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Radiomics Based on Lumbar Spine Magnetic Resonance Imaging to Detect Osteoporosis

      Rationale and Objectives

      Signal intensity of the lumbar spine in magnetic resonance imaging (MRI) correlates to bone mineral density (BMD). This study aims to explore a lumbar spine magnetic resonance imaging based on the radiomics model for detecting osteoporosis.

      Materials and Methods

      A total of 109 patients, who underwent both dual-energy X-ray absorptiometry (DEXA) and MRI of the lumbar spine, were recruited. Among these patients, 38 patients were normal, 32 patients had osteopenia, and 39 patients had osteoporosis, according to the DEXA results. A total of 396 × 2 radiomic features were extracted from the T1WI and T2WI images of the segmentation images in the lumbar magnetic resonance imaging. The correlated radiomic features were selected to establish the radiomic classification model. Then, the classification models (based on T1WI, T2WI, and T1WI+T2WI) of normal vs. osteopenia, normal vs. osteoporosis, and osteopenia vs. osteoporosis were established. The performance of the classification models was evaluated through the estimated area under the receiver operating characteristic curve.

      Results

      The area under the receiver operating characteristic curves based on T1WI, T2WI, and T1WI+T2WI were 0.772, 0.772, and 0.810, respectively, for the models of normal vs. osteopenia, 0.724, 0.682, and 0.797, respectively, for the models of normal vs. osteoporosis, and 0.730, 0.734, and 0.769, respectively, for the models of osteopenia vs. osteoporosis.

      Conclusion

      Radiomic models established based on lumbar spine MRI can be used to detect osteoporosis.

      Key Words

      Abbreviations:

      MRI (magnetic resonance imaging), BMD (bone mineral density), nBMD (normal bone mineral density), DEXA (dual-energy X-ray absorptiometry), RFs (radiomic features), WHO (World Health Organization), CT (computed tomography), CTL (cervical-thoracic-lumber), VOI (volume of interest), GLCM (grey level co-occurrence matrix), RLM (run length matrix), GLSZM (grey level size zone matrix), ROC (receiver operating characteristic), AUC (area under the curve), DCAs (Decision curve analyses), ROI (region of interest)
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