Quantifying the potential of morphological parameters for human dental identification: part 1-proof of concept.

In forensic identification, lack of eccentric characteristics of intact dentitions hinders correct ante-mortem/post-mortem (AM/PM) matching. It remains unclear which morphological dental parameters hold strong potential as identifiers. This study aimed to establish a method to quantify and rank the identifying potential of one (or a combination of) continuous morphological parameter(s), and to provide a proof of concept. First, a statistic was defined that quantifies the identifying potential: the mean potential set (MPS). The MPS is derived from inter-observer agreement data and it indicates the percentage of subjects in the AM reference dataset who at least need to be considered to detect the correct PM subject. This was calculated in a univariate and a multivariate setting. Second, the method was validated on maxillary first molar crowns of 82 3D-digitally scanned cast models. Standardized measurements were registered using 3D modeling software (3-Matic Medical 12.0, Materialise N.V., Leuven, Belgium): tooth depth, angles between cusps, distances between cusps, distances between the cusps, and the mesial pit. A random sample of 40 first molars was measured by a second examiner. Quantifying and ranking the parameters allowed selecting those with the strongest identifying potential. This was found for the tooth depth (1 measurement, MPS = 17.1%, ICC = 0.879) in the univariate setting, and the angles between cusps (4 measurements, MPS = 3.9%) in the multivariate setting. As expected, the multivariate approach held significantly stronger identifying potential, but more measurements were needed (i.e., more time-consuming). Our method allows quantifying and ranking the potential of dental morphological parameters as identifiers using a clear-cut statistic.

An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study.

BACKGROUND: Automated methods to evaluate growth of hand and wrist bones on radiographs and magnetic resonance imaging have been developed. They can be applied to estimate age in children and subadults. Automated methods require the software to (1) recognise the region of interest in the image(s), (2) evaluate the degree of development and (3) correlate this to the age of the subject based on a reference population. For age estimation based on third molars an automated method for step (1) has been presented for 3D magnetic resonance imaging and is currently being optimised (Unterpirker et al. 2015). AIM: To develop an automated method for step (2) based on lower third molars on panoramic radiographs. MATERIALS AND METHODS: A modified Demirjian staging technique including ten developmental stages was developed. Twenty panoramic radiographs per stage per gender were retrospectively selected for FDI element 38. Two observers decided in consensus about the stages. When necessary, a third observer acted as a referee to establish the reference stage for the considered third molar. This set of radiographs was used as training data for machine learning algorithms for automated staging. First, image contrast settings were optimised to evaluate the third molar of interest and a rectangular bounding box was placed around it in a standardised way using Adobe Photoshop CC 2017 software. This bounding box indicated the region of interest for the next step. Second, several machine learning algorithms available in MATLAB R2017a software were applied for automated stage recognition. Third, the classification performance was evaluated in a 5-fold cross-validation scenario, using different validation metrics (accuracy, Rank-N recognition rate, mean absolute difference, linear kappa coefficient). RESULTS: Transfer Learning as a type of Deep Learning Convolutional Neural Network approach outperformed all other tested approaches. Mean accuracy equalled 0.51, mean absolute difference was 0.6 stages and mean linearly weighted kappa was 0.82. CONCLUSION: The overall performance of the presented automated pilot technique to stage lower third molar development on panoramic radiographs was similar to staging by human observers. It will be further optimised in future research, since it represents a necessary step to achieve a fully automated dental age estimation method, which to date is not available.

Forensic age estimation based on development of third molars: a staging technique for magnetic resonance imaging.

BACKGROUND: The development of third molars can be evaluated with medical imaging to estimate age in subadults. The appearance of third molars on magnetic resonance imaging (MRI) differs greatly from that on radiographs. Therefore a specific staging technique is necessary to classify third molar development on MRI and to apply it for age estimation. AIM: To develop a specific staging technique to register third molar development on MRI and to evaluate its performance for age estimation in subadults. MATERIALS AND METHODS: Using 3T MRI in three planes, all third molars were evaluated in 309 healthy Caucasian participants from 14 to 26 years old. According to the appearance of the developing third molars on MRI, descriptive criteria and schematic representations were established to define a specific staging technique. Two observers, with different levels of experience, staged all third molars independently with the developed technique. Intra- and inter-observer agreement were calculated. The data were imported in a Bayesian model for age estimation as described by Fieuws et al. (2016). This approach adequately handles correlation between age indicators and missing age indicators. It was used to calculate a point estimate and a prediction interval of the estimated age. Observed age minus predicted age was calculated, reflecting the error of the estimate. RESULTS: One-hundred and sixty-six third molars were agenetic. Five percent (51/1096) of upper third molars and 7% (70/1044) of lower third molars were not assessable. Kappa for inter-observer agreement ranged from 0.76 to 0.80. For intra-observer agreement kappa ranged from 0.80 to 0.89. However, two stage differences between observers or between staging sessions occurred in up to 2.2% (20/899) of assessments, probably due to a learning effect. Using the Bayesian model for age estimation, a mean absolute error of 2.0 years in females and 1.7 years in males was obtained. Root mean squared error equalled 2.38 years and 2.06 years respectively. The performance to discern minors from adults was better for males than for females, with specificities of 96% and 73% respectively. CONCLUSION: Age estimations based on the proposed staging method for third molars on MRI showed comparable reproducibility and performance as the established methods based on radiographs.

Magnetic resonance imaging of the medial extremity of the clavicle in forensic bone age determination: a new four-minute approach.

OBJECTIVES: The use of 3T magnetic resonance imaging (MRI) of the clavicle in forensic bone age determination was prospectively examined and compared with plain radiography. METHODS: Four MRI sequences and three radiographs of 121 healthy subjects between 11 and 30 were studied by two observers. RESULTS: The number of images assessable for bone age determination was lower for plain radiography (PA: 68.7%; oblique: 97.5%) compared with MRI (VIBE: 99.0%). Concerning the subjective level of difficulty to assess bone age, the observers found it easier to assess bone age on MRI than on radiography. The developmental stages of the clavicle, as used on plain radiography, were transferable to MRI. Especially the VIBE gradient echo sequence provided an excellent depiction of the growth cartilage and ossification centre with a slice thickness of 0.9 mm and only a 4-min acquisition time. When the developmental stages were assigned, less variability between the observers was seen on MRI, compared with plain radiography. CONCLUSION: We conclude that 3T MRI provides high resolution, cross-sectional images of the maturation of the clavicle without ionising radiation in a very short time, allowing more accurate determination of bone age than plain radiography.