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      Significant correlations between human cortical bone mineral density and quantitative susceptibility mapping (QSM) obtained with 3D Cones ultrashort echo time magnetic resonance imaging (UTE-MRI)

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      Magnetic Resonance Imaging

      Elsevier BV

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          Quantitative susceptibility mapping (QSM) MRI is a tool that can characterize changes in susceptibility, an intrinsic property which is associated with compositional changes in the tissue. Current QSM estimation of cortical bone is challenging because conventional clinical MRI cannot acquire signal in cortical bone. This study aimed to implement Cones 3D ultrashort echo time MRI (UTE-MRI) for ex vivo QSM measurements in human tibial cortical bone, investigating the correlations of QSM with volumetric intracortical bone mineral density (BMD). Nine tibial midshaft cortical bone specimens (25 mm long specimens cut at the mid-point of tibial shaft, 67±20 years old, 5 women and 4 men) were scanned on a clinical 3T MRI scanner for QSM measurement. The specimens were also scanned on a high-resolution micro-computed tomography (μCT) scanner for volumetric BMD estimation. QSM and μCT results were compared at approximately nine regions of interest (ROIs) per specimen. Average 3D UTE-MRI QSM showed significantly strong correlation with volumetric BMD (R=−0.82, P<0.01) and bone porosity (R=0.72, P<0.01). Combining all data points together (77 ROIs), QSM showed significant moderate to strong correlation with volumetric BMD after correction for interdependencies in specimens (R=−0.70, P<0.01). The corrections were required because the data points were not independent in each specimen. Similarly, the correlation between QSM and porosity was significant (R=0.68, P<0.01). These results suggest that the Cones 3D UTE-MRI QSM technique can potentially serve as a novel and accurate tool to assess intracortical bone mineral density whilst avoiding ionizing radiation.

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          Author and article information

          Magnetic Resonance Imaging
          Magnetic Resonance Imaging
          Elsevier BV
          October 2019
          October 2019
          : 62
          : 104-110
          © 2019


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