Development of a protocol to quantify local bone adaptation over space and time: Quantification of reproducibility.
In vivo micro-computed tomography (µCT) scanning of small rodents is a powerful method for longitudinal monitoring of bone adaptation. However, the life-time bone growth in small rodents makes it a challenge to quantify local bone adaptation. Therefore, the aim of this study was to develop a protocol, which can take into account large bone growth, to quantify local bone adaptations over space and time. The entire right tibiae of eight 14-week-old C57BL/6J female mice were consecutively scanned four times in an in vivo µCT scanner using a nominal isotropic image voxel size of 10.4µm. The repeated scan image datasets were aligned to the corresponding baseline (first) scan image dataset using rigid registration. 80% of tibia length (starting from the endpoint of the proximal growth plate) was selected as the volume of interest and partitioned into 40 regions along the tibial long axis (10 divisions) and in the cross-section (4 sectors). The bone mineral content (BMC) was used to quantify bone adaptation and was calculated in each region. All local BMCs have precision errors (PE%CV) of less than 3.5% (24 out of 40 regions have PE%CV of less than 2%), least significant changes (LSCs) of less than 3.8%, and 38 out of 40 regions have intraclass correlation coefficients (ICCs) of over 0.8. The proposed protocol allows to quantify local bone adaptations over an entire tibia in longitudinal studies, with a high reproducibility, an essential requirement to reduce the number of animals to achieve the necessary statistical power.
Department of Engineering Mechanics, Dalian University of Technology, Dalian, China; Department of Mechanical Engineering and INSIGNEO Institute for in Silico Medicine, the University of Sheffield, Sheffield, UK. Electronic address: yongtaolu@dlut.edu.cn.
Yongtao
Y
Lu
Department of Oncology and Metabolism and INSIGNEO Institute for in Silico Medicine, University of Sheffield, Sheffield, UK.
Maya
M
Boudiffa
Department of Oncology and Metabolism and INSIGNEO Institute for in Silico Medicine, University of Sheffield, Sheffield, UK.
Enrico
E
Dall'Ara
Department of Oncology and Metabolism and INSIGNEO Institute for in Silico Medicine, University of Sheffield, Sheffield, UK.
Ilaria
I
Bellantuono
Department of Mechanical Engineering and INSIGNEO Institute for in Silico Medicine, the University of Sheffield, Sheffield, UK.
Marco
M
Viceconti
D000818:Animals; D015519:Bone Density; D001846:Bone Development; D005260:Female; D008810:Mice, Inbred C57BL; D015203:Reproducibility of Results; D013977:Tibia / Q000000981:diagnostic imaging* / Q000254:growth & development* / Q000378:metabolism; D055114:X-Ray Microtomography
In vivo micro-CT; Local bone adaptation; Mouse tibia; Space and time