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Differences in skeletal growth patterns: an exploratory approach using elliptic Fourier analysis.

Tania Camila Niño-Sandoval1, Marco Frazão2, Belmiro C E Vasconcelos3

  • 1Department of Oral and Maxillofacial Surgery and Traumatology, University of Pernambuco - School of Dentistry (UPE/FOP), University Hospital Oswaldo Cruz, Rua Arnóbio Marquês, 310 - Santo Amaro, Recife, PE, CEP: 50.100-130, Brazil.

Clinical Oral Investigations
|August 15, 2020
PubMed
Summary

Elliptic Fourier analysis reveals distinct mandibular and maxillary shape differences across facial growth patterns. This method effectively differentiates skeletal classes, particularly for the mandible, aiding in facial biotype analysis.

Keywords:
Elliptical Fourier analysisMandibular shapeMaxillary shapeSkeletal growth patterns

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Area of Science:

  • Orthodontics and Dental Anthropology
  • Biometrics and Morphometrics
  • Skeletal Biology

Background:

  • Facial growth patterns (hypodivergent, normodivergent, hyperdivergent) influence skeletal classes (I, II, III).
  • Quantifying shape differences in mandibular and maxillary curves is crucial for understanding craniofacial morphology.
  • Traditional methods may not fully capture subtle shape variations.

Purpose of the Study:

  • To apply elliptic Fourier analysis to identify shape differences in mandibular and maxillary curves across varying facial growth patterns and skeletal classes.
  • To evaluate the discriminatory power of these shape differences.

Main Methods:

  • Inclusion of 626 adult patients (Brazilian and Colombian) with lateral cephalometric radiographs.
  • Digitization of maxillary and mandibular curves.
  • Application of elliptic Fourier analysis (20 harmonics) with size, rotation, and translation filtering.
  • Statistical analysis using non-parametric MANOVA and a confusion matrix for discriminatory capacity assessment.

Main Results:

  • Significant shape differences were observed in mandibular and maxillary contours among hypodivergent, normodivergent, and hyperdivergent patterns across skeletal classes I, II, and III (p < 0.05).
  • Confusion matrix analysis yielded accuracies of 74.1%, 79.5%, and 90.1% for mandibular curves in classes I, II, and III, respectively.
  • Accuracies for maxillary curves were 71.9%, 73.9%, and 75% for classes I, II, and III, respectively.

Conclusions:

  • Elliptic Fourier analysis is a viable method for detecting shape variations in mandibular and maxillary contours with acceptable discriminatory capacity, especially for the mandible.
  • Both mandibular and maxillary bone curves significantly define facial biotypes, independent of size and positional variations.
  • This approach provides a quantitative method for mandibular morphology, potentially enabling the development of cost-effective prediction systems for the Latin American population.