QUANTIFICATION OF THE 3D MORPHOLOGY OF THE BONE CELL NETWORK FROM SYNCHROTRON MICRO-CT IMAGES

Pei Dong; Alexandra Pacureanu; Maria Alejandra Zuluaga; Cécile Olivier; Quentin Grimal; Françoise Peyrin

doi:10.5566/ias.v33.p157-166

Authors

Pei Dong CREATIS, CNRS UMR 5220; Inserm U1044; Université de Lyon; Université Lyon 1 ; INSA-Lyon; 69621, Villeurbanne; European Synchrotron Radiation Facility, 38043 Grenoble
Alexandra Pacureanu Centre for Image Analysis and Science for Life Laboratory, Uppsala, University Box, 337SE-751 05 Uppsala
Maria Alejandra Zuluaga
Cécile Olivier CREATIS, CNRS UMR 5220; Inserm U1044; Université de Lyon; Université Lyon 1 ; INSA-Lyon; 69621, Villeurbanne; European Synchrotron Radiation Facility, 38043 Grenoble
Quentin Grimal UMPC Univ Paris 6, UMR 7623, Laboratoire d’Imagerie Paramétrique, 75005 Paris, France
Françoise Peyrin CREATIS, CNRS UMR 5220; Inserm U1044; Université de Lyon; Université Lyon 1 ; INSA-Lyon; 69621, Villeurbanne; European Synchrotron Radiation Facility, 38043 Grenoble

DOI:

https://doi.org/10.5566/ias.v33.p157-166

Keywords:

3D image analysis, cortical bone, morphology of lacuno-canalicular network, ramification of canaliculi, synchrotron micro-CT

Abstract

In the context of bone diseases research, recent works have highlighted the crucial role of the osteocyte system. This system, hosted in the lacuno-canalicular network (LCN), plays a key role in the bone remodeling process. However, few data are available on the LCN due to the limitations of current microscopy techniques, and have mainly only been obtained from 2D histology sections. Here we present, for the first time, an automatic method to quantify the LCN in 3D from synchrotron radiation micro-tomography images. After segmentation of the LCN, two binary images are generated, one of lacunae (hosting the cell body) and one of canaliculi (small channels linking the lacunae). The binary image of lacunae is labeled, and for each object, lacunar descriptors are extracted after calculating the second order moments and the intrinsic volumes. Furthermore, we propose a specific method to quantify the ramification of canaliculi around each lacuna. To this aim, a signature of the numbers of canaliculi at different distances from the lacunar surface is estimated through the calculation of topological parameters. The proposed method was applied to the 3D SR micro-CT image of a human femoral mid-diaphysis bone sample. Statistical results are reported on 399 lacunae and their surrounding canaliculi.

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