The Fourth Cervical Vertebra Anterior and Posterior Body Height Projections (Vba) for the Assessment of Pubertal Growth Spurt

Cameriere, Roberto; Palacio, Luz Andrea Velandia; Nakaš, Enita; Galić, Ivan; Brkić, Hrvoje; Govorko, Danijela Kalibović; Jerković, Daniel; Jara, Liliana; Ferrante, Luigi

doi:10.3390/app13031819

Cited by 3 publications

(2 citation statements)

References 56 publications

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“…In science, further methods are being investigated that show promising results for certain age groups, such as age diagnosis using the fourth vertebra in a study by Gulsahi et al They investigated the correlation between age and the fourth cervical vertebra in a Turkish population group including children and young adults and could demonstrate the suitability of this method [ 22 ]. Another study by Cameriere et al also investigated the relationship between age and the fourth vertebra and developed a statistical model based on the ratio of anterior to posterior vertebral height [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Forensic Age Estimation: A Multifactorial Approach in a Retrospective Population Study

Bjelopavlovic,

Reder,

Fritzen

et al. 2023

Diagnostics

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Objectives: The objective of this study was to evaluate the accuracy of forensic age estimation in a German population by combining clavicle and wisdom teeth assessments based on cone beam computed tomography (CT) data. The study aimed to determine the reliability of this approach in predicting biological age. Material and Methods: A total of 161 CT data sets from 120 males and 41 females with known exact ages were evaluated by three raters. The clavicle was assessed according to stages 1–5 (including substages 2a–c and 3a–c), and the Demirjian stage’s classification method was used for the wisdom teeth. Inter-class correlation (ICC) was calculated to assess the agreement among the three raters. Additionally, ordinary least square regressions were performed to predict chronological age using the clavicle or one of the four teeth. Finally, age prediction models using multiple indicators were developed. Results: The ICCs ranged from 0.82 for the clavicle to 0.86 and 0.88 for the wisdom teeth. Linear estimation tended to overestimate chronological age, especially in subjects over 18 years old. The clavicle showed the strongest overestimation. Combining age estimation from the clavicle with the upper and lower wisdom teeth improved the predictive power, resulting in a 14% and 15% increase in R² for the upper and lower wisdom teeth, respectively. Adding more than one tooth to the prediction did not improve the predictive power (all ΔR² < 1%). Conclusions: Age estimation using CT can be significantly improved by combining information from the analysis of wisdom teeth with age estimation based on the clavicle.

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Section: Introductionmentioning

confidence: 99%

Forensic Age Estimation: A Multifactorial Approach in a Retrospective Population Study

Bjelopavlovic,

Reder,

Fritzen

et al. 2023

Diagnostics

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“…The validation process results showed that the proposed model did not produce any incorrect forecasts. Therefore, this proposed method could estimate the beginning and end of the pubertal growth spurt, together with the residual proportion of skeletal maturation for a given Vba [11].…”

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confidence: 99%

Special Issue on Dental Materials: Latest Advances and Prospects—Volume II

Checchi

2023

Applied Sciences

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Accuracy of Artificial Intelligence for Cervical Vertebral Maturation Assessment—A Systematic Review

Kazimierczak,

Jedliński,

Issa

et al. 2024

JCM

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Background/Objectives: To systematically review and summarize the existing scientific evidence on the diagnostic performance of artificial intelligence (AI) in assessing cervical vertebral maturation (CVM). This review aimed to evaluate the accuracy and reliability of AI algorithms in comparison to those of experienced clinicians. Methods: Comprehensive searches were conducted across multiple databases, including PubMed, Scopus, Web of Science, and Embase, using a combination of Boolean operators and MeSH terms. The inclusion criteria were cross-sectional studies with neural network research, reporting diagnostic accuracy, and involving human subjects. Data extraction and quality assessment were performed independently by two reviewers, with a third reviewer resolving any disagreements. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool was used for bias assessment. Results: Eighteen studies met the inclusion criteria, predominantly employing supervised learning techniques, especially convolutional neural networks (CNNs). The diagnostic accuracy of AI models for CVM assessment varied widely, ranging from 57% to 95%. The factors influencing accuracy included the type of AI model, training data, and study methods. Geographic concentration and variability in the experience of radiograph readers also impacted the results. Conclusions: AI has considerable potential for enhancing the accuracy and reliability of CVM assessments in orthodontics. However, the variability in AI performance and the limited number of high-quality studies suggest the need for further research.

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The Fourth Cervical Vertebra Anterior and Posterior Body Height Projections (Vba) for the Assessment of Pubertal Growth Spurt

Cited by 3 publications

References 56 publications

Forensic Age Estimation: A Multifactorial Approach in a Retrospective Population Study

Forensic Age Estimation: A Multifactorial Approach in a Retrospective Population Study

Special Issue on Dental Materials: Latest Advances and Prospects—Volume II

Accuracy of Artificial Intelligence for Cervical Vertebral Maturation Assessment—A Systematic Review

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