Avaliação 3D da densidade da sutura palatina mediana: proposta de diagnóstico

• Ano de defesa: 2018
• Autor(a) principal: Cognetti, Flávio Henrique
• Orientador(a): Capelozza Filho, Leopoldino
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade do Sagrado Coração
• Programa de Pós-Graduação: Ortodontia
• Departamento: Ciências da Saúde e Biológicas
• País: Brasil
• Palavras-chave em Português: Tomografia Computadorizada; Densidade Óssea; Suturas Cranianas; Expansão Maxilar
• Palavras-chave em Inglês: Computed tomography; Bone density; Cranial sutures; Maxillary expansion
• Área do conhecimento CNPq: CIENCIAS DA SAUDE::ODONTOLOGIA
• Link de acesso: https://tede2.usc.br:8443/handle/tede/452

Introduction: This study evaluated the maturation of the midpalatal suture (MPS), by analysis of bone density, using numerical parameters defined by softwares and calculating, according to differences in shades of grey on computed tomographies (CBCT), its diagnostic potential to predict the rapid maxillary expansion (RME). Methods: The sample was composed of 196 CBCT examinations from 117 females and 79 males, aged 11 to 20 years. A previously calibrated examiner guided the tomographic images, which were generated in DICOM format and positioned in axial, sagittal and coronal planes. Density measurements were obtained on axial sections of the MPS region. The densities at the region of the midpalatal suture (dmps), maxillary palatal process (dmpp) and soft palate (dsp) were then measured to obtain a density value and establish individual parameters of density for the diagnosis. Comparison between genders was performed by the t test for independent groups. The correlation between age and density ratio at the midpalatal suture (DMPS) was calculated by the Pearson correlation coefficient. All tests were conducted at a significance level of 5% (p<0.05). All statistical procedures were performed on the software SPSS version 13. Results: The results revealed that the factors age and gender (*statistically significant difference p < 0.05) influenced the density, yet with greater influence for age (Beta = 0.167) than gender (Beta = -0.153). The mean density in the comparison between genders was greater for females (0.807) compared to males (0.714), and the age range 11 to 15 years presented statistically significantly lower density compared to the age range 16 to 20 years. Conclusions: The correlation between age and density evidenced that the older the age, the greater the density observed, and the methods have well-defined parameters to differentiate between genders, since higher density values were observed for the females and lower for the males.