Palmer notation

Abstract: Background: Universal system, Palmer notation and FDI system are used to record dental problems which give different numbers to same tooth. For example, central incisor is #8 (Universal system) and #11 (FDI system).Thus they create confusion in transferring dental information. A new tooth notation uses letters I- incisor, C-canine, P-premolar, M-molar (MICAP) and digits 1, 2, 3. The digits are printed as superscript and subscript on the relevant letters (I, C, P, M) to indicate the maxillary and mandibular teeth. Aim: to assess the learning of format of MICAP system by students of undergraduate dental degree and dental allied health programmes using a mock MICAP dental chart. Materials and Methods: A mock MICAP dental chart was prepared. Students of undergraduate dental degree [group A (n=39)] and dental allied health programme [group B (n=39)] who were further subdivided base on age such as [group 1=15-25 yrs, group 2=26-35 yrs, group 3=36-45 yrs], translated four MICAP symbols and vice versa in a cross sectional study after an hour lecture and video demonstration about the MICAP format. One way ANOVA and independent t test were performed to analyse the data. Results: Group A was better in translation of #1C (maxillary right canine) than group B [mean difference 95% CI: -0.128 (-0.285, 0.028) p=0.001]. In terms of age, group 1 was better in translation of MICAP format (p 50% agreed that MICAP notation system was easy to understand. Conclusion: Format of new notation is easy to learn. Teeth can be identified by new method. However, additional data is required before the reliability of the system is suggested as alternate dental charting system.

Abstract: Dental healthcare providers need to examine a large number of panoramic X-ray images every day. It is quite time consuming, tedious, and error-prone job. The examination quality is also directly related to the experience and the personal factors, i.e., stress, fatigue, etc., of the dental care providers. To assist them handling this problem, a residual network-based deep learning technique, i.e., faster R-CNN technique, is proposed in this study. Two kinds of residual networks, i.e., ResNet-50 and ResNet-101, are used as the base network of faster R-CNN separately. A modified version of Palmer notation (PN) system is proposed in this research for numbering the teeth. The modified Palmer notation (MPN) system does not use any notation like PN system. The MPN system is proposed for mainly three reasons: (i) teeth are divided into total eight categories, and to keep this similarity, a new numbering system is proposed that has the same number of category, (ii) 8-category MPN system is less complex to implement than 32-category universal tooth numbering (UTN) system, and with some preprocessing steps, MPN system can be converted into 32-category UTN system, and finally (iii) for the convenience of the dentist, i.e., it is more feasible to utilize 8-category MPN system than 32-category UTN system. Total 900 dental X-ray images were used as training data, while 100 images were used as test data. The method achieved 0.963 and 0.965 mean average precision (mAP) for ResNet-50 and ResNet-101, respectively. The obtained results demonstrate the effectiveness of the proposed method and satisfy the condition of clinical implementation. Therefore, the method can be considered as a useful and reliable tool to assist the dental care providers in dentistry.

Abstract: A teenager began an orthodontic treatment. During his orthodontic treatment, the orthodontist refferd the teenager to an Oral and maxillofacial surgeon to extract tooth no. 25. The orthodontist used the Palmer notation method to mark the tooth - 5 - and the Oral and maxillofacial surgeon read it as the no. 15, which is a completely different tooth according to the FDI World Dental Federation notation system. As a result, the Oral and maxillofacial surgeon extracted a healthy tooth by mistake. The teenager submitted a claim in tort for the harm he had suffered as a result of the mistake.