ArticleThe Journal of forensic odonto-stomatology2020
Volume analysis of second molar pulp chamber using cone beam computed tomography for age estimation in Egyptian adults.
Article in The Journal of forensic odonto-stomatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic overview of dental methods for age assessment in living individuals: from traditional to artificial intelligence-based approaches.International journal of legal medicine · 2023Pooled it
- CBCT in dental age estimation: A systematic review and meta analysis.Dento maxillo facial radiology · 2022Pooled it
- Volumetric Pulp Analysis of Mandibular Molars on CBCT as a Supplementary Indicator for Age-Related Dental Changes: A Preliminary Investigation in a Turkish Population Sample.Diagnostics (Basel, Switzerland) · 2026Article
- Silent Witnesses: Exploring the Impact of Cone Beam Computed Tomography on Forensic Investigations.Cureus · 2025Review
- Comparative analysis of estimated age by pulp-to-tooth area ratio using CBCT in three different teeth on a subset of Hyderabad population: A preliminary study.The Journal of forensic odonto-stomatology · 2024Article
- Article
- Machine learning assisted 5-part tooth segmentation method for CBCT-based dental age estimation in adults.The Journal of forensic odonto-stomatology · 2024Article
- The Study and Relevance of Pulp Chamber Anatomy in Endodontics - A Comprehensive Review.European endodontic journal · 2024Review
- Age estimation based on 3D pulp segmentation of first molars from CBCT images using U-Net.Dento maxillo facial radiology · 2023Article
- Dental age estimation in Indonesian adults: An investigation of the maxillary canine pulp-to-tooth volume ratio using cone-beam computed tomography.Imaging science in dentistry · 2023Article
- Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars.International journal of legal medicine · 2023Article
- Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes.International journal of legal medicine · 2023Article
- Age Estimation Using Maxillary Central Incisor Analysis on Cone Beam Computed Tomography Human Images.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThe present work aimed to evaluate age-related variations in the dental pulp chamber volume of second molars using cone beam computed tomography (CBCT) imaging, in order to establish a specific mathematical model for second molars and measure its accuracy, especially in the case of Egyptian adults. SUBJECTS AND
methodsFrom 187 subjects between 21-50 years of age, CBCT images of 257 maxillary and 248 mandibular second molars were included. A mathematical model for human age estimation was established. An independent additional set of CBCT images was obtained to test the model's accuracy.
resultsFor maxillary and mandibular teeth, R2 for the pooled sexes were 0.51 and 0.52, and SEE were 5.92 and 5.71, respectively. A model for each sex was established, due to the significant difference between them, where R2 was equal to 0.668 and 0.650 in males and 0.46 and 0.48 in females, concerning maxillary and mandibular teeth, respectively. When testing the validation samples, the mean absolute error (MAE) between the actual and estimated ages from the pooled sex model were 4.89 and 4.61 for maxillary and mandibular teeth, respectively.
conclusionThe pulp chamber volume of second molars is a relatively accurate indicator for age estimation in Egyptian adults.
Indexed as
Identifiers
33507164PMC8565657What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.