OBJECTIVE: The present study was designed to define a novel algorithm capable of predicting female adolescents\' cervical vertebrae maturation stage with high recall and accuracy.
METHODS: A total of 560 female cephalograms were collected, and cephalograms with unclear vertebral shapes and deformed scales were removed. 480 films from female adolescents (mean age: 11.5 years; age range: 6-19 years) were used for the model development phase, and 80 subjects were randomly and stratified allocated to the validation cohort to further assess the model\'s performance. Derived significant predictive parameters from 15 anatomic points and 25 quantitative parameters of the second to fourth cervical vertebrae (C2-C4) to establish the ordinary logistic regression model. Evaluation metrics including precision, recall, and F1 score are employed to assess the efficacy of the models in each identified cervical vertebrae maturation stage (iCS). In cases of confusion and mispredictions, the model underwent modification to improve consistency.
RESULTS: Four significant parameters, including chronological age, the ratio of D3 to AH3 (D3:AH3), anterosuperior angle of C4 (@4), and distance between C3lp and C4up (C3lp-C4up) were administered into the ordinary regression model. The primary predicting model that implements the novel algorithm was built and the performance evaluation with all stages of 93.96% for accuracy, 93.98% for precision, 93.98% for recall, and 93.95% for F1-score were obtained. Despite the hybrid logistic-based model achieving high accuracy, the unsatisfactory performance of stage estimation was noticed for iCS3 in the primary cohort (89.17%) and validation cohort (85.00%). Through bivariate logistic regression analysis, the posterior height of C4 (PH4) was further selected in the iCS3 to establish a corrected model, thus the evaluation metrics were upgraded to 95.83% and 90.00%, respectively.
CONCLUSIONS: An unbiased and objective assessment of the cervical vertebrae maturation (CVM) method can function as a decision-support tool, assisting in the evaluation of the optimal timing for treatment in growing adults. Our novel proposed logistic model yielded individual formulas for each specific CVM stage and attained exceptional performance, indicating the capability to function as a benchmark for maturity evaluation in clinical craniofacial orthopedics for Chinese female adolescents.

OBJECTIVE: To develop new logistic regression estimative models of the cervical vertebral maturation index (CVMI) based on cone-beam CT (CBCT)-derived parameters for intelligent evaluating skeletal maturation.
METHODS: From 231 CBCT volumes (age range 7-17, mean age 11.09 years), 154 were randomly selected to produce 2D sagittal projections of the second to fourth cervical vertebrae (C2-C4). From 19 quantitative parameters, significant predictors were deduced to formulate logistic models. Using the CVMI and significant predictors of 77 other subjects, performance of the models was externally examined by direct comparison and the area under the receiver operating characteristic curve (AUC). Models were modified if required, to improve their accuracy.
RESULTS: Chronological age, C3 height ([Formula: see text], and ratio of posterior height to lower width of C4 [Formula: see text] were entered as significant predictors. Accuracy of the models was acceptable (total AUC = 0.91) except for 4th and 5th stage (AUC of 0.82 and 0.83, respectively), which were mis-predicted inversely. Adjusted models were generated by bivariate logistic regression analysis and adding significant parameters ([Formula: see text] and [Formula: see text], with odds ratios of 3.308 and 3.38, respectively) from 58 subjects in 4th and 5th stages of CVMI in the model establishment group. The total AUC increased to 0.94, along with an increase in the accuracy of the latter optimized models to 77.9 and 87%, respectively.
CONCLUSIONS: The new intelligent models reliably estimated skeletal maturation and can be utilized in the clinical field or machine learning-based skeletal maturation assessment.

UNASSIGNED: The objective of this systematic review was to evaluate the evidence regarding skeletal maturation in patients with cleft lip and/or palate (CL/P) and to investigate whether the skeletal maturation is delayed in these patients.
UNASSIGNED: Systematic review.
UNASSIGNED: Electronic and manual searches of scientific literature were conducted in 4 databases (MEDLINE, Embase, Cochrane Library, and Web of Science). Cohort studies that compared the skeletal maturation of patients with CL/P with that of children without CL/P were eligible for inclusion. The quality of included cohort studies was assessed using the Newcastle-Ottawa Scale.
UNASSIGNED: Patients of any sex and ethnicity with CL/P and children without CL/P were included in this systematic review.
UNASSIGNED: Difference in skeletal maturation between patients with CL/P and patients without CL/P.
UNASSIGNED: Thirteen retrospective cohort studies were included in this systematic review. Ten studies were considered of high quality and 3 were considered of general quality. The results of the included studies comparing skeletal maturation of patients with CL/P and children without CL/P were heterogeneous.
UNASSIGNED: Heterogeneity of skeletal maturation assessment methods, chronological age, sex, cleft type, and race may influence the final results of clinical studies on skeletal maturation in patients with CL/P. Overall, there is limited evidence to determine whether the skeletal maturation level of patients with CL/P is delayed compared to that of normal children. Further studies are needed to determine the skeletal maturation patterns in patients with CL/P.