Costal Cartilage Calcification in a Caucasian Population: Machine Learning Recommendations for Chest CT-guided...

Area of Science:

• Plastic Surgery
• Radiology
• Biomedical Engineering

Background:

• Autologous costal cartilage calcification (CCC) can affect rhinoplasty outcomes.
• Preoperative assessment of CCC is crucial for donor site selection and surgical planning.

Purpose of the Study:

• To determine sex-specific age thresholds for identifying relevant CCC using machine learning.
• To guide preoperative chest CT scan utility in rhinoplasty planning.

Main Methods:

• Retrospective analysis of 662 Caucasian adults' chest CT scans.
• Assessment of CCC prevalence, severity, and patterns in ribs 5-8 by three reviewers.
• Machine learning algorithm to predict age thresholds for beneficial chest CT scans.

Main Results:

• 89.6% prevalence of CCC in Caucasian adults; nearly all individuals over 50 showed CCC.
• Younger females exhibited more severe and prevalent CCC in central ribs compared to males.
• Recommended chest CT screening: females > 23 years, males > 40 years.

Conclusions:

• Chest CT scans are beneficial for identifying costal cartilage calcification in specific age groups for rhinoplasty.
• Sex-specific age thresholds can optimize the use of preoperative imaging for rhinoplasty planning.
• Further research is needed to establish upper age limits for costal cartilage graft viability.