Charting neuroimaging-based head circumference and cranial shape across development
- 1Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
Abstract
Quantitative assessment of head growth supports early detection of neurological disease, yet current clinical practice relies on manual measurements that are variable, anatomically limited, and difficult to scale. Here we introduce a fully automated imaging-native framework (CranioTrace) that transforms routine neuroimaging into standardized, population-referenced markers of cranial development. By integrating topology-constrained segmentation, contour regularization, and geometry-based quality control for automated slice selection, CranioTrace robustly extracts head circumference and cranial morphology from heterogeneous MRI and CT data without manual intervention. The framework enabled construction of sex-specific population growth models across pediatric development in a dataset comprising 9,685 scans spanning birth to early adulthood across 25 cohorts. Imaging-derived head circumference shows strong agreement with tape measurements across independent datasets, high reproducibility (intraclass correlation up to 0.99), and consistent performance across modalities. Beyond conventional head circumference, CranioTrace quantifies cranial shape and asymmetry, capturing developmental dynamics that are not accessible through conventional measurements. Population modeling reveals rapid early-life expansion followed by nonlinear deceleration and stable sex differences. Application to neurogenetic cohorts identifies disease-consistent shifts in growth trajectories: head circumference was higher in neurofibromatosis type 1 and 16p11.2 deletion and lower in 22q11.2 deletion and 16p11.2 duplication. By converting clinical imaging archives into scalable cranial phenotypes linked to probabilistic reference models, CranioTrace provides a foundation for imaging-based growth charting, integrated skull-brain phenotyping, and precise assessment of neurodevelopment.
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BibTeX
@misc{mattisson2026charting,
title = {{Charting neuroimaging-based head circumference and cranial shape across development}},
author = {P. Mattisson and A. S. Mandal and M. Gardner and A. Zapaishchykova and B. Jung and S. Prem and S. Karandikar and H. E. Akouri and D. Zimmerman and E. Levitis and J. A. Berken and G. Ball and R. A. I. Bethlehem and J. D. Bernstock and T. P. Roberts and L. Bloy and H. Huang and A. Vossough and S. Sotardi and E. Liao and M. Fisher and D. M. McDonald-McGinn and R. T. Shinohara and B. H. Kann and A. F. Alexander-Bloch and J. Seidlitz},
howpublished = {bioRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.29.747918},
url = {https://www.biorxiv.org/content/10.64898/2026.08.29.747918v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Charting neuroimaging-based head circumference and cranial shape across development
AU - P. Mattisson
AU - A. S. Mandal
AU - M. Gardner
AU - A. Zapaishchykova
AU - B. Jung
AU - S. Prem
AU - S. Karandikar
AU - H. E. Akouri
AU - D. Zimmerman
AU - E. Levitis
AU - J. A. Berken
AU - G. Ball
AU - R. A. I. Bethlehem
AU - J. D. Bernstock
AU - T. P. Roberts
AU - L. Bloy
AU - H. Huang
AU - A. Vossough
AU - S. Sotardi
AU - E. Liao
AU - M. Fisher
AU - D. M. McDonald-McGinn
AU - R. T. Shinohara
AU - B. H. Kann
AU - A. F. Alexander-Bloch
AU - J. Seidlitz
PY - 2026
DA - 2026/08/29
PB - bioRxiv
DO - 10.64898/2026.08.29.747918
UR - https://www.biorxiv.org/content/10.64898/2026.08.29.747918v1
AB - Quantitative assessment of head growth supports early detection of neurological disease, yet current clinical practice relies on manual measurements that are variable, anatomically limited, and difficult to scale. Here we introduce a fully automated imaging-native framework (CranioTrace) that transforms routine neuroimaging into standardized, population-referenced markers of cranial development. By integrating topology-constrained segmentation, contour regularization, and geometry-based quality control for automated slice selection, CranioTrace robustly extracts head circumference and cranial morphology from heterogeneous MRI and CT data without manual intervention. The framework enabled construction of sex-specific population growth models across pediatric development in a dataset comprising 9,685 scans spanning birth to early adulthood across 25 cohorts. Imaging-derived head circumference shows strong agreement with tape measurements across independent datasets, high reproducibility (intraclass correlation up to 0.99), and consistent performance across modalities. Beyond conventional head circumference, CranioTrace quantifies cranial shape and asymmetry, capturing developmental dynamics that are not accessible through conventional measurements. Population modeling reveals rapid early-life expansion followed by nonlinear deceleration and stable sex differences. Application to neurogenetic cohorts identifies disease-consistent shifts in growth trajectories: head circumference was higher in neurofibromatosis type 1 and 16p11.2 deletion and lower in 22q11.2 deletion and 16p11.2 duplication. By converting clinical imaging archives into scalable cranial phenotypes linked to probabilistic reference models, CranioTrace provides a foundation for imaging-based growth charting, integrated skull-brain phenotyping, and precise assessment of neurodevelopment.
ER -