Porosity Variation In Hydroxyapatite and Osteoblast Morphology: A Scanning Electron Microscopy Study

Basil Annaz, K. A. Hing, M. Kayser, T. Buckland, L. Di Silvio

Research output: Contribution to journalArticlepeer-review

112 Citations (Scopus)

Abstract

The biocompatibility of hydroxyapatite has been demonstrated by previous studies, with enhancement of osteointegration through the use of porous hydroxyapatite (pHA). Emphasis has been focused on the use of coralline hydroxyapatite or the introduction of macroporosity into synthetic hydroxyapatite. The current study investigates the role of macro- and microporosities in synthetic phase-pure porous hydroxyapatite on the morphological aspects of human osteoblast-like cells using scanning electron microscopy. Cells were seeded on four different types of porous hydroxyapatite (HA1, HA2, HA3 and HA4) and examined following 1, 2, 14 and 30 days of incubation in vitro. The results indicated that the cells had an affinity to micropores through filopodia extensions, at initial stage of attachment. Cellular proliferation and colonization was evident on all materials with cells forming cellular bridges across the macropores at day 14 with cellular canopy formation covering entire macropores observed by day 30. This study demonstrates that while the introduction of microporosity has no evident effect on cellular morphology at later time points. it seems to play a role in initial cellular anchorage and attachment.

Original languageEnglish
Pages (from-to)100-110
Number of pages10
JournalJournal of Microscopy
Volume215
DOIs
Publication statusPublished - 2004

Keywords

  • hydroxyapatite
  • macroporosity
  • microporosity
  • osteoblasts
  • scanning electron microscopy
  • CELL-ADHESION
  • BONE
  • FIBRONECTIN
  • DIFFERENTIATION
  • ATTACHMENT
  • SURFACES
  • HEXAMETHYLDISILAZANE
  • TRANSPLANTATION
  • FIBROBLASTS
  • ALLOGRAFTS

Fingerprint

Dive into the research topics of 'Porosity Variation In Hydroxyapatite and Osteoblast Morphology: A Scanning Electron Microscopy Study'. Together they form a unique fingerprint.

Cite this