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DOI: 10.1055/a-2731-5948
Costal Cartilage Calcification in a Caucasian Population: Machine Learning Recommendations for Chest CT-Guided Rhinoplasty Planning
Authors

Introduction: Autologous costal cartilage calcification (CCC) can impact the course and long-term results of rhinoplasty. Preoperative information about the presence, severity and pattern of CCC helps to assess donor site suitability and rhinoplasty planning. Objective: To use machine learning to identify a sex-specific age threshold, beyond which a preoperative chest CT is likely to reveal CCC relevant for rhinoplasty planning. Study Design: Cross-sectional retrospective study of 662 Caucasian adults. Methods: Prevalence, severity and patterns of CCC in ribs 5-8 were assessed by three independent reviewers. A machine learning algorithm was used to predict the age threshold beyond which a chest CT scan is beneficial to rhinoplasty planning. Results: The prevalence of CCC in Caucasian adults was 89.6%. Nearly all individuals over age 50 exhibited some form of CCC. In young females CCC was more severe and prevalent in the central core of ribs 5-8 compared to age-matched males. Conclusion: A chest CT is recommended in females over 23 years and males over 40 years. No data-driven recommendations regarding an upper age limit for costal cartilage use could be determined from the data.
Publikationsverlauf
Eingereicht: 07. Juli 2025
Angenommen: 12. Oktober 2025
Accepted Manuscript online:
27. Oktober 2025
© . The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/).
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