Influence of residential characteristics on the association between the oral health status and BMI of older adults in Indonesia

Comparison of Multi-Label U-Net and Mask R-CNN for panoramic radiograph segmentation to detect periodontitis

Purpose

Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches.

Materials and Methods

Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models.

Results

The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics (i.e., dice coefficient and intersection-over-union [IoU] score). Multi-Label U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively.

Conclusion

Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.

Awareness and Attitudes of Dental Students toward Older Adults in Indonesia

In this study, we aimed to analyse the awareness and attitudes of dental students (DS) toward older adults (OAs) in Indonesia. Compromised oral health (OH) among OAs is a significant public health problem that is a global health burden. Furthermore, appropriate education can provide DS with information about strategic and efficient treatments for OAs. An online invitation was provided to every dental student in Indonesia in the third to sixth year of study to answer a web-based questionnaire as a part of a survey on awareness and attitudes (14 questions) towards OAs. From 1288 valid forms submitted, it was evident that most students (87%) expressed a positive attitude toward OAs. Female students showed a more positive attitude compared to males, with an odds ratio of 1.539 (p = 0.036), and students who had a connection to an older adult demonstrated a more positive attitude than those who did not (OR = 2.076; p < 0.001). The majority of the DS (98%) were conscious of the importance of geriatrics in dentistry, with female students showing more awareness than their male counterparts (OR = 2.553; p = 0.033). Positive awareness and attitudes must be accompanied by knowledge so that DS can offer appropriate and effective oral care to geriatric patients.

Self-perceived oral health among institutionalized older adults in Taubate, Brazil

PURPOSE/AIM

To assess self-perception of oral health among institutionalized older adults in Taubate, Brazil.

METHOD AND MATERIALS

Demographics, oral, and systemic health data were collected from a sample of 89 institutionalized older adults. The Geriatric Oral Health Assessment Index (GOHAI) was applied to assess their self-perception of oral health. A linear regression model using GOHAI scores and considering age, BMI, gender, race, dry mouth, denture status, number of teeth, number of comorbid conditions, and number of medications as independent variables was generated.

RESULTS

Fifty-five percent were male, with an average age of 75.9 years (±9.1), 43.8% identified as mixed race, and 42.7% as white. The average BMI was 23.9 (±3.8), the average number of comorbid condition was 1.8 (±1.4), and the average number of daily medications was 6.2 (±3.6). The average number of teeth was 3.9 (±7.4), and 57.3% of the participants reported dry mouth sensation; 8.9% presented oral lesions, with denture stomatitis as the most common oral lesion (5.6%). The average GOHAI score was 31.1 (±3.7). Regression analysis showed a negative correlation between BMI and GOHAI scores (P = .032, R²  = 7.2%).

CONCLUSIONS

Self-perception of oral health was good and negatively correlated with BMI.

Hand motor functions on the presence of red fluorescent dental biofilm in older community-dwelling Koreans

BACKGROUND

The Quantitative Light-induced Fluorescence-Digital (QLF-D) system visualizes old and mature dental biofilm as red fluorescence. Risk factors for poor oral hygiene have been identified, however, few studies have evaluated the relationship between mature dental biofilm and hand motor functions. This study aimed to investigate the effects of two important manual motor functions for object manipulation -handgrip strength and manual dexterity- on the presence of red fluorescent dental biofilm in older community-dwelling Koreans using QLF-D, an optical device that reveals dental biofilm.

METHODS

This cross-sectional study included 70 Korean participants aged ≥65 years, all of whom completed questionnaires and were tested for handgrip strength and manual dexterity. In total, 840 dental surfaces were photographed using QLF-D, and ΔR₂₀ values, which reflect mature dental biofilm accumulation, were calculated. The t-test was performed to analyze the differences in the ∆R₂₀ values according to sociodemographic characteristics, health-related characteristics and hand motor functions, while multiple linear regression analysis was used to investigate the effects of hand motor functions on the ∆R₂₀ values.

RESULTS

Multivariate regression analysis revealed that handgrip strength (β = -0.294) was the factor most strongly affecting mature dental biofilm accumulation (ΔR₂₀), followed by tooth-brushing time (β = -0.262) and manual dexterity (β = -0.241).

CONCLUSIONS

Reductions in handgrip strength and manual dexterity were independent risk factors for pathogenic dental biofilm accumulation. The results of this investigation suggest that programs designed to prevent the decline, as well as improve, handgrip strength and manual dexterity might improve the oral hygiene of older adults.