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.

scholarly journals Modifications of Midfacial Soft-Tissue Thickness Among Different Skeletal Classes in Italian Children

2018 ◽  
Vol 10 (1) ◽  
pp. 1-8
Author(s):  
Daniele Gibelli ◽  
Matteo Zago ◽  
Annalisa Cappella ◽  
Claudia Dolci ◽  
Chiarella Sforza
Keyword(s):  
Soft Tissue ◽  
Soft Tissues ◽  
Class Ii ◽  
Class Iii ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Skeletal Class ◽  
Soft Tissue Thickness ◽  
Italian Children ◽  
The Relationship

Background: The anatomical assessment of the arrangement of facial soft tissues has important applications in different fields from orthodontics to plastic surgery. One of the issues concerns the relationship between facial soft tissue thickness and skeletal class. Literature mainly deals with adult populations, whereas very few studies have been focused on children. Objective: This study aims at investigating the relationship between midline facial soft tissue thickness and skeletal classes in Italian pre-treatment orthodontic child patients. Methods: Lateral cephalometric X-ray films were obtained from 220 healthy Caucasoid children (91 males and 129 females), aged between 6 and 18 years (Class I: 41 males and 70 females; Class II: 18 males and 25 females; Class III: 32 males and 34 females). All the films were digitized and 14 soft tissue thicknesses were measured on the midface; in addition, the skeletal class was assessed according to the corrected ANB angle (ANBc). Differences in facial soft tissue thickness according to sex and skeletal class were assessed through two-way ANOVA test (p<0.01). Results: Statistically significant differences according to sex were found for labrale superius, stomion and labrale inferius, with thicker soft tissues in males than in females (p<0.01). Only measurements at labrale superius and gnathion showed statistically significant differences according to skeletal class, with thicker soft tissues in Class III children and thinner ones in Class II children (p<0.01). Conclusion: The limited number of investigations, as well as the differences in protocols, renders the comparison of results from different studies difficult, suggesting further investigations to enlighten this complex and debated anatomical issue.

scholarly journals Evaluation of facial soft tissue thickness in asymmetric mandibular deformities after orthognathic surgery

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
Luo Huang ◽  
Zhicong Li ◽  
Jing Yan ◽  
Lunqiu Chen ◽  
Zheng-guo Piao
Keyword(s):  
Soft Tissue ◽  
Orthognathic Surgery ◽  
Class Iii ◽  
Class Iii Malocclusion ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Thickness Change ◽  
Skeletal Class ◽  
Soft Tissue Thickness ◽  
The Face

Abstract Objectives The purpose of this study was to compare differences in facial soft tissue thickness in three-dimensional (3D) images before and after orthognathic surgery in patients with skeletal Class III malocclusion and to obtain a better understanding of the relationship between hard and soft tissue changes after surgery. Materials and method The present retrospective study included 31 patients with skeletal Class III malocclusion with mandibular chin deviation greater than 4 mm who had undergone cone-beam computed tomography before and 6 months after surgery. Seven bilateral points were established. Measurements were taken from software-generated multiplanar reconstructions. The predictor variables were timing (pre- and postoperatively) and side (deviated vs. nondedicated). A regression model and correlation analysis were conducted for statistical analysis. Results The difference of bilateral facial soft tissue thickness was statistically significantly different between deviated and nondeviated sides (P < 0.05), with lower values observed on the deviated side. The soft tissue thickness has become nearly symmetric at local regions of the lower thirds of the face after orthognathic surgery. However, most measurements showed a negative correlation between changes in soft tissue thickness and changes in bone tissues. Conclusions Skeletal Class III malocclusion with facial asymmetry is accompanied by differences in soft tissue thickness when comparing Dev and N-Dev sides of the posterior region of the mandible, where soft tissues are thinner on the Dev side. Soft tissue thickness can compensate for or camouflage the underlying asymmetric mandible. In addition, the asymmetric soft tissue thickness on the lower third of the face can be partially improved by orthognathic surgery, but the amount of soft tissue thickness change is not consistent with that of hard tissue positional change.

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

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.

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