3D quantification of the lacunocanalicular network on human femoral diaphysis through synchrotron radiation-based nanoCT.

Human bone Lacunocanalicular network Morphology Synchrotron X-rays phase nanotomography

Journal

Journal of structural biology
ISSN: 1095-8657
Titre abrégé: J Struct Biol
Pays: United States
ID NLM: 9011206

Informations de publication

Date de publication:
24 Jul 2024
Historique:
received: 09 02 2024
revised: 09 07 2024
accepted: 22 07 2024
medline: 27 7 2024
pubmed: 27 7 2024
entrez: 26 7 2024
Statut: aheadofprint

Résumé

Osteocytes are the major actors in bone mechanobiology. Within bone matrix, they are trapped close together in a submicrometric interconnected network: the lacunocanalicular network (LCN). The interstitial fluid circulating within the LCN transmits the mechanical information to the osteocytes that convert it into a biochemical signal. Understanding the interstitial fluid dynamics is necessary to better understand the bone mechanobiology. Due to the submicrometric dimensions of the LCN, making it difficult to experimentally investigate fluid dynamics, numerical models appear as a relevant tool for such investigation. To develop such models, there is a need for geometrical and morphological data on the human LCN. This study aims at providing morphological data on the human LCN from measurement of 27 human femoral diaphysis bone samples using synchrotron radiation nano-computed tomography with an isotropic voxel size of 100 nm. Except from the canalicular diameter, the canalicular morphological parameters presented a high variability within one sample. Some differences in terms of both lacunar and canalicular morphology were observed between the male and female populations. But it has to be highlighted that all the canaliculi cannot be detected with a voxel size of 100 nm. Hence, in the current study, only a specific population of large canaliculi that could be characterize. Still, to the authors knowledge, this is the first time such a data set was introduced to the community. Further processing will be achieved in order to provide new insight on the LCN permeability.

Identifiants

pubmed: 39059753
pii: S1047-8477(24)00051-0
doi: 10.1016/j.jsb.2024.108111
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

108111

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Boliang Yu (B)

Univ Lyon, INSA Lyon, Universite Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS UMR 5220, Inserm U1206, CREATIS, 69621 Lyon, France.

Remy Gauthier (R)

CNRS, INSA Lyon, Universite Claude Bernard Lyon 1 UCBL, MATEIS UMR CNRS 5510, Bât. Saint Exupéry, 23 Av. Jean Capelle, F-69621 Villeurbanne, France. Electronic address: remy.gauthier@cnrs.fr.

Cécile Olivier (C)

Université Grenoble Alpes, Institut National de la Santé et de la Recherche Médicale, UA7 Synchrotron Radiation for Biomedicine, Saint-Martin d'Hères, France.

Julie Villanova (J)

ESRF, The European Synchrotron, 38043 Grenoble, France.

Hélène Follet (H)

Univ Lyon, Universite Claude Bernard Lyon 1, INSERM, LYOS UMR1033, Lyon, France.

David Mitton (D)

Univ Lyon, Univ Gustave Eiffel, Universite Claude Bernard Lyon 1, LBMC UMR_T9406, 69622 Lyon, France.

Francoise Peyrin (F)

Univ Lyon, INSA Lyon, Universite Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS UMR 5220, Inserm U1206, CREATIS, 69621 Lyon, France.

Classifications MeSH