## 4 Discussion  
CBCT is a precise imaging technique that provides a three-dimensional analysis of head and neck anatomy to assist clinicians in the planning of maxillofacial and orthognathic surgery, as well as postoperative assessment [7; 8]. CBCT provides clinicians with multi-planar views of the skull, facilitating more accurate treatment planning, diagnosis and therapy while minimising x-ray radiation exposure compared to traditional computed tomography [3; 8]. In this study, we used CBCT to identify changes associated with maxillofacial surgery. Our research highlighted that data derived from 3D CBCT scans, including measurements and spatial points, can overcome the limitations of data obtained from 2D orthopantomogram (OPG) images, such as lack of depth, real-world scale, and perspective distortion [3; 8; 27]. This is consistent with a retrospective pilot study that supported the replacement of two-dimensional analysis with three-dimensional methods in orthognathic surgery planning [11; 18]. We have shown that CBCT scans are compatible with both basic measurements and more sophisticated exploration and analysis methods, such as surface-based and landmark-based data processing. Our manuscript confirms the fact that oral and maxillofacial surgery (OMFS) can transform the current concepts of reconstruction and rehabilitation of maxillofacial defects using Artificial Intelligence (AI) by providing various 3D techniques that can improve the accuracy, efficiency, and outcomes of surgical procedures [28]. Computer-aided design and computer-aided manufacturing (CAD/CAM) uses three-dimensional (3D) CBCT and facial scans not only for treatment planning, but also for precise reconstruction of maxillofacial defects. All 3D systems were responsible for more precise function and aesthetics of the therapy [29]. The results of our manuscript also demonstrated quantitative and qualitative differences in the power of each methodological approach. The initial study using cranial linear distances revealed significant postoperative changes, particularly an increase in mandibular width (go dx-go sin measurement). The subsequent landmark-based approach, while confirming this increase, effectively depicted both numerical and visual changes in the configuration of the maxilla and mandible. The third study design focused on exploring 3D facial scans using landmark-based and surface-based approaches. Unlike the complex 3D cranial data, 3D facial scans, which take the form of an open-ended digital shell, are easier to process as polygonal models or point clouds. The surface-based approach allows postoperative changes to be investigated independently of preoperatively selected feature points or linear distances. This allows practitioners the freedom to examine changes without bias, and to view them both numerically and visually. For example, this approach has shown how regions such as the chin, cheeks, and nasal area have been affected by surgery and postoperative treatment. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & & **Males** & **Females** & **Total** \\ \hline RMS & means & 2.090 & 1.582 & 1.813 \\  & SD & 0.367 & 0.220 & 0.385 \\  & min & 1.719 & 1.293 & 1.293 \\  & max & 2.610 & 1.959 & 2.610 \\ \hline PERC75 & means & 2.137 & 1.767 & 1.935 \\  & SD & 0.251 & 0.239 & 0.302 \\  & min & 1.950 & 1.457 & 1.457 \\  & max & 2.533 & 2.184 & 2.533 \\ \hline PDs & means & 18.859 & 15.225 & 17.987 \\  & SD & 0.933 & 1.085 & 0.810 \\  & min & 14.086 & 10.929 & 10.929 \\  & max & 26.869 & 18.697 & 26.869 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Descriptive statistics for deviation metrics. The results in Tables 1-6 confirm our new clinical strategy based on 3D planning and treatment for the precision, optimal control, and prediction of treatment outcomes. For all interventions, we propose 3D treatment planning, which is much more precise than 2D imaging, following the guidelines of the American Dental Association (ADA).