Examination of the radiographic visibility of the root pulp of the mandibular second molars as an age marker

Evaluation of radiographic visibility of root pulp in mandibular second molars using cone beam computed tomography images for age estimation

The purpose of this study is to estimate chronological age and determine whether individuals were aged under or over 18 years using root pulp visibility (RPV) in cone-beam computed tomography (CBCT) images. The study included CBCT images of 699 individuals aged between 15 and 75 years. One thousand twenty-three mandibular second molar (2M) teeth were evaluated using Olze's RPV method in four stages. Descriptive statistics of the stages and the relationship between the stages and the chronological age were assessed. The distribution of the stages was analyzed according to the 18-year age threshold. There was a positive correlation between RPV stages and chronological ages in both sexes. For females and males, the mean ages of stage 0, stage 1, and stage 2, for females and males, were found as 27.21, 28.93, and 33.68 years, and 37.69, 40.9, and 44.88 years, respectively. Stage 0 and stage 1 were found both in individuals aged under and over 18 years, and stage 2 and stage 3 were not observed in individuals aged under 18 years. The presence of stage 2 and stage 3 may be an indication that an individual is aged over 18 years according to Olze's RPV age estimation method. For more reliable results, 2M teeth should be examined bilaterally in forensic science.

Automatic Pulp and Teeth Three-Dimensional Modeling of Single and Multi-Rooted Teeth Based on Cone-Beam Computed Tomography Imaging: A Promising Approach With Clinical and Therapeutic Outcomes

Background Cone-beam computed tomography (CBCT) imaging offers high-quality three-dimensional (3D) acquisition with great spatial resolution, given by the use of isometric voxels, when compared with conventional computed tomography (CT). The current literature supports a median reduction of 76% (up to 85% reduction) of patients' radiation exposure when imaged by CBCT versus CT. Clinical applications of CBCT imaging can benefit both medical and dental professions. Because these images are digital, the use of algorithms can facilitate the diagnosis of pathologies and the management of patients. There is pertinence to developing rapid and efficient segmentation of teeth from facial volumes acquired with CBCT. Methodology In this paper, a segmentation algorithm using heuristics based on pulp and teeth anatomy as a pre-personalized model is proposed for both single and multi-rooted teeth. Results A quantitative analysis was performed by comparing the results of the algorithm to a gold standard obtained from manual segmentation using the Dice index, average surface distance (ASD), and Mahalanobis distance (MHD) metrics. Qualitative analysis was also performed between the algorithm and the gold standard of 78 teeth. The Dice index average for all pulp segmentation (n = 78) was 83.82% (SD = 6.54%). ASD for all pulp segmentation (n = 78) was 0.21 mm (SD = 0.34 mm). Pulp segmentation compared with MHD averages was 0.19 mm (SD = 0.21 mm). The results of teeth segmentation metrics were similar to pulp segmentation metrics. For the total teeth (n = 78) included in this study, the Dice index average was 92% (SD = 13.10%), ASD was low at 0.19 mm (SD = 0.15 mm), and MHD was 0.11 mm (SD = 0.09 mm). Despite good quantitative results, the qualitative analysis yielded fair results due to large categories. When compared with existing automatic segmentation methods, our approach enables an effective segmentation for both pulp and teeth. Conclusions Our proposed algorithm for pulp and teeth segmentation yields results that are comparable to those obtained by the state-of-the-art methods in both quantitative and qualitative analysis, thus offering interesting perspectives in many clinical fields of dentistry.

Population-specific age estimation in Black Americans and Chinese people based on pulp chamber volume of first molars from cone beam computed tomography

OBJECTIVES

To validate the fitness of the age estimation model in Black Americans, which was previously and solely established for the Chinese population based on pulp chamber volume of the first molars from cone beam computed tomography (CBCT), and to establish a new age estimation model for Black Americans.

MATERIALS AND METHODS

A total of 203 subjects with CBCT scans, including 119 Chinese and 84 Black Americans, were retrospectively identified. The age range of subjects was between 11 and 87 years. For both populations, automated 3D pulp chamber segmentation of the first molars was performed by deep learning, followed by volume calculation and age estimation by a logarithmic regression model, which was established in a prior study solely on Chinese population. Additionally, a separate logarithmic regression analysis was carried out on Black Americans. The performance of age estimation was assessed by the mean absolute error (MAE), root mean square error (RMSE), Wilcoxon signed rank test, and coefficient of determination (R²) between the actual and estimated human ages.

RESULTS

When applying the age estimation model established in the prior study, MAE = 7.994 years and RMSE = 10.065 years were observed in the Chinese population, while MAE = 14.049 years and RMSE = 17.866 years were observed in Black Americans. The new age estimation model established for Black Americans was AGE = 89.752 - 21.176 × lnV (V = pulp chamber volume), with MAE = 7.930 years, RMSE = 10.664 years, and coefficient of determination (R²) = 0.600.

CONCLUSIONS

Population-specific age estimation is needed when applied in Black Americans and Chinese people based on pulp chamber volume of the first molars from CBCT.

Chronological Age Assessment Based on the Root Pulp Visibility in Lower Third Molars in a Group of Thai Population: Panoramic Radiographic Study

Background:

Radiographic visibility of the root pulp in lower third molars is one of the reliable methodologies for chronological age estimation.

Objective:

To evaluate the radiographic visibility of the lower third molar root pulp using digital panoramic radiographs of the Thai population, and determine the appropriation of this technique in age assessment, especially at the age of 18 years.

Methods:

A total of 746 digital panoramic radiographs of the Thai population aged from 16 to 26 years were recruited for the present study. The visibility of root pulp of lower third molars with completed root formation was recorded in the four stages. Descriptive statistics were performed for each stage in both males and females.

Results:

The first appearance of stage 0 is 16.71 years in males and 17.00 years in females. The minimum age of stage 1 was found at 17.08 years in males and 17.18 years in females. The beginning of stage 2 was 18.33 years in males and 18.17 years in females. For stage 3, the earliest presence was started at 18.58 years in males and 18.83 years in females.

Conclusion:

The occurrence of stages 2 or 3 in both males and females indicated that the subject is over 18 years of age. Further study on the Thai population should be conducted to confirm the results of the present study.

Age estimation based on 3D pulp chamber segmentation of first molars from cone-beam-computed tomography by integrated deep learning and level set

OBJECTIVES

To develop an automatic segmentation method to segment the pulp chamber of first molars from 3D cone-beam-computed tomography (CBCT) images, and to estimate ages by calculated pulp volumes.

MATERIALS AND METHODS

Patients with CBCT scans were retrospectively identified. The age estimation was formulated as CBCT image segmentation using a coarse-to-fine strategy by integrated deep learning (DL) and level set (LS), followed by establishing a linear regression model. On the training data, DL model was trained for coarse segmentation. The validation set was to determine the optimal DL model, and a LS method established on it was to refine the coarse segmentation. On the testing data, the integrated DL and LS method was applied for pulp chamber segmentation, followed by volume calculation and age estimation. Statistical analysis was performed by Wilcoxon rank sum test to demonstrate gender difference in pulp chamber volume, and volume difference between maxillary and mandibular molars. Wilcoxon signed-rank test was adopted to compare true and estimated ages.

RESULTS

A total of 180 CBCT studies were randomly divided into 37/10/133 patients for training, validation, and testing data, respectively. In the training and validation sets, the results showed high spatial overlaps between manual and automatic segmentation (dice = 87.8%). For the testing set, the estimated human ages were not significantly different with true human age (p = 0.57), with a correlation coefficient r = 0.74.

CONCLUSIONS

An integrated DL and LS method was able to segment pulp chamber of first molars from 3D CBCT images, and the derived pulp chamber volumes could effectively estimate the human ages.