Test-retest validation of a cranial deformity index in unilateral coronal craniosynostosis. Issue 15 (17th November 2020)

• Record Type: Journal Article
• Authors: Robertson, Emilie; Kwan, Peter; Louie, Gorman; Boulanger, Pierre; Aalto, Daniel
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 23:Issue 15(2020)
• Page Start: 1247
• Page End: 1259
• Publication Date: 2020-11-17
• Subjects: Craniosynostosis -- unicoronal synostosis -- craniofacial -- pediatric -- surgery -- outcome measurement -- cranial vault remodelling -- 3D; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2020.1795143
• Languages: English
• ISSNs: 1025-5842

Abstract

Abstract: Unilateral coronal craniosynostosis (UCS) affects many infants resulting in abnormalities affecting the forehead and orbits. As a result, the deformity caused by UCS is very noticeable and there are several surgical treatment options available to normalize the head shape. However, there is a lack of consistently used outcome measures, resulting in difficulty assessing surgical outcomes and on-going debate over optimal treatments. Current techniques to quantify deformity in UCS are cumbersome, provide limited information, or are based on subjective assessments. In this study, a cranial deformity index was developed to quantify abnormality at the frontal bones for UCS that is accessible, user-friendly, and generates objective surface distance measurements. The cranial deformity index is defined as the Euclidean distance at the point of the largest deviation between the deformed skull compared to a reference skull. In addition, the index was successfully used to quantify post-operative changes in a single case of UCS that underwent corrective surgery. The reproducibility of the index was assessed using test-retest reliability and was demonstrated to be highly reproducible (ICC = 0.93). A user-friendly measurement index that is based on open-source software may be a valuable tool for surgical teams. In addition, this information can augment the consultation experience for patients and their families.