Objective Evaluation of 3D Morphology by Statistical Shape Modeling or Geometric Morphometrics Enabling...

Craniosynostoses are rare congenital conditions characterized by variable severity and a multifactorial relation between morphology and function that remains incompletely understood, impacting outcomes and prognosis. There is no consensus on how to objectively quantify severity. This systematic review aimed to evaluate the use of statistical shape modeling (SSM) and geometric morphometrics (GM) in addressing these challenges and explore their relevance in developing patient-specific treatments. A comprehensive search was conducted using PubMed, Scopus, and Web of Science to identify relevant studies based on predefined keywords. The inclusion criteria were peer-reviewed original articles in English that applied SSM or GM to assess morphology, guide preoperative planning, or evaluate outcomes in craniosynostosis patients. Out of 289 screened articles, 47 studies met the inclusion criteria. All studies focused on objective quantification of morphology, most commonly using principal component analysis (66%), 36% focused on outcomes, 30% specifically aimed to develop severity indices, and 15% aimed at objective diagnosis. CT was the predominantly used modality (79%). Notable methodological discrepancies were observed between studies. SSM and GM demonstrated promising potential in achieving precise, objective quantification of the complex morphology and severity of craniosynostosis. However, there is a need for consensus on how to optimize the application of these methods, integrate them into clinical practice, and use them for informed decision-making in patient-specific treatments to improve outcomes. Multicenter studies, the inclusion of large patient and control cohorts, and close collaboration between imaging specialists, scientists trained in morphometrics, and craniofacial surgeons are essential to facilitate their clinical implementation.