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Related Experiment Video

Updated: Feb 8, 2026

Live Imaging of Mouse Secondary Palate Fusion
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Quantifying Soft Tissue Changes in Cleft Lip and Palate Using Nonionizing Three-Dimensional Imaging: A Systematic

Laurent A M Thierens1, Noëmi M C De Roo2, Guy A M De Pauw3

  • 1Resident, Department of Orthodontics, Oral Health Sciences, Ghent University, Ghent, Belgium; and Centre for Congenital Facial Anomalies, Ghent University Hospital, Ghent, Belgium.

Journal of Oral and Maxillofacial Surgery : Official Journal of the American Association of Oral and Maxillofacial Surgeons
|June 23, 2018
PubMed
Summary

Quantifying soft tissue changes in cleft lip and palate (CLP) patients using 3D imaging relies on landmark-dependent methods. However, the reliability of these 3D assessment techniques requires further investigation and standardization for improved clinical application.

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Area of Science:

  • Medical Imaging
  • Craniofacial Surgery
  • Orthodontics

Background:

  • Nonionizing 3D imaging is established in cleft lip and palate (CLP) research.
  • General guidelines for assessing 3D images in CLP are currently lacking.

Purpose of the Study:

  • To review methods for quantifying soft tissue changes on 3D surface images in CLP patients.
  • Focus on assessments before and after orthopedic or surgical interventions.

Main Methods:

  • Systematic literature search across major databases (MEDLINE, CENTRAL, Web of Science, EMBASE).
  • Inclusion criteria: longitudinal studies, pre- and postoperative 3D images, minimum 10 CLP patients.
  • Eligibility assessment by two independent reviewers.

Main Results:

  • Fifteen studies (1996-2017) met the criteria.
  • 3D image assessment primarily used landmark-dependent analyses and image superimposition.
  • A wide variety of superimposition techniques were reported.
  • Reliability of assessment methods was often poorly reported.

Conclusions:

  • Soft tissue changes in CLP can be quantified using 3D surface images via landmark identification and superimposition.
  • Landmark-dependent analyses inherently involve operator bias.
  • Insufficient reporting of method reliability is a significant issue.