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Multimodal-3D imaging based on microMRI and microCT techniques bridges the gap with histology in visualization of the bone regenerat ion process

Academic Article
Publication Date:
2018
abstract:
Bone repair/regeneration is usually investigated through X-ray computed microtomography (?CT) supported by histology of extracted samples, to analyse biomaterial structure and new bone formation processes. Magnetic resonance imaging (? MRI) shows a richer tissue contrast than ?CT, despite at lower resolution, and could be combined with ?CT in the perspective of conducting non-destructive 3D investigations of bone. A pipeline designed to combine ?MRI and ?CT 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 ?CT and ?MRI 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, ?MRI and ?CT 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.
Iris type:
01.01 Articolo in rivista
Keywords:
3D mapping; bone regeneration; image coregistration; micro magnetic resonance imaging; multimodal imaging; multivariate clustering; X-ray computed microtomography
List of contributors:
Capuani, Silvia
Authors of the University:
CAPUANI SILVIA
Handle:
https://iris.cnr.it/handle/20.500.14243/372885
Published in:
JOURNAL OF TISSUE ENGINEERING AND REGENERATIVE MEDICINE
Journal
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