Quantification of skeletal growth, modeling, and remodeling by in vivo micro computed tomography.

In this study we established an image analysis scheme for the investigation of cortical and trabecular bone development during skeletal growth and tested this concept on in vivo μCT images of rats. To evaluate its efficacy, we applied the technique to young (1-month-old) and adult (3-month-old) rat tibiae with vehicle (Veh) or intermittent parathyroid hormone (PTH) treatment. By overlaying 2 sequential scans based on their distinct trabecular microarchitecture, we calculated the linear growth rate of young rats to be 0.31 mm/day at the proximal tibia. Due to rapid growth (3.7 mm in 12 days), the scanned bone region at day 12 had no overlap with the bone tissue scanned at day 0. Instead, the imaged bone region at day 12 represented newly generated bone tissue from the growth plate. The new bone of the PTH-treated rats had significantly greater trabecular bone volume fraction, number, and thickness than those of the Veh-treated rats, indicating PTH's anabolic effect on bone modeling. In contrast, the effect of PTH on adult rat trabecular bone was found to be caused by PTH's anabolic effect on bone remodeling. The cortical bone at the proximal tibia of young rats also thickened more in the PTH group (23%) than the Veh group (14%). This was primarily driven by endosteal bone formation and coalescence of trabecular bone into the cortex. This process can be visualized by aligning the local bone structural changes using image registration. As a result, the cortex after PTH treatment was 31% less porous, and had a 22% greater polar moment of inertia compared to the Veh group. Lastly, we monitored the longitudinal bone growth in adult rats by measuring the distance of bone flow away from the proximal tibial growth plate from 3 months to 19 months of age and discovered a total of 3.5mm growth in 16 months. It was demonstrated that this image analysis scheme can efficiently evaluate bone growth, bone modeling, and bone remodeling, and is ready to be translated into a clinical imaging platform.

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