Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Micro-computed tomography (µCT) imaging analysis of bone volume is a necessary quantitative tool for investigating bone regeneration potential and outcomes within longitudinal in vivo studies. Established methods for bone segmentation utilize visualization software for whole bone µCT segmentation and alignment of complex anatomical structures. These segmentation protocols provide a robust, high-accuracy method for segmentation, alignment, and analysis but are limited in abilities of user-defined region of interest (ROI) analysis. We present a protocol expanding upon these methods to permit user-defined ROI bone volume analysis surrounding a critical-sized bone defect. The user-defined ROI surrounding the defect can be analyzed over time for in vivo longitudinal studies. Herein, we investigate µCT images of three unique rat specimens each implanted with a polycaprolactone (PCL) control scaffold. Models are analyzed by three users (2 experienced and 1 novice) at time points of 0 and 6 weeks to illustrate the ability to measure an ROI surrounding a critical-sized defect throughout a longitudinal study.