Metopic craniosynostosis (MCS) refers to the premature fusion of the metopic cranial suture resulting in trigonocephaly, characterized by a keel-shaped forehead, suture ridging, orbital hypotelorism, retrusion and upsloping of the lateral supraorbital rim, and bitemporal narrowing. 1 Although severe trigonocephaly is pathognomonic for MCS, mild to moderate phenotypes are more difficult to diagnose and classify by severity. There is currently no standard for classification of severity, and variability in management protocols exists. Surgical intervention for mild to moderate phenotypes remains controversial as objective methods to delineate which patients require surgery are lacking. 1 Although operative intervention effectively preserves normal neurocognition, studies have demonstrated a worsening aesthetic result with Background: Quantifying the severity of head shape deformity and establishing a threshold for operative intervention remains challenging in patients with metopic craniosynostosis (MCS). This study combines three-dimensional skull shape analysis with an unsupervised machine-learning algorithm to generate a quantitative shape severity score (cranial morphology deviation) and provide an operative threshold score. Methods: Head computed tomography scans from subjects with MCS and normal controls (5 to 15 months of age) were used for objective three-dimensional shape analysis using ShapeWorks software and in a survey for craniofacial surgeons to rate head-shape deformity and report whether they would offer surgical correction based on head shape alone. An unsupervised machine-learning algorithm was developed to quantify the degree of shape abnormality of MCS skulls compared to controls. Results: One hundred twenty-four computed tomography scans were used to develop the model; 50 (24% MCS, 76% controls) were rated by 36 craniofacial surgeons, with an average of 20.8 ratings per skull. The interrater reliability was high (intraclass correlation coefficient, 0.988). The algorithm performed accurately and correlates closely with the surgeons assigned severity ratings (Spearman correlation coefficient, r = 0.817). The median cranial morphology deviation for affected skulls was 155.0 (interquartile range, 136.4 to 194.6; maximum, 231.3). Skulls with ratings of 150.2 or higher were very likely to be offered surgery by the experts in this study. Conclusions: This study describes a novel metric to quantify the head shape deformity associated with MCS and contextualizes the results using clinical assessments of head shapes by craniofacial experts. This metric may be useful in supporting clinical decision making around operative intervention and in describing outcomes and comparing patient population across centers. (Plast.

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