Severity indices for non-syndromic craniosynostosis: quantifying sagittal and metopic malformations

Abstract

This work develops a new set of severity scores that combine several cranial features in order to quantify sagittal and metopic craniosynostosis. Computed tomography head scans were obtained from 90 children affected with single-suture sagittal synostosis, 40 children with single-suture metopic synostosis, and 60 age-matched nonsynostotic controls. Tridimensional reconstructions of the skull were used to trace image analysis planes defined in terms of skullbase plane and internal landmarks. For each patient, a new set of descriptive measures or severity indices of skull shape malformation were computed. A statistical classification approach (regularized logistic regression) was used for combining individual severity indices into summarizing severity scores. The linear separation index that measures the ability of a classification function to separate the affected (sagittal or metopic) and nonsynostotic populations was used to evaluate the severity scores. The proposed scores are sensitive measures of the calvarial malformation that achieve linear separation indices of 95.83% and 98.9% for sagittal vs. control and metopic vs. control populations, respectively. As opposed to individual severity indices, the summarizing severity scores encapsulate a number of distinctive calvarial features associated with sagittal and metopic synostoses crania. The proposed scores enable quantitative analysis in clinical settings of skull features observed in isolated sagittal and metopic synostoses that may not be accurately detected by separate analysis of individual severity indices.