• M A Al-Attas, P Koppolu, S A Alanazi, K T Alduaji, P J Parameaswari, L A Swapna, H Almoallim, and P Krishnan.
• Dental Implants and Maxillofacial Prosthodontics, King Saud Medical City, Riyadh, KSA.
• Niger J Clin Pract. 2020 Feb 1; 23 (2): 258-265.

BackgroundThe Cone Beam Computed Tomography (CBCT) is currently being used as the most common diagnostic method to evaluate the bone density of the maxilla and the mandible for planning dental implant. Aim: The aim of the study is to check the quantitative alveolar bone density in complete or partial edentulous and dentulous male and female patients among Riyadh sample population in Saudi Arabia.Materials And MethodsThe study involved a cross-sectional analysis of 231 consecutive CBCT images of 231 different patients (115 males and 116 females). The scans were of Saudi National patients who were partially or completely edentulous without any bone infections in the maxilla and the mandible. The findings are presented as descriptive statistics and inferential statistics: student -t-test for two group means, ANOVA for three groups, Post-hoc LSD test for multiple comparisons, Levene statistics for testing the homogeneity of variances and a statistical significance at 5% level.ResultsComparison of mean alveolar bone density in maxillae of dentulous male smokers showed a statistically significant difference for bucco-cortical plate and cancellous bone among different regions. In dentulous male nonsmokers, no significant difference was observed for maxillary regions, while in mandibular areas, a statistically significant difference was seen for buccal cortex, palatal cortex, and cancellous bone among different regions. While studying the scans of female dentulous patients, a statistically significant difference was observed in alveolar bone density for all the areas.ConclusionEvaluation of bone density is an important step in treatment planning and this study was aimed to provide insight into bone density patterns of population in Riyadh, Saudi Arabia. Further similar studies in different populations can help in planning for more efficient treatment outcomes.

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