Multimodal‐3D imaging based on μMRI and μCT techniques bridges the gap with histology in visualization of the bone regeneration process. (2nd October 2017)

• Record Type: Journal Article
• Authors: Sinibaldi, R.; Conti, A.; Sinjari, B.; Spadone, S.; Pecci, R.; Palombo, M.; Komlev, V.S.; Ortore, M.G.; Tromba, G.; Capuani, S.; Guidotti, R.; De Luca, F.; Caputi, S.; Traini, T.; Della Penna, S.
• Is Part Of: Journal of tissue engineering and regenerative medicine. Volume 12:Number 3(2018)
• Page Start: 750
• Page End: 761
• Publication Date: 2017-10-02
• Subjects: 3D mapping -- bone regeneration -- image coregistration -- micro magnetic resonance imaging -- multimodal imaging -- multivariate clustering -- X‐ray computed microtomography; Tissue engineering -- Periodicals; Regeneration (Biology) -- Periodicals; 610.28
• DOI: 10.1002/term.2494
• Languages: English
• ISSNs: 1932-6254

Abstract

Abstract: Bone repair/regeneration is usually investigated through X‐ray computed microtomography (μCT) supported by histology of extracted samples, to analyse biomaterial structure and new bone formation processes. Magnetic resonance imaging (μMRI) shows a richer tissue contrast than μCT, despite at lower resolution, and could be combined with μCT in the perspective of conducting non‐destructive 3D investigations of bone. A pipeline designed to combine μMRI and μCT images of bone samples is here described and applied on samples of extracted human jawbone core following bone graft. We optimized the coregistration procedure between μCT and μMRI images to avoid bias due to the different resolutions and contrasts . Furthermore, we used an Adaptive Multivariate Clustering, grouping homologous voxels in the coregistered images, to visualize different tissue types within a fused 3D metastructure. The tissue grouping matched the 2D histology applied only on 1 slice, thus extending the histology labelling in 3D. Specifically, in all samples, we could separate and map 2 types of regenerated bone, calcified tissue, soft tissues, and/or fat and marrow space. Remarkably, μMRI and μCT alone were not able to separate the 2 types of regenerated bone. Finally, we computed volumes of each tissue in the 3D metastructures, which might be exploited by quantitative simulation. The 3D metastructure obtained through our pipeline represents a first step to bridge the gap between the quality of information obtained from 2D optical microscopy and the 3D mapping of the bone tissue heterogeneity and could allow researchers and clinicians to non‐destructively characterize and follow‐up bone regeneration.