Objectives: This study aimed to assess whether texture feature maps (TFMs) derived from CBCT images improve the detection of small simulated condylar defects and to examine the influence of voxel size.
Methods: Eight dry mandibles received three spherical defects (0.9, 1.0, 1.2 mm) in each condyle. CBCT scans were performed at voxel sizes of 0.20 mm and 0.40 mm. Sagittal and coronal slices were exported and processed in MaZda software to generate GLCM-based texture maps (contrast, entropy, etc). Three experienced radiologists independently evaluated randomized images for the presence of cortical defects. Kappa, McNemar, and Fisher tests (α = 0.05) were used.
Results: Contrast-based TFMs yielded the highest diagnostic performance, with Kappa values ranging from 0.78-1.00 and significant improvement over unprocessed images (p < 0.05). Entropy maps showed the poorest performance. There was no significant effect of voxel size or defect dimension. TFMs enhanced interobserver agreement.
Conclusions: Texture feature maps, especially based on contrast, may enhance visualization of subtle condylar bone defects independent of voxel size. This post-processing approach could provide a low-dose adjunct to improve CBCT diagnostic confidence in TMJ imaging.
Advances in knowledge: This study introduces the use of texture feature maps in CBCT evaluation of the mandibular condyle, demonstrating that contrast-based mapping enhances detection of subtle bone defects and may support early TMJ diagnosis.
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