Scholarlink

Background <p>Considering the difficulties presented by changed tooth growth patterns in amelogenesis imperfecta (AI), which might influence clinical decisions and treatment planning, the purpose of this study is to assess the accuracy of dental age assessment in Turkish children with AI in comparison to controls.</p> Methods <p>A total of 416 Turkish children, ages 5 to 13.99, had their panoramic images examined in this retrospective study (104 with AI and 312 controls, 1:3 ratio). The London Atlas method and Cameriere’s European formula were used to estimate dental age. To improve accuracy, a new regression equation was created, and the outcomes were compared using statistical analysis.</p> Results <p>Chronologic age and Cameriere’s European formula did not differ statistically significantly in either group (<i>p</i> = 0.226). However, there were statistically significant variations (<i>p</i> &lt; 0.001) in the dental age estimates from the London Atlas approach, which were overstated by roughly 0.39–0.69 years in both groups. Using Cameriere’s formula, the new regression equation described 90.8% of the deviance in children with AI, while the London Atlas technique explained 83.0%.</p> Conclusions <p>Accurate dental age estimation is crucial for children with AI, and the findings emphasize the superiority of Cameriere’s European formula over the London Atlas method, reinforcing the need for reliable techniques tailored to this unique population.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Dental age estimation in children and adolescents with amelogenesis imperfecta

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月8日

查看全文
  • Selin Saygili,
  • Sedef Ayse Tasyapan,
  • Roberto Cameriere,
  • Hulya Cakir Karabas,
  • Mine Koruyucu,
  • Yelda Kasimoglu

摘要

Background

Considering the difficulties presented by changed tooth growth patterns in amelogenesis imperfecta (AI), which might influence clinical decisions and treatment planning, the purpose of this study is to assess the accuracy of dental age assessment in Turkish children with AI in comparison to controls.

Methods

A total of 416 Turkish children, ages 5 to 13.99, had their panoramic images examined in this retrospective study (104 with AI and 312 controls, 1:3 ratio). The London Atlas method and Cameriere’s European formula were used to estimate dental age. To improve accuracy, a new regression equation was created, and the outcomes were compared using statistical analysis.

Results

Chronologic age and Cameriere’s European formula did not differ statistically significantly in either group (p = 0.226). However, there were statistically significant variations (p < 0.001) in the dental age estimates from the London Atlas approach, which were overstated by roughly 0.39–0.69 years in both groups. Using Cameriere’s formula, the new regression equation described 90.8% of the deviance in children with AI, while the London Atlas technique explained 83.0%.

Conclusions

Accurate dental age estimation is crucial for children with AI, and the findings emphasize the superiority of Cameriere’s European formula over the London Atlas method, reinforcing the need for reliable techniques tailored to this unique population.