Associations of incidental vertebral fractures and longitudinal changes of MR-based proton density fat fraction and T2* measurements of vertebral bone marrow

Higher systemic immune-inflammation index associates with vertebral marrow proton density fat fraction in postmenopausal women

INTRODUCTION

The systemic immune-inflammation index (SII) may influence bone homeostasis through inflammatory modulation. Although bone marrow adipocytes regulate bone metabolism via adipokine secretion, their interaction with SII remains unexplored. We investigated the SII-marrow adiposity relationship in postmenopausal women.

MATERIALS AND METHODS

This retrospective study included 187 postmenopausal women. Lumbar spine MRI using chemical shift encoding generated proton density fat fraction (PDFF) maps, with bone mineral density (BMD) measured by dual x-ray absorptiometry. The relationship between SII and marrow PDFF was evaluated through multivariable-adjusted linear regression, smooth curve fittings, and threshold analysis.

RESULTS

The results revealed a negative correlation between marrow PDFF values and BMD (r = - 0.438, P < 0.001). After accounting for age, time since menopause, body mass index, physical activity, C-reactive protein, interleukin (IL)-1β, IL-6, tumor necrosis factor-α, and BMD in the regression analysis, each unit increase in SII was found to be inked to an increase of 0.247 (β = 0.247; 95% confidence interval [CI], 0.212 to 0.281; P <0.001) in PDFF. After converting SII to a categorical variable (quartiles), participants in the highest SII quartile had a 16.8% higher vertebral marrow PDFF than those in the lowest SII quartile (β = 16.753, 95% CI: 11.036-18.522, P <0.001). Furthermore, a curvilinear relationship and threshold effect were also identified. Turning point was identified at the SII value of 441 on the adjusted smooth curve.

CONCLUSIONS

SII levels were positively associated with marrow adiposity in postmenopausal women.

Longitudinal assessment of changes in muscle composition using proton density fat fraction and T2* in patients with and without incidental vertebral compression fractures

Objective

Chemical shift encoded-based water-fat separation magnetic resonance imaging (CSE-MRI) is an emerging noninvasive tool for the assessment of bone and muscle composition. This study aims to examine both the predictive value and the longitudinal change of proton density fat fraction (PDFF) and T2* in the paraspinal muscles (PSM) in patients with and without the development of an incidental vertebral compression fracture (VCFs) after 6 months of follow-up.

Methods

Patients (N=56) with CT and 3T CSE-MRI of the lumbar spine at baseline and CSE-MRI at 6 months follow-up were included in this retrospective study. Patients who, on average, developed an incidental VCF one year after baseline MRI (VCF: N=14, 9 males, 66.8 ± 7.9 years) were frequency matched by age and sex to patients without VCFs (non-VCF) at baseline and follow-up (non-VCF: N=42, 27 males, 64.6 ± 13.3 years). Mean PDFF, T2*, and cross-sectional area (CSA) values from the autochthonous PSM of the thoracolumbar spine (T11-L4) and opportunistic CT-based bone mineral density (BMD) measurements were obtained for each individual. The associations between baseline measurements, longitudinal changes in PDFF, T2*, CSA of the PSM and the occurrence of VCFs at follow-up were evaluated using linear and logistic multivariable regression models. ROC analyses were used to assess cutoff values for predicting the development of VCFs.

Results

No significant difference in PDFF of the PSM was found between the VCF and non-VCF group at baseline (VCF/non-VCF 8.5 ± 13.8% vs. 5.0 ± 4.6%; p=0.53). In multivariable linear regression models adjusted for sex, age and baseline BMD, PDFF values of the PSM increased significantly over 6 months in the VCF group (2.4 ± 2.8% vs. -1.0 ± 2.3%, p<0.001), while T2* values of the PSM showed a significant decrease (p ≤ 0.01). ROC analyses identified a PDFF increase of 0.2% in the PSM as the optimal cutoff value to distinguish between patients with and without VCF (AUC 0.86, 95% CI [0.74-0.98], p<0.001).

Conclusion

Longitudinal PDFF-based assessment of the PSM composition may be a useful indicator for the prediction of the development of vertebral compression fractures.

Magnetic Resonance Assessment of Bone Quality in Metabolic Bone Diseases

Metabolic bone diseases (MBDs) are a diverse group of diseases, affecting the mass or structure of bones and leading to reduced bone quality. Parameters representing different aspects of bone health can be obtained from various magnetic resonance imaging (MRI) methods such as proton MR spectroscopy, as well as chemical shift encoding-based water-fat imaging, that have been frequently applied to study bone marrow in particular. Furthermore, T2* mapping and high-resolution trabecular bone imaging have been implemented to study bone microstructure. In addition, quantitative susceptibility mapping and ultrashort echo time imaging are used for trabecular and cortical bone assessment. This review offers an overview of technical aspects, as well as major clinical applications and derived main findings, for MRI-based assessment of bone quality in MBDs. It focuses on osteoporosis as the most common MBD.

Quantitative Analysis of Whole-Body MRI for Accessing the Degree of Diffuse Infiltration Patterns and Identifying High Risk Cases of Newly Diagnosed Multiple Myeloma

BACKGROUND

Accurate identification of high-risk multiple myeloma (HRMM) is important for prognostication. The degree of diffuse infiltration patterns on magnetic resonance imaging (MRI) is associated with patient prognosis in multiple myeloma. However, objective indexes to determine the degree of diffuse infiltration patterns are unavailable.

PURPOSE

To investigate whether qualitative and quantitative evaluations of diffuse infiltration patterns on MRI could identify HRMM.

STUDY TYPE

Retrospective.

SUBJECTS

Totally, 180 patients (79 HRMM and 101 standard-risk MM) were assessed. The presence of del(17p), t(4;14), t(14;16), t(14;20), gain 1q, and/or p53 mutations was considered to indicate HRMM.

FIELD STRENGTH/SEQUENCE

3.0 T/diffusion-weighted whole-body imaging with background body signal suppression (DWIBS), modified Dixon chemical-shift imaging Quant (mDIXON Quant), and short TI inversion recovery (STIR).

ASSESSMENT

Qualitative analysis involved assessing the degree of diffuse marrow infiltration (mild, moderate, or severe), and quantitative analysis involved evaluating apparent diffusion coefficient (ADC), fat fraction (FF), and T2* values. Clinical data such as sex, age, hemoglobin, serum albumin, serum calcium, serum creatinine, serum lactate dehydrogenase, β2-microglobulin, and bone marrow plasma cells (BMPCs) were also included.

STATISTICAL TESTS

Univariate and multivariate analyses, receiver operating characteristic (ROC) curve. P < 0.05 was considered statistically significant.

RESULTS

The high-risk group had significantly higher ADC and T2* and lower FF compared with the standard-risk group. Multivariate analysis indicated BMPCs as a significant independent risk factor for HRMM (odds ratio (OR) = 1.019, 95% CI 1.004-1.033), while FF was a significant independent protective factor associated with HRMM (OR = 0.972, 95% CI 0.946-0.999). The combination of BMPCs and FF achieved the highest areas under the curve (AUC) of 0.732, with sensitivity and specificity of 70.9% and 68.3%, respectively.

DATA CONCLUSION

Compared with qualitative analysis, FF value was independently associated with HRMM. The quantitative features of diffuse marrow infiltration on MRI scans are more effective in detecting HRMM.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Associations of gestational diabetes and proton density fat fraction of vertebral bone marrow and paraspinal musculature in premenopausal women

Background and objective

Fat content in bones and muscles, quantified by magnetic resonance imaging (MRI) as a proton density fat fraction (PDFF) value, is an emerging non-invasive biomarker. PDFF has been proposed to indicate bone and metabolic health among postmenopausal women. Premenopausal women with a history of gestational diabetes (GDM) carry an increased risk of developing type 2 diabetes and an increased risk of fractures. However, no studies have investigated the associations between a history of GDM and PDFF of bone or of paraspinal musculature (PSM), composed of autochthonous muscle (AM) and psoas muscle, which are responsible for moving and stabilizing the spine. This study aims to investigate whether PDFF of vertebral bone marrow and of PSM are associated with a history of GDM in premenopausal women.

Methods

A total of 37 women (mean age 36.3 ± 3.8 years) who were 6 to 15 months postpartum with (n=19) and without (n=18) a history of GDM underwent whole-body 3T MRI, including a chemical shift encoding-based water-fat separation. The PDFF maps were calculated for the vertebral bodies and PSM. The cross-sectional area (CSA) of PSM was obtained. Associations between a history of GDM and PDFF were assessed using multivariable linear and logistic regression models.

Results

The PDFF of the vertebral bodies was significantly higher in women with a history of GDM (GDM group) than in women without (thoracic: median 41.55 (interquartile range 32.21-49.48)% vs. 31.75 (30.03-34.97)%; p=0.02, lumbar: 47.84 (39.19-57.58)% vs. 36.93 (33.36-41.31)%; p=0.02). The results remained significant after adjustment for age and body mass index (BMI) (p=0.01-0.02). The receiver operating characteristic curves showed optimal thoracic and lumbar vertebral PDFF cutoffs at 38.10% and 44.18%, respectively, to differentiate GDM (AUC 0.72 and 0.73, respectively, sensitivity 0.58, specificity 0.89). The PDFF of the AM was significantly higher in the GDM group (12.99 (12.18-15.90)% vs. 10.83 (9.39-14.71)%; p=0.04) without adjustments, while the CSA was similar between the groups (p=0.34).

Conclusion

A history of GDM is significantly associated with a higher PDFF of the vertebral bone marrow, independent of age and BMI. This statistical association between GDM and increased PDFF highlights vertebral bone marrow PDFF as a potential biomarker for the assessment of bone health in premenopausal women at risk of diabetes.

Feasibility Study of 3D FACT and IVIM Sequences in the Evaluation of Female Osteoporosis

BACKGROUND

The aim of this study is to search for the predictive value of 3D fat analysis and calculation technique (FACT) and intravoxel incoherent motion (IVIM) parameters in identifying osteoporosis in women.

METHODS

We enrolled 48 female subjects who underwent 3.0 T MRI, including 3D FACT and IVIM sequences. Bone mineral density (BMD) values and Fracture Risk Assessment (FRAX) scores were obtained. Proton density fat fraction (PDFF) in the bone marrow and the real diffusion (D) value of intervertebral discs were measured on 3D FACT and IVIM images, respectively. Accuracy and bias were assessed by linear regression analysis and Bland-Altman plots. Intraclass correlation coefficients were used to assess the measurements' reproducibility. Spearman's rank correlation was applied to explore the correlation. MRI-based parameters were tested for significant differences among the three groups using ANOVA analyses. A receiver operating characteristic (ROC) analysis was performed.

RESULTS

The PDFF of the vertebral body showed a negative correlation with BMD (R = -0.393, p = 0.005) and a positive correlation with the FRAX score (R = 0.706, p < 0.001). The D value of intervertebral discs showed a positive correlation with BMD (R = 0.321, p = 0.024) and a negative correlation with the FRAX score (R = -0.334, p = 0.019). The area under the curve values from the ROC analysis showed that the 3D FACT and IVIM sequences could accurately differentiate between normal and osteoporosis (AUC = 0.88 using the PDFF; AUC = 0.77 using the D value). The PDFF value demonstrated a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 78.6%, 89.5%, 84.6%, and 85.0%, respectively, in its ability to predict osteoporosis. The D value had a sensitivity, specificity, PPV, and NPV of 63.16%, 92.9%, 65.0%, and 77.8%, respectively, for predicting osteoporosis.

CONCLUSIONS

The 3D FACT- and IVIM-measured PDFF and D values are promising biomarkers in the assessment of bone quality and fracture risk.