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Development and validation of a predictive nomogram for bilateral posterior condylar displacement using cone-beam
Huachao Sui1, Mo Xiao1,2,3, Xueqing Jiang1
1Department of Endodontics, Tianjin Medical University School and Hospital of Stomatology & Tianjin Key Laboratory of Oral Soft and Hard Tissues Restoration and Regeneration, No. 12 Qixiangtai Road, Heping District, Tianjin, 300070, China.
BMC Oral Health
|June 5, 2025
Summary
Predicting bilateral posterior condylar displacement in temporomandibular disorders (TMDs) is challenging. A new model using age and articular eminence inclination (AEI) shows promise for early risk assessment in TMD patients.
Area of Science:
- Dentistry
- Radiology
- Biomedical Engineering
Background:
- Temporomandibular disorders (TMDs) often involve posterior condylar displacement.
- Early prediction of this displacement is crucial but remains challenging.
Purpose of the Study:
- To develop and evaluate a predictive model for bilateral posterior condylar displacement.
- To identify key risk factors associated with this condition.
Main Methods:
- Retrospective analysis of 166 cone-beam computed tomography (CBCT) images.
- Application of machine learning algorithms (Random Forest, LASSO, XGBoost) for risk factor identification and model development.
- Evaluation of model performance using calibration curves, ROC curves, and decision curve analysis.
Main Results:
- Articular eminence inclination (AEI) and age were significant risk factors.
- LASSO and Random Forest models demonstrated satisfactory discriminative ability (AUC > 0.7).
- The LASSO model incorporating age, AEI, ANB angle, and facial height ratio showed superior clinical utility.
Conclusions:
- Steeper AEI, older age, specific ANB angle, and reduced posterior vertical distance are associated with increased risk.
- A validated prognostic nomogram can aid clinicians in assessing bilateral posterior condylar displacement risk.
