Identification of abnormal BMD and osteoporosis in postmenopausal women with T2*-corrected Q-Dixon and reduced-FOV IVIM: correlation with QCT

Development and validation of a diagnostic nomogram model for osteoporosis in the elderly using 3D multi-echo Dixon sequence combined with magnetization transfer imaging

OBJECTIVE

To develop a novel combined nomogram based on 3D multi-echo Dixon (qDixon), magnetization transfer imaging (MTI) and clinical risk factors for the diagnosis of osteoporosis.

MATERIALS AND METHODS

A total of 287 subjects who underwent MR examination with qDixon and MTI sequences participated in this study. These participants were randomly assigned to a training cohort and a validation cohort at a ratio of 7:3. We extracted and analyzed the bone marrow fat fraction (FF) and magnetization transfer ratio (MTR) of L1 ∼ 3 vertebrae, along with clinical data. Univariate and multivariate logistic regression analyses was used to assess independent predictors of OP in the training cohort. We established a diagnostic nomogram and evaluated its performance in terms of discrimination, calibration, and clinical value using the receiver operating characteristic curve (ROC) and calibration curve. Decision curve analysis (DCA) was performed to determine the clinical validity of the nomogram by measuring the net benefits at different threshold probabilities.

RESULTS

Gender, age, FF, and MTR (all P﹤0.05) emerged as independent indicators for diagnosing osteoporosis. The AUCs for the FF, MTR, FF + MTR, and nomogram models were 0.842, 0.903, 0.923, and 0.941, respectively, in the training cohort and 0.779, 0.872, 0.901, and 0.929, respectively, in the validation cohort. The nomogram model exhibited good calibration and discrimination. DCA revealed that the nomogram model yielded a higher net benefit than the FF and MTR models.

CONCLUSION

The nomogram model, integrating qDixon, MTI, and clinical parameters, could serve as a reliable tool for diagnosing the individual risk for the osteoporosis in the elderly.

Assessing fat fraction and R2* value of lumbar spine based on MRI as a marker of bone mineral density

OBJECTIVES

The study aimed to investigate the correlation between fat fraction (FF), R2* value of vertebrae based on IDEAL-IQ sequence and bone mineral density (BMD) based on QCT, and their diagnostic value for low BMD and osteoporosis.

METHODS

Subgroups were divided according to different gender, age, BMI, and bone mass to compare the differences in parametric variables. One-way ANOVA, independent samples t-test, correlation coefficient analysis, linear regression analysis, and ROC curve analysis were performed.

RESULTS

Significant differences were found in FF among different bone mass groups, and between different gender and age groups. While R2* only had a significant difference between different gender groups and males with different ages. BMD was significantly negatively correlated with FF, especially in women, and FF significantly negatively affected BMD after controlling for gender, age, and BMI. There was mildly positive correlation between BMD and R2* in men, and R2* significantly positively influenced BMD controlling for the confounders. In addition, FF was positively correlated with age, whereas R2* was negatively correlated with age in men. FF had high diagnostic efficacy for low bone mass and osteoporosis, while R2* alone was weakly diagnostic.

CONCLUSIONS

Vertebral FF can be served as a potentially important imaging biomarker for assessing low BMD and osteoporosis, and R2* of males can be utilized as a complementary parameter for evaluating osteoporosis.

ADVANCES IN KNOWLEDGE

The IDEAL-IQ sequence has the potential to be used as an accessory examination in the diagnosis of osteoporosis, assessment of treatment efficacy, and prediction of fracture risk.

Quantitative analysis of vertebral fat fraction and R2* in osteoporosis using IDEAL-IQ sequence

OBJECTIVE

To investigate the correlation between FF, R2* value of IDEAL-IQ sequence and bone mineral density, and to explore their application value in the osteoporosis.

METHODS

We recruited 105 women and 69 men aged over 30 years who voluntarily underwent DXA and MRI examination of lumbar spine at the same day. Participants were divided into normal, osteopenia and osteoporosis group based on T-score and BMD value of DXA examination. One-way ANOVA was adopted to compare the quantitative parameters among the three groups. Independent samples t-test was utilized to compare FF and R2* value between men and women.Pearson correlation analysis was used to research the correlation between FF, R2* value and BMD.

RESULTS

Age, height, weight, BMD and FF value were significantly different among three groups (p < 0.05). No significant difference was found in FF value between male and female group, while R2* value were significantly different. Vertebral FF was moderately negatively correlated with aBMD, especially in women (r = -0.638, p < 0.001). R2* was mildly to moderately positively correlated with aBMD in men (r = 0.350, p = 0.003), but not in women. Moreover, FF was positively correlated with age, R2* was negatively correlated with age in men, and BMD was negatively correlated with age.

CONCLUSIONS

The vertebral FF value of IDEAL-IQ sequence has the potential to be a new biological marker for the assessment of osteoporosis. Vertebral FF is moderately negatively correlated with aBMD, especially in women, allowing accuratly quantify the bone marrow fat. R2* value is mildly to moderately correlated with BMD in men and can be served as a complementary tool in the assessment of osteoporosis.

mDIXON-Quant technique diagnostic accuracy for assessing bone mineral density in male adult population

BACKGROUND

To investigate the diagnostic efficacy of mDIXON-Quant technique for prediction of bone loss in male adults.

METHODS

One hundred thirty-eight male adults were divided into normal, osteopenia, and osteoporosis groups based on DXA and QCT for the lumbar spine. Differences in mDIXON-Quant parameters [fat fraction (FF) and T2^* value] among three groups, as well as the correlation of mDIXON-Quant parameters and bone mineral density (BMD) were analyzed. The areas under the curves (AUCs) for mDIXON-Quant parameters for prediction of low bone mass were calculated.

RESULTS

According to DXA standard, FF and T2^* value were significantly increased in osteoporosis group compared with normal group (P = 0.012 and P < 0.001). According to QCT standard, FF was significantly increased in osteopenia and osteoporosis groups compared with normal group (both P < 0.001). T2^* values were significantly different among three groups (all P < 0.05). After correction for age and body mass index, FF was negatively correlated with areal BMD and volumetric BMD (r = -0.205 and -0.604, respectively; both P < 0.05), and so was T2^* value (r = -0.324 and -0.444, respectively; both P < 0.05). The AUCs for predicting low bone mass according to DXA and QCT standards were 0.642 and 0.898 for FF, 0.648 and 0.740 for T2^* value, and 0.677 and 0.920 for both combined, respectively.

CONCLUSIONS

FF combined with T2^* value has a better diagnostic efficacy than FF or T2^* value alone in prediction of low bone mass in male adults, which is expected to be a promising MRI method for the screening of bone quality.

TRIAL REGISTRATION

ChiCTR1900024511 (Registered 13-07-2019).

Adding liver R2* quantification to proton density fat fraction MRI of vertebral bone marrow improves the prediction of osteoporosis

OBJECTIVES

To assess the predictive value of the combination of bone marrow (BM) proton density fat fraction (PDFF) and liver R2* for osteopenia and osteoporosis and the additional role of liver R2*.

METHODS

A total of 107 healthy women were included between June 2019 and January 2021. Each participant underwent dual-energy X-ray absorptiometry (DXA) and chemical shift-encoded 3.0-T MRI. PDFF measurements were performed for each lumbar vertebral body, and R2* measurements were performed in liver segments. Agreement among measurements was assessed by Bland-Altman analysis. Receiver operating characteristic (ROC) curves were generated to select optimised cut-offs for BM PDFF and liver R2*. Univariable and multivariable logistic regressions were performed. The C statistic and continuous net reclassification improvement (NRI) were adopted to explore the incremental predictive ability of liver R2*.

RESULTS

Bone mass decreased in 42 cases (39.3%) and nonbone mass decreased in 65 cases (60.7%). There were significant differences among the age groups, menopausal status groups, PDFF > 45.0% groups, and R2* > 67.7 groups. Each measurement had good reproducibility. The odds ratios (95% CIs) were 4.05 (1.22-13.43) for PDFF and 4.34 (1.41-13.35) for R2*. The C statistic (95% CI) without R2* was 0.888 (0.827-0.950), and with R2* was 0.900 (0.841-0.960). The NRI resulting from the combination of PDFF and R2* was 75.6% (p < 0.01).

CONCLUSION

The predictive improvement over the use of BM PDFF and other traditional risk factors demonstrates the potential of liver R2* as a biomarker for osteopenia and osteoporosis in healthy women.

KEY POINTS

• Liver R2* is a biomarker for the assessment of osteopenia and osteoporosis. • Liver R2* improved the ability to predict osteopenia and osteoporosis. • The intra- and interobserver measurements showed high agreement.