In vivo facial tissue depth for Canadian Mi'kmaq adults: a case study from Nova Scotia, Canada

Global facial soft tissue thicknesses for craniofacial identification (2023): a review of 140 years of data since Welcker's first study

This year (2023) marks 140 years since the first publication of a facial soft tissue thickness (FSTT) study. Since 1883, a total of 139 studies have been published, collectively tallying > 220,000 tissue thickness measurements of > 19,500 adults. In just the last 5-years, 33 FSTT studies have been conducted. Herein, we add these data (plus an additional 20 studies) to the 2018 T-Table to provide an update of > 81,000 new datapoints to the global tallied facial soft tissue depths table. In contrast to the original 2008 T-Table, some notable changes are as follows: increased FSTTs by 3 mm at infra second molar (ecm2-iM2'), 2.5 mm at gonion (go-go'), 2 mm at mid-ramus (mr-mr'), and 1.5 mm at zygion (zy-zy'). Rolling grand means indicate that stable values have been attained for all nine median FSTT landmarks, while six out of nine bilateral landmarks continue to show ongoing fluctuations, indicating further data collection at these landmarks holds value. When used as point estimators for individuals with known values across 24 landmarks (i.e., C-Table data), the updated grand means produce slightly less estimation error than the 2018 T-Table means (3.5 mm versus 3.6 mm, respectively). Future efforts to produce less noisy datasets (i.e., reduce measurement and sampling errors as much as possible between studies) would be useful.

The relationship between biological parameters and facial soft tissue thickness measured by ultrasound and its forensic implications

Facial soft tissue thickness (FSTT) data are currently widely used in forensic and medical science. In the forensic sciences, they form the basis for craniofacial reconstruction and identification methods. Since there are few FSTT data in the Slovak population, this study aims to enrich the data in well-defined age categories, taking into account differences between sexes and body mass index (BMI). The sample consisted of 127 participants aged 17 to 86 years from Slovakia. In addition to biological sex and age information, stature and body weight were recorded to calculate BMI. Subsequently, 17 facial anthropometric landmarks were used to measure FSTT using a noninvasive General Electric LOGIQe R7 ultrasound device. The mean values of FSTT were greater in the mouth region in males and in the zygomatic and eye regions in females. Differences between males and females, regardless of sex and BMI, were significant only at two landmarks. When BMI and age were taken into account, there were differences in 12 of 17 landmarks. Linear regression results showed the strongest correlation of most landmarks with BMI, followed by age and sex. When the FSTT was estimated in association with sex/age/BMI, landmarks in the zygomatic, mandibular, and frontal regions were the best regressors. The results of the present study demonstrate that B-mode ultrasound measurements of FSTT can be used in facial reconstruction as a function of BMI, age, and sex of the subject. Furthermore, the present regression equations can help practitioners in the forensic/medical field to calculate individual tissue thickness.

Three-Dimensional Prediction of the Nose for Facial Approximation in a Thai Population

Most of the previous studies about nose prediction were concentrated only some landmarks of the nose. This study aimed to generate prediction equations for ten landmarks of the nose in the midline and alar regions for forensic facial approximation. The six midline landmarks were the sellion, nasion-pronasale posterior, nasion-pronasale anterior, pronasale, nasal drop, and subnasale. The four landmarks of the alar region were the alare, superior alar groove, posterior alar groove, and inferior alar groove. We used the skull landmarks in the nasal, zygomatic, and maxillary bone to predict the landmarks of the nose. Cone-beam computed tomography scans of 108 Thai subjects with normal BMI and age ranging from 21.0 to 50.9 years were obtained in a sitting position. The data were converted into three-dimensional (3-D) images of the skull and face. The Cartesian coordinates of the landmarks of the skull and nose were used to formulate the multiple regression equations. The formulated equations were tested in 24 new subjects. The mean differences in the predicted midline landmarks varied between -0.4 mm and 0.5 mm, whereas those for bilateral landmarks varied between -1.0 mm and 1.4 mm. In conclusion, the prediction equations formulated here will be beneficial for facial approximation of the nose in a Thai population.

Re-assessment of South African juvenile facial soft tissue thickness data for craniofacial approximation: A comparative analysis using central tendency statistics

Facial soft tissue thickness (FSTT) data form the basis of craniofacial identification methods such as facial approximation in cases where unknown skeletal remains lack unique identifiers such as fingerprints, DNA and dental records. Appropriate FSTT data are said to be required to produce accurate facial approximations that may be recognised by relatives. This view led to a vast number of studies considering subdivisions of FSTT data according to ancestry, age and sex. The paucity of South African juvenile FSTT standards of particular age groups, sex and ancestry is therefore problematic as "accurate" facial approximations cannot be produced. However, the use of pooled datasets and central tendency statistics offers a unique opportunity to circumvent the problem of small or absent FSTT datasets. The aim of this study was to use central tendency statistics of previously published South African data in order to assess whether it is necessary to subdivide FSTT datasets into different subgroups. In addition, a meta-analysis using central tendency statistics of 11 datasets within the C-table repository using the free open source TDStats programme (available through CRANIOFACIALidentification.com) for midfacial landmarks was performed. These datasets comprised of raw juvenile and adult FSTT data gathered from 1895 to 2015 as measured by a variety of methods Scatter plots showed that FSTT correlation with age is rather weak, while Kernel density plots of FSTT by sex and landmark indicated no difference between South African juvenile males and females. In order to test the practical application of FSTT data, two facial approximations were constructed - one based on the shorth from South African data and C-tables and one based on an American dataset. When comparing the two facial approximations based on different datasets, geometric deviation indicated differences at midline and bilateral landmarks, but the visual presentation of the facial approximations was similar. Therefore it is suggested that differences of less than 3mm at any landmark do not result in profound practical differences in the juvenile face. Subcategorizing juvenile data is not necessary as the same result can be achieved by weighted means as presented in the sub-adult C-tables.