A 2D Photo Score for Phenotypic Severity in Unilateral Coronal Synostosis Patients
Year: 2026
Type: article
Abstract: BACKGROUND: Unilateral coronal synostosis (UCS) presents with a wide range of phenotypic severity, yet commonly used outcome measures are heterogeneous and often subjective, resource-intensive, or non-suture-specific. Reliable grading of phenotypic severity is crucial for evaluating aesthetic outcomes and for benchmarking treatment results across centers. The aim of this study was to develop a simple, suture-specific, 2D photo-based scoring system for UCS and to assess its reliability across multiple expert centers. METHODS: A retrospective multicenter study was conducted using standardized photos of patients with nonsyndromic UCS from 6 European expert centers. A UCS-specific photo score was developed through expert consensus and included 5 items: forehead shape, temporal hollowing, orbital dystopia, and nasal deviation, together with an overall phenotype item. All items were scored on a 4-point ordinal scale. A cumulative severity score was calculated from the 4 feature-specific items, excluding the overall phenotype. Twenty craniofacial plastic surgeons and pediatric neurosurgeons independently scored 60 photo sets. RESULTS: Agreement for individual items was moderate (κ=0.48-0.56), with lower reliability for the overall phenotype item (κ=0.41). The agreement was highest for the cumulative score of feature-specific items (intraclass correlation coefficient: 0.64). Reliability was consistent between 2D photos and 3D-renderings. CONCLUSION: This study introduces the first multicenter, suture-specific photo score for UCS. Combining multiple UCS-specific features into a cumulative score substantially improves reliability, supporting its use as a practical tool for standardized phenotypic severity assessment and multicenter benchmarking.
Source: Journal of Craniofacial Surgery
Institution: Erasmus MC
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W7162789108