Development of a predictive model for identifying previously undetected vertical root fractures
Dantong Cao1, Peng Zhang2, Antian Gao1
1Department of Dentomaxillofacial Radiology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, China.
Summary
A new predictive model can effectively screen for undetected vertical root fractures (VRFs) in root canal treated teeth. This model shows high diagnostic efficacy, aiding in identifying VRFs with vertical bone loss and overfilled canals.
Area of Science:
- Dentistry
- Endodontics
- Radiology
Background:
- Vertical root fractures (VRFs) are a significant cause of tooth loss in endodontically treated teeth.
- Accurate and early diagnosis of VRFs remains challenging, impacting treatment decisions and prognosis.
Purpose of the Study:
- To develop and validate a predictive model for screening undetected vertical root fractures (VRFs) in root canal treated teeth.
- To identify key clinical and radiographic parameters associated with VRFs.
Main Methods:
- A predictive model was developed using logistic regression based on clinical and cone-beam CT parameters.
- Parameters included: type of bone loss (BL), apical extent of root filling (AR), and root filling diameter ratios (2/3TA).
- The model was trained on 77 teeth and validated on 18 teeth with suspected VRFs.
Main Results:
- The predictive model demonstrated high diagnostic efficacy with a sensitivity of 0.852 and specificity of 0.875 for training data.
- Validation data showed improved performance with a sensitivity of 0.917 and specificity of 0.833.
- Teeth with VRFs were significantly associated with vertical bone loss and overfilled root canals.
Conclusions:
- The developed predictive model shows high diagnostic efficacy for screening vertical root fractures in root canal treated teeth.
- Vertical bone loss and overfilled root canals are key indicators for VRFs.
- This model can aid clinicians in identifying teeth at higher risk for VRFs, improving diagnostic accuracy.
