In-vivo facial soft-tissue thickness measurement

1998 ◽  
Author(s):  
Haidong Liang ◽  
Abdul Daya ◽  
Steven Hughes
Keyword(s):  
Soft Tissue ◽  
Thickness Measurement ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Soft Tissue Thickness

Large-scale in-vivo Caucasian facial soft tissue thickness database for craniofacial reconstruction

2006 ◽  
Vol 159 ◽  
pp. S126-S146 ◽  
Author(s):  
S. De Greef ◽  
P. Claes ◽  
D. Vandermeulen ◽  
W. Mollemans ◽  
P. Suetens ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Large Scale ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Craniofacial Reconstruction ◽  
Soft Tissue Thickness

scholarly journals Evaluation of the facial soft tissue thickness in a Brazilian in vivo population "facial soft tissue thickness in Brazilians"

2018 ◽  
Vol 33 (4) ◽  
pp. 518-527
Author(s):  
MARÍLIA MOURA FREITAS DA-SILVA ◽  
GABRIELA GRANJA PORTO ◽  
ANTÔNIO AZOUBEL ANTUNES ◽  
EVELYNE PESSOA SORIANO ◽  
MARCUS VITOR DINIZ DE-CARVALHO ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Soft Tissue Thickness

In vivo facial soft tissue thickness measurements for Turkish Subadults

2015 ◽  
Vol 47 (4) ◽  
pp. 475-490 ◽  
Author(s):  
Ozgur Bulut ◽  
Namik Kemal Altinbas ◽  
Havva Akmaz Unlu ◽  
Ismail Hizliol ◽  
Taner Bora ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Soft Tissue Thickness ◽  
Thickness Measurements

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

scholarly journals Improvement of biohistological response of facial implant materials by tantalum surface treatment

2019 ◽  
Vol 41 (1) ◽  
Author(s):  
Mohammed Mousa Bakri ◽  
Sung Ho Lee ◽  
Jong Ho Lee
Keyword(s):  
Foreign Body ◽  
Soft Tissue ◽  
Surface Treatment ◽  
Clinical Applications ◽  
Tissue Response ◽  
Bone Surface ◽  
Tissue Thickness ◽  
Implant Materials ◽  
Soft Tissue Thickness

Abstract Background A compact passive oxide layer can grow on tantalum (Ta). It has been reported that this oxide layer can facilitate bone ingrowth in vivo though the development of bone-like apatite, which promotes hard and soft tissue adhesion. Thus, Ta surface treatment on facial implant materials may improve the tissue response, which could result in less fibrotic encapsulation and make the implant more stable on the bone surface. The purposes of this study were to verify whether surface treatment of facial implant materials using Ta can improve the biohistobiological response and to determine the possibility of potential clinical applications. Methods Two different and commonly used implant materials, silicone and expanded polytetrafluoroethylene (ePTFE), were treated via Ta ion implantation using a Ta sputtering gun. Ta-treated samples were compared with untreated samples using in vitro and in vivo evaluations. Osteoblast (MG-63) and fibroblast (NIH3T3) cell viability with the Ta-treated implant material was assessed, and the tissue response was observed by placing the implants over the rat calvarium (n = 48) for two different lengths of time. Foreign body and inflammatory reactions were observed, and soft tissue thickness between the calvarium and the implant as well as the bone response was measured. Results The treatment of facial implant materials using Ta showed a tendency toward increased fibroblast and osteoblast viability, although this result was not statistically significant. During the in vivo study, both Ta-treated and untreated implants showed similar foreign body reactions. However, the Ta-treated implant materials (silicone and ePTFE) showed a tendency toward better histological features: lower soft tissue thickness between the implant and the underlying calvarium as well as an increase in new bone activity. Conclusion Ta surface treatment using ion implantation on silicone and ePTFE facial implant materials showed the possibility of reducing soft tissue intervention between the calvarium and the implant to make the implant more stable on the bone surface. Although no statistically significant improvement was observed, Ta treatment revealed a tendency toward an improved biohistological response of silicone and ePTFE facial implants. Conclusively, tantalum treatment is beneficial and has the potential for clinical applications.

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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