Publikationen

Mesiodistal width correlation between primary and successor mandibular teeth

2025-12-29T12:16:44Z

Mesiodistal width correlation between primary and successor mandibular teeth Cakir, Aleyna; Both, Annika; Kirschneck, Christian; Daratsianos, Nikolaos; Miranda de Araújo, Cristiano; Corá, Juliane; Calvano Küchler, Erika; Beisel-Memmert, Svenja Grassia, Vincenzo Background: Most studies on permanent tooth width prediction focus on the predictive value of permanent teeth, however only a few studies examine the predictive value of primary teeth. The aim of this study was to investigate the correlation between the mesiodistal widths of the mandibular primary canines and molars and those of their permanent successors. In addition, the study evaluated whether the mesiodistal width of the primary canines and molars can serve as reliable predictors for the width of the permanent mandibular first molars.
Methods: This cross-sectional study analyzed records from 143 orthodontic patients (78 males and 65 females) who had digitized dental models in the mixed and in the permanent dentition stage. Mesiodistal measurements were performed on left-sided mandibular permanent teeth (canines, first and second premolars, first molar), and primary teeth (canines, first and second molars). The Pearson correlation coefficient test was used to determine the correlation strength between the mesiodistal dimensions of primary and permanent teeth (p < 0.05).
Results: Significant correlations were found between second primary molars and second premolars (Pearson r = 0.400–0.461) as well as between primary and permanent canines (Pearson r = 0.462–0.512), across the total sample and within both sexes. The dimensions of all three evaluated primary teeth were correlated with first permanent molar with r ranging from 0.402 to 0.625. The primary first molar showed a weak correlation with the first premolar for the total sample (Pearson r = 0.240) and males (Pearson r = 0.302), and none was observed for female patients (Pearson r = 0.048).
Conclusions: A link between primary and permanent tooth width of canines and posterior dentition was observed, but a difference between sexes exists. Therefore, primary teeth may offer early insight into future space requirements, however their predictive strength is influenced by tooth type and sex.

Evaluating the accuracy of generative artificial intelligence models in dental age estimation based on the Demirjian's method

2025-11-07T07:33:59Z

Evaluating the accuracy of generative artificial intelligence models in dental age estimation based on the Demirjian's method Abuabara, Allan; Vilalba Paniagua Machado do Nascimento, Thais; Trentini, Seandra Maria; Costa Gonçalves, Angela Mairane; Hueb de Menezes, Maria Angélica; Madalena, Isabela Ribeiro; Beisel-Memmert, Svenja; Kirschneck, Christian; Azeredo Alves Antunes, Livia; Miranda de Araujo, Cristiano; Baratto-Filho, Flares; Calvano Küchler, Erika Introduction: Dental age estimation plays a key role in forensic identification, clinical diagnosis, treatment planning, and prognosis in fields such as pediatric dentistry and orthodontics. Large language models (LLM) are increasingly being recognized for their potential applications in Dentistry. This study aimed to compare the performance of currently available generative artificial intelligence LLM technologies in estimating dental age using the Demirjian's scores.
Methods: Panoramic radiographs were analyzed using Demirjian's method (1973), with each left permanent mandibular tooth classified from stage A to H. Untrained LLM, ChatGPT (GPT-4-turbo), Gemini 2.0 Flash, and DeepSeek-V3 were tasked with estimating dental age based on the patient's Demirjian score for each tooth. Due to the probabilistic nature of ChatGPT, Gemini, and DeepSeek, which can produce varying responses to the same question, three responses were collected per case per day (three different computers) from each model on three separate days. The age estimates obtained from LLM were compared to the individuals' chronological ages. Intra- and interexaminer reliability was assessed using the Intraclass Correlation Coefficient (ICC). Model performance was evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Coefficient of Determination (R²), and Bias.
Results: Thirty panoramic radiographs (40% female, 60% male; mean age 10.4 ± 2.32 years) were included. Both intra- and inter-examiner ICC values exceeded 0.85. ChatGPT and DeepSeek exhibited comparable but suboptimal performance, with higher errors (MAE: 1.98–2.05 years; RMSE: 2.33–2.35 years), negative R² values (−0.069 to −0.049), and substantial overestimation biases (1.90–1.91 years), indicating poor model fit and systematic flaws. Gemini demonstrated intermediate results, with a moderate MAE (1.57 years) and RMSE (1.81 years), a positive R² (0.367), and a lower bias (1.32 years).
Discussion: This study demonstrated that, although LLM like ChatGPT, Gemini, and DeepSeek can estimate dental age using Demirjian's scores, their performance remains inferior to the traditional method. Among them, DeepSeek-V3 showed the best results, but all models require task-specific training and validation before clinical application.

Fibroblast growth factor receptor 2 (FGFR2) genetic polymorphisms contribute to fused roots in human molars

2025-10-27T12:31:30Z

Fibroblast growth factor receptor 2 (FGFR2) genetic polymorphisms contribute to fused roots in human molars Santos Meyfarth, Sandra Regina; Baratto-Filho, Flares; Nunis Locks, Maria Eduarda; Proff, Peter; Oliveira Zandoná, Giordano; Oliveira Fernandes, Thaís de; França, Paulo Henrique Condeixa de; Kirschneck, Christian; Antunes, Leonardo Santos; Calvano Küchler, Erika Fibroblast growth factors (FGFRs) signaling are required for human tooth development. Its dysregulation affects tooth formation and patients with FGFR2 mutations often present dental anomalies in the spectrum of the syndrome. This study aimed to investigate whether genetic polymorphisms in FGFR2 are associated with molar fused roots. The null hypothesis is that genetic variations in FGFR2 are not associated with isolated cases (non-syndromic) of molars fused roots. Panoramic radiographs of non-syndromic patients were used to assess the occurrence of fused roots in molars. Genomic DNA analysis was performed to investigate polymorphisms within the candidate gene. The association between fused roots and genetic polymorphisms was analyzed using allelic and genotypic distributions, and haplotype frequencies. Odds ratio and 95% confidence interval were calculated to assess the chance of presenting fused roots. The significance level was set at p < 0.05 for all the analysis. A total of 170 patients were included. Statistically significant differences in genotype distribution were observed in rs10736303 and rs2162540. Individuals carrying at least one G allele of rs10736303 had an increased chance to present fused roots. A total of 154 haplotype combinations demonstrated statistically significant associations. The polymorphisms rs10736303 and rs2162540 in FGFR2 were associated with fused roots in human molars.

Investigating the impact of polymorphisms in the ANKK1 and DRD2 genes on oral health-related quality of life in male patients with temporomandibular disorders

2025-10-21T14:46:40Z

Investigating the impact of polymorphisms in the ANKK1 and DRD2 genes on oral health-related quality of life in male patients with temporomandibular disorders Schaffer Pugsley Baratto, Samantha; Abuabara, Allan; Cardozo Bueno, Débora Cristina; de Paris Matos, Thalita; Paiva Perin, Camila; Correr, Gisele Maria; Penazzo Lepri, César; Kirschneck, Christian; Baratto-Filho, Flares; Calvano Küchler, Erika Introduction: Previous studies have reported that genetic polymorphisms may impact the signs and symptoms of temporomandibular disorder (TMD). Therefore, this study aimed to investigate the association between polymorphisms in the Dopamine Receptor D2 (DRD2) and Ankyrin Repeat and Kinase Domain Containing 1 (ANKK1) genes and oral health-related quality of life of male patients with TMD.
Methods: This cross-sectional study included construction workers with at least one sign or symptom of TMD. The reduced version of the Oral Health Impact Profile questionnaire (OHIP-14) was used to assess oral health-related quality of life. Genomic DNA was used to genotype genetic polymorphisms in the locus 11q22-q23, one in ANKK1 (rs1800497) and two in DRD2 (rs6275 and rs6276), using real-time polymerase chain reaction. The total OHIP-14 score and those for each domain were compared among the genotypes using the Kruskal–Wallis test and Dunn's test in the genotypic co-dominant model. The Mann–Whitney test was used in the recessive model (alpha = 0.05).
Results: The sample included a total of 114 male patients. OHIP-14 total score ranged from 0 to 33. Chronic pain (87.7%), followed by disc displacement (38.2%), was the most common sign and symptom observed. All the genetic polymorphisms assessed were within the Hardy–Weinberg equilibrium. The "Handicap" domain (D6) was statistically associated with the genetic polymorphism rs1800497 in ANKK1 ( p = 0.008). The genetic polymorphism rs1800497 Taq1A in DRD2/ANKK1 was associated with oral health-related quality of life, as measured by the handicap domain in OHIP-14, in male patients with TMD.
Discussion: This study showed that genetic polymorphisms can negatively impact the oral health-related quality of life, as measured by the handicap domain of the OHIP-14. The physical and emotional condition of patients, together with biological pathways, should receive more attention in future studies, and personalized treatment plans should be created to improve patients' quality of life.