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Quantifying Soft Tissue Changes in Cleft Lip and Palate Using Nonionizing Three-Dimensional Imaging: A Systematic Review. | LitMetric

Quantifying Soft Tissue Changes in Cleft Lip and Palate Using Nonionizing Three-Dimensional Imaging: A Systematic Review.

J Oral Maxillofac Surg

Full Professor, Department of Otorhinolaryngology, Ghent University Hospital, Ghent, Belgium; Centre for Translational Microbiome Research, Department of Microbiology, Cell and Tumor Biology, Karolinska Institutet, Stockholm, Sweden; and SciLifeLab, Stockholm, Sweden.

Published: October 2018

Purpose: The use of nonionizing 3-dimensional (3D) imaging in cleft lip and palate (CLP) research is well-established; however, general guidelines concerning the assessment of these images are lacking. The aim of the present study was to review the methods for quantification of soft tissue changes on 3D surface images acquired before and after an orthopedic or surgical intervention in CLP patients.

Materials And Methods: A systematic literature search was performed using the databases MEDLINE (through PubMed), CENTRAL, Web of Science, and EMBASE. The literature search and eligibility assessment were performed by 2 independent reviewers in a nonblinded standardized manner. Only longitudinal studies reporting the assessment of pre- and postoperative 3D surface images and at least 10 CLP patients were considered eligible.

Results: Fifteen unique studies (reported from 1996 to 2017) were identified after an eligibility assessment. The assessment of the 3D images was performed with landmark-dependent analyses, mostly supported by superimposition of the pre- and postoperative images. A wide spectrum of superimposition techniques has been reported. The reliability of these assessment methods was often not reported or was insufficiently reported.

Conclusions: Soft tissue changes subsequent to a surgical or an orthopedic intervention can be quantified on 3D surface images using assessment methods that are primarily based on landmark identification, whether or not followed by superimposition. Operator bias is inherently enclosed in landmark-dependent analyses. The reliability of these methods has been insufficiently reported.

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http://dx.doi.org/10.1016/j.joms.2018.05.020DOI Listing

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