scholarly journals Orthodontists in forensic facial approximation (FFA): current inter-disciplinary perspective

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Priyanka Kapoor ◽  
Aman Chowdhry ◽  
Deepika Bablani Popli
Keyword(s):  
Soft Tissue ◽  
Three Dimensional ◽  
Data Retrieval ◽  
Forensic Odontology ◽  
Normative Values ◽  
Facial Soft Tissue ◽  
Research Areas ◽  
Soft Tissue Thickness ◽  
Facial Approximation ◽  
General Dentists

AbstractForensic odontology has contributed significantly in forensic investigations and involves various branches of dentistry including orthodontics. The current communication presents evidence-based perspective highlighting synergistic union of different specialties for Forensic Facial Approximation (FFA). It brings forth commonality in principles of anthropology, forensic science, anthropometry, anatomy, paleontology, forensic odontology, with orthodontics, used in FFA. Various attributes and skills of orthodontists’ aid in dental and skull profiling and the corresponding sex, age, and ethnicity-based soft tissue assessments for facial soft tissue thickness (FSTT), may aid a life-like appearance. They can assist hard tissue profiling by their expertise in growth of skeletal and soft tissue, along with the evolutionary trends in occlusion, and diet formulations. Their knowledge in identifying teeth patterns, dental/skeletal jaw relationships, cranial/facial indices, vertical/horizontal facial proportions, can help prepare skull for orientation and reconstruction. The dental, photographic, and radiographic records maintained by orthodontists and general dentists are instrumental in data retrieval, used in various software, clinical, or research areas. These can provide normative values for comparative analysis or facial recreation. The orthodontists can also assist anthropologists and forensic specialists in the virtual reconstructions due to their ease in using latest digital technologies including three-dimensional (3D) facial scan, stereo-photogrammetry, 3D printing, automated soft-tissue landmarks, growth, and age predictions. Thus, the current study established the commonality in concepts of various forensic disciplines with orthodontics, which can strengthen both forensic on-field facial approximations and hard/soft tissue research to further enhance the accuracy of contemporary digital software used in FFA.

scholarly journals A computerized facial approximation method for archaic humans based on dense facial soft tissue thickness depths

2021 ◽  
Vol 13 (11) ◽  
Author(s):  
Wuyang Shui ◽  
Yameng Zhang ◽  
Xiujie Wu ◽  
Mingquan Zhou
Keyword(s):  
Soft Tissue ◽  
Modern Human ◽  
Middle Pleistocene ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Skull Morphology ◽  
Morphological Variations ◽  
Soft Tissue Thickness ◽  
Facial Approximation ◽  
Upper Face

Abstract Facial approximation (FA) is a common tool used to recreate the possible facial appearance of a deceased person based on the relationship between soft tissue and the skull. Although this technique has been primarily applied to modern humans in the realm of forensic science and archaeology, only a few studies have attempted to produce FAs for archaic humans. This study presented a computerized FA approach for archaic humans based on the assumption that the facial soft tissue thickness depths (FSTDs) of modern living humans are similar to those of archaic humans. Additionally, we employed geometric morphometrics (GM) to examine the geometric morphological variations between the approximated faces and modern human faces. Our method has been applied to the Jinniushan (JNS) 1 archaic human, which is one of the most important fossils of the Middle Pleistocene, dating back to approximately 260,000 BP. The overall shape of the approximated face has a relatively lower forehead and robust eyebrows; a protruding, wider, and elongated middle and upper face; and a broad and short nose. Results also indicate skull morphology and the distribution of FSTDs influence the approximated face. These experiments demonstrate that the proposed method can approximate a plausible and reproducible face of an archaic human.

The development and testing of Thai facial soft tissue thickness data in three-dimensional computerized forensic facial reconstruction

2021 ◽  
pp. 002580242110576
Author(s):  
Pagorn Navic ◽  
Patison Palee ◽  
Sangsom Prapayasatok ◽  
Sukon Prasitwattanaseree ◽  
Apichat Sinthubua ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Computer Animation ◽  
Three Dimensional ◽  
Facial Reconstruction ◽  
Forensic Investigation ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Thai Population ◽  
Soft Tissue Thickness ◽  
Virtual Face

Forensic facial reconstruction is a useful tool to assist the public in recognizing human remains, leading to positive forensic investigation outcomes. To reproduce a virtual face, facial soft tissue thickness is one of the major guidelines to reach the accuracy and reliability for three-dimensional computerized facial reconstruction, a method that is making a significant contribution to improving forensic investigation and identification. This study aimed to develop a facial soft tissue thickness dataset for a Thai population, and test its reliability in the context of facial reconstruction. Three-dimensional facial reconstruction was conducted on four skulls (2 males and 2 females, with ages ranging between 51 to 60 years). Two main tools of three-dimensional computer animation and modeling software—Blender and Autodesk Maya—were used to rebuild the three-dimensional virtual face. The three-dimensional coordinate ( x, y, z) cutaneous landmarks on the mesh templates were aligned homologous to the facial soft tissue thickness markers on the three-dimensional skull model. The final three-dimensional virtual face was compared to the target frontal photograph using face pool comparison. Four three-dimensional virtual faces were matched at low to moderate levels, ranging from 30% to 70% accuracy. These results demonstrate that the facial soft tissue thickness database of a Thai population applied in this study could be useful for three-dimensional computerized facial reconstruction purposes.

A dense approach for computation of facial soft tissue thickness data

2021 ◽  
pp. 200460
Author(s):  
Diana Toneva ◽  
Silviya Nikolova ◽  
Stanislav Harizanov ◽  
Dora Zlatareva ◽  
Vassil Hadjidekov
Keyword(s):  
Soft Tissue ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Soft Tissue Thickness

Midsagittal facial soft tissue thickness norms in an adult Mediterranean population

2019 ◽  
Vol 294 ◽  
pp. 217.e1-217.e7 ◽  
Author(s):  
Fouad Ayoub ◽  
Maria Saadeh ◽  
Georges Rouhana ◽  
Ramzi Haddad
Keyword(s):  
Soft Tissue ◽  
Mediterranean Population ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Soft Tissue Thickness

“A NOVEL ATTEMPT IN ESTIMATION OF FETAL WEIGHT USING NEW SOFT TISSUE MEASUREMENTS”

2021 ◽  
pp. 1-3
Author(s):  
Sathyan Gnanasigamani ◽  
Sudhakar Vadivel ◽  
Bala Subramaniam ◽  
Sakthivel Raja Ganesan ◽  
Pradeebaa Thiyagarajan ◽  
...  
Keyword(s):  
Birth Weight ◽  
Soft Tissue ◽  
Strong Predictor ◽  
Three Dimensional ◽  
Fetal Weight ◽  
Ultrasound Measurement ◽  
Accurate Estimation ◽  
Tissue Thickness ◽  
Third Trimester ◽  
Soft Tissue Thickness

Background: The Accurate estimation of fetal weight is important in modern obstetrics. Currently, Hadlock's formula is used widely for fetal weight estimation, which includes BPD, AC, FL and HC. The correct plane of measurement of various standard parameters is difcult to obtain especially in third trimester. Hence soft tissue thicknesses of the fetus are tested for correlation with birth weight in this study. Materials & Methods: A prospective observational study conducted among 90 pregnant females referred for Ultrasound examination in the third trimester with an interval from the ultrasound scan to delivery of ≤7 days from 2019 to 2020. Results: The measurements of abdominal, fetal mid-thigh and mid-arm soft tissue thicknesses correlated well with birth weight in a high statistically signicant positive linear relationship. A new regression model developed out of the soft tissue thicknesses(FASTT, FMASTT, FTSTT) correlates better than the Hadlock's model and Sujitkumar Hiwale et al model (For Indian population) based on BPD, HC, AC and FL Conclusion: Ultrasound measurement of soft tissue thickness may prove to be a strong predictor of fetal weight essential for sonographic assessment of pregnancy. They are easy and simple hence fetal soft tissue thickness measurements, both two- and three-dimensional, may prove to be a diagnostic parameter that has as small an error rate as possible, is quick to use and reproducible by different examiners

Testing regression and mean model approaches to facial soft-tissue thickness estimation

2020 ◽  
pp. 002580242097701
Author(s):  
Tobias MR Houlton ◽  
Nicolene Jooste ◽  
Maryna Steyn
Keyword(s):  
Soft Tissue ◽  
Regression Model ◽  
South African ◽  
Goodness Of Fit ◽  
Regression Equations ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Soft Tissue Thickness ◽  
Subject Specific ◽  
Model Approach

Average facial soft-tissue thickness (FSTT) databanks are continuously developed and applied within craniofacial identification. This study considered and tested a subject-specific regression model alternative for estimating the FSTT values for oral midline landmarks using skeletal projection measurements. Measurements were taken from cone-beam computed tomography scans of 100 South African individuals (60 male, 40 female; Mage = 35 years). Regression equations incorporating sex categories were generated. This significantly improved the goodness-of-fit ( r2-value). Validation tests compared the constructed regression models with mean FSTT data collected from this study, existing South African FSTT data, a universal total weighted mean approach with pooled demographic data and collection techniques and a regression model approach that uses bizygomatic width and maximum cranial breadth dimensions. The generated regression equations demonstrated individualised results, presenting a total mean inaccuracy (TMI) of 1.53 mm using dental projection measurements and 1.55 mm using cemento-enamel junction projection measurements. These slightly outperformed most tested mean models (TMI ranged from 1.42 to 4.43 mm), and substantially outperformed the pre-existing regression model approach (TMI = 5.12 mm). The newly devised regressions offer a subject-specific solution to FSTT estimation within a South African population. A continued development in sample size and validation testing may help substantiate its application within craniofacial identification.

Three-Dimensional Analysis Techniques—Part 1: Three-Dimensional Soft-Tissue Analysis of 24 Adult Cleft Palate Patients following Le Fort I Maxillary Advancement: A Preliminary Report

1997 ◽  
Vol 34 (1) ◽  
pp. 36-45 ◽  
Author(s):  
Andrew M. Mccance ◽  
James P. Moss ◽  
W. Rick Fright ◽  
Alf D. Linney ◽  
David R. James
Keyword(s):  
Soft Tissue ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Tissue Analysis ◽  
Facial Soft Tissue ◽  
Le Fort ◽  
Analysis Techniques ◽  
Tissue Changes ◽  
Soft Tissue Changes ◽  
Le Fort I

The three-dimensional, facial soft-tissue changes of 24 patients with various cleft types following transpalatal Le Fort I osteotomy were measured using laser scanning techniques, radial measurements, and a color millimetric scale. There was a varying degree of midface retrusion in the different cleft groups, and a very similar pattern of retrusion over the nasal complex. Each group of patients showed a varying degree of relapse postsurgically, but there was a failure in all the cleft groups to correct the lack of nasal projection.

scholarly journals Variation of Facial Soft Tissue Thickness in Nepalese Adult Orthodontic Subjects

2018 ◽  
Vol 8 (2) ◽  
pp. 22-28
Author(s):  
Ravi Kumar Mahto ◽  
Dashrath Kafle ◽  
Pankaj Kumar Singh ◽  
Sonika Khanal ◽  
Siddhartha Khanal
Keyword(s):  
Soft Tissue ◽  
Measurement Data ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Male And Female ◽  
Skeletal Class ◽  
Skeletal Malocclusion ◽  
Soft Tissue Thickness ◽  
Significant Difference ◽  
Female Subjects

Introduction: Variations in facial soft tissue thickness have been established previously by studies conducted in different population. Hence, it is essential to obtain facial soft tissue thickness measurement data specific to a population and develop individual standards. The objective of this research is to obtain facial soft tissue thickness data of Nepalese adult male and female subjects seeking orthodontic treatment with different sagittal skeletal malocclusion and evaluate variations in facial soft tissue thickness. Materials & Method: Facial soft tissue thicknesses was measured manually on ninety pretreatment lateral cephalogram at eleven points (Glabella, Nasion, Rhinion, Subnasale, Labrale superius, Stomion, Labrale inferius, Labiomentale, Pogonion,Gnathion and Menton). One-way Analysis of variances [one-way ANOVA] followed by Least significant difference (LSD) post hoc test was used to determine difference in facial soft tissue thickness measurements among three sagittal skeletal group for both sexes. In addition, Student’s t-test was used to find difference in facial soft tissue thickness between the male and female subjects in each skeletal Class. Result: Statistically significant differences were found at points Rhinion, Subnasale, Labrale superius, Stomion and Gnathion in males and at Subnasale, Labrale superius, Stomion and Labrale inferius in females while comparing facial soft tissue thickness among three sagittal skeletal classes. Also, it was observed that mean facial soft tissue thickness was greater for males as compared to female subjects with significant differences at Subnasale, Labrale superius, and Labrale inferius in each skeletal Class. Conclusion: Facial soft tissue thickness varies considerably among different population group, sex and sagittal relationship of jaws.

Sign in / Sign up

Export Citation Format

Share Document