BACKGROUND/ PURPOSE: This paper reports a study on the quasi-static mechanical response of the superficial soft tissue of the face, in particular the skin and the superficial muscoloaponeurotic system (SMAS) plus the superficial fat. The mechanical characterization of soft tissues represents one of the main uncertainties of previously developed numerical models for face simulation. METHODS: Two instruments based on the suction method were used for collecting experimental data: the Cutometer(®) (2 mm probe aperture diameter) and the Aspiration device (8 mm). Tests were performed in five different regions of the face (jaw, nasolabial, parotideomasseteric, zygomatic and forehead) on the same subject whose magnetic resonance imaging (MRI) scans were used to generate a full 3D finite element model of the face and for whom a series of experimental results for different loading cases are already available. The mechanical parameters of the tissue layers were determined through an inverse finite element analysis. Anatomical data (tissue layers' thickness) were determined through the analysis of a set of high-resolution MRI scans and ultrasound measurements performed in the regions tested. RESULTS: The results of Cutometer(®) measurements show a relatively homogeneous mechanical response in different face regions, while the results of aspiration device measurements, which involve deeper tissues, show a larger variability. Mechanical model parameters of the skin and SMAS were determined for two constitutive model equations: a hyperelastic model based on the Rubin-Bodner formulation and a reduced polynomial model of second order. CONCLUSION: The results reported in this work suggest that for simulations of the global behavior of facial soft tissue, such as craniofacial and maxillofacial surgery planning, the skin could be considered as a layer of uniform thickness and of uniform mechanical response through the different regions. Additionally, mechanical models were determined for skin and SMAS that could be used for simulations of surgical procedures requiring a distinction between these tissue layers.
BACKGROUND/ PURPOSE: This paper reports a study on the quasi-static mechanical response of the superficial soft tissue of the face, in particular the skin and the superficial muscoloaponeurotic system (SMAS) plus the superficial fat. The mechanical characterization of soft tissues represents one of the main uncertainties of previously developed numerical models for face simulation. METHODS: Two instruments based on the suction method were used for collecting experimental data: the Cutometer(®) (2 mm probe aperture diameter) and the Aspiration device (8 mm). Tests were performed in five different regions of the face (jaw, nasolabial, parotideomasseteric, zygomatic and forehead) on the same subject whose magnetic resonance imaging (MRI) scans were used to generate a full 3D finite element model of the face and for whom a series of experimental results for different loading cases are already available. The mechanical parameters of the tissue layers were determined through an inverse finite element analysis. Anatomical data (tissue layers' thickness) were determined through the analysis of a set of high-resolution MRI scans and ultrasound measurements performed in the regions tested. RESULTS: The results of Cutometer(®) measurements show a relatively homogeneous mechanical response in different face regions, while the results of aspiration device measurements, which involve deeper tissues, show a larger variability. Mechanical model parameters of the skin and SMAS were determined for two constitutive model equations: a hyperelastic model based on the Rubin-Bodner formulation and a reduced polynomial model of second order. CONCLUSION: The results reported in this work suggest that for simulations of the global behavior of facial soft tissue, such as craniofacial and maxillofacial surgery planning, the skin could be considered as a layer of uniform thickness and of uniform mechanical response through the different regions. Additionally, mechanical models were determined for skin and SMAS that could be used for simulations of surgical procedures requiring a distinction between these tissue layers.
Authors: Alessandra Aldieri; Mara Terzini; Cristina Bignardi; Elisabetta M Zanetti; Alberto L Audenino Journal: Med Biol Eng Comput Date: 2018-05-19 Impact factor: 2.602
Authors: Paul G M Knoops; Alessandro Borghi; Federica Ruggiero; Giovanni Badiali; Alberto Bianchi; Claudio Marchetti; Naiara Rodriguez-Florez; Richard W F Breakey; Owase Jeelani; David J Dunaway; Silvia Schievano Journal: PLoS One Date: 2018-05-09 Impact factor: 3.240
Authors: Bettina Müller; Julia Elrod; Marco Pensalfini; Raoul Hopf; Oliver Distler; Clemens Schiestl; Edoardo Mazza Journal: PLoS One Date: 2018-08-08 Impact factor: 3.240