Predicting Radial Head Dislocation in Hereditary Multiple Osteochondromatosis: A Quantitative Radiologic Approach

Abdulbaki Kurt1, Berkay Doğan1, Mustafa Kavasoğlu1

  • 1Metin Sabanci Baltalimani Bone Diseases Training and Research Hospital, Istanbul, Türkiye.

Insights

Proportional ulnar length is a key predictor of radial head dislocation in children with hereditary multiple osteochondromatosis (HMO). A new classification system using this measure aids in risk stratification for better management.

Area of Science:

  • Orthopedics
  • Pediatric Radiology
  • Skeletal Dysplasias

Background:

  • Hereditary multiple osteochondromatosis (HMO) frequently causes forearm deformities in children.
  • Radial head dislocation (RHD) is a significant complication, potentially preventable with early detection.
  • Current classification systems lack reliability for guiding surveillance and treatment decisions.

Purpose of the Study:

  • Identify radiologic predictors of RHD in pediatric HMO patients.
  • Develop a quantitative, clinically applicable classification system for RHD risk stratification.
  • Support growth-oriented surveillance and surgical decision-making.

Main Methods:

  • Retrospective review of 143 patients (186 forearms) with HMO (2006-2024).
  • Radiographic analysis included lesion distribution, proportional ulnar length (PUL), radial bowing, ulnar variance, and RHD presence.
  • Multivariate analysis to identify RHD predictors and develop a risk-based classification framework.

Main Results:

  • RHD occurred in 36% of forearms.
  • Lower PUL (≤0.89) was a significant predictor of RHD.
  • Absence of distal radius lesions increased RHD likelihood; radial bowing and ulnar variance were not independent predictors.
  • A 3-tier risk classification (Type A1, A2, B) based on PUL and distal radius lesions was developed.

Conclusions:

  • Proportional ulnar length (PUL) is the most reliable radiographic predictor of RHD in HMO.
  • Integrating distal radius lesion status enhances risk stratification for pediatric patients.
  • The proposed system offers a reproducible, growth-oriented framework, addressing limitations of existing classifications.
Abstract