe results revealed a fair-to-moderate significant correlation between BMD and 13 TAs (r=-0.20 to 0.39; p<0.05). Eight TAs (autocorrelation, energy, homogeneity 1, homogeneity 1.1, maximum probability, sum average, sum variance, and inverse difference normalized) negatively correlated with BMD (r=-0.20 to -0.38; p<0.05), whereas five TAs (dissimilarity, difference entropy, entropy, sum entropy, and information measure corr 1) positively correlated with BMD (r=0.29-0.39; p<0.05). The interobserver agreement was almost perfect for all significant TAs (95% confidence interval, 0.92-1.00; p<0.05).
conclusionSpecific TAs could be reliably extracted from routine MRI and correlated with BMD. Our results encourage future evaluation of the potential usefulness of quantitative texture measurements from MRI scans for predicting fragility fractures.
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