0001 for both) For the Hologic cohort, which consisted of early

0001 for both). For the Hologic cohort, which consisted of early Selleckchem MM-102 postmenopausal subjects with Pictilisib a narrow range of spinal and femoral aBMDdxa, there were no significant correlations to aBMD of the total femur or lumbar spine for either aBMDsim or aBMDdxa at the UD radius (R 2 < 0.02). Fig. 6 Regression analysis plots for aBMDsim and aBMDdxa at the UD radius against standard aBMD measurements at the proximal femur (a, b) and lumbar spine (c, d) Discussion In this study, we have demonstrated an automated method for simulating areal BMD measures from 3D HR-pQCT images of the ultra-distal radius. Similar techniques have previously been developed for the proximal femur for traditional

QCT imaging [25]. This technique would primarily be beneficial for clinical osteoporosis studies as a controlled complement to standard forearm DXA densitometry or where DXA is not available. The algorithm is advantageous in several respects: First, it automatically orients the radius and ulna in a standard anatomic position that approximately corresponds to patient positioning for a clinical DXA examination such that there is no ulnar–radial superposition. In LY2874455 mw a multi-center, clinical study this would significantly minimize inter-operator variability in patient positioning inherent to DXA. Furthermore, it is

reasonable to expect that different HR-pQCT sites have access to DXA devices from different manufacturers. The use of HR-pQCT-derived aBMD measures would avoid variability known to exist between DXA manufacturers

[19, 24]. Finally, when appropriate, this approach provides the option of eliminating forearm DXA scans altogether from a clinical research protocol, thereby reducing the minor radiation dose to human subjects subjected to this procedure. In DXA, two X-ray energies are used to compensate for variable soft tissue attenuation path lengths. In the algorithm presented here, spatial segmentation of the 3D image approximates this compensation by masking peripheral soft tissue and the ulna prior to forward projection. This method does not account for intra-medullary Tideglusib soft tissue (i.e., bone marrow) nor potential compositional variability of the marrow itself (hematopoietic vs. fatty marrow). However, for the ultra-distal radius, these effects are expected to be minimal compared to differences in extra-osseal soft tissue across subjects and compared to axial skeletal sites. In this study, we have validated the simulation technique against standard clinical DXA of the UD radius in a total of 117 subjects, spanning a large range of ages and BMD values. The algorithm successfully generated projections for all subjects in the study. Reproducibility for measuring aBMDsim (including patient positioning and acquisition) was approximately 1.1% RMS-CV. This is similar to previously reported reproducibility results for standard volumetric BMD indices determined by HR-pQCT [11, 14]. Regression analysis revealed strong correlations (R 2 > 0.

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