OPG-based dental age estimation using a data-technical exploration of deep learning techniques.

Dental age estimation, a cornerstone in forensic age assessment, has been extensively tried and tested, yet manual methods are impeded by tedium and interobserver variability. Automated approaches using deep transfer learning encounter challenges like data scarcity, suboptimal training, and fine-tuning complexities, necessitating robust training methods. This study explores the impact of convolutional neural network hyperparameters, model complexity, training batch size, and sample quantity on age estimation. EfficientNet-B4, DenseNet-201, and MobileNet V3 models underwent cross-validation on a dataset of 3896 orthopantomograms (OPGs) with batch sizes escalating from 10 to 160 in a doubling progression, as well as random subsets of this training dataset. Results demonstrate the EfficientNet-B4 model, trained on the complete dataset with a batch size of 160, as the top performer with a mean absolute error of 0.562 years on the test set, notably surpassing the MAE of 1.01 at a batch size of 10. Increasing batch size consistently improved performance for EfficientNet-B4 and DenseNet-201, whereas MobileNet V3 performance peaked at batch size 40. Similar trends emerged in training with reduced sample sizes, though they were outperformed by the complete models. This underscores the critical role of hyperparameter optimization in adopting deep learning for age estimation from complete OPGs. The findings not only highlight the nuanced interplay of hyperparameters and performance but also underscore the potential for accurate age estimation models through optimization. This study contributes to advancing the application of deep learning in forensic age estimation, emphasizing the significance of tailored training methodologies for optimal outcomes.

Are palatal rugae reliable markers for 3D superimposition and forensic human identification after palatal expansion? A systematic review.

OBJECTIVES: Palatal rugae are periodic structures situated in the palatal mucosa, often used as landmarks for human identification and superimposition of digital dental models. This review aims to collect the current evidence regarding whether orthodontic palatal expansion could affect the stability of the palatal rugae and to give preliminary guidelines. MATERIALS AND METHODS: A systematic review of the literature was performed in the scientific databases Pubmed; Embase; WoS; and Cochrane. Grey Literature was also sought (clinicaltrial.gov; ICTRP; AHRQ; INAHTA). The search protocol, was registered in PROSPERO (N*208722). Data extraction comprised: year of publication, journal, sample size, characteristics of the experimental and control group, type of expander, expansion protocol, rugae classification, measurement method on casts, time between casts, method error, rugae change, morphology change and overall outcome. Risk of bias of the included articles was evaluated with the Newcastle-Ottawa Scale. RESULTS: A total of 12394 manuscripts were retrieved after duplicate removal. From these, nine articles were finally included for data extraction. three studies scored as low risk of bias, two as medium and four as high. CONCLUSIONS: The morphology of the palatal rugae can be modified by palatal expansion techniques, especially by rapid maxillary expansion. The first rugae is the most stable along with the points close to the palatal midline, which should be used as a reference both for manual or semi-automatic superimpositions. Human identification and serial superimpositions based on palatal rugae should not be carried immediately post expansion and be taken in consideration with caution in patients who underwent prior palatal expansion.

Skeletal age estimation of living adolescents and young adults: A pilot study on conventional radiography versus magnetic resonance imaging and staging technique versus atlas method.

OBJECTIVE: To compare conventional radiography (CR) and magnetic resonance imaging (MRI) of the left hand/wrist and both clavicles for forensic age estimation of adolescents and young adults. MATERIALS AND METHODS: CR and MRI were prospectively conducted in 108 healthy Caucasian volunteers (52 males, 56 females) aged 16 to 21 years. Skeletal development was assessed by allocating stages (wrist, clavicles) and atlas standards (hand/wrist). Inter- and intra-observer agreements were quantified using linear weighted Cohen's kappa, and descriptive statistics regarding within-stage/standard age distributions were reported. RESULTS: Inter- and intra-observer agreements for hand/wrist CR (staging technique: 0.840-0.871 and 0.877-0.897, respectively; atlas method: 0.636-0.947 and 0.853-0.987, respectively) and MRI (staging technique: 0.890-0.932 and 0.897-0.952, respectively; atlas method: 0.854-0.941 and 0.775-0.978, respectively) were rather similar. The CR atlas method was less reproducible than the staging technique. Inter- and intra-observer agreements for clavicle CR (0.590-0.643 and 0.656-0.770, respectively) were lower than those for MRI (0.844-0.852 and 0.866-0.931, respectively). Furthermore, although shifted, wrist CR and MRI within-stage age distribution spread were similar, as were those between staging techniques and atlas methods. The possibility to apply (profound) substages to clavicle MRI rendered a more gradual increase of age distributions with increasing stages, compared to CR. CONCLUSIONS: For age estimation based on the left hand/wrist and both clavicles, reference data should be considered anatomical structure- and imaging modality-specific. Moreover, CR is adequate for hand/wrist evaluation and a wrist staging technique seems to be more useful than an atlas method. By contrast, MRI is of added value for clavicle evaluation.

Quantifying the potential of morphological parameters for human dental identification: part 3-selecting the strongest skeletal identifiers in the mandible.

The current study aimed to select the best mandibular morphological identifiers. One-hundred eighty-five panoramic radiographs were retrospectively collected, in which four landmarks were located on the mandible: the most superior point of the condyle right/left (CONR/L), of the coronoid right/left (CORR/L), of the mandibular lingula right/left (LINR/L), and the most mesial point of the mental foramen right/left (MMFR/L). Five linear measurements, 6 angles, and 10 ratios were measured bilaterally. Three groups of statistics were considered: (1) mean potential set; (2) inter-observer agreement quantified by intra-class correlation (ICC) and within-subject coefficient of variation (WSCV); and (3) Spearman correlation. Parameters were selected for a step-by-step cascade. In a univariate approach, the following parameters proved to have the best identifying capacity: ratio 3 right (between lines CONR - CORR and LINR - MMFR) with mean potential set 13%, ICC 0.90, and WSCV 4.8%; ratio 4 (between lines CONR/L - CORR/L and MMFR - MMFL) with mean potential set 13%, ICC 0.92, and WSCV 8.9%; and angle 4 left (between landmarks LINL, MMFL, and MMFR) with mean potential set of 18%, ICC 0.91, and WSCV 1.2%. The correlation coefficients ranged from 0.01 to 0.33. In a multivariate approach, the identifying capacity improved drastically, with all ratios combined as the strongest identifier (mean potential set 1.29%). In conclusion, a single ratio or a single angle already narrows down the set of potential matches, but the mean potential set remains relatively large. Combining all ratios drastically increases the certainty of the match.

Quantifying the potential of morphological parameters for human dental identification: part 2-selecting the strongest identifiers in mandibular permanent teeth.

The current study aimed to select the best dental morphological identifiers for human identification. Sixty-two panoramic radiographs were collected retrospectively, in which six measurements were performed on all seven mandibular left permanent teeth: tooth length (TL), crown length (CL), root length (RL), crown width (CW), cervical width (CEJW), and root width (RW). Nine length-width ratios were then calculated using these measurements. Three groups of statistics were considered: (1) inter-observer reliability quantified by intra-class correlation (ICC); (2) mean "potential set"; and (3) Spearman correlation. A step-by-step cascade was then established based on selected parameters. In a univariate approach, the following parameters were the best identifiers: TL/CW for tooth 36 (ICC 0.82; mean potential set 13.7%), TL/CEJW for tooth 35 (ICC 0.87; mean potential set 15.2%), and TL/RW for tooth 32 (ICC 0.89; mean potential set 16.0%). The correlations between these three parameters ranged from 0.24 to 0.47. In a multivariate approach, the following parameters had the best identifying capacity: all parameters combined for tooth 31 (mean potential set 8.1%), for tooth 35 (mean potential set 11.9%), and for tooth 32 (mean potential set 16.3%). In conclusion, a single ratio in a specific tooth narrows down the potential set of matches, but the mean potential set remains relatively large. Combining all ratios of a single specific tooth increases the certainty of the match. In particular, tooth 31 was the strongest identifier.

Is third molar development affected by third molar impaction or impaction-related parameters?

OBJECTIVE: To evaluate the effect of third molar impaction and impaction-related parameters on third molar development. MATERIALS AND METHODS: Panoramic radiographs (N=3972) from 473 males and 558 females between 3.2 and 23.5 years old were analysed. Three parameters of impaction were examined: hindering contact between third and adjacent second molar, retromolar space availability (only in lower third molars), and angulation between the third and adjacent second molar. From the separate parameters, a definition for impaction was derived. Third molars' development was staged according to a modified Köhler et al. staging technique. A linear model was used to compare within-stage and overall age, as a function of hindering contact, retromolar space, and impaction. Furthermore, a quadratic function was used to study the correlation between age and angulation. RESULTS: Significant differences were found in mean age as a function of hindering contact and retromolar space, depending on third molar location and stage. There was a significant relation between angulation and age, depending on the stage, with all third molars evolving to a more upright position (closer to 0°). Mean ages of subjects with impacted third molars were significantly lower in certain third molar stages, but the differences were clinically small (absolute differences ≤0.65 years). Moreover, after correction for stage differences, no significant differences in age could be demonstrated. CONCLUSIONS: The development of impacted and non-impacted third molars can be considered clinically equal in our study population. CLINICAL RELEVANCE: There is no distinction required between impacted and non-impacted third molars for dental age estimation.

Dental development in patients with and without unilateral cleft lip and palate (UCLP): a case control study.

OBJECTIVE: To evaluate if the presence of unilateral cleft lip and palate (UCLP) causes delay in dental age and tooth development. MATERIALS AND METHODS: Panoramic radiographs of 189 non-syndromic UCLP patients, aged from 6 to 20 years, were collected. Two measures of tooth development were examined: dental maturity scale for the seven left mandibular teeth (dental age-DA) and the degree of each tooth development (developmental score-DS). All the teeth except third molars were staged according to the Demirjian's method. The data of the cleft group were compared with a control group matched for age and gender, based on the findings observed in other 189 panoramic radiographs. RESULTS: At all ages, DA was lower in the UCLP group, but not always significantly; the highest difference was - 1.411 for females at 13 years old and - 0.776 for males at 12 years old. DS of all teeth was significantly lower in the UCLP group, at all ages under 17 in females, and at all ages under 18 in males. In UCLP group, tooth development was more delayed in the maxilla compared with the mandible. No evidence of a slower development at the cleft side compared with the non-cleft side was highlighted. CONCLUSIONS: Significant lower dental development was observed in UCLP patients compared with control ones by using DS and DA indexes. CLINICAL RELEVANCE: These findings can help the clinicians in establishing a proper orthodontic and surgical diagnosis and treatment planning in UCLP patients and for forensic age estimation's purposes.

Validating dental age estimation in Kenyan black children and adolescents using the Willems method.

PURPOSE: This study aimed to validate the Willems Belgian Caucasian (Willems BC) age estimation model in a Kenyan sample, to develop and validate a Kenyan-specific (Willems KB) age estimation model and to compare the age prediction performances of both models. METHODS: Panoramic radiographs of 1038 (523 female, 515 male) Kenyan children without missing permanent teeth and without all permanent teeth fully developed (except third molars) were retrospectively selected. Tooth development of the seven lower-left permanent teeth was staged according to Demirjian et al. The Willems BC model, performed on a Belgian Caucasian sample and a constructed Kenyan-specific model (Willems KB) were validated on the Kenyan sample. Their age prediction performances were quantified and compared using the mean error (ME), mean absolute error (MAE) and root-mean-square error (RMSE). RESULTS: The ME with Willems BC method equalled zero. Hence, there was no systematic under- or overestimation of the age. For males and females separately, the ME with Willems BC was significantly different from zero, but negligible in magnitude (-0.04 and 0.04, respectively). Willems KB was found not to outperform Willems BC, since the MAE and RMSE were comparable (0.98 vs 0.97 and 1.31 vs 1.29, respectively). Although Willems BC resulted in a higher percentage of subjects with predicted age within a one-year difference of the true age (63.3% vs 60.4%, p=0.018), this cannot be considered as clinically relevant. CONCLUSION: There is no reason to use a country-specific (Willems KB) model in children from Kenya instead of the original Willems (BC) model.

Implant functionalization with mesoporous silica: A promising antibacterial strategy, but does such an implant osseointegrate?

OBJECTIVES: New strategies for implant surface functionalization in the prevention of peri-implantitis while not compromising osseointegration are currently explored. The aim of this in vivo study was to assess the osseointegration of a titanium-silica composite implant, previously shown to enable controlled release of therapeutic concentrations of chlorhexidine, in the Göttingen mini-pig oral model. MATERIAL AND METHODS: Three implant groups were designed: macroporous titanium implants (Ti-Porous); macroporous titanium implants infiltrated with mesoporous silica (Ti-Porous + SiO2 ); and conventional titanium implants (Ti-control). Mandibular last premolar and first molar teeth were extracted bilaterally and implants were installed. After 1 month healing, the bone in contact with the implant and the bone regeneration in the peri-implant gap was evaluated histomorphometrically. RESULTS: Bone-to-implant contact and peri-implant bone volume for Ti-Porous versus Ti-Porous + SiO2 implants did not differ significantly, but were significantly higher in the Ti-Control group compared with Ti-Porous + SiO2 implants. Functionalization of titanium implants via infiltration of a SiO2 phase into the titanium macropores does not seem to inhibit implant osseointegration. Yet, the importance of the implant macro-design, in particular the screw thread design in a marginal gap implant surgery set-up, was emphasized by the outstanding results of the Ti-Control implant. CONCLUSIONS: Next-generation implants made of macroporous Ti infiltrated with mesoporous SiO2 do not seem to compromise the osseointegration process. Such implant functionalization may be promising for the prevention and treatment of peri-implantitis given the evidenced potential of mesoporous SiO2 for controlled drug release.

Dental and Skeletal Imaging in Forensic Age Estimation: Disparities in Current Approaches and the Continuing Search for Optimization.

Medical imaging for forensic age estimation in living adolescents and young adults continues to be controversial and a subject of discussion. Because age estimation based on medical imaging is well studied, it is the current gold standard. However, large disparities exist between the centers conducting age estimation, both between and within countries. This review provides an overview of the most common approaches applied in Europe, with case examples illustrating the differences in imaging modalities, in staging of development, and in statistical processing of the age data. Additionally, the review looks toward the future because several European research groups have intensified studies on age estimation, exploring four strategies for optimization: (1) increasing sample sizes of the reference populations, (2) combining single-site information into multifactorial information, (3) avoiding ionizing radiation, and (4) conducting a fully automated analysis.

Magnetic resonance imaging for forensic age estimation in living children and young adults: a systematic review.

The use of MRI in forensic age estimation has been explored extensively during the last decade. The authors of this paper synthesized the available MRI data for forensic age estimation in living children and young adults to provide a comprehensive overview that can guide age estimation practice and future research. To do so, the authors searched MEDLINE, Embase and Web of Science, along with cited and citing articles and study registers. Two authors independently selected articles, conducted data extraction, and assessed risk of bias. They considered study populations including living subjects up to 30 years old. Fifty-five studies were included in qualitative analysis and 33 in quantitative analysis. Most studies had biases including use of relatively small European (Caucasian) populations, varying MR approaches and varying staging techniques. Therefore, it was not appropriate to pool the age distribution data. The authors found that reproducibility of staging was remarkably lower in clavicles than in any other anatomical structure. Age estimation performance was in line with the gold standard, radiography, with mean absolute errors ranging from 0.85 years to 2.0 years. The proportion of correctly classified minors ranged from 65% to 91%. Multifactorial age estimation performed better than that based on a single anatomical site. The authors found that more multifactorial age estimation studies are necessary, together with studies testing whether the MRI data can safely be pooled. The current review results can guide future studies, help medical professionals to decide on the preferred approach for specific cases, and help judicial professionals to interpret the evidential value of age estimation results.

Towards fully automated third molar development staging in panoramic radiographs.

Staging third molar development is commonly used for age assessment in sub-adults. Current staging techniques are, at most, semi-automated and rely on manual interactions prone to operator variability. The aim of this study was to fully automate the staging process by employing the full potential of deep learning, using convolutional neural networks (CNNs) in every step of the procedure. The dataset used to train the CNNs consisted of 400 panoramic radiographs (OPGs), with 20 OPGs per developmental stage per sex, staged in consensus between three observers. The concepts of transfer learning, using pre-trained CNNs, and data augmentation were used to mitigate the issues when dealing with a limited dataset. In this work, a three-step procedure was proposed and the results were validated using fivefold cross-validation. First, a CNN localized the geometrical center of the lower left third molar, around which a square region of interest (ROI) was extracted. Second, another CNN segmented the third molar within the ROI. Third, a final CNN used both the ROI and the segmentation to classify the third molar into its developmental stage. The geometrical center of the third molar was found with an average Euclidean distance of 63 pixels. Third molars were segmented with an average Dice score of 93%. Finally, the developmental stages were classified with an accuracy of 54%, a mean absolute error of 0.69 stages, and a linear weighted Cohen's kappa coefficient of 0.79. The entire automated workflow on average took 2.72 s to compute, which is substantially faster than manual staging starting from the OPG. Taking into account the limited dataset size, this pilot study shows that the proposed fully automated approach shows promising results compared with manual staging.

The influence of motion artefacts on magnetic resonance imaging of the clavicles for age estimation.

PURPOSE: To determine how motion affects stage allocation to the clavicle's sternal end on MRI. MATERIALS AND METHODS: Eighteen volunteers (9 females, 9 males) between 14 and 30 years old were prospectively scanned with 3-T MRI. One resting-state scan was followed by five intentional motion scans. Additionally, a control group of 72 resting-state scans were selected from previous research. Firstly, six observers allocated developmental stages to the clavicles independently. Secondly, they re-assessed the images, allocating developmental statuses (immature, mature). Finally, the resting-state scans of the 18 volunteers were assessed in consensus to decide on the "correct" stage/status. Results were compared between groups (control, prospective resting state, prospective motion), and between staging techniques (stages/statuses). RESULTS: Inter-observer agreement was low (Krippendorff α 0.23-0.67). The proportion of correctly allocated stages (64%) was lower than correctly allocated statuses (83%). Overall, intentional motion resulted in fewer assessable images and less images of sufficient evidential value. The proportion of correctly allocated stages did not differ between resting-state (64%) and motion scans (65%), while correctly allocated statuses were more prevalent in resting-state scans (83% versus 77%). Remarkably, motion scans did not render a systematically higher or lower stage/status, compared to the consensus. CONCLUSION: Intentional motion impedes clavicle MRI for age estimation. Still, in case of obvious disturbances, the forensic expert will consider the MRI unsuitable as evidence. Thus, the development of the clavicle as such and the staging technique seem to play a more important role in allocating a faulty stage for age estimation.

Staging Clavicular Development on MRI: Pitfalls and Suggestions for Age Estimation.

BACKGROUND: MRI of the clavicle's sternal end has been studied for age estimation. Several pitfalls have been noted, but how they affect age estimation performance remains unclear. PURPOSE/HYPOTHESIS: To further study these pitfalls and to make suggestions for a proper use of clavicle MRI for forensic age estimation. Our hypotheses were that age estimation would benefit from 1) discarding stages 1 and 4/5; 2) including advanced substages 3aa, 3ab, and 3ac; 3) taking both clavicles into account; and 4) excluding morphological variants. STUDY TYPE: Prospective cross-sectional. POPULATION: Healthy Caucasian volunteers between 11 and 30 years old (524; 277 females, 247 males). FIELD STRENGTH/SEQUENCE: 3T, T1 -weighted gradient echo volumetric interpolated breath-hold examination (VIBE) MR-sequence. ASSESSMENT: Four observers applied the most elaborate staging technique for long bone development that has been described in the current literature (including stages, substages, and advanced substages). One of the observers repeated a random selection of the assessments in 110 participants after a 2-week interval. Furthermore, all observers documented morphological variants. STATISTICAL TESTS: Weighted kappa quantified reproducibility of staging. Bayes' rule was applied for age estimation with a continuation ratio model for the distribution of the stages. According to the hypotheses, different models were tested. Mean absolute error (MAE) differences between models were compared, as were MAEs between cases with and without morphological variants. RESULTS: Weighted kappa equaled 0.82 for intraobserver and ranged between 0.60 and 0.64 for interobserver agreement. Stages 1 and 4/5 were allocated interchangeably in 4.3% (54/1258). Age increased steadily in advanced substages of stage 3, but improvement in age estimation was not significant (right P = 0.596; left P = 0.313). The model that included both clavicles and discarded stages 1 and 4/5 yielded an MAE of 1.97 years, a root mean squared error of 2.60 years, and 69% correctly classified minors. Morphological variants rendered significantly higher MAEs (right 3.84 years, P = 0.015; left 2.93 years, P = 0.022). DATA CONCLUSION: Our results confirmed hypotheses 3) and 4), while hypotheses 1) and 2) remain to be investigated in larger studies. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:377-388.

Effect of Lower Third Molar Segmentations on Automated Tooth Development Staging using a Convolutional Neural Network.

Staging third molar development is commonly used for age estimation in subadults. Automated developmental stage allocation to the mandibular left third molar in panoramic radiographs has been examined in a pilot study. This method used an AlexNet Deep Convolutional Neural Network (CNN) approach to stage lower left third molars, which had been selected by manually drawn bounding boxes around them. This method (bounding box AlexNet = BA) still contained parts of surrounding structures which may have affected the automated stage allocation performance. We hypothesize that segmenting only the third molar could further improve the automated stage allocation performance. Therefore, the current study aimed to determine and validate the effect of lower third molar segmentations on automated tooth development staging. Retrospectively, 400 panoramic radiographs were collected, processed and segmented in three ways: bounding box (BB), rough (RS), and full (FS) tooth segmentation. A DenseNet201 CNN was used for automated stage allocation. Automated staging results were compared with reference stages - allocated by human observers - overall and per stage. FS rendered the best results with a stage allocation accuracy of 0.61, a mean absolute difference of 0.53 stages and a Cohen's linear κ of 0.84. Misallocated stages were mostly neighboring stages, and DenseNet201 rendered better results than AlexNet by increasing the percentage of correctly allocated stages by 3% (BA compared to BB). FS increased the percentage of correctly allocated stages by 7% compared to BB. In conclusion, full tooth segmentation and a DenseNet CNN optimize automated dental stage allocation for age estimation.

Multi-factorial age estimation: A Bayesian approach combining dental and skeletal magnetic resonance imaging.

PURPOSE: To study age estimation performance of combined magnetic resonance imaging (MRI) data of all four third molars, the left wrist and both clavicles in a reference population of females and males. To study the value of adding anthropometric and sexual maturation data. MATERIALS AND METHODS: Three Tesla MRI of the three anatomical sites was prospectively conducted from March 2012 to May 2017 in 14- to 26-year-old healthy Caucasian volunteers (160 females, 138 males). Development was assessed by allocating stages, anthropometric measurements were taken, and self-reported sexual maturation data were collected. All data was incorporated in a continuation-ratio model to estimate age, applying Bayes' rule to calculate point and interval predictions. Two performance aspects were studied: (1) accuracy and uncertainty of the point prediction, and (2) diagnostic ability to discern minors from adults (≥18 years). RESULTS: Combining information from different anatomical sites decreased the mean absolute error (MAE) compared to incorporating only one site (P<0.0001). By contrast, adding anthropometric and sexual maturation data did not further improve MAE (P=0.11). In females, combining all three anatomical sites rendered a MAE equal to 1.41 years, a mean width of the 95% prediction intervals of 5.91 years, 93% correctly classified adults and 91% correctly classified minors. In males, the corresponding results were 1.36 years, 5.49 years, 94%, and 90%, respectively. CONCLUSION: All aspects of age estimation improve when multi-factorial MRI data of the three anatomical sites are incorporated. Anthropometric and sexual maturation data do not seem to add relevant information.

Comparing third molar root development staging in panoramic radiography, extracted teeth, and cone beam computed tomography.

This study aimed at performing and comparing third molar development staging in extracted teeth (EX), panoramic radiography (PAN), and cone beam computed tomography (CBCT). Extracted third molars (n = 158, 95 maxillary, 63 mandibular) from 102 patients (36 males, 66 females) having at least one preoperative PAN and one CBCT were studied. Third molar development staging was performed in PAN, EX, and CBCT using Gleiser et al. (1955) technique modified by Köhler et al (1994). A polytomous logistic regression model was used to compare the staging performed in EX and CBCT with the gold standard staging in PAN. The pair-wise stage comparisons between third molar modalities revealed 63.3% equal staging. In all other comparisons, a maximum difference of one stage was detected. No statistically significant differences between the three staging modalities were detected (p = 0.26). The comparison between EX and PAN staging revealed higher similarity (p = 0.98 in stages 5-10) than the comparison between CBCT and PAN staging (p = 0.81 in stages 5, 7, and 9, and p = 0.80 in stages 6, 8, and 10). The studied third molar staging technique originally designed in PAN can be applied for third molar staging EX and in CBCT.

Comparing dental identifier charting in cone beam computed tomography scans and panoramic radiographs using INTERPOL coding for human identification.

According to INTERPOL, the comparison of antemortem and postmortem dental identifiers is a scientifically reliable approach for human identification. This study aimed to quantify the prevalence of corresponding INTERPOL coded dental identifiers in cone beam computed tomography (CBCT) scans and panoramic radiographs (PR). The sample consisted of 100 CBCT scans and 100 PR taken the same day from the same patients (35 males and 65 females). Randomly and independently, forty-one INTERPOL coded dental identifiers were searched in each image. Wilcoxon test compared the prevalence of codes in CBCT scans and PR, Chi-square tested the dependence between codes and teeth; and multiple correspondence analyses (MCA) explored the association between codes and teeth in color maps for CBCT scans and PR. No statistically significant differences between the prevalence of identifiers in CBCT scans and PR were detected (p=0.693). In CBCT scans and PR, dependence between teeth and codes was detected (p<0.05). In the study sample, the strongest associations were found between the codes unerupted (UNE), partially erupted (ERU) and impacted (IMV) and third molars, both in CBCT scans and PR. INTERPOL coded dental identifiers registered on CBCT scans and PR can be exchanged during human identification.

Dental age estimation in Somali children and sub-adults combining permanent teeth and third molar development.

Estimation of an individual's age has important applications in forensics. In young individuals, it often relies on separate evaluations of permanent teeth (PT) and third molars (TM) development. Here, we analysed the age prediction performance of combined information from PT and TM in an unusual sample of healthy Somalis, born and living in Finland. PT development was staged according to Demirjian et al. (Hum Biol, 1973) and TM development according to Köhler et al. (Ann Anat, 1994), using panoramic radiographs from 803 subjects (397 males, 406 females) aged 3-23 years. A sex-specific Bayesian age-estimation model for the multivariate distribution of the stages conditional on age was fitted on PT, TM and PT and TM combined. The age-estimation performances were validated and quantified. The approach combining PT and TM only overestimated age with an ME of - 0.031 years in males and - 0.011 years in females, indicating the best age prediction performance.

Forensic age estimation based on T1 SE and VIBE wrist MRI: do a one-fits-all staging technique and age estimation model apply?

OBJECTIVES: Providing recommendations for wrist MRI in age estimation by determining (1) which anatomical structures to include in the statistical model, (2) which MRI sequence to conduct, and (3) which staging technique to apply. METHODS: Radius and ulna were prospectively studied on 3 T MRI in 363 healthy Caucasian participants (185 females, 178 males) between 14 and 26 years old, using T1 spin echo (SE) and T1 gradient echo VIBE. Bone development was assessed applying a 5-stage staging technique with several amelioration attempts to optimise staging. A Bayesian model rendered point predictions of age and diagnostic indices to discern minors from adults. RESULTS: All approaches rendered similar results, with none of them outperforming the others. A single bone assessment of radius or ulna sufficed. SE and VIBE sequences were both suitable, but needed sequence-specific age estimation. A one-fits-all 5-stage staging technique-with substages in stage 3-was suitable and did not benefit from profound substaging. Age estimation based on SE radius resulted in a mean absolute error of 1.79 years, a specificity (correctly identified minors) of 93%, and a discrimination slope of 0.640. CONCLUSION: Radius and ulna perform similarly to estimate age, and so do SE and VIBE. A one-fits-all staging technique can be applied. KEY POINTS: • Radius and ulna perform similarly to estimate age. • SE and VIBE perform similarly, but age estimation should be based on the corresponding sequence-specific reference data. • A one-fits-all 5-stage staging technique with substages 3a, 3b, and 3c can be applied to both bones and both sequences.