Data-driven Normative Reference of Pediatric Cranial Bone Development
Ontology highlight
ABSTRACT: Methods:
The model was built using a cross-sectional and multi-institutional pediatric computed tomography image dataset with 2068 subjects without cranial pathology (age 0–10 years). We combined principal component analysis and temporal regression to build a statistical model of cranial bone development at every location of the calvaria. We studied the influences of sex on cranial bone growth, and our bone density model allowed quantifying for the first time suture fusion as a continuous temporal process. We evaluated the predictive accuracy of our model using an independent longitudinal image dataset of 51 subjects. Results:
Our model achieved temporal predictive errors of 2.98 ± 0.69 mm, 0.27 ± 0.29 mm, and 76.72 ± 91.50 HU in cranial bone shape, thickness, and mineral density changes, respectively. Significant sex differences were found in intracranial volume and bone surface areas (P < 0.01). No significant differences were found in cephalic index, bone thickness, mineral density, or suture fusion. Conclusions:
We presented the first pediatric age- and sex-specific statistical reference for local cranial bone shape, thickness, and mineral density changes. We showed its predictive accuracy using an independent longitudinal dataset, we studied developmental differences associated with sex, and we quantified suture fusion as a continuous process.
SUBMITTER: Liu J
PROVIDER: S-EPMC9377678 | biostudies-literature | 2022 Aug
REPOSITORIES: biostudies-literature
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