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

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.