Categories
Nevin Manimala Statistics

Application of Geometric Morphometrics for Facial Congenital Anomaly Studies

Congenit Anom (Kyoto). 2022 Feb 8. doi: 10.1111/cga.12461. Online ahead of print.

ABSTRACT

The face is a small complex three-dimensional structure composed of various bones and essential organs. Congenital anomalies of those organs represent various deformities; therefore, their quantification has been challenging. Linear measurements, such as lengths or angles between landmarks, called conventional morphometrics, have been used to quantify their phenotypes usually using two-dimensional images, such as photographs or X-ray images. During analysis, geometric information, which refers to the relative position of each structure, is lost. Geometric morphometrics uses shape configurations, including anatomical landmarks, which can retain geometric information throughout analysis and can help visualize the results, making it tremendously advantageous compared to conventional methods. Morphometric studies investigate variations within groups, identification of group differences, simulation of the ontogeny, or association with specific organs or genetic disorders, and geometric morphometrics can be applied to these purposes using multivariate statistical methods. The calculation of high-dimensional data is usually required and has prevented geometric morphometrics from becoming a major morphometric method. However, recent developments in computer technology and software have enabled us to perform it easily with ordinary home computers, and the number of morphometric studies applying geometric morphometrics for facial congenital anomalies has been increasing recently. In this article, we introduce the concept and application of geometric morphometrics and review previous morphometric studies with geometric morphometrics regarding congenital facial anomalies. This article is protected by copyright. All rights reserved.

PMID:35133047 | DOI:10.1111/cga.12461

By Nevin Manimala

Portfolio Website for Nevin Manimala