The face in marfan syndrome: A 3D quantitative approach for a better definition of dysmorphic features

Claudia Dolci1, Valentina Pucciarelli1, Daniele M Gibelli1

  • 1Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milano, Italy.

Clinical Anatomy (New York, N.Y.)
|December 12, 2017
PubMed

Insights

Marfan syndrome (MFS) diagnosis is improved by a new 3D facial analysis. This quantitative approach identifies specific facial abnormalities, aiding early recognition and preventing severe cardiovascular issues in MFS patients.

Area of Science:

  • Medical Genetics
  • Anthropology
  • Biotechnology

Background:

  • Marfan syndrome (MFS) is a rare genetic connective tissue disorder caused by FBN1 gene mutations.
  • Early diagnosis of MFS is crucial for preventing life-threatening cardiovascular complications.
  • Phenotypic variability in MFS often complicates diagnosis, with no standardized definition for facial abnormalities.

Purpose of the Study:

  • To refine the definition of the facial phenotype associated with Marfan syndrome.
  • To evaluate the efficacy of a 3D noninvasive quantitative approach for early MFS recognition.

Main Methods:

  • Acquired 3D facial images of 61 Italian MFS subjects (aged 16-64) using stereophotogrammetry.
  • Computed linear distances and angles from 17 soft-tissue facial landmarks.
  • Calculated z-scores to compare MFS patients with 779 healthy controls matched for sex and age.

Main Results:

  • MFS subjects exhibited significantly greater facial divergence (mean z=+1.9) and lower facial height index (mean z=-1.9) compared to controls.
  • These differences were linked to a shorter mandibular ramus (mean z=-1.9) and increased facial height (mean z=+1.2).
  • Down-slanting palpebral fissures were observed in 85% of MFS patients; no sex differences were noted.

Conclusions:

  • Quantitative facial abnormalities identified in this study enhance the understanding of MFS dysmorphism.
  • The 3D quantitative approach proves useful for the early recognition of Marfan syndrome.
  • This method aids in identifying MFS patients who may be at risk for cardiovascular complications.

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