Shape differences among symmetrically shaped skeletal growth patterns in a panoramic view: a Fourier analysis.

Area of Science:

• Orthodontics
• Anthropometry
• Biometrics

Background:

• Facial skeletal growth patterns exhibit diverse morphological characteristics.
• Accurate analysis of mandibular shape is crucial for diagnosing and predicting craniofacial development.
• Existing methods may lack the precision to capture subtle shape variations.

Purpose of the Study:

• To apply Elliptic Fourier Analysis (EFA) for quantifying shape differences in mandibular contours.
• To investigate skeletal growth patterns in hypodivergent, normodivergent, and hyperdivergent facial types.
• To assess the utility of EFA in differentiating facial biotypes from radiographic and tomographic panoramic views.

Main Methods:

• Digitization of mandibular contours from 240 panoramic radiographic and tomographic images.
• Application of EFA with 20 harmonics, filtering for rotation, translation, and size.
• Statistical analysis using MANOVA with Bonferroni correction and Hotelling's p-values.
• Classification of images based on mandibular plane and ANB angles.

Main Results:

• Significant shape differences were detected among hypodivergent, normodivergent, and hyperdivergent patterns across skeletal Classes I, II, and III (p < 0.05).
• These morphological variations were predominantly located in the symphyseal region of the mandible.
• No significant differences were observed between radiographic and tomographic imaging modalities.

Conclusions:

• Elliptic Fourier Analysis (EFA) provides a robust mathematical framework for analyzing mandibular shape and its variations.
• EFA can effectively distinguish between different facial biotypes based on mandibular morphology.
• This technique holds potential for improving the accuracy of craniofacial growth prediction models.