Using principal component analysis to describe the midfacial deformities in patients with craniofacial microsomia. Issue 12 (December 2018)

• Record Type: Journal Article
• Authors: Maas, Britta D.P.J.; Pluijmers, Britt I.; Knoops, Paul G.M.; Ruff, Clifford; Koudstaal, Maarten J.; Dunaway, David
• Is Part Of: Journal of cranio-maxillofacial surgery. Volume 46:Issue 12(2018)
• Page Start: 2032
• Page End: 2041
• Publication Date: 2018-12
• Subjects: Hemifacial microsomia -- Craniofacial abnormalities -- Principal component analysis -- Skull -- Midface; Skull -- Surgery -- Periodicals; Maxilla -- Surgery -- Periodicals; Face -- Surgery -- Periodicals; Surgery, Plastic -- Periodicals; Maxilla -- surgery -- Periodicals; Face -- surgery -- Periodicals; Skull -- surgery -- Periodicals; Oral Surgical Procedures -- Periodicals; Reconstructive Surgical Procedures -- Periodicals; Surgery, Plastic -- Periodicals; Surgery, Oral -- Periodicals; Electronic journals; 617.514
• DOI: 10.1016/j.jcms.2018.09.019
• Languages: English
• ISSNs: 1010-5182

Abstract

Abstract: Purpose: Craniofacial microsomia (CFM) is the result of a disturbance in embryologic development and is characterised by an asymmetric, mostly unilateral facial underdevelopment. The aim of this study is to understand the midfacial involvement in CFM using principal component analysis (PCA). Materials and methods: Pre-operative data from 19 CFM and 23 control patients were collected. A set of 71 landmarks was placed on three-dimensional (3D) reconstructions of all skulls to compare both populations. PCA visualised variation within both groups and calculated the vector of change. Linear measurements were taken to compare ratios between the populations and between the affected and unaffected sides in CFM patients. Results: PCA defined a vector that described shape changes between both populations. Videos showed the variation within the control and CFM group and the transformation from a mean CFM skull into a normal phenotype. Linear measurements showed a significant difference between the affected and unaffected sides in CFM patients. Conclusion: PCA has not been applied on asymmetrical data before, but it has proved to be a useful method to describe CFM. The virtual normalisation of a mean CFM skull enables visualisation of the bony shape changes, which is promising to delineate and to plan surgical correction and could be used as an outcome measure.