Literature DB >> 23657410

A methodology to measure cervical vertebral bone maturation in a sample from low-income children.

Luciana Barreto Vieira Aguiar1, Maria de Paula Caldas, Francisco Haiter Neto, Glaucia Maria Bovi Ambrosano.   

Abstract

This study evaluated the applicability of the regression method for determining vertebral age developed by Caldas et al. (2007) by testing this method in children from low-income families of the rural zone. The sample comprised cephalometric and hand-wrist radiographs of 76 boys and 64 girls aged 7.0 to 14.9 years living in a medium-sized city in the desert region of the northeastern region of Brazil, with an HDI of 0.678. C3 and C4 vertebrae were traced and measured on cephalometric radiographs to estimate the bone age. The average age, average hand-wrist age and average error estimated for girls and boys were, respectively, 10.62 and 10.44 years, 11.28 and 10.57 years, and 1.42 and 1.18 years. Based on these results, the formula proposed by Caldas et al. (2007) was not applicable to the studied population, and new multiple regression models were developed to obtain the children's vertebral bone age accurately.

Entities:  

Mesh:

Year:  2013        PMID: 23657410     DOI: 10.1590/0103-6440201301787

Source DB:  PubMed          Journal:  Braz Dent J        ISSN: 0103-6440


  3 in total

1.  A large sample-sized study on dental development of children treated at the Central Dental Clinic (OCEx) of the Brazilian Army.

Authors:  Marcos Vinicius Fernandes Machado; Mariana Quirino Silveira Soares; Andrea Maia Sampaio Alonso Baz; Jose Luiz Cintra Junqueira; Ademir Franco
Journal:  Clin Oral Investig       Date:  2022-04-29       Impact factor: 3.606

2.  Ultrasonographic localization of the thyroid gland for its optimal shielding prior to lateral cephalometric radiography: a pilot study.

Authors:  Elmira Pakbaznejad Esmaeili; Kirsti Hurmerinta; David Rice; Anni Suomalainen
Journal:  Dentomaxillofac Radiol       Date:  2016-02-03       Impact factor: 2.419

3.  Cervical vertebral maturation assessment on lateral cephalometric radiographs using artificial intelligence: comparison of machine learning classifier models.

Authors:  Hakan Amasya; Derya Yildirim; Turgay Aydogan; Nazan Kemaloglu; Kaan Orhan
Journal:  Dentomaxillofac Radiol       Date:  2020-03-09       Impact factor: 2.419

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.