Evidence map›Paper›PMID 42091729›Full record

ArticleChild's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery2026

Is a standardised severity index needed in unicoronal craniosynostosis? Challenges in developing an objective metric.

Robin van der Straeten, Hanna Lif, Maya Geoffroy, Maxime Taverne, Giovanna Paternoster, Sébastien Laporte, Roman Hossein Khonsari

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Article in Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Robin van der StraetenCraniofacial Growth and Form Laboratory, Institut Imagine, Paris, France.ORCID 0000-0001-9738-6779
Hanna LifCraniofacial Growth and Form Laboratory, Institut Imagine, Paris, France. hanna.lif@uu.se.ORCID 0009-0000-5562-0942
Maya GeoffroyCraniofacial Growth and Form Laboratory, Institut Imagine, Paris, France.ORCID 0000-0002-6474-8144
Maxime TaverneCraniofacial Growth and Form Laboratory, Institut Imagine, Paris, France.ORCID 0000-0003-3355-6200
Giovanna PaternosterDepartment of Neurosurgery, Hôpital Necker - Enfants Malades, Assistance Publique-Hôpitaux de Paris, Paris, France.ORCID 0000-0002-2970-0858
Sébastien LaporteArts Et Métiers Institute of Technology, Université Paris Nord, IBHGC - Institut de Biomécanique Humaine Georges Charpak, HESAM Université, Paris, France.ORCID 0000-0001-5104-7499
Roman Hossein KhonsariCraniofacial Growth and Form Laboratory, Institut Imagine, Paris, France.ORCID 0000-0002-0649-1432

Funding

Uppsala Univerisity
6 · The paper itself

Abstract

purposeMorphological severity of unicoronal synostosis (UCS) is highly variable. Yet, there is no consensus on an objective and standardised metric to quantify 3D severity to evaluate preoperative severity and surgical outcomes. This study aimed to investigate previously described severity indices and compared these to a statistical shape model (SSM) of the cranial vault and expert rating.

methodsComputed tomography of 77 patients with non-syndromic UCS and 75 healthy controls were included. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to identify latent axes of shape variation and derived severity estimates, thereby defining an SSM and UCS Skull Shape-based Severity Index (UCS-SI). Expert-based severity ranking served as an independent reference standard. Correlation analyses assessed associations of severity with skull vault shape and expert rankings.

resultsThe UCS-SI strongly correlated with expert severity ranking and outperformed classical severity indices. PCA and PLS-DA robustly discriminated UCS from controls, with high variable-importance scores localised to the frontal, supraorbital and parietal regions.

conclusionUCS-SI might be a promising severity index in UCS regarding expert perception and objective morphology, offering a clinically interpretable and scalable approach for severity stratification, phenotypic characterisation, and evaluation of surgical outcome trajectories. However, the development of a severity algorithm rather than a severity score might be needed to fully characterise UCS severity. The optimal objective severity metric in UCS is yet to be defined.

Indexed as

CraniosynostosesSeverity of Illness IndexChild, PreschoolFemaleHumansImaging, Three-DimensionalInfantMalePrincipal Component AnalysisSkullTomography, X-Ray ComputedCraniosynostosisPrincipal component analysisSeverity indicesStatistical shape modelling

Identifiers

PMID42091729
PMCPMC13149726

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.