Radiomic texture mapping improves visualization of simulated condylar bone lesions in cone beam computed tomography.

OBJECTIVES

This study aimed to assess whether texture feature maps (TFMs) derived from cone beam computed tomography (CBCT) images improve the detection of small simulated condylar defects and to examine the influence of voxel size.

METHODS

Eight dry mandibles received 3 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 Gray-Level Co-occurrence Matrix (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 = .05) were used.

RESULTS

Contrast-based TFMs yielded the highest diagnostic performance, with Kappa values ranging from 0.78 to 1.00 and significant improvement over unprocessed images (P < .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 temporomandibular joint (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.