Reliability of age estimation using periodontal ligament visibility in South Indian Population

Ray, Ayan Bhadra; Rastogi, Kushaggr; Srikant, NS; Yellapurkar, Shweta; Jose, Nidhin Philip; Denny, Ceena

doi:10.5958/0974-083x.2021.00033.9

Cited by 3 publications

(2 citation statements)

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“…Moreover, future comparative studies need to clarify whether the Guo method is superior in targeted cohorts and whether the correlation with age is better in these cohorts. A first validation study in a South Indian population from 2021 by Ray et al reports correlations of 0.455 to 0.555 for the Guo method [ 58 ]. Overall, the use of the Guo method can be considered a viable alternative in cases where the inter-radicular periodontal ligament is not evaluable, such as it is the case with fused roots which preclude the use of the Olze or Lucas method.…”

Section: Discussionmentioning

confidence: 99%

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Radiological assessment of periodontal ligament space visibility on third molars for forensic age assessment — a comparison study of three different staging scales

Timme,

Steffens,

Viktorov

et al. 2024

Int J Legal Med

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Various staging scales have been proposed for the assessment of the visibility of the periodontal ligament space of mandibular third molars on dental panoramic radiographs (PANs) for forensic age assessment in living individuals. However, up to now, there has been no systematic comparison between these staging scales available. We directly compared the 2010 staging scale proposed by Olze et al. with the 2017 staging by Lucas et al. and the 2020 staging by Guo et al. in a German study population. We evaluated 233 PANs from 115 females and 118 males aged 20.0 to 40.9 years using three independent examiners, with one examiner conducting two assessments. We examined the correlation between age and stage, as well as the inter- and intra-rater reliabilities. While the point estimates for the correlation coefficient and the reliability measures were lowest for the Guo scale and highest for the Olze scale, confidence intervals showed a large overlap, particularly for the scales of Olze et al. and Lucas et al. The correlation coefficients between stage and age were consistently lower in females than in males across all methods. In summary, we showed that the staging scales of Olze et al. and Lucas et al. were very similar. The Olze method showed higher point estimates across all analyses, and because there are more reference data available for this method, we argue that it should be preferred as the method of choice for further studies in the field. However, Guo method could be considered for instances, in which the inter-radicular periodontal ligament is not evaluable.

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Section: Discussionmentioning

confidence: 99%

“…Previous studies using the Olze method have examined far in excess of two thousand individuals in various populations [ 28 , 36 – 39 , 53 , 54 ]. In contrast, the methods presented by Lucas et al and Guo et al are supported in particular by the studies of their first description [ 48 , 49 ] or in single smaller studies [ 58 ].…”

Section: Discussionmentioning

confidence: 99%

Radiological assessment of periodontal ligament space visibility on third molars for forensic age assessment — a comparison study of three different staging scales

Timme,

Steffens,

Viktorov

et al. 2024

Int J Legal Med

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The relevance of taurodontism in forensic dental age estimation

Timme,

Smit,

Robinson

et al. 2024

Legal Medicine

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Predicting chronological age of 14 or 18 in adolescents: integrating dental assessments with machine learning

Shen,

Guo,

Han

et al. 2024

BMC Pediatr

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Aim Age estimation plays a critical role in personal identification, especially when determining compliance with the age of consent for adolescents. The age of consent refers to the minimum age at which an individual is legally considered capable of providing informed consent for sexual activities. The purpose of this study is to determine whether adolescents meet the age of 14 or 18 by using dental development combined with machine learning. Methods This study combines dental assessment and machine learning techniques to predict whether adolescents have reached the consent age of 14 or 18. Factors such as the staging of the third molar, the third molar index, and the visibility of the periodontal ligament of the second molar are evaluated. Results Differences in performance metrics indicate that the posterior probabilities achieved by machine learning exceed 93% for the age of 14 and slightly lower for the age of 18. Conclusion This study provides valuable insights for forensic identification for adolescents in personal identification, emphasizing the potential to improve the accuracy of age determination within this population by combining traditional methods with machine learning. It underscores the importance of protecting and respecting the dignity of all individuals involved.

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Reliability of age estimation using periodontal ligament visibility in South Indian Population

Cited by 3 publications

References 0 publications

Radiological assessment of periodontal ligament space visibility on third molars for forensic age assessment — a comparison study of three different staging scales

Radiological assessment of periodontal ligament space visibility on third molars for forensic age assessment — a comparison study of three different staging scales

The relevance of taurodontism in forensic dental age estimation

Predicting chronological age of 14 or 18 in adolescents: integrating dental assessments with machine learning

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