Abstract
OBJECTIVES: To propose a skeletal maturity assessment method by developing a statistical regression analysis model through the integration of lateral and axial images of the cervical vertebrae of patients with cleft lip and palate obtained through CBCT. METHODS: 49 patients with cleft lip and palate (28 females, 21 males; age range, 4-16 years) underwent CBCT examination, and the hand-wrist radiographic data were selected. With coordinates of landmarks from lateral and axial images of the cervical vertebrae, Procrustes analysis and principal component (PC) analysis yielded PC scores of each cervical vertebra, with the centroid size as the size factor. The meaningful PC scores from these were used for multiple regression models. RESULTS: When both axial and lateral cervical vertebrae were used together, there was a 6.7% increase in the Sempé maturation level explanatory power for skeletal maturation estimation in females and an 11.4% increase in males compared with that when only the chronological age was used. CONCLUSIONS: This study improved the estimating regression models using statistical shape analysis with lateral and axial cervical vertebral shapes. The obtained models had improved explanatory power for skeletal maturity estimation than previous studies with healthy people.