CBCT-based three-dimensional phenotyping of skeletal Class II malocclusion in Yemeni adults: principal components and cluster analysis

Objectives To reduce 63 CBCT variables into principal components (PCs) describing major dimensions of skeletal Class II variation in Yemeni adults, derive phenotypic subgroups by clustering, and outline treatment implications. Materials and methods Pretreatment CBCT scans of 120 adults (16–30 years) with skeletal Class II were analyzed. Variables were z‑standardized; PCA with varimax rotation retained components with eigenvalues > 1. K‑means clustering on PC scores yielded phenotypes. Between‑cluster differences used ANOVA/Kruskal–Wallis (α = 0.05). Reliability was assessed using intraclass correlation coefficients (ICC). Results Seven PCs explained 60.2% of total variance. Five clusters with distinct skeletal and dentoalveolar patterns were identified; key variables differed significantly among clusters. ICCs exceeded 0.85 across variables, indicating excellent measurement reliability. Conclusions CBCT‑based PCA and clustering uncovered five clinically coherent Class II phenotypes that map to different management pathways (e.g., growth modification or camouflage for hypodivergent patterns; vertical control/TADs and, in severe cases, combined orthodontic–orthognathic care for hyperdivergent open‑bite–prone patterns). Clinical relevance Multivariate CBCT phenotyping clarifies heterogeneity in Class II malocclusion and can guide case‑specific mechanics and surgery decisions in adult patients.