Facial soft tissue thicknesses in the present Czech Population

Facial soft tissue depth of a contemporary adult Greek population

Facial approximation is a technique that involves constructing the facial muscles and applying a suitable facial soft tissue depth (FSTD) dataset. To date, several FSTD studies have been conducted for varying population groups. This study aims to establish a FSTD dataset of an adult Greek population sample for the first time. The facial depths of subjects were measured on 100 head CT scans of 50 male and 50 female subjects aged from 18 to 99. The 3D head and skull models of subjects were segmented in Amira 6.1 by using histogram method. FSTDs were measured at 22 cranial landmarks (5 mid-sagittal, 17 bilateral). The FSTD dataset was generated by considering the age and sex of subjects. The impact of age and sex on the FSTD was limited. Slight inter-population depth variations were reported. Facial asymmetry calculated between the bilateral landmarks was insignificant for both male and female subjects.

Evaluation of the soft tissue facial profile in different skeletal malocclusions in relation to age

BACKGROUND

The aim of the study was to assess the thickness of the soft tissue facial profile (STFP) in relation to the skeletal malocclusion, age and gender.

METHODS

All patients, aged 7-35 years, who were seeking orthodontic treatment at the Department of Orthodontics, Medical University of Warsaw between 2019 and 22 were included in the study. All patients had lateral head radiographs taken before the treatment. The cephalometric analysis was performed including the STFP analysis. The patients were allocated to one of six groups based on age and skeletal relations (ANB angle). The minimum number of patients in each group was 60 with equal gender distribution. The STFP analysis included ten linear measurements.

RESULTS

A total of 300 patients were included in the study and allocated to five groups. Group 6 (growing patients with skeletal Class III malocclusion) was not included in the study as it failed to achieve the assumed group size. There were significant differences in the thickness of the STFP in relation to the skeletal malocclusions. Adults with skeletal Class III malocclusion had significantly thicker subnasal soft tissues compared to patients with skeletal Class I and Class II malocclusions. The thickness of the lower lip in patients with Class II skeletal malocclusion was significantly bigger compared to the other groups. Children and adolescents with Class II malocclusions had thicker lower lip in comparison to the group with Class I malocclusion. The majority of the STFP measurements were significantly smaller in children and adolescents compared to adults. The thickness of the STFP in males was significantly bigger in all age groups compared to females.

CONCLUSIONS

The thickness of facial soft tissues depends on the patient's age and gender. The degree of compensation of the skeletal malocclusion in the STFP may be a decisive factor during orthodontic treatment planning regarding a surgical approach or a camouflage treatment of skeletal defects.

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.

Facial Soft Tissue Thickness Differences among Three Skeletal Classes in Korean Population Using CBCT

Studies related to facial soft tissue thickness (FSTT) have been conducted since the late 19th century. Soft tissue is any tissue in the body that is not hardened by ossification or calcification processes, such as bones and teeth; and varies according to sex, age, race, and nutritional status. Forensically, soft tissue thickness plays an important role in cases where a cadaver has no unique characteristics; and the remains cannot be identified through DNA analysis, fingerprints, or examination of dental records. Therefore, the results of the current study suggest that the average thickness of the three skeletal classes (i.e., straight, concave, and convex) should be used for face restoration and forensic art research. It is thought that the current study's results will be invaluable in the fields of forensic science, forensic art, anthropology, and dentistry. As a result, gender differences were observed in all classes, and the facial tissue thickness in Korean adults differed according to gender and occlusion type.

Lip morphology estimation models based on three-dimensional images in a modern adult population from China

Lips are the main part of the lower facial soft tissue and are vital to forensic facial approximation (FFA). Facial soft tissue thickness (FSTT) and linear measurements in three dimensions are used in the quantitative analysis of lip morphology. With most FSTT analysis methods, the surface of soft tissue is unexplicit. Our study aimed to determine FSTT and explore the relationship between the hard and soft tissues of lips in different skeletal occlusions based on cone-beam CT (CBCT) and 3dMD images in a Chinese population. The FSTT of 11 landmarks in CBCT and 29 lip measurements in CBCT and 3dMD of 180 healthy Chinese individuals (90 males, 90 females) between 18 and 30 years were analyzed. The subjects were randomly divided into two groups with different skeletal occlusions distributed equally: 156 subjects in the experimental group to establish the prediction regression formulae of lip morphology and 24 subjects in the test group to assess the accuracy of the formulae. The results indicated that FSTT in the lower lip region varied among different skeletal occlusions. Furthermore, sex discrepancy was noted in the FSTT in midline landmarks and linear measurements. Measurements showing the highest correlation between soft and hard tissues were between total upper lip height and Ns-Pr (0.563 in males, 0.651 in females). The stepwise multiple regression equations were verified to be reliable with an average error of 1.246 mm. The method of combining CBCT with 3dMD provides a new perspective in predicting lip morphology and expands the database for FFA.

Using Computed Tomography (CT) Data to Build 3D Resources for Forensic Craniofacial Identification

Forensic craniofacial identification encompasses the practices of forensic facial approximation (aka facial reconstruction) and craniofacial superimposition within the field of forensic art in the United States. Training in forensic facial approximation methods historically has used plaster copies, high-cost commercially molded skulls, and photographs. Despite the increased accessibility of computed tomography (CT) and the numerous studies utilizing CT data to better inform facial approximation methods, 3D CT data have not yet been widely used to produce interactive resources or reference catalogs aimed at forensic art practitioner use or method standardization. There are many free, open-source 3D software packages that allow engagement in immersive studies of the relationships between the craniofacial skeleton and facial features and facilitate collaboration between researchers and practitioners. 3D CT software, in particular, allows the bone and soft tissue to be visualized simultaneously with tools such as transparency, clipping, and volume rendering of underlying tissues, allowing for more accurate analyses of bone to soft tissue relationships. Analyses and visualization of 3D CT data can not only facilitate basic research into facial variation and anatomical relationships relevant for reconstructions but can also lead to improved facial reconstruction guidelines. Further, skull and face surface models exported in digital 3D formats allow for 3D printing of custom reference models and novel training materials and modalities for practitioners. This chapter outlines the 3D resources that can be built from CT data for forensic craniofacial identification methods, including how to view 3D craniofacial CT data and modify surface models for 3D printing.

Facial average soft tissue depth variation based on skeletal classes in Indonesian adult population: A retrospective lateral cephalometric study

OBJECTIVE

To understand the influence of three types of skeletal classes (Class I, Class II and Class III) on midline average soft tissue depth (ASTD).

METHODS

Lateral cephalograms of 335 pre-treatment orthodontic patients were obtained from the archive of Radiology Clinic Universitas Padjadjaran Dental Hospital Bandung Indonesia. The linear measurements of 10 midline facial landmarks ASTD and angular measurement of ANB were extracted and analysed statistically.

RESULTS

A database of ASTD grouped by skeletal classes, specific for the Indonesian population, within the South East Asian ancestry group was obtained.

CONCLUSIONS

A generic pattern of deeper upper lip than lower lip in class III compared to class II and conversely, deeper lower lip than upper lip in class II compared to class III, was visible in both male and female groups.

Facial soft tissue thicknesses in craniofacial identification: Data collection protocols and associated measurement errors

Facial soft tissue thicknesses (FSTT) form a key component of craniofacial identification methods, but as for any data, embedded measurement errors are highly pertinent. These in part dictate the effective resolution of the measurements. As herein reviewed, measurement methods are highly varied in FSTT studies and associated measurement errors have generally not been paid much attention. Less than half (44%) of 95 FSTT studies comment on measurement error and not all of these provide specific quantification. Where informative error measurement protocols are employed (5% of studies), the mean error magnitudes range from 3% to 45% rTEM and are typically in the order of 10-20%. These values demonstrate that FSTT measurement errors are similar in size to (and likely larger than) the magnitudes of many biological effects being chased. As a result, the attribution of small millimeter or submillimeter differences in FSTT to biological variables must be undertaken with caution, especially where they have not been repeated across different studies/samples. To improve the integrity of FSTT studies and the reporting of FSTT measurement errors, we propose the following standard: (1) calculate the technical error of measurement (TEM or rTEM) in any FSTT research work; (2) assess the error embedded in the full data collection procedure; and (3) conduct validation testing of FSTT means proposed for point estimation prior to publication to ensure newly calculated FSTT means provide improvements. In order to facilitate the latter, a freely available R tool TDValidator that uses the C-Table data for validation testing is provided.

The Influence of Facial Muscle Training on the Facial Soft Tissue Profile: A Brief Review

In this review, we summarize recent literature investigating facial-exercise-induced changes in facial soft tissue. A literature search was performed in PubMed for the terms facial exercise, rejuvenation, muscle, skin, and aging. Four studies were identified from the search and were subject to further assessment. Four studies were included in our analysis. Two of the four studies included compared the experimental (training) group to a control group. The other two studies had no control group. The participants were mainly middle-aged women. Training conditions varied; neuromuscular electrical stimulation (NMES) was used in two studies, the other two studies used an oscillatory movement device and voluntary facial isometric exercise. Two studies measured facial muscle size using ultrasonography before and after 12 weeks of NMES or 8 weeks of oscillatory movement of the face. One study assessed the changes in facial skin elasticity in a single group following 8 weeks of facial isometric exercise, while one study measured strength of labial and lingual muscles before and following 4 weeks of NMES. We found two studies that reported facial-exercise-induced increases in facial muscle size in middle-aged women. It was also reported that facial skin function may improve following facial isometric exercise. Future research is needed to clarify how these changes link with facial rejuvenation. Compared to extremity muscles, the facial muscles are small in size, their shapes are complex, and the boundaries with other tissues may be unclear. Future study is also necessary to examine the reliability of measurements of the facial muscles.

Midsagittal facial soft tissue thickness norms in an adult Mediterranean population

The use of facial soft tissue thickness (FSTT) values is essential in forensic facial approximation. Few studies have assessed the FSTT norms in Mediterranean populations and none in the Lebanese population. The purpose of this study was to (1) present midsagittal facial FSTT norms for Lebanese adults with well-balanced faces and normal occlusion; (2) evaluate the presence of sexual dimorphism within these measurements; (3) establish a potential correlation between these measurements and (4) build on the existing database of FSTT data from previously published studies. FSTT measurements at 10 midsagittal locations were obtained from the lateral cephalometric radiographs of 87 males and 135 females (mean age of 23.49±6.24years). In additional to means, Shorth and 75-Shormax values are presented. Differences between sexes were assessed using the MANOVA test and correlations between different measurements were computed. The thinnest (3.07±0.72mm) and thickest (15.61±2.38mm) craniofacial soft tissue measurements existed at Rhinion and Subnasale, respectively. There was a statistically significant and large effect of sex on the combined FSTT variables (p<0.001; eta-squared=0.393). Males displayed larger FSTT values at all landmarks except at Glabella (p=0.162). Significant correlations were observed between almost all measurements with the highest being between the upper and lower lips (r=0.763) and between Pogonion and Gnathion (r=0.784). The descriptive values of FSTT values reported in this study add to the body of research necessary for the enhancement of facial approximation methods The uniquely strong effects of sex on FSTT measurements combined and on selected single FSTT measurements are an area for further research.

An overview of the latest developments in facial imaging

Facial imaging is a term used to describe methods that use facial images to assist or facilitate human identification. This pertains to two craniofacial identification procedures that use skulls and faces-facial approximation and photographic superimposition-as well as face-only methods for age progression/regression, the construction of facial graphics from eyewitness memory (including composites and artistic sketches), facial depiction, face mapping and newly emerging methods of molecular photofitting. Given the breadth of these facial imaging techniques, it is not surprising that a broad array of subject-matter experts participate in and/or contribute to the formulation and implementation of these methods (including forensic odontologists, forensic artists, police officers, electrical engineers, anatomists, geneticists, medical image specialists, psychologists, computer graphic programmers and software developers). As they are concerned with the physical characteristics of humans, each of these facial imaging areas also falls in the domain of physical anthropology, although not all of them have been traditionally regarded as such. This too offers useful opportunities to adapt established methods in one domain to others more traditionally held to be disciplines within physical anthropology (e.g. facial approximation, craniofacial superimposition and face photo-comparison). It is important to note that most facial imaging methods are not currently used for identification but serve to assist authorities in narrowing or directing investigations such that other, more potent, methods of identification can be used (e.g. DNA). Few, if any, facial imaging approaches can be considered honed end-stage scientific methods, with major opportunities for physical anthropologists to make meaningful contributions. Some facial imaging methods have considerably stronger scientific underpinnings than others (e.g. facial approximation versus face mapping), some currently lie entirely within the artistic sphere (facial depiction), and yet others are so aspirational that realistic capacity to obtain their aims has strongly been questioned despite highly advanced technical approaches (molecular photofitting). All this makes for a broad-ranging, dynamic and energetic field that is in a constant state of flux. This manuscript provides a theoretical snapshot of the purposes of these methods, the state of science as it pertains to them, and their latest research developments.

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.

Male and Female Characteristics of Facial Soft Tissue Thickness in Different Orthodontic Malocclusions Evaluated by Cephalometric Radiography

Background

The facial profile is determined by the facial soft tissue thickness (FSTT) and dentoskeletal characteristics. The aim of this study was to compare male and female characteristics of FSTT in different orthodontic malocclusions using cephalometric radiography.

Material/Methods

One hundred and twenty lateral cephalometric radiography-derived cephalograms of adult male (n=47) and female (n=73) orthodontic patients, aged between 16–22 years were classified according to their dentoskeletal relationships as Class I (n=30), Class II Division 1 (n=30), Class II Division 2 (n=30), Class III (n=30). Burstone analysis of seven linear dimensions of FSTT was used.

Results

Men had a thicker FSTT in dentoskeletal relationships Class I, Class II Division 2, and Class III. Sex differences varied from significant (t=2.056; p<0.05) for the sub-nasal area in Class II Division 2, to highly significant (t=3.772; p<0.001) for the upper lip sulcus in Class II Division 2. Women in Class II Division 1 had significantly thicker FSTT in the lower jaw area (t=2.800; p<0.01) and for the lower lip sulcus and the chin area (t=3.961; p<0.001).

Conclusions

Men with orthodontic malocclusions were characterized by thicker facial soft tissue compared with female patients in Class I and Class II Division 2; female patients in Class II Division 1 were characterized by thicker facial soft tissue of the mentolabial sulcus and chin. Men and women with a skeletal jaw relationship in Class III showed no significant difference in their FSTT.

Facial soft tissue thickness (FSTT) estimation models-And the strength of correlations between craniometric dimensions and FSTTs

It has been speculated that craniometric dimensions can be used to improve estimations of facial soft tissue thickness (FSTT) in craniofacial identification. Subsequently, linear regression (LR) models have been published, but the practical utility of these models (lower errors than means) has never been tested/demonstrated. Using 71 living subjects measured by B-mode ultrasound, this study calculates and compares standard errors for previously published LR models and untrimmed FSTT means. Correlations between craniometric dimensions and FSTTs were calculated and regression model reproducibility examined by: generating new models using a 61 subject training set; and three-fold cross validation. Published regression models, applied to the above mentioned new individuals of this study, provided substantially worse estimates of ground truth FSTTs than untrimmed arithmetic means (mean S_est=4.0mm compared to 2.8mm, n=61-71). Correlations between craniometrics and FSTTs were generally small (mean of absolute values=0.17, raw interval=-0.24 to 0.48) and only two of 15 previously published LR models were reproducible (mr-mr' and g-g')-i.e., contained the same independent variable with no more than one other different independent variable entering the model. Under three-fold cross-validation (training sets of 40-41 individuals), no LR equation was reproduced across all three validation test runs. Basic craniometric dimensions do not appear to generally improve FSTT estimations and relationships between craniometric dimensions and FSTTs are much weaker and less reliable than previously thought. B-mode ultrasound data for adult Australians were pooled herein to provide larger sampled and updated FSTT statistics for this cohort (n=118-123).

Densely calculated facial soft tissue thickness for craniofacial reconstruction in Chinese adults

Craniofacial reconstruction (CFR) is used to recreate a likeness of original facial appearance for an unidentified skull; this technique has been applied in both forensics and archeology. Many CFR techniques rely on the average facial soft tissue thickness (FSTT) of anatomical landmarks, related to ethnicity, age, sex, body mass index (BMI), etc. Previous studies typically employed FSTT at sparsely distributed anatomical landmarks, where different landmark definitions may affect the contrasting results. In the present study, a total of 90,198 one-to-one correspondence skull vertices are established on 171 head CT-scans and the FSTT of each corresponding vertex is calculated (hereafter referred to as densely calculated FSTT) for statistical analysis and CFR. Basic descriptive statistics (i.e., mean and standard deviation) for densely calculated FSTT are reported separately according to sex and age. Results show that 76.12% of overall vertices indicate that the FSTT is greater in males than females, with the exception of vertices around the zygoma, zygomatic arch and mid-lateral orbit. These sex-related significant differences are found at 55.12% of all vertices and the statistically age-related significant differences are depicted between the three age groups at a majority of all vertices (73.31% for males and 63.43% for females). Five non-overlapping categories are given and the descriptive statistics (i.e., mean, standard deviation, local standard deviation and percentage) are reported. Multiple appearances are produced using the densely calculated FSTT of various age and sex groups, and a quantitative assessment is provided to examine how relevant the choice of FSTT is to increasing the accuracy of CFR. In conclusion, this study provides a new perspective in understanding the distribution of FSTT and the construction of a new densely calculated FSTT database for craniofacial reconstruction.