Assessing Lumbar Spine Microstructure in Osteoporosis Using IVIM-DWI and IDEAL-IQ Sequences
Zhaojuan Shi1, Lingdong Hu2, Datian Su1
1Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, 271000, People's Republic of China.
Background:
Currently, dual-energy X-ray absorptiometry (DEXA) and quantitative CT (QCT) are commonly used in clinical practice to measure bone mineral density (BMD), offering diagnostic value but involving radiation and inability to visualize bone microstructure. This study aims to assess lumbar spine bone microstructure changes in normal, osteopenic, and osteoporotic groups using IVIM-DWI and IDEAL-IQ sequences to provide useful information for clinical practice.
Methods:
A total of 346 patients (50-87 years, 232 females, 114 males) underwent spinal DEXA and MRI. Based on the BMD obtained from DEXA, the patients were stratified into: normal (n=79), osteopenia (n=92), and OP (n=175) groups. Then to evaluated the results of IVIM-DWI and IDEAL-IQ and extracted quantitative parameters from regions of interest covering the L1 to L4 vertebrae. Group comparisons used One-way analysis of variance and the Kruskal‒Wallis H-test. Receiver operating characteristic (ROC) and Spearman's analyses evaluated diagnostic performance and correlations.
Results:
Significant differences existed in the ADCslow, f, FF and R2* between groups (P<0.05). BMD was weakly positively correlated with ADCslow, f, and R2* (r=0.494, 0.153, 0.182, 0.029, P<0.001) but a negative correlation with FF (r=-0.402, P<0.001). BMD and the ADCslow and R2* decreased but FF increased with age (P<0.05 for all), whereas no significant association existed between age and ADCfast or f value (P>0.05). FF had the highest areas under the curve (AUCs) (0.624, 0.831 and 0.747) and sensitivity (72.2%, 70.9% and 81.5%) in differentiating normal from osteopenia patients, normal from osteoporosis patients, and osteopenia from osteoporosis patients, respectively. ADCslow and f had the highest specificity (88%) in differentiating between normal and osteopenia patients, while ADCslow had the highest specificity (91.4%) in differentiating between normal and osteoporosis patients.
Conclusion:
Quantitative parameters extracted from IVIM-DWI and IDEAL-IQ have the potential to become good biomarkers for diagnosing OP.
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Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...


