Gingival pigmentation: Concurrent assessment of distribution, intensity, and extent in a black population

Explaining the colour of natural healthy gingiva

To examine the differences between natural gingival colour in men and women. To determine the degree of predictability of changes in the gingival colour coordinates recorded for healthy gingiva, according to age, long-term medication, frequency of toothbrushing, and smoking habits. The CIELAB colour coordinates were recorded using a spectrophotometer for 360 Caucasian adult participants (aged 18-92 years), in three zones of the healthy attached gingiva of the maxillary central incisor. Regression models were created for each zone and each sex, taking the L*, a* and b* coordinates as dependent variables and age, frequency of toothbrushing, smoking habits (0-non-smoker; 1-smoker) and whether participants were taking long-term medication (0-no; 1-yes) as independent variables. The statistical analysis was conducted with SPSS version 26.0, using multiple regression models. Statistically significant differences between men and women were found only for colour coordinate b*, in all three zones. The only colour coordinate on which the predictor variables had a significant effect was the L* coordinate. In men, age and long-term medication had the greatest effect as predictors (maximum R2 = 0.149). In women, frequency of toothbrushing was the strongest predictor in the predictive models (maximum R2 = 0.099). The colour of gingiva in men contained a larger amount of blue, given that significantly lower values for colour coordinate b* were recorded in men than women, although this difference lacked clinical implications. For both sexes, the regression models produced had a modest predictive capacity. The L* coordinate was the dependent variable that showed the greatest predictability.

Evaluation of Gingival Pigmentation and Related Factors on Former Smokers

Objectives

Gingival pigmentation, the most common etiological factor of which is smoking, is a clinical condition that causes aesthetic complaints. Due to the dose-dependent effect of smoking, gingival pigmentation may present regression following cessation. This cross-sectional study aimed to evaluate gingival pigmentation in former tobacco consumers and compare with current ones.

Material and Methods

A total of 110 people, 70 of whom were current smokers (Group CS) and 40 of whom were former smokers (Group FS), were included in the study. Participants filled out the data collection forms containing questions on demographic features and information related to tobacco consumption. In addition, all individuals were examined with Hedin's melanin index (HMI) to evaluate gingival pigmentation. Statistical significance was set at the P < 0.05 level.

Results

The population consisted of 57.3% male, and the mean age of all participants was 39.43 (SD 12.3) years. The mean duration of tobacco consumption did not differ between groups, whereas the mean HMI score of Group FS was significantly lower (P = 0.001). The correlation analyses showed that while the HMI score of Group CS was in relation to both daily consumption amount and duration of consumption (for both, P < 0.01), the HMI score of Group FS showed a negative association with only time elapsed after cessation (P = 0.000).

Conclusions

Considering the limitations of this study, the outcomes revealed a dose- and a time-dependent relation of gingival pigmentation in smokers. However, gingival pigmentation in former tobacco consumers was negatively correlated only with time elapsed after cessation.

Comparison between clinical and computerized methods for assessing gingival pigmentation

Background and Objective

Digital computerized assessment can provide objective values for the measurement of gingival pigmentation. This study aims to compare the Commission Internationale de l'Eclairage Lab color space (CIELAB) values and the computerized intensity values (CIVs) from digital imaging with clinical evaluations using the Dummett-Gupta Oral Pigmentation Index (DOPI) for assessing gingival pigmentation in a multi-ethnic population.

Methodology

Digital photographs of 188 participants were taken using standardized parameters. The buccal gingival pigmentation was evaluated using three methods (a) a clinical evaluation by two independent assessors using the DOPI, (b) the CIELAB values using the Adobe Photoshop® software (Version 23.1.1) and (c) the CIV calculated using the ImageJ software (Version 1.53k). A hierarchical clustering analysis was used to identify colour groups that clustered together. Agreement between the clinical and digital categorization of the pigmentation was carried out using weighted kappa analysis. Agreements between CIELAB and CIV were compared using intra-class correlation coefficient.

Results

There was a statistically significant difference in the DOPI, the L*, a*, and b* coordinates, and the CIV between the different ethnic groups of the participants. Cluster analysis for the CIELAB and CIV both identified four clusters. The gingival pigmentation categorization using the L*, a*, and b* values moderately agreed with the clinical evaluation using the DOPI index while the categorization with the CIV was in slight agreement with the clinical evaluations.

Conclusion

This study identified four clusters of gingival pigmentation in 188 multi-ethnic participants. The clusters, determined by CIELAB values, align with the clinical assessment of gingival pigmentation. Digital measurements derived from clinical photographs can serve as an effective means of pigmentation measurement in dental clinics.

Fifteen ceramic gingival samples: A proposed gingival shade guide

OBJECTIVE

(1) To put forward a set of valid pink ceramic samples for subjective gingival colour selection in the Caucasian population, and (2) to assess the quality of the shade matches provided by the selected pink samples.

METHODS

The ceramic gingival shade samples (n = 133) were obtained by mixing pairs of basic colours from a single system. In each mixture, the proportions of the colours were altered in 10% increments, following the numerical order used by the manufacturers of the three colour systems under study (Heraceram, Vita VM9 and IPS Style). The CIELAB colour coordinates were recorded using spectrophotometry in three zones of healthy anterior gingiva (n = 360). The sample was randomly divided into two subsamples, each of which contained 180 participants. Subsample 1 was used to select the ceramic gingival samples that provided the best shade matches, using the k-means clustering method. Subsample 2 was used to assess the chromatic validity of the selected gingival samples, according to the coverage error.

RESULTS

To identify the ceramic gingival samples that best represented participants' gingival colour, the minimum colour differences (ΔEab∗, ΔE00) between the cluster centroids and the 133 gingival samples were calculated. Fifteen gingival samples were selected: 8 from the Heraceram system, 4 from the VM9 system, and 3 from the IPS Style system. Coverage errors for the 15 gingival samples fell below the gingival clinical acceptability thresholds in the three gingival zones examined.

CONCLUSIONS

The 15 ceramic gingival colour samples provide satisfactory coverage of the gingival colour space, with coverage errors below the ΔE00 clinical acceptability threshold of 2.9 units. These pink colour samples have the potential to provide good gingival shade matches in subjective colour selection.

CLINICAL SIGNIFICANCE

Mixing basic ceramic colours is a viable method for generating a series of pink shades that can be used as a physical gingival shade guide. The resulting guide provides valid results (under the acceptability thresholds) for subjective selection gingival colour selection in clinical practice.

Assessment of gingival thickness in multi-ethnic subjects with different gingival pigmentation levels

AIM

Assessment of the thickness of gingival tissues using the probe visibility test is regarded as the method of choice during routine examinations. However, the probe visibility test has not been validated for patients with gingival pigmentation and its accuracy in populations with physiological gingival pigmentation is yet unknown. This study aims to evaluate different methods for the clinical assessment of gingival thickness in participants with varying levels of gingival pigmentation.

MATERIALS AND METHODS

Buccal mucosa of the maxillary right central incisor teeth of 171 participants was evaluated using four methods, which were direct measurements using calliper, transgingival probing method using an endodontic probe, and probe visibility method using Colorvue biotype probe (CBP) and UNC-15 probe. The pigmentation of the gingiva was assessed using the Dummett-Gupta oral pigmentation lesion index.

RESULTS

The average gingival thickness of the selected population was 1.22 ± 0.38 mm with a distribution of 70% thick and 30% thin gingiva. Transgingival and calliper methods showed good agreement and significant correlation (r = 0.229; p = .003). Visual assessment using CBP and UNC-15 probe showed poor agreement with the direct measurement methods. Gingival pigmentation significantly affected the probe visibility assessment, reducing the visibility of both the CBP (odds ratio [OR] = 4.00; 95% confidence interval [CI], 1.83-8.74) and UNC-15 probe (OR = 1.84; 95% CI, 1.05-3.23) while controlling for thickness of the gingiva.

CONCLUSION

The probe visibility method using either CBP or the UNC-15 probe is affected by the degree of gingival pigmentation. Direct measurements using either a calliper or transgingival probing are recommended as methods to measure the gingival thickness in populations with gingival pigmentation.