A novel method for segmenting and aligning the pre- and post-implantation scaffolds of resorbable calcium-phosphate...

Micro-computed tomography (microCT) is commonly used to characterize the three-dimensional structure of bone graft scaffolds before and after implantation in order to assess changes occurring during implantation. The accurate processing of the microCT datasets of explanted β-tricalcium phosphate (β-TCP) scaffolds poses significant challenges because of (a) the overlap in the grey values distribution of ceramic remnants, bone, and soft tissue, and of (b) the resorption of the bone substitute during the implantation. To address those challenges, this article introduces and rigorously validates a new processing technique to accurately distinguish these three phases found in the explanted β-TCP scaffolds. Specifically, the microCT datasets obtained before and after implantation of β-TCP scaffolds were aligned in 3D, and the characteristic grey value distributions of the three phases were extracted, thus allowing for (i) the accurate differentiation between these three phases (ceramic remnants, bone, soft tissue), and additionally for (ii) the localization of the defect site in the post-implantation microCT dataset. Using the similarity matrix, a 94±1% agreement was found between algorithmic results and the visual assessment of 556,800 pixels. Moreover, the comparison of the segmentation results of the same microCT and histology section further confirmed the validity of the present segmentation algorithm. This new technique could lead to a more common use of microCT in analyzing the complex 3D processes and to a better understanding of the biological processes occurring after the implantation of ceramic bone graft substitutes.

Calcium-phosphate scaffolds are being increasingly used to repair critical bone defects. Methods for the accurate characterization of the repair process are still lacking. The present study introduced and validated a novel image-processing technique, using micro-computed tomography (mCT) datasets, to investigate material phases present in biopsies. Specifically, the new method combined mCT datasets from the scaffold before and after implantation to access the characteristic data of the ceramic for more accurate analysis of bone biopsies, and as such to better understand the interactions of the scaffold design and the bone repair process.