Adding marrow R2∗ to proton density fat fraction improves the discrimination of osteopenia and osteoporosis in postmenopausal women assessed with 3D FACT sequence.

Objective: To evaluate the role of three-dimensional Fat Analysis & Calculation Technique sequence in improving the diagnostic accuracy for the detection of osteopenia and osteoporosis by simultaneous quantification of proton density fat fraction (PDFF) and fat-corrected R2∗.

Methods: Fat Analysis & Calculation Technique imaging of lumbar spine was obtained in 99 postmenopausal women including 52 normal bone mass, 29 osteopenia, and 18 osteoporosis. The diagnostic performance of PDFF and R2∗ in the differentiation of different bone-density groups was evaluated with the receiver operating characteristic curve.

Results: The reproducibility of PDFF and R2∗ measures was satisfactory with the root mean square coefficient of variation, 2.16% and 2.70%, respectively. The intra- and interobserver agreements for the PDFF and R2∗ were excellent with the intraclass correlation coefficient > 0.9 for all. There were significant differences in PDFF and R2∗ among the three groups (P < 0.05). Bone density had a moderate inverse correlation with PDFF (r  = -0.659) but a positive association with R2∗ (r = 0.508, P < 0.001). Adjusted for age, years since menopause and body mass index, odds ratios (95% confidence interval) for osteopenia and osteoporosis per standard deviation higher marrow PDFF and R2∗ were 2.9 (1.4-5.8) and 0.4 (0.2-0.8), respectively. The areas under the curve were 0.821 for PDFF, 0.784 for R2∗, and 0.922 for both combined for the detection of osteoporosis (P < 0.05). Similar results were obtained in distinguishing osteopenia from healthy controls.

Conclusions: Simultaneous estimation of marrow R2∗ and PDFF improves the discrimination of osteopenia and osteoporosis in comparison with the PDFF or R2∗ alone.