Midface hypoplasia in syndromic craniosynostosis: predicting craniofacial growth via a novel regression model from anatomical morphometric analysis

Hariri, Firdaus and Malek, R. A. and Abdullah, Norli Anida and Hassan, Siti Fatimah (2024) Midface hypoplasia in syndromic craniosynostosis: predicting craniofacial growth via a novel regression model from anatomical morphometric analysis. International Journal of Oral and Maxillofacial Surgery, 53 (4). pp. 293-300. ISSN 0901-5027, DOI https://doi.org/10.1016/j.ijom.2023.08.009.

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Official URL: https://doi.org/10.1016/j.ijom.2023.08.009

Abstract

Midface hypoplasia in syndromic craniosynostosis (SC) may lead to serious respiratory issues. The aim of this study was to analyse the morphometric correlation between midface and cranial base parameters in paediatric SC patients in order to formulate predictive regression models. The computed tomography scans of 18 SC patients and 20 control were imported into Materialise Mimics Medical version 21.0 software for the measurement of multiple craniofacial landmarks and correlation analysis. The results showed a strong correlation of anterior cranial base (SN), posterior cranial base (SBa), and total cranial base (NBa) (r = 0.935) to maxilla length and width (ZMR-ZML) (r = 0.864). The model of NBa = - 1.554 + 1.021(SN) + 0.753(SBa) with R2 = 0.875 is proposed to demonstrate the development of the cranial base that causes a certain degree of midface hypoplasia in SC patients. The formula is supported using a prediction model of ZMR-ZML = 5.762 + 0.920(NBa), with R2 = 0.746. The mean absolute difference and standard deviation between the predicted and true NBa and ZMR-ZML were 2.08 +/- 1.50 mm and 3.11 +/- 2.32 mm, respectively. The skeletal growth estimation models provide valuable foundation for further analysis and potential clinical application.

Item Type: Article
Funders: Technology Development Fund 1 (TED1) from the Ministry of Science, Technology and Innovation Malaysia (TDF08211448)
Uncontrolled Keywords: Craniosynostosis; Facial bones; Craniofacial abnormalities; Cephalometry; Cranial base; Statistical model
Subjects: R Medicine > RK Dentistry
Divisions: Centre for Foundation Studies in Science > Mathematics Division
Faculty of Dentistry > Department of Oral & Maxillofacial Clinical Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 29 Oct 2024 06:52
Last Modified: 29 Oct 2024 06:52
URI: http://eprints.um.edu.my/id/eprint/45559

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