title: Quantitative analysis of three-dimensional complexity and connectivity changes in trabecular microarchitecture in relation to aging, menopause, and inflammation.
abstract: There are several types of bone loss besides that associated with normal aging, eg, that associated with the menopause, and that associated with chronic inflammation, and these are considered to be caused by different mechanisms. The microarchitecture that results from these different bone-loss mechanisms would not be the same. The purpose of this study was to investigate differences in the three-dimensional trabecular microarchitecture in various types of osteopenia, using microcomputed tomography (Micro-CT). Thirty-five Fisher 344 rats were divided into five groups (control, young, senile, ovariectomized [OVX], and inflammation-mediated osteopenia [IMO]) and distal femoral metaphysis was scanned by Micro-CT to nondestructively acquire a 3-D CT stack consisting of 50 consecutive slices at a spatial resolution of 26 microm. The volume of interest, consisting of the secondary spongiosa, was prepared to analyze the 3-D trabecular microarchitecture. A parametric analysis was carried out using bone volume fractions, fractal dimensions, and the first Betti number in order to quantitatively express the mass, complexity, and connectivity of the trabecular microarchitecture. Complexity tended to decrease with age, and decreased significantly in estrogen deficiency-induced and inflammation-mediated osteopenia. Connectivity did not appear to change with aging, but was significantly decreased in estrogen deficiency-induced and inflammation-mediated osteopenia. There was no significant difference between the OVX and the IMO groups.
authors.affiliation: Department of Orthopaedic Surgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan.
authors.forename: T
authors.initials: T
authors.lastname: Mawatari
authors.forename: H
authors.initials: H
authors.lastname: Miura
authors.forename: H
authors.initials: H
authors.lastname: Higaki
authors.forename: K
authors.initials: K
authors.lastname: Kurata
authors.forename: T
authors.initials: T
authors.lastname: Moro-oka
authors.forename: T
authors.initials: T
authors.lastname: Murakami
authors.forename: Y
authors.initials: Y
authors.lastname: Iwamoto
mesh_terms: D000367:Age Factors; D000704:Analysis of Variance; D000818:Animals; D001851:Bone Diseases, Metabolic / Q000000981:diagnostic imaging / Q000378:metabolism / Q000473:pathology*; D001862:Bone Resorption / Q000000981:diagnostic imaging / Q000378:metabolism / Q000473:pathology; D004195:Disease Models, Animal; D005260:Female; D005269:Femur / Q000000981:diagnostic imaging / Q000473:pathology*; D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007249:Inflammation; D015663:Osteoporosis, Postmenopausal / Q000000981:diagnostic imaging / Q000378:metabolism / Q000473:pathology*; D010052:Ovariectomy; D011897:Random Allocation; D051381:Rats; D011916:Rats, Inbred F344; D015203:Reproducibility of Results; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods