3D surface defect map for assessing buccolingual profile of single tooth gaps following alveolar ridge preservation

Aim: A new, non-invasive approach suggests using single intraoral optical scanning to analyze the ridge profile of single-tooth gaps following alveolar ridge preservation in the absence of a baseline scan. This method involves creating a three-dimensional (3D) surface map to identify and assess contour changes and ridge profiles based on the adjacent teeth. Materials and Methods: The present study was designed as a cross-sectional pilot analysis on a convenience sample of patients undergoing alveolar ridge preservation. Intraoral optical scans were taken on 23 patients, capturing data from 30 edentulous sites. The digital models were then imported into an image analysis software for a 3D surface defect map analysis performed by one examiner. This analysis characterized the buccolingual profile of the single tooth gap relative to the adjacent teeth. 10 linear divergence points, spaced 0.5 mm apart in a corona-apical direction, were identified at the midfacial aspect of the sites. Based on these points the sites were plotted and grouped in three different buccolingual profiles (linear, concave, and convex). Clinical parameters including Keratinized mucosa Width (KMW), and soft tissue phenotype with Colorvue biotype probes were also recorded. Results: Three different buccolingual patterns (linear, convex, and concave) were identified. Seven sites exhibited a linear profile, 10 sites displayed a concave shape, and 13 showed a convex profile. The linear profile had surface discrepancies similar to the neighboring teeth. In contrast, the convex profile revealed mid-buccal discrepancy localized only at the crestal aspect, while the concave had an extended divergence ranging from 1 to 5 mm below the soft tissue margin. Univariate and multiple logistic regression analyses did not reveal any statistically significant variables influencing profilometric analysis; however, when combining phenotype and KMW, thick phenotypes demonstrated a higher proportion of concavity (OR = 4.83) compared to thin ones, suggesting a significant trend. With every 1 mm of increase in KMW, the probability of showing a concavity decreased (p = 0.057). Conclusion: A 3D surface defect map represents a useful tool for objectively quantifying ridge defects and profiles by assessing profilometric and surface differences compared to adjacent dentition using a single intraoral scan. This method also indicates that KMW may play a critical role in preventing concavity defects. The 3D defect map can guide decision-making during soft tissue augmentation procedures by emphasizing the specific location of the defect and providing more detailed insights into its localization. These parameters can enable the tailoring of flap management and soft tissue grafting strategies to address the patient's individual needs.