Detection of bone loss via subchondral bone analysis

Area of Science:

• Biomedical Imaging
• Osteoarthritis Research
• Radiology

Background:

• Early diagnosis of Temporomandibular Joint Osteoarthritis (TMJ OA) lacks definitive markers.
• Subtle structural bone changes in texture and morphometry occur in early TMJ OA.
• Current radiological methods struggle to detect TMJ OA before significant morphological changes.

Purpose of the Study:

• To present an open-source software tool for detecting subtle subchondral bone variations.
• To aid in the early diagnosis of Temporomandibular Joint Osteoarthritis (TMJ OA).
• To quantify subchondral bone biomarkers for early TMJ OA detection.

Main Methods:

• Development of a tool using ITK and 3DSlicer for analyzing high-resolution Cone Beam Computed Tomography (hr-CBCT) data.
• Validation of texture and morphometry analysis biomarkers by comparing hr-CBCT with micro-CT (μCT).
• Computation of multidimensional features from subchondral bone structure.

Main Results:

• The developed tool successfully highlights subtle variations in subchondral bone structure.
• Texture and morphometry biomarkers demonstrated the ability to classify areas with trabecular bone loss in both μCT and hr-CBCT.
• Initial statistical results show potential for classifying early bone changes indicative of TMJ OA.

Conclusions:

• The developed open-source tool represents a significant step towards early TMJ OA diagnosis.
• Quantifying subchondral bone biomarkers using texture and morphometry analysis shows promise for identifying at-risk patients.
• This approach can help diagnose TMJ OA before advanced morphological changes are apparent.