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Multi-Height Extraction of Clinical Parameters Improves Classification of Craniosynostosis

Becker, Anna Maria 1; Schaufelberger, Matthias ORCID iD icon 1; Kühle, Reinald Peter; Freudlsperger, Christian; Nahm, Werner 1
1 Institut für Biomedizinische Technik (IBT), Karlsruher Institut für Technologie (KIT)

Abstract:

Introduction: 3D surface scan-based diagnosis of craniosynostosis is a promising radiation-free alternative to traditional diagnosis using computed tomography. The cranial index (CI) and the cranial vault asymmetry index (CVAI) are well-established clinical parameters that are widely used. However, they also have the benefit of being easily adaptable for automatic diagnosis without the need of extensive preprocessing.
Methods: We propose a multi-height-based classification approach that uses CI and CVAI in different height layers and compare it to the initial approach using only one layer. We use ten-fold cross-validation and test seven different classifiers. The dataset of 504 patients consists of three types of craniosynostosis and a control group consisting of healthy and non-synostotic subjects.
Results: The multi-height-based approach improved classification for all classifiers. The k-nearest neighbors classifier scored best with a mean accuracy of 89 % and a mean F1-score of 0.75.
Conclusion: Taking height into account is beneficial for the classification. Based on accepted and widely used clinical parameters, this might be a step towards an easy-to-understand and transparent classification approach for both physicians and patients.


Verlagsausgabe §
DOI: 10.5445/IR/1000163815
Veröffentlicht am 03.11.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Biomedizinische Technik (IBT)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 09.2023
Sprache Englisch
Identifikator ISSN: 2364-5504
KITopen-ID: 1000163815
Erschienen in Current Directions in Biomedical Engineering
Verlag De Gruyter
Band 9
Heft 1
Seiten 198 – 201
Vorab online veröffentlicht am 20.09.2023
Schlagwörter Craniosynostosis, Classification, Clinical Parameters, Cranial Index, Cranial Vault Asymmetry Index
Nachgewiesen in Scopus
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