Background: Radiographic severity of metopic synostosis has been suggested as a predictor of long-term neurocognitive outcomes, and artificial intelligence (AI) has recently been used to quantify severity. Age at surgery is predictive of long-term neurocognition in sagittal synostosis but has not been adequately explored in metopic synostosis.
Methods: Children ages 6 to 18 years old with corrected metopic synostosis underwent testing of intelligence quotient (IQ), academic achievement, and visuomotor integration (VMI). Various manual measurements and AI-derived severity scores were determined. Scans were categorized as moderate or severe for head-to-head comparisons and multivariable linear regressions were used to assess the relationship of age at surgery and severity with neurocognitive outcomes.
Results: 41 patients with average age at testing of 10.8 ± 3.4 years were included. 18 patients were in the severe group while 23 patients were in the moderate group with average ages at surgery 6.6 ± 2.7 and 10.6 ± 8.4 months, respectively (p = 0.062). Greater AI-derived severity was significantly associated with lower reading comprehension (p = 0.040 and 0.018) and reading composite scores (p = 0.024 and p = 0.008). Older age at surgery was significantly associated with lower VMI scores (p-values ranging from 0.017 to 0.045) and reading composite scores (p = 0.047 and 0.019).
Conclusions: This study suggests an association between greater AI-derived radiographic severity and lower reading ability in corrected metopic synostosis. Older age at surgery was independently associated with lower reading ability and visuomotor integration. Surgical correction may mitigate neurodevelopmental differences based on severity that have been observed pre-operatively.
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