For optimal orthodontic treatment, a comprehensive assessment of a patient’s growth and maturation status is essential [17]. However, frequent dental radiography for maturation assessment should be avoided, as clinicians must adhere to the ALADA (As Low As Diagnostically Achievable) principle, which emphasizes minimal radiation exposure [18]. If panoramic radiographs, routinely taken for assessing dental anomalies and development, can provide insights into bone maturity status, they can significantly assist clinicians in obtaining diagnostic information with minimal radiation exposure. Previous studies primarily determined the relationship between dental and skeletal maturity by identifying the specific tooth and developmental stage exhibiting the highest correlation with skeletal maturation for boys and girls respectively [2, 11, 14, 15]. However, the wide variation of age in the developmental stage of individual teeth presents limitations in predicting a child’s skeletal maturation through this statistical correlation in clinical practice.

The purpose of this study was to investigate clinical differences in the relationship between dental maturity and bone maturity by comparing the ages corresponding to skeletal maturity stages in children with advanced and delayed dental maturity. Research on whether differences in dental maturation occur when skeletal maturity varies has been conducted in studies on children with precocious puberty, which reported early maturation of teeth in the precocious puberty group [19, 20]. However, studies on whether differences in dental maturation are associated with variations in skeletal maturity have been limited. There have been studies confirming advanced dental maturity in cases of systemic diseases such as juvenile rheumatoid arthritis [21], but it is difficult to determine whether dental maturity is accelerated in healthy children. To determine whether an individual’s dental maturation is advanced or delayed for their age, the use of dental maturity percentiles is necessary [22]. Since dental maturity varies by race, ethnicity, and over time, it is important to employ percentiles specific to the population at that given time for accurate classification [8, 10, 16]. Furthermore, differences between dental age and chronological age do not necessarily indicate differences in maturity. The estimated dental age, when converted from dental maturity, tends to over/underestimate chronological age, and its accuracy varies between populations and maturity estimation methods [23, 24]. Therefore, since there was no dental maturity percentile curve available for Korean children, this study developed a dental maturity percentile graph and table for Korean children using Demirjian’s method (Fig. 1 and Supplementary Table 1). The participants were then classified as having advanced or delayed dental maturity based on the 50th percentile (Fig. 2).

Distribution of the samples in the advanced and delayed dental maturity groups. (A) Boys, (B) Girls

Demirjian’s original method, which evaluates seven left mandibular teeth for assessing dental maturity, is widely recognized and accepted in forensic science due to its universally applicable maturity scoring system, simplicity, reliable standardization, and excellent reproducibility [7]. Both the tooth calcification stages described by Demirjian and the cervical vertebral maturation method by Baccetti are easy to measure, with substantial intra- and interexaminer reliability [7, 23, 25]. The study utilized dental panoramic radiographs of children who visited Seoul National University Dental Hospital in Korea. Given the ethnically homogeneous nature of the Korean population, the dental maturity scores calculated from this database are likely to represent those of Korean children in general. Quantile regression was employed to establish the standard percentile curve for dental maturity in Korean children. Scores corresponding to the 5th, 16th, 50th, 84th, and 95th percentiles from ages 4 to 16 years are presented in Supplementary Table 1. Scores near the 5th percentile indicate delayed dental maturity, while those near the 95th percentile indicate advanced dental maturation. Completion of dental development (maturity score 100) was faster in girls (14.75 years for girls and 15.25 years for boys), consistent with other studies showing that girls exhibit faster dental development than boys [8, 16].

In the present study, the advanced dental maturity group exhibited earlier skeletal maturation than the delayed group in both boys and girls (Table 3). A significant difference was observed in the CS 1 stage for boys and the CS 4 stage for girls. In the remaining cervical stages, no significant differences were observed. However, except for the CS 5 stage in boys and the CS 2 stage in girls, all the cervical stages showed earlier maturation in the advanced group. The earlier maturation of the CS 3 and CS 4 stages observed in the advanced group in both boys and girls, as well as the significant difference in the CS 4 stage in girls, suggests that the relationship between dental and skeletal maturity may have clinical applicability in detecting a pubertal peak in mandibular growth, which is crucial for orthodontic diagnosis and treatment. The CS 3 and CS 4 stages are known as the circumpubertal stage, in which the peak mandibular growth will occur during the year after the CS 3 stage, and the peak in mandibular growth will occur within 1 or 2 years before the CS 4 stage [3, 25]. The overall correlation of the dental maturity score and cervical vertebral maturation stages is shown in Table 4. In both boys and girls, both the advanced group and the delayed group exhibited a significant correlation between dental maturity and skeletal maturity. If the relationship between dental and skeletal maturity becomes more apparent through further studies, dental maturity could be used to complement chronological age in determining the timing of radiography for skeletal maturity assessment. This approach could enable patients to receive optimal orthodontic diagnosis and treatment at the right time while minimizing radiation exposure. The results of this study also emphasize the importance of establishing percentile curves for specific populations, as they can serve as valuable tools for clinicians to assess an individual’s dental maturity relative to their age group in the population and may also find utility in skeletal maturation assessments.

The limitations of this study include the relatively small number of cephalometric samples compared to the entire panoramic sample, as cephalometric radiographs were only taken for orthodontic analysis, and not routinely. Additionally, our study used Demirjian’s method and the CVM method for the evaluation of dental and skeletal maturity. However, since there are various other evaluation methods available, further research is needed to identify the most representative evaluation method that exhibits the strongest correlation with dental and skeletal maturity. Despite these limitations, the results of the study confirmed that the correlation between dental maturity and skeletal maturity could be observed in clinical practice with the help of dental maturity percentiles, and the differences in dental maturity appeared to provide valuable insights into skeletal maturity. Dental maturity may offer a deeper understanding of an individual’s growth and development, extending beyond the assessment of tooth development stages. Therefore, it is imperative for clinicians and forensic odontologists to pay more attention to dental maturity, and further research on growth and development related to dental maturity, with larger sample sizes, will be necessary.