Semi-Automated Three-Dimensional Condylar Reconstruction.

Area of Science:

• Dentistry
• Radiology
• Medical Imaging

Background:

• Accurate 3D reconstruction of the mandibular condyle is crucial for diagnosing and monitoring bone diseases.
• Cone beam computed tomography (CBCT) provides detailed anatomical data but requires robust segmentation methods for analysis.

Purpose of the Study:

• To validate a semi-automated segmentation method for 3D mandibular condyle reconstruction using CBCT data.
• To assess the accuracy and reproducibility of this method for volumetric analysis.
• To demonstrate its utility in tracking morphological changes in bone tissue.

Main Methods:

• Ten CBCT datasets were used. A standardized orientation protocol and grey-scale cut-off were applied for automatic surface reconstruction.
• Manual optimization of the condylar contour was performed.
• The process was repeated by two independent investigators to assess inter-examiner reliability.

Main Results:

• Excellent intra-examiner reproducibility (CV=3.65%, ICC=0.97) and good inter-examiner reproducibility (CV=7.15%, ICC=0.89) were achieved.
• The mean segmentation time was 6.31 ± 2.78 minutes.
• The method demonstrated high accuracy and consistency in condylar volume measurements.

Conclusions:

• The proposed semi-automated protocol is an accurate and reproducible tool for 3D mandibular condyle reconstruction from CBCT.
• This method facilitates reliable volumetric analysis and follow-up of morphological bone changes.
• It enables Hounsfield unit-based imaging segmentation for enhanced diagnostic capabilities.