Cortical porosity assessment in the distal radius: A comparison of HR-pQCT measures with Synchrotron-Radiation micro-CT-based measures
| Autor: | Nikoo Soltan, David M. L. Cooper, Saija A. Kontulainen, James D. Johnston, C. E. Kawalilak |
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| Rok vydání: | 2019 |
| Předmět: |
Male
0301 basic medicine Histology Materials science Physiology Endocrinology Diabetes and Metabolism Synchrotron radiation 030209 endocrinology & metabolism computer.software_genre 03 medical and health sciences 0302 clinical medicine Cortical porosity Voxel Linear regression Cortical Bone Image Processing Computer-Assisted medicine Humans Quantitative computed tomography Porosity Micro ct Aged Radiation medicine.diagnostic_test X-Ray Microtomography Radius 030104 developmental biology Linear Models Female computer Synchrotrons Biomedical engineering |
| Zdroj: | Bone. 120:439-445 |
| ISSN: | 8756-3282 |
| DOI: | 10.1016/j.bone.2018.12.008 |
| Popis: | Objective To determine the agreement between cortical porosity derived from high resolution peripheral quantitative computed tomography (HR-pQCT) ( via standard threshold, mean density and density inhomogeneity methods) and synchrotron radiation micro-CT (SR-μCT) derived porosity at the distal radius. Methods We scanned 10 cadaveric radii (mean donor age: 79, SD 11 years) at the standard distal region using HR-pQCT and SR-μCT at voxel sizes of 82 μm and 17.7 μm, respectively. Common cortical regions were delineated for each specimen in both imaging modalities. HR-pQCT images were analyzed for cortical porosity using the following methods: Standard threshold, mean density, and density inhomogeneity ( via recommended and optimized equations). We assessed agreement in porosity measures between HR-pQCT methods and SR-μCT by reporting predicted variance from linear regression and mean bias with limits of agreement (LOA). Results The standard threshold and mean density methods predicted 85% and 89% of variance and indicated underestimation (mean bias −9.1%, LOA −15.9% to −2.2%) and overestimation (10.4%, 4.6% to 16.2%) of porosity, respectively. The density inhomogeneity method with recommended equation predicted 89% of variance and mean bias of 14.9% (−4.3 to 34.2) with systematic over-estimation of porosity in more porous specimens. The density inhomogeneity method with optimized equation predicted 91% of variance without bias (0.0%, −5.3 to 5.2). Conclusion HR-pQCT imaged porosity assessed with the density inhomogeneity method with optimized equation indicated the best agreement with SR-μCT derived porosity. |
| Databáze: | OpenAIRE |
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