## 4 Discussion
The evaluated parameters (M1-IPP, M2-IPP, and CP-IPP) showed no significant differences between the left and right sides. The average M1-IPP and M2-IPP measurements were 15.52 mm and 15.02 mm, respectively. The highest mean CP-IPP length was noted in regio 1 (13.3 mm), whereas the lowest was in regio 3\({}^{\prime}\) (12.54 mm). All measurements showed a positive correlation between left and right quadrants. This may be of clinical significance, because measurements from one side of the maxilla can be applied to the opposite side, where some dental landmarks may be absent. Recent advancements in digital orthodontics emphasize the role of artificial intelligence (AI) and augmented reality (AR) in enhancing diagnostic precision and clinical outcomes. AI-based CBCT analysis has demonstrated high accuracy in identifying edentulous regions and evaluating bone volume, with reported precision levels of up to 96% for the mandible and 83% for the maxilla [57]. Such systems automate anatomical segmentation and suggest optimal implant sites, thereby improving clinical efficiency and reducing human error. Augmented reality (AR) has also gained attention in guided implantology. Studies report that AR-guided navigation enables improved accuracy in TAD insertion, with mean positional deviations ranging between 0.9 and 1.2 mm and angular deviations around 3.96\({}^{\circ}\), significantly outperforming freehand techniques [58]. Additionally, AR facilitates the enhanced visualization of anatomical landmarks and enables real-time guidance during surgery. Integrating AI and AR into orthodontic implant planning aligns with current trends in digital dentistry and provides a pathway toward more predictable, efficient, and minimally invasive treatments. Future clinical protocols should explore these technologies as part of the standard workflow in anchorage planning. Furthermore, digital surgical guide systems represent another emerging technology that could enhance the accuracy of TAD placement. When combined with AI-driven planning and AR navigation, these guides offer the potential for semi- or fully guided insertion protocols based on individualized CBCT-derived anatomical data. Their use may reduce operator variability, prevent root proximity, and improve the reproducibility of implant positioning. Although such technologies are not yet routine in orthodontics, they show promise in bridging the gap between virtual planning and clinical execution [59]. Based on the available public data, we have not identified any studies employing a similar methodological approach for morphometric evaluations. By focusing on these specific points, the research contributes to the existing literature on anterior maxillary anatomy. Using three clinically visible reference points for linear measurements enhances the identification of optimal TAD placement sites, making procedures more predictable. Unlike previous studies that focused solely on bone dimensions and anatomical safety zones, the present study introduces the novel concept of correlating radiographically defined ideal implant points with readily observable intraoral dental landmarks. This relationship may help clinicians orient more easily during implant placement, especially in anatomically demanding regions. While the findings hold clinical significance, this study has limitations, including a sample size that despite being statistically justified, may not encompass broader anatomical variations or ethnic differences. Although the study was conducted exclusively on a Serbian population to ensure sample homogeneity, we acknowledge that this may limit the generalizability of the findings to other ethnic groups, as anatomical variability can exist between populations [60]. Therefore, further studies on different ethnic groups are recommended to confirm the broader applicability of the findings. Additionally, this study focused exclusively on radiographic parameters without clinically validating the ideal placement points through actual TAD insertions and follow-ups.