Comparative Analysis of Mandibular Cortical Bone Indicators of Osteoporosis: CBCT vs. Traditional Panoramic Radiographs

Osteoporosis decreases bone density and increases fracture risk. Radiographic techniques, such as panoramic radiography (PAN) and cone-beam computed tomography (CBCT), can aid in assessing bone health, particularly through mandibular cortical indices.

This study aimed to compare the values of radiomorphometric mandibular indices between conventional panoramic radiographs (PAN) and CBCT-reformatted panoramic radiographs (CRP).

A retrospective analysis of the radiographic records of 96 patients was performed. The recorded measurements and indices included anteroinferior mandibular cortex thickness (AIMC), mental index (MI), panoramic mandibular index (PMI), gonial index (GI), antegonial index (AI), mandibular cortical index (MCI), and molar cortical thickness (MCT). Intra-class coefficient (ICC) analysis was carried out to assess inter- and intra-examiner reliability.

Significant differences (p < 0.05) were found between CRP and PAN measurements for most indices (AIMC, MI, PMI, MCT, and AI), with CRP values generally lower. The GI index showed no significant difference between both modalities. Two-way ANOVA revealed significant effects of age and gender on specific indices. Additionally, MCI categorical analysis demonstrated a significant association between CRP and PAN.

Different mandibular indices varied across the imaging modalities, with AIMC, MI, PMI, MCT, and AI showing lower values on CRP, while GI remained consistent across methods. This suggests that some indices may be more sensitive to imaging resolution and projection geometry. The moderate agreement in MCI classification highlights CRP’s potential for improved visualization of cortical erosion. The influence of age and gender highlights the importance of demographic context. However, the lack of DXA comparison remains a limitation.

Although the differences in indices measured on PAN and CRP were statistically significant, their mean values differed by less than a millimeter. Age and gender influence certain indices, underscoring the need for their consideration in clinical assessments. CBCT can be a valuable tool for enhancing the accuracy of osteoporosis diagnosis.