Diagnosing Maxillary Occlusal Cant with average 3D Skeletofacial Model Template.

Abstract

Diagnosing maxillary occlusal cant involves varied methods, yet classification remains incomplete. This includes determining if the cant results from equal faults on both sides or if one side exhibits overdevelopment while the other underdevelops. This study introduces an innovative average 3D skull template for classifying maxillary occlusal cant instances. Sixty adult patients were divided into two groups: 30 with a mesoprosopic facial type and 30 with a leptoprosopic facial type. Using seven pairs of anatomical landmarks (N, Or (L, R), Lo (L, R), Zy (L, R)), the average skull models were aligned and superimposed onto the patients' skull models. Image resizing facilitated optimal registration area fitting. Vertical distances from the U6 mesial buccal cusp tip to the FH plane were measured to analyze occlusal cant, classified into three classes: overdevelopment (Class A), underdevelopment (Class B) and equal fault on both sides (Class C). In the mesoprosopic group, Class B t was most common (40%), followed by Class A (27%) and Class C (33%). In the leptoprosopic facial type group, Class B remained prevalent (50%), followed by Class A (43%) and Class C (7%). Statistical analysis revealed a significant association between facial types and the three classes. Contrary to expectations, equal fault patterns were not predominant; instead, underdevelopment of the maxilla constituted the majority of occlusal cant cases. Utilizing average 3D skeletofacial models as templates emerges as an effective tool and alternative for diagnosing the instance of maxillary occlusal cant. Therapeutic, II.