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Fatty Acid Composition of Proximal Femur Bone Marrow Adipose Tissue in Subjects With Systemic Lupus Erythematous Using 3 T Magnetic Resonance Spectroscopy

Martel, Dimitri; Saxena, Amit; Belmont, Howard Michael; Honig, Stephen; Chang, Gregory
BACKGROUND:Systemic lupus erythematosus (SLE) is a chronic, inflammatory disease with common musculoskeletal manifestations, notably reductions in bone quality. Bone marrow adipose tissue composition and quantity has been previously linked to bone quality and may play a role in SLE pathophysiology but has not been thoroughly studied. PURPOSE/OBJECTIVE:To use magnetic resonance spectroscopy (MRS) to investigate bone marrow adipose tissue quantity and composition in proximal femur subregions of untreated SLE patients compared to controls and treated patients. STUDY TYPE/METHODS:Prospective. SUBJECTS/METHODS:A total of 64 female subjects: 28 SLE, 15 glucocorticoid (GC)-treated SLE and 21 matched controls. FIELD STRENGTH/SEQUENCE/UNASSIGNED:Stimulated echo acquisition mode (STEAM) sequence at 3 T. ASSESSMENT/RESULTS:MRS was performed at multiple echo times in the femoral neck and trochanter regions and fatty acids (FA) composition was computed. STATISTICAL TESTS/UNASSIGNED:Intergroup comparisons were carried out using ANOVA. A P value < 0.05 was considered statistically significant. RESULTS:SLE patients had significantly higher saturated FA compared to controls in both the femoral neck (+0.12) and trochanter (+0.11), significantly lower monounsaturated FA in the trochanter compared to controls (-0.05), and significantly lower polyunsaturated FA in the femoral neck compared to both controls (-0.07) and SLE patients on GC therapy (-0.05). DATA CONCLUSION/UNASSIGNED:SLE patients have altered proximal femur marrow fat metabolism, which may reflect a manifestation of, or play a role in, the altered inflammatory response of these patients. EVIDENCE LEVEL/UNASSIGNED:2 TECHNICAL EFFICACY: Stage 2.
PMID: 34964533
ISSN: 1522-2586
CID: 5108212

The effects of caffeine on bone mineral density and fracture risk

Berman, N K; Honig, S; Cronstein, B N; Pillinger, M H
Caffeine is a regular part of the diet of many adults (coffee, tea, soft drinks, and energy drinks). Multiple molecular effects of caffeine suggest that it may promote bone loss. Given the extensive consumption of caffeine worldwide, any impact of caffeine consumption on bone strength and/or density would have large population health implications. The most well-established pharmacological effect of caffeine is non-specific antagonism of adenosine receptors. Adenosine regulates bone metabolism in a complex manner, with in vitro studies suggesting that direct stimulation of adenosine A2A and A2B receptors induces bone formation by activating osteoblasts and suppressing osteoclast differentiation and function. Thus, competitive inhibition of adenosine A2 receptors by caffeine may inhibit bone formation and promote bone resorption. However, antagonism of adenosine A1 receptors may have opposing effects. Caffeine has also been suggested to affect bone through derangement of calcium metabolism, alteration of vitamin D responses, and other mechanisms. In clinical and population-based studies, the impact of caffeine consumption on bone metabolism offers a mixed picture, with some but not all studies suggesting a potential link between caffeine intake and reduced bone mineral density or increased fracture risk. Differences in methodology, selected populations, and duration/timing of the studies may account for study outcome discrepancies. The in vitro effects of caffeine on cells involved in bone metabolism suggest that caffeine intake may promote osteoporosis, and some but not all clinical studies support a modest adverse caffeine impact. Herein, we describe the basic biology of caffeine as it pertains to bone, review the clinical literature to date, and consider the implications of the current data on clinical practice and future studies.
PMID: 34981132
ISSN: 1433-2965
CID: 5106942

Quantitative 3T MRI of multiple adipose tissue in osteoporosis patient with varying fracture risk [Meeting Abstract]

Martel, D; Honig, S; Chang, G
Purpose: Osteoporosis (OP) is a disease of weak bone associated with increased fracture risk (Fx). An important component of bone tissue is bone marrow adipose tissue (BAT), which has been previously associated with Fx and OP. Recent studies have shown an association between BMD and fat quantity in the spine and femur using Chemical Shift Encoded MRI (CSE-MRI). The aim of our study was to apply CSE-MRI in thigh muscle (MUS), BAT, and subcutaneous fat (SAT) of the pelvic region in osteoporosis patients with varying degrees of Fx.
Material(s) and Method(s): This study had institutional review board approval and written informed consent was obtained from all n=128 recruited female subjects with OP. Patients were divided into three groups for analysis based upon overall FRAX score: low (LOW, FRAX < 10, n=42, 57+/-6.9y, BMI 23+/-4.1 kg/m2), moderate (MOD, 10>FRAX>20, n=52, 62+/-6.9y, BMI 22+/-3.4 kg/m2) and high (HIGH, FRAX>20, n=34, 64+/-5.8y, BMI 22+/-3.1 kg/m2). 3T MRI acquisition were performed a 3T using a 3D spoiled gradient-echo sequence. An automatic reconstruction pipeline allowed computation of proton density fat fraction (PDFF), susceptibility mapping (QSM) and R2*. BAT, MUS and SAT were segmented by thresholding the PDFF map. An unpaired one-way ANOVA test was used to assess significant differences.
Result(s): Overall, in BAT, we found a higher amount of PDFF in HIGH subjects compared to LOW subjects (+5%, p= 0.032). In muscle, we found a higher amount of PDFF in HIGH compared to both LOW (+8.87%, p =0.008) and MOD subjects (+9.25%, p= 0.006). There were no differences between groups with regards to R2*measured. We found diamagnetic BAT and MUS and paramagnetic SAT. Susceptibility of SAT was higher in LOW compared to both HIGH (-31%, p= 0.008) and MOD (-23%, p= 0.04) subjects. Volume of MUS was lower in MOD compared to LOW (-8%, p=0.009) and HIGH (-9%, p=0.045).
Conclusion(s): Our result suggests that fracture risk is related to an increased amount of adipose tissue. 3T CSE-MRI could be used in the future to study the relationship between adipose tissue and bone health and possibly even provide an additional surrogate marker of Fx beyond BMD
ISSN: 1432-2161
CID: 4792472

Analysis of muscle, hip, and subcutaneous fat in osteoporosis patients with varying degrees of fracture risk using 3T Chemical Shift Encoded MRI

Martel, Dimitri; Honig, Stephen; Monga, Anmol; Chang, Gregory
Osteoporosis (OP) is a major disease that affects 200 million people worldwide. Fatty acid metabolism plays an important role in bone health and plays an important role in bone quality and remodeling. Increased bone marrow fat quantity has been shown to be associated with a decrease in bone mineral density (BMD), which is used to predict fracture risk. Chemical-Shift Encoded magnetic resonance imaging (CSE-MRI) allows noninvasive and quantitative assessment of adipose tissues (AT). The aim of our study was to assess hip or proximal femoral bone marrow adipose tissue (BMAT), thigh muscle (MUS), and subcutaneous adipose tissue (SAT) in 128 OP subjects matched for age, BMD, weight and height with different degrees of fracture risk assessed through the FRAX score (low, moderate and high). Our results showed an increase in BMAT and in MUS in high compared to low fracture risk patients. We also assessed the relationship between fracture risk as assessed by FRAX and AT quantities. Overall, the results of this study suggest that assessment of adipose tissue via 3T CSE-MRI provides insight into the pathophysiology fracture risk by showing differences in the bone marrow and muscle fat content in subjects with similarly osteoporotic BMD as assessed by DXA, but with varying degrees of fracture risk as assessed by FRAX.
PMID: 32322608
ISSN: 2352-1872
CID: 4401462

Evaluation of factors associated with bone structure in an SLE cohort measured by clinical 3T MRI and DEXA [Meeting Abstract]

Saxena, A; Izmirly, P; Buyon, J; Honig, S; Zhang, X; Saha, P; Belmont, H M; Chang, G
Background/Purpose : Osteoporosis and bone fractures are a frequent cause of morbidity in systemic lupus erythematosus (SLE), and are felt to be related both to disease activity and glucocorticoid (GC) exposure. Dual energy X-ray absorptiometry (DEXA) is the standard tool to assess bone density, but it does not measure bone quality or strength and is not a robust predictor of fractures in SLE. Clinical 3T MRI scans have been shown to assess information about bone not captured by DEXA. This study aims to evaluate factors associated with bone structure measured by DEXA and MRI in an SLE cohort. Methods : DEXAs were performed on 31 women with SLE and 3T MRI of the non-dominant hip were performed on 29 of these cases. Results were associated with multiple demographic, clinical and laboratory measures. MRI parameters measured included trabecular plate width (PW), trabecular plate to rod ratio (PRR), plate volume fraction (PVF), rod volume fraction (RVF), trabecular bone thickness (Tb.Th), trabecular spacing (Tb.Sp) and trabecular network area (TNA). DEXA BMD was measured, and osteoporosis (OP) was defined as hip, spine or femoral neck Z score < -2.0 in premenopausal women, and T score < -2.5 in others, and low bone density (LBD) as Z score < -2.0 in premenopausal women and T score < -1.0 in others. Results : By DEXA, 8/31 (25.8%) had OP and 12 (38.7%) had LBD. History of lymphopenia (75.0% vs. 31.8%, p=0.049) and lower concurrent HCQ dose (340 vs. 400 mg, p=0.006) associated with DEXA OP, while older age (48.3 vs. 36.3 y, p=0.024) associated with LBD. Higher ESR was inversely correlated with favorable bone structure (PW r(22) = -.49, p=0.025, PRR rs = -.51, p=0.018, PVF rs = -.51, p=0.018, RVF rs = .51, p=0.018, Tb.Th rs = -.58, p=0.005, Tb.Sp rs = .44, p=0.046, TNA rs = -.50, p=0.022). Higher CRP was likewise inversely correlated with favorable bone structure (PW r(20) = -.61, p=0.004, PRR rs = -.57, p=0.009, PVF rs = -.57, p=0.009, RVF rs =.57, p=0.009, Tb.Th rs = -.56, p=.011, Tb.Sp rs =.67, p=0.001, TNA rs = -.64, p=0.002). A history of lupus nephritis was associated with unfavorable bone structure (PW 705.3 vs. 833.3 mum, p=0.048, PRR 6.6 vs. 8.1, p=0.024, PVF 0.83 vs. 0.89, p=0.024, RVF 0.17 vs. 0.11, p=0.024, Tb.Th 178.1 vs. 193.4 mm, p=0.012, Tb.Sp 358.6 vs. 296.5 mm, p=0.056, TNA 0.41 vs. 0.54 (1/mm), p=0.009). ESR, CRP and history of lupus nephritis were not significantly associated with DEXA hip BMD, OP or LBD. MRI parameters for favorable bone structure were inversely correlated with DEXA hip BMD (PW r(28) = -.47, p=0.011, Tb.Th rs = -.53, p=0.003) and BMI (PW r(28) = -.54, p=0.003, TbTh rs = -.72, p< 0.001, TNA rs = -.44, p=0.017). Conclusion : Higher ESR and CRP and a history of lupus nephritis associated with MRI parameters of unfavorable bone structure, but did not associate with DEXA abnormalities in SLE patients. MRI may be a more sensitive tool than DEXA to measure inflammatory effects on bone and potentially cumulative dose of steroid exposure. There were inverse correlations of MRI parameters with traditional osteoporosis risk factors and BMD measures on DEXA, and it is possible that each tool evaluates different aspects of bone health. Further evaluation of MRI screening for fracture risk in SLE and GC exposed individuals is warranted to better quantify risk and guide treatment
ISSN: 2326-5205
CID: 4633412

3T chemical shift-encoded MRI: Detection of altered proximal femur marrow adipose tissue composition in glucocorticoid users and validation with magnetic resonance spectroscopy

Martel, Dimitri; Leporq, Benjamin; Saxena, Amit; Belmont, H Michael; Turyan, Gabrielle; Honig, Stephen; Regatte, Ravinder R; Chang, Gregory
BACKGROUND:Osteoporosis (OP) results in weak bone and can ultimately lead to fracture. Drugs such as glucocorticoids can also induce OP (glucocorticoid-induced osteoporosis [GIO]). Bone marrow adipose tissue composition and quantity may play a role in OP pathophysiology, but has not been thoroughly studied in GIO compared to primary OP. PURPOSE/HYPOTHESIS/UNASSIGNED:Chemical shift-encoded (CSE) MRI allows detection of subregional differences in bone marrow adipose tissue composition and quantity in the proximal femur of GIO compared to OP subjects and has high agreement with the reference standard of magnetic resonance spectroscopy (MRS). STUDY TYPE/METHODS:Prospective. SUBJECTS/METHODS:In all, 18 OP and 13 GIO subjects. FIELDS STRENGTH/UNASSIGNED:3T. SEQUENCE/UNASSIGNED:Multiple gradient-echo, stimulated echo acquisition mode (STEAM). ASSESSMENT/RESULTS:Subjects underwent CSE-MRI in the proximal femurs, and for each parametric map regions of interest (ROIs) were assessed in the femoral head (fHEAD), femoral neck (fNECK), Ward's triangle (fTRIANGLE), and the greater trochanter (GTROCH). In addition, we compared CSE-MRI against the reference standard of MRS performed in the femoral neck and Ward's triangle. STATISTICAL TESTS/UNASSIGNED:Differences between OP/GIO were investigated using the Mann-Whitney nonparametric test. Bland-Altman methodology was used to assess measurement agreement between CSE-MRI and MRS. RESULTS: DATA CONCLUSION/UNASSIGNED:3T CSE-MRI may allow reliable assessment of subregional bone marrow adipose tissue (bMAT) quantity and composition in the proximal femur in a clinically reasonable scan time. Glucocorticoids may alter the lipid profile of bMAT and potentially result in reduced bone quality. LEVEL OF EVIDENCE/METHODS:2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.
PMID: 30548522
ISSN: 1522-2586
CID: 3961382

Artificial intelligence, osteoporosis and fragility fractures

Ferizi, Uran; Honig, Stephen; Chang, Gregory
PURPOSE OF REVIEW/OBJECTIVE:Artificial intelligence tools have found new applications in medical diagnosis. These tools have the potential to capture underlying trends and patterns, otherwise impossible with previous modeling capabilities. Machine learning and deep learning models have found a role in osteoporosis, both to model the risk of fragility fracture, and to help with the identification and segmentation of images. RECENT FINDINGS/RESULTS:Here we survey the latest research in the artificial intelligence application to the prediction of osteoporosis that is published between January 2017 and March 2019. Around half of the articles that are covered here predict (by classification or regression) an indicator of osteoporosis, such as bone mass or fragility fractures; the other half of studies use tools for automatic segmentation of the images of patients with or at risk of osteoporosis. The data for these studies include diverse signal sources: acoustics, MRI, CT, and of course, X-rays. SUMMARY/CONCLUSIONS:New methods for automatic image segmentation, and prediction of fracture risk show promising clinical value. Though these recent developments have had a successful initial application to osteoporosis research, their development is still under improvement, such as accounting for positive/negative class bias. We urge care when reporting accuracy metrics, and when comparing such metrics between different studies.
PMID: 31045948
ISSN: 1531-6963
CID: 3854882

Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data

Ferizi, Uran; Besser, Harrison; Hysi, Pirro; Jacobs, Joseph; Rajapakse, Chamith S; Chen, Cheng; Saha, Punam K; Honig, Stephen; Chang, Gregory
BACKGROUND:A current challenge in osteoporosis is identifying patients at risk of bone fracture. PURPOSE/OBJECTIVE:To identify the machine learning classifiers that predict best osteoporotic bone fractures and, from the data, to highlight the imaging features and the anatomical regions that contribute most to prediction performance. STUDY TYPE/METHODS:Prospective (cross-sectional) case-control study. POPULATION/METHODS:. Field Strength/ Sequence: 3D FLASH at 3T. ASSESSMENT/RESULTS:Quantitative MRI outcomes by software algorithms. Mechanical and topological microstructural parameters of the trabecular bone were calculated for five femoral regions, and added to the vector of features together with bone mineral density measurement, fracture risk assessment tool (FRAX) score, and personal characteristics such as age, weight, and height. We fitted 15 classifiers using 200 randomized cross-validation datasets. Statistical Tests: Data: Kolmogorov-Smirnov test for normality. Model Performance: sensitivity, specificity, precision, accuracy, F1-test, receiver operating characteristic curve (ROC). Two-sided t-test, with P < 0.05 for statistical significance. RESULTS:The top three performing classifiers are RUS-boosted trees (in particular, performing best with head data, F1 = 0.64 ± 0.03), the logistic regression and the linear discriminant (both best with trochanteric datasets, F1 = 0.65 ± 0.03 and F1 = 0.67 ± 0.03, respectively). A permutation of these classifiers comprised the best three performers for four out of five anatomical datasets. After averaging across all the anatomical datasets, the score for the best performer, the boosted trees, was F1 = 0.63 ± 0.03 for All-features dataset, F1 = 0.52 ± 0.05 for the no-MRI dataset, and F1 = 0.48 ± 0.06 for the no-FRAX dataset. Data Conclusion: Of many classifiers, the RUS-boosted trees, the logistic regression, and the linear discriminant are best for predicting osteoporotic fracture. Both MRI and FRAX independently add value in identifying osteoporotic fractures. The femoral head, greater trochanter, and inter-trochanter anatomical regions within the proximal femur yielded better F1-scores for the best three classifiers. LEVEL OF EVIDENCE/METHODS:2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.
PMID: 30252971
ISSN: 1522-2586
CID: 3316002

Influence of bone lesion location on femoral bone strength assessed by MRI-based finite-element modeling

Rajapakse, Chamith S; Gupta, Nishtha; Evans, Marissa; Alizai, Hamza; Shukurova, Malika; Hong, Abigail L; Cruickshank, Nicholas J; Tejwani, Nirmal; Egol, Kenneth; Honig, Stephen; Chang, Gregory
Currently, clinical determination of pathologic fracture risk in the hip is conducted using measures of defect size and shape in the stance loading condition. However, these measures often do not consider how changing lesion locations or how various loading conditions impact bone strength. The goal of this study was to determine the impact of defect location on bone strength parameters in both the sideways fall and stance-loading conditions. We recruited 20 female subjects aged 48-77 years for this study and performed MRI of the proximal femur. Using these images, we simulated 10-mm pathologic defects in greater trochanter, superior, middle, and inferior femoral head, superior, middle, and inferior femoral neck, and lateral, middle, and medial proximal diaphysis to determine the effect of defect location on change in bone strength by performing finite element analysis. We compared the effect of each osteolytic lesion on bone stiffness, strength, resilience, and toughness. For the sideways fall loading, defects in the inferior femoral head (12.21%) and in the greater trochanter (6.43%) resulted in the greatest overall reduction in bone strength. For the stance loading, defects in the mid femoral head (-7.91%) and superior femoral head (-7.82%) resulted in the greatest overall reduction in bone strength. Changes in stiffness, yield force, ultimate force, resilience, and toughness were not found to be significantly correlated between the sideways fall and stance-loading for the majority of defect locations, suggesting that calculations based on the stance-loading condition are not predictive of the change in bone strength experienced in the sideways fall condition. While stiffness was significantly related to yield force (R2 > 0.82), overall force (R2 > 0.59), and resilience (R2 > 0.55), in both, the stance-loading and sideways fall conditions for most defect locations, stiffness was not significantly related to toughness. Therefore, structure-dependent measure such as stiffness may not fully explain the post-yield measures, which depend on material failure properties. The data showed that MRI-based models have the sensitivity to determine the effect of pathologic lesions on bone strength.
PMID: 30851438
ISSN: 1873-2763
CID: 3747652

A Novel MRI Tool for Evaluating Cortical Bone Thickness of the Proximal Femur

Ramme, Austin J; Vira, Shaleen; Hotca, Alexandra; Miller, Rhiannon; Welbeck, Arakua; Honig, Stephen; Egol, Kenneth A; Rajapakse, Chamith S; Chang, Gregory
BACKGROUND:Osteoporotic hip fractures heavily cost the health care system. Clinicians and patients can benefit from improved tools to assess bone health. Herein, we aim to develop a three-dimensional magnetic resonance imaging (MRI) method to assess cortical bone thickness and assess the ability of the method to detect regional changes in the proximal femur. METHODS:Eighty-nine patients underwent hip magnetic resonance imaging. FireVoxel and 3DSlicer were used to generate three-dimensional proximal femur models. ParaView was used to define five regions: head, neck, greater trochanter, intertrochanteric region, and subtrochanteric region. Custom software was used to calculate the cortical bone thickness and generate a color map of the proximal femur. Mean cortical thickness values for each region were calculated. Statistical t-tests were performed to evaluate differences in cortical thickness based on proximal femur region. Measurement reliability was evaluated using coefficient of variation, intraclass correlation coefficients, and overlap metrics. RESULTS:Three-dimensional regional cortical thickness maps for all subjects were generated. The subtrochanteric region was found to have the thickest cortical bone and the femoral head had the thinnest cortical bone. There were statistically significant differences between regions (p < 0.01) for all possible comparisons. CONCLUSIONS:Cortical bone is an important contributor to bone strength, and its thinning results in increased hip fracture risk. We describe the development and measurement reproducibility of an MRI tool permitting assessment of proximal femur cortical thickness. This study represents an important step toward longitudinal clinical trials interested in monitoring the effectiveness of drug therapy on proximal femur cortical thickness.
PMID: 31128580
ISSN: 2328-5273
CID: 4044402