Evaluation of in-vivo measurement errors associated with micro-computed tomography scans by means of the bone surface distance approach
Autor: | Marco Viceconti, Enrico Dall'Ara, Yongtao Lu, Maya Boudiffa, Ilaria Bellantuono |
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Rok vydání: | 2015 |
Předmět: |
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Observational error X-ray microtomography Materials science Tibia Biomedical Engineering Biophysics Datasets as Topic Reproducibility of Results X-Ray Microtomography Metaphysis Mice Inbred C57BL Imaging Three-Dimensional medicine.anatomical_structure In vivo Region of interest medicine Animals Female Tomography Biomedical engineering |
Zdroj: | Medical Engineering & Physics. 37:1091-1097 |
ISSN: | 1350-4533 |
DOI: | 10.1016/j.medengphy.2015.08.017 |
Popis: | In vivo micro-computed tomography (µCT) scanning is an important tool for longitudinal monitoring of the bone adaptation process in animal models. However, the errors associated with the usage of in vivo µCT measurements for the evaluation of bone adaptations remain unclear. The aim of this study was to evaluate the measurement errors using the bone surface distance approach. The right tibiae of eight 14-week-old C57BL/6 J female mice were consecutively scanned four times in an in vivo µCT scanner using a nominal isotropic image voxel size (10.4 µm) and the tibiae were repositioned between each scan. The repeated scan image datasets were aligned to the corresponding baseline (first) scan image dataset using rigid registration and a region of interest was selected in the proximal tibia metaphysis for analysis. The bone surface distances between the repeated and the baseline scan datasets were evaluated. It was found that the average (±standard deviation) median and 95th percentile bone surface distances were 3.10 ± 0.76 µm and 9.58 ± 1.70 µm, respectively. This study indicated that there were inevitable errors associated with the in vivo µCT measurements of bone microarchitecture and these errors should be taken into account for a better interpretation of bone adaptations measured with in vivo µCT. |
Databáze: | OpenAIRE |
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