Evaluation of secondary dentin formation for forensic age assessment by means of semi-automatic segmented ultrahigh field 9.4 T UTE MRI datasets

Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars

PURPOSE

To investigate prediction of age older than 18 years in sub-adults using tooth tissue volumes from MRI segmentation of the entire 1st and 2nd molars, and to establish a model for combining information from two different molars.

MATERIALS AND METHODS

We acquired T2 weighted MRIs of 99 volunteers with a 1.5-T scanner. Segmentation was performed using SliceOmatic (Tomovision©). Linear regression was used to analyse the association between mathematical transformation outcomes of tissue volumes, age, and sex. Performance of different outcomes and tooth combinations were assessed based on the p-value of the age variable, common, or separate for each sex, depending on the selected model. The predictive probability of being older than 18 years was obtained by a Bayesian approach using information from the 1st and 2nd molars both separately and combined.

RESULTS

1st molars from 87 participants, and 2nd molars from 93 participants were included. The age range was 14-24 years with a median age of 18 years. The transformation outcome (high signal soft tissue + low signal soft tissue)/total had the strongest statistical association with age for the lower right 1st (p= 7.1*10-4 for males) and 2nd molar (p=9.44×10-7 for males and p=7.4×10-10 for females). Combining the lower right 1st and 2nd molar in males did not increase the prediction performance compared to using the best tooth alone.

CONCLUSION

MRI segmentation of the lower right 1st and 2nd molar might prove useful in the prediction of age older than 18 years in sub-adults. We provided a statistical framework to combine the information from two molars.

Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes

PURPOSE

Our aim was to investigate tissue volumes measured by MRI segmentation of the entire 3rd molar for prediction of a sub-adult being older than 18 years.

MATERIAL AND METHOD

We used a 1.5-T MR scanner with a customized high-resolution single T2 sequence acquisition with 0.37 mm iso-voxels. Two dental cotton rolls drawn with water stabilized the bite and delineated teeth from oral air. Segmentation of the different tooth tissue volumes was performed using SliceOmatic (Tomovision^©). Linear regression was used to analyze the association between mathematical transformation outcomes of the tissue volumes, age, and sex. Performance of different transformation outcomes and tooth combinations were assessed based on the p value of the age variable, combined or separated for each sex depending on the selected model. The predictive probability of being older than 18 years was obtained by a Bayesian approach.

RESULTS

We included 67 volunteers (F/M: 45/22), range 14-24 years, median age 18 years. The transformation outcome (pulp + predentine)/total volume for upper 3rd molars had the strongest association with age (p = 3.4 × 10^-9).

CONCLUSION

MRI segmentation of tooth tissue volumes might prove useful in the prediction of age older than 18 years in sub-adults.

Three-dimensional verification of the radiographic visibility of the root pulp used for forensic age estimation in mandibular third molars

OBJECTIVES

The aim of this study was to assess the reliability of panoramic radiography (OPG) using age estimation method using cone beam computed tomography (CBCT) verification in the evaluation of radiographic visibility of root pulp (RPV) of mandibular third molars for age estimation.

METHODS

CBCT and OPG images of 429 mandibular third molars from 290 patients were evaluated. RPV of fully mineralized mandibular third molars was evaluated as stages 0, 1, 2, and 3 for both imaging methods. Descriptive statistics were performed separately for stages by age for both genders. The consistency of these scores with chronological age was evaluated for both imaging methods. The reliability of OPG evaluation was also analyzed with CBCT scores.Results Spearman's rho correlation demonstrated a positive correlation between RPV and chronological age for both genders and for OPG and CBCT evaluation. Considering the minimum ages of both imaging methods, all stages were above the age of 18 except for the female group of Stage 2 and all Stage 0. For the comparison of OPG and CBCT RPV Staging scores, the κ score was found to be 0.312 (p < 0.001), indicating a fair agreement.

CONCLUSION

In conclusion, the absence of Stage 3 at age of 18 and under might have a forensic value for RPV age estimation method. Considering the fair agreement in the verification of OPG scores, it is not possible to determine the exact age with the RPV detected in OPG images, the use of CBCT for the RPV evaluation is recommended to available cases.

Age-dependent decrease in dental pulp cavity volume as a feature for age assessment: a comparative in vitro study using 9.4-T UTE-MRI and CBCT 3D imaging

Evaluation of secondary dentin formation is generally suitable for age assessment. We investigated the potential of modern magnetic resonance imaging (MRI) technology to visualize the dental pulp in direct comparison with cone beam computed tomography (CBCT). To this end, we examined 32 extracted human teeth (teeth 11–48 [FDI]) using 9.4-T ultrashort echo time (UTE)-MRI and CBCT (methods). 3D reconstruction was performed via both manual and semi-automatic segmentation (settings) for both methods in two runs by one examiner. Nine teeth were also examined by a second examiner. We evaluated the agreement between examiners, scan methods, and settings. CBCT was able to determine the pulp volume for all teeth. This was not possible for two teeth on MRI due to MRI artifacts. The mean pulp volume estimated by CBCT was consistently higher (~ 43%) with greater variability. With lower variability in its measurements, evaluation of pulp volume using the MRI method exhibited greater sensitivity to differences between settings (p = 0.016) and between examiners (p = 0.009). The interactions of single-rooted teeth and multi-rooted teeth and method or setting were not found to be significant. For examiner agreement, the mean pulp volumes were similar with overlapping measurements (ICC > 0.995). Suitable for use in age assessment is 9.4-T UTE-MRI with good reliability and lower variation than CBCT. For MRI, manual segmentation is necessary due to a more detailed representation of the interior of the pulp cavity. Since determination of pulp volume is expected to be systematically larger using CBCT, method-specific reference values are indispensable for practical age assessment procedures. The results should be verified under in vivo conditions in the future.

Accurate age classification using manual method and deep convolutional neural network based on orthopantomogram images

Age estimation is an important challenge in many fields, including immigrant identification, legal requirements, and clinical treatments. Deep learning techniques have been applied for age estimation recently but lacking performance comparison between manual and machine learning methods based on a large sample of dental orthopantomograms (OPGs). In total, we collected 10,257 orthopantomograms for the study. We derived logistic regression linear models for each legal age threshold (14, 16, and 18 years old) for manual method and developed the end-to-end convolutional neural network (CNN) which classified the dental age directly to compare with the manual method. Both methods are based on left mandibular eight permanent teeth or the third molar separately. Our results show that compared with the manual methods (92.5%, 91.3%, and 91.8% for age thresholds of 14, 16, and 18, respectively), the end-to-end CNN models perform better (95.9%, 95.4%, and 92.3% for age thresholds of 14, 16, and 18, respectively). This work proves that CNN models can surpass humans in age classification, and the features extracted by machines may be different from that defined by human.

Ultrasonographic assessment of ossification of the distal radial epiphysis for estimating forensic age

Since forensic age estimation is not a valid medical indication, research on the use of nonionizing methods is increasing. Ultrasonography is a radiological approach that protects patients from radiation exposure and offers special convenience to them. In this study, ultrasonography was used for age estimation by investigating the degree of ossification of the distal radial epiphysis. Its applicability on the Turkish population was investigated. The left wrist of 688 (322 males, 366 females) patients between the ages of 9 and 25 years was prospectively evaluated by ultrasonography. The intra- and interobserver reliabilities in evaluating the distal radial epiphysis and Cohen’s kappa statistics show that the interobserver error was very low, and the kappa value was found to be 0.919. Stage 3 and 4 ossification of the distal radial epiphysis was first detected at age 14.3 and 15.3 years in males and 12.7 and 14.8 years in females, respectively. The data obtained may help determine legally critical age limits of 14 and 15. Although it does not seem useful for the age of 18, ultrasonography may be recommended in selected cases as a fast, inexpensive, frequently reproducible radiological method without concern about radiation and without a predictable health risk.