Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living.
Inês Oliveira-SantosIsabel Poiares BaptistaRicardo Henrique Alves da SilvaEugenia CunhaPublished in: Forensic sciences research (2024)
Age assessment of the living is a fundamental procedure in the process of human identification, in order to guarantee fair treatment of individuals, which has ethical, civil, legal, and medical repercussions. The careful selection of the appropriate methods requires evaluation of several parameters: accuracy, precision of the method, as well as its reproducibility. The approach proposed by Mincer et al . adapted from Demirjian et al . exploring third molar mineralisation, is one of the most frequently considered for age estimation of the living. Thus, this work aims to assess potential bias in the data collection when applying the classification stages for dental mineralisation adapted by Mincer et al . A total of 102 orthopantomographs, of clinical origin, belonging to individuals aged between 12 and 25 years ([Formula: see text] = 20.12 years, SD = 3.49 years; 65 females, 37 males, all of Portuguese nationality) were included and a retrospective analysis performed by five observers with different levels of experience (high, average, and basic). The performance and agreement between five observers were evaluated using Weighted Cohen's Kappa and the Intraclass Correlation Coefficient. To access the influence of impaction on third molar classification, variables were tested using ordinal logistic regression Generalised Linear Model. It was observed that there were variations in the number of teeth identified among the observers, but the agreement levels ranged from moderate to substantial (0.4-0.8). Upon closer examination of the results, it was observed that although there were discernible differences between highly experienced observers and those with less experience, the gap was not as significant as initially hypothesised, and a greater disparity between the classifications of the upper (0.24-0.49) and lower third molars (>0.55) was observed. When bone superimposition is present, the classification process is not significantly influenced; however, variation in teeth angulation affects the assessment. The results suggest that with an efficient preparation, the level of experience as a factor can be overcome. Mincer and colleague's classification system can be replicated with ease and consistency, even though the classification of upper and lower third molars presents distinct challenges.
Keyphrases
- deep learning
- machine learning
- electronic health record
- big data
- endothelial cells
- healthcare
- nuclear factor
- immune response
- artificial intelligence
- magnetic resonance imaging
- minimally invasive
- high intensity
- climate change
- smoking cessation
- human health
- oral health
- contrast enhanced
- combination therapy
- diffusion weighted imaging
- bioinformatics analysis
- cone beam computed tomography
- molecularly imprinted