BACKGROUND: Micro-computed tomography is an efficient method for quantifying the density and mineralization of mandibular microarchitecture. Conventional radiomorphometrics such as bone and tissue mineral density are useful in determining the average overall mineral content of a scanned specimen; however, relying solely on these metrics has limitations. Using bone mineral density distribution (BMDD), the complex array of mineralization densities within a bone sample can be portrayed. This information is particularly useful as a computational feature reflective of the rate of bone turnover. We demonstrate the utility of BMDD analyses in the rat mandible and generate a platform for further exploration of mandibular pathology and treatment. METHODS: Male Sprague-Dawley rats (n = 8) underwent micro-computed tomography, and histogram data were generated from a selected volume of interest. A standard curve was derived for each animal, and reference criteria were defined. An average histogram was produced for the group, and descriptive analyses including the means and SDs are reported for each of the normative metrics. RESULTS: M(peak) (3444 Hounsfield units [SD, 138]) and M(width) (2221 Hounsfield units [SD, 628]) are 2 metrics demonstrating reproducible parameters of BMDD with minimal variance. A total of 8 valuable metrics quantifying biologically significant events concerning mineralization are reported. CONCLUSIONS: We quantify the vast wealth of information depicted in the complete spectrum of mineralization established by the BMDD analysis. We demonstrate its potential in delivering mineralization data that encompass and enhance conventional reporting of radiomorphometrics. Moreover, we explore its role and translational potential in craniofacial experimentation.
BACKGROUND: Micro-computed tomography is an efficient method for quantifying the density and mineralization of mandibular microarchitecture. Conventional radiomorphometrics such as bone and tissue mineral density are useful in determining the average overall mineral content of a scanned specimen; however, relying solely on these metrics has limitations. Using bone mineral density distribution (BMDD), the complex array of mineralization densities within a bone sample can be portrayed. This information is particularly useful as a computational feature reflective of the rate of bone turnover. We demonstrate the utility of BMDD analyses in the rat mandible and generate a platform for further exploration of mandibular pathology and treatment. METHODS: Male Sprague-Dawley rats (n = 8) underwent micro-computed tomography, and histogram data were generated from a selected volume of interest. A standard curve was derived for each animal, and reference criteria were defined. An average histogram was produced for the group, and descriptive analyses including the means and SDs are reported for each of the normative metrics. RESULTS: M(peak) (3444 Hounsfield units [SD, 138]) and M(width) (2221 Hounsfield units [SD, 628]) are 2 metrics demonstrating reproducible parameters of BMDD with minimal variance. A total of 8 valuable metrics quantifying biologically significant events concerning mineralization are reported. CONCLUSIONS: We quantify the vast wealth of information depicted in the complete spectrum of mineralization established by the BMDD analysis. We demonstrate its potential in delivering mineralization data that encompass and enhance conventional reporting of radiomorphometrics. Moreover, we explore its role and translational potential in craniofacial experimentation.
Authors: S Blouin; H W Thaler; C Korninger; R Schmid; J G Hofstaetter; R Zoehrer; R Phipps; K Klaushofer; P Roschger; E P Paschalis Journal: Bone Date: 2009-01-09 Impact factor: 4.398
Authors: Barbara M Misof; Eleftherios P Paschalis; Stéphane Blouin; Nadja Fratzl-Zelman; Klaus Klaushofer; Paul Roschger Journal: J Bone Miner Res Date: 2010-11 Impact factor: 6.741
Authors: Jeffrey A Meganck; Kenneth M Kozloff; Michael M Thornton; Stephen M Broski; Steven A Goldstein Journal: Bone Date: 2009-08-06 Impact factor: 4.398
Authors: P Roschger; A Lombardi; B M Misof; G Maier; N Fratzl-Zelman; P Fratzl; K Klaushofer Journal: J Bone Miner Res Date: 2010-01 Impact factor: 6.741
Authors: Alexis Donneys; Noah S Nelson; Joseph E Perosky; Yekaterina Polyatskaya; Jose J Rodriguez; Christian Figueredo; Cheyenne A Vasseli; Hannah C Ratliff; Sagar S Deshpande; Kenneth M Kozloff; Steven R Buchman Journal: Bone Date: 2015-12-23 Impact factor: 4.398
Authors: Catherine N Tchanque-Fossuo; Alexis Donneys; Deniz Sarhaddi; Behdod Poushanchi; Sagar S Deshpande; Daniela M Weiss; Steven R Buchman Journal: Bone Date: 2013-07-13 Impact factor: 4.398
Authors: Eoin Parle; Sherdya Tio; Annie Behre; John J Carey; Colin G Murphy; Timothy F O'Brien; William A Curtin; Stephen R Kearns; John P McCabe; Cynthia M Coleman; Ted J Vaughan; Laoise M McNamara Journal: JBMR Plus Date: 2019-12-11