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Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging.

ABSTRACT: OBJECTIVE:Dual-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. METHODS:Forty-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. RESULTS:The 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). CONCLUSION:Specific 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.

SUBMITTER: Maciel JG

PROVIDER: S-EPMC7442400 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging.

Maciel Jamilly Gomes JG Araújo Iana Mizumukai de IM Trazzi Lucio C LC Azevedo-Marques Paulo Mazzoncini de PM Salmon Carlos Ernesto Garrido CEG Paula Francisco José Albuquerque de FJA Nogueira-Barbosa Marcello Henrique MH

Clinics (Sao Paulo, Brazil) 20200826

<h4>Objective</h4>Dual-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.<h4>Methods</h4>Forty-nine volunteers underwent lumbar spine 1.5- ...[more]

PMID: 32876107

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Project description:ObjectiveThis study aimed to assess the relationship between bone marrow edema (BME) on magnetic resonance imaging (MRI) and bone mineral density (BMD) in patients with ankylosing spondylitis (AS).MethodsThe study included 333 patients with AS who underwent BMD measurements and axial MRI. Additionally, 106 normal controls were included. The modified New York criteria were used as the classification criteria of AS. Clinical, laboratory, and imaging data were collected and analyzed. Lumbar spine and proximal femur BMD were assessed using dual-energy X-ray absorptiometry. Low BMD was defined by a Z-score ≤-2. The Spondyloarthritis Research Consortium of Canada (SPARCC) MRI index was used to assess inflammation at the sacroiliac joint (SIJ) and spine.ResultsAmong the 333 patients, the male:female ratio was 4.6:1, mean patient age was 28.5±10.6 years, and mean disease duration was 7.3±6.8 years. The prevalences of low BMD, osteopenia, and osteoporosis were significantly higher among AS patients than among controls (19.8%, 62.8%, and 5.7% vs. 4.7%, 33.0%, and 0%, respectively, P = 0.000). The BMD values were significantly lower and prevalences of low BMD at both the spine and femur were significantly higher among patients with BME on MRI than among those without BME. Multivariate logistic regression analysis showed that male sex (OR 3.87, 95% CI 1.21-7.36, P = 0.023), high ASDAS-CRP score (OR 2.83, 95% CI 1.36-4.76, P = 0.015), the presence of BME on sacroiliac MRI (OR 2.83, 95% CI 1.77-6.23, P = 0.000) and spinal MRI (OR 4.06, 95% CI 1.96-8.46, P = 0.000), and high grade of sacroiliitis (OR 2.93, 95% CI 1.82-4.45, P = 0.002) were risk factors for low BMD (any site). The SPARCC scores of the SIJ were negatively correlated with femoral BMD (r = -0.22, 95% CI -0.33 to -0.10, P = 0.000). Additionally, the SPARCC scores of the spine were negatively correlated with BMD values (r = -0.23, 95% CI -0.36 to -0.09, P = 0.003) and Z-scores (r = -0.24, 95% CI -0.36 to -0.12, P = 0.001) at the spine.ConclusionLow BMD is common in AS patients. BME on MRI is highly associated with low BMD at both the spine and femur.

Project description:OBJECTIVES:To assess whether initial or 12-18-month change in magnetic resonance imaging (MRI) subchondral bone texture is predictive of radiographic knee osteoarthritis (OA) progression over 36 months. METHODS:This was a nested case-control study including 122 knees/122 participants in the Osteoarthritis Initiative (OAI) Bone Ancillary Study, who underwent MRI optimised for subchondral bone assessment at either the 30- or 36-month and 48-month OAI visits. Case knees (n = 61) had radiographic OA progression between the 36- and 72-month OAI visits, defined as ? 0.7 mm minimum medial tibiofemoral radiographic joint space (minJSW) loss. Control knees (n = 61) without radiographic OA progression were matched (1:1) to cases for age, sex, body mass index and initial medial minJSW. Texture analysis was performed on the medial femoral and tibial subchondral bone. We assessed the association of texture features with radiographic progression by creating a composite texture score using penalised logistic regression and calculating odds ratios. We evaluated the predictive performance of texture features for predicting radiographic progression using c-statistics. RESULTS:Initial (odds ratio [95% confidence interval] = 2.13 [1.41-3.40]) and 12- 18-month change (3.76 [2.04-7.82]) texture scores were significantly associated with radiographic OA progression. Combinations of texture features were significant predictors of radiographic progression using initial (c-statistic [95% confidence interval] = 0.65 [0.64-0.65], p = 0.003) and 12-18-month change (0.68 [0.68-0.68], p < 0.001) data. CONCLUSIONS:Initial and 12-18-month changes in MRI subchondral bone texture score were significantly associated with radiographic progression at 36 months, with better predictive performance for 12-18-month change in texture. These results suggest that texture analysis may be a useful biomarker of subchondral bone in OA. KEY POINTS:• Subchondral bone MRI texture analysis is a promising knee osteoarthritis imaging biomarker. • In this study, subchondral bone texture was associated with knee osteoarthritis progression. • This demonstrates predictive and concurrent validity of MRI subchondral bone texture analysis. • This method may be useful in clinical trials with interventions targeting bone.

Project description:BackgroundTo investigate reproducibility of texture features and volumetric bone mineral density (vBMD) extracted from trabecular bone in the thoracolumbar spine in routine clinical multi-detector computed tomography (MDCT) data in a single scanner environment.MethodsPatients who underwent two routine clinical thoraco-abdominal MDCT exams at a single scanner with a time interval of 6 to 26 months (n=203, 131 males; time interval mean, 13 months; median, 12 months) were included in this observational study. Exclusion criteria were metabolic and hematological disorders, bone metastases, use of bone-active medications, and history of osteoporotic vertebral fractures (VFs) or prior diagnosis of osteoporosis. A convolutional neural network (CNN)-based framework was used for automated spine labeling and segmentation (T5-L5), asynchronous Hounsfield unit (HU)-to-BMD calibration, and correction for the intravenous contrast medium phase. Vertebral vBMD and six texture features [varianceglobal, entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP)] were extracted for mid- (T5-T8) and lower thoracic (T9-T12), and lumbar vertebrae (L1-L5), respectively. Relative annual changes were calculated in texture features and vBMD for each vertebral level and sorted by sex, and changes were checked for statistical significance (P<0.05) using paired t-tests. Root mean square coefficient of variation (RMSCV) and root mean square error (RMSE) were calculated as measures of variability.ResultsSRE, LRE, RLN, and RP exhibited substantial reproducibility with RMSCV-values below 2%, for both sexes and at all spine levels, while vBMD was less reproducible (RMSCV =11.9-16.2%). Entropy showed highest variability (RMSCV =4.34-7.69%) due to statistically significant increases [range, mean ± standard deviation: (4.40±5.78)% to (8.36±8.66)%, P<0.001]. RMSCV of varianceglobal ranged from 1.60% to 3.03%.ConclusionsOpportunistic assessment of texture features in a single scanner environment using the presented CNN-based framework yields substantial reproducibility, outperforming vBMD reproducibility. Lowest scan-rescan variability was found for higher-order texture features. Further studies are warranted to determine, whether microarchitectural changes to the trabecular bone may be assessed through texture features.

Dataset Information

Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging.

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Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging.

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