Temporal mapping of the closure of the anterior fontanelle and contiguous sutures using computed tomography, in silico models of modern infants
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Alston, CL
Barry, MD
MacGregor, DM
Gregory, LS
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Abstract
The aim of this study is to quantify and statistically model the age‐related decline in the fibrous connective tissue interface of the anterior fontanelle in modern Australian infants, using three‐dimensional, semi‐automated computed‐assisted design protocols. Non‐linear regression with variance models, using power functions, combined with quantile regression of the 5th and 95th population percentiles, were utilised to assess absolute anterior fontanelle surface area (AFSA) as a function of age, using multi‐slice cranial computed tomography scans obtained from 256 infants aged < 30 months (males: n = 126, females: n = 109) from Brisbane children’s hospitals. Normalised AFSA (NFSA), standardised for variation in cephalic size, followed a progressive decline from birth, the greatest velocity change occurring between the 3–6 and 6–9 month cohorts. Growth of the neurocranium is the most significant within the first 8 months postpartum, with a mean increase of 19.03 mm in maximum cranial length and 10.04 mm in breadth. Directionality of fontanelle closure, quantified using spline curves refutes fundamental assumptions that the anterior fontanelle is consistent with a quadrilateral, and contiguous sutures exhibit constant velocity of closure. The present study provides normative values for fontanelle size and diameters as well as new predictive non‐linear models for age substantiation, screening of developmental abnormalities and indicators of suspected child maltreatment in modern infants aged birth to 30 months.
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Journal of Anatomy
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237
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2
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Biomedical engineering
Medical physiology
anterior fontanelle
computed tomography
growth and development
logistic regression
subadult age estimation
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Lottering, N; Alston, CL; Barry, MD; MacGregor, DM; Gregory, LS, Temporal mapping of the closure of the anterior fontanelle and contiguous sutures using computed tomography, in silico models of modern infants, Journal of Anatomy, 2020, 237 (2), pp. 379-390