Simulating full-facial injectable aesthetic procedures using biomechanics and python: A computational approach for predicting soft tissue deformation in private aesthetic clinics
Abstract
Injectable aesthetic procedures, such as dermal fillers, have become increasingly popular for facial rejuvenation. However, predicting the deformation of soft tissues during these procedures remains a challenge. This study presents a biomechanical model that combines finite element analysis (FEA) and Python programming to simulate soft tissue deformation during full-facial injectable treatments. The model integrates patient-specific anatomical data to predict the spread and effect of injectable materials, considering factors such as volume, material properties, and underlying facial musculature. Performance metrics, including Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), were calculated and compared against clinical data, demonstrating strong predictive accuracy. The results show that the model effectively simulates localized tissue expansion and provides insights into how different injection volumes and filler viscosities affect tissue deformation. The model’s ability to simulate muscle-filler interactions and predict long-term filler behavior offers significant potential for enhancing treatment planning and optimizing outcomes. Despite its strengths, the model has limitations, including simplified tissue properties and the exclusion of long-term filler behavior. Future research should focus on incorporating more dynamic muscle activity, patient-specific tissue data, and long-term effects to refine the model further. This work provides a valuable foundation for personalized, data-driven approaches to injectable aesthetic procedures.
References
1. Ramirez SPB, Scherz G, Smith H. Characteristics of patients seeking and proceeding with non-surgical facial aesthetic procedures. Clin Cosmet Investig Dermatol. 2021; 14: 197-207. doi: 10.2147/CCID.S296970
2. Fabi S, Alexiades M, Chatrath V, Colucci L. Facial aesthetic priorities and concerns: a physician and patient perception global survey. Aesthet Surg J. 2022; 42(4): NP218-NP229. doi: 10.1093/asj/sjab358
3. Shome D, van der Hulst RRWJ, Kumar V. Evolution and trends of facial plastic surgery and facial aesthetic procedures. Aesthetic Surgery Journal Open Forum. 2023; 5: ojad022. doi: 10.1093/asjof/ojad022
4. Trévidic P, Kaufman-Janette J, Weinkle S. Injection guidelines for treating midface volume deficiency with hyaluronic acid fillers. Aesthet Surg J. 2022; 42(8): 920-934. doi: 10.1093/asj/sjac007
5. Cotofana S, Gaete A, Hernandez CA. Biomechanical aspects of soft tissues. Springer Verlag.
6. De Maio M. Myomodulation with injectable fillers: an innovative approach to addressing facial muscle movement. Aesthetic Plast Surg. 2018; 42(3): 798-814.
7. Attenello NH, Maas CS. Injectable fillers: review of material and properties. Facial Plast Surg. 2015; 31(1): 29-34. doi: 10.1055/s-0035-1544924
8. Cassuto D, Bellia G, Schiraldi C. An overview of soft tissue fillers in cosmetic dermatology. J Cosmet Dermatol. 2021; 14: 1857-1866. doi: 10.2147/CCID.S276676
9. Lee W, Hwang SG, Oh W, et al. Practical Guidelines for Hyaluronic Acid Soft-Tissue Filler Use in Facial Rejuvenation. Dermatologic Surgery. 2020; 46(1): 41-49. doi: 10.1097/dss.0000000000001858
10. Cotofana S, Arsiwala SD, Fagien S. Myomodulation with facial fillers: a comprehensive technical guide and retrospective case series. Aesthetic Surg J. 2022; 42(12): 1343-1356.
11. Mazza E, Barbarino GG. 3D mechanical modeling of facial soft tissue for surgery simulation. Facial Plast Surg Clin North Am. 2011; 19(4): 623-637, viii. doi: 10.1016/j.fsc.2011.07.006
12. Chabanas M, Luboz V, Payan Y. Patient specific finite element model of the face soft tissues for computer-assisted maxillofacial surgery. Med Image Anal. 2003; 7(4): 423-431.
13. Barbarino GG, Jabareen M, Trzewik J, et al. Development and Validation of a Three-Dimensional Finite Element Model of the Face. Journal of Biomechanical Engineering. 2009; 131(4). doi: 10.1115/1.3049857
14. Mollemans W, Schutyser F, Nadjmi N, et al. Predicting soft tissue deformations for a maxillofacial surgery planning system: From computational strategies to a complete clinical validation. Medical Image Analysis. 2007; 11(3): 282-301. doi: 10.1016/j.media.2007.02.003
15. Sifakis LC, Sifakis E, Terzopoulos D. A Finite-Element Facial Model for Simulating Plastic Surgery. Journal of Biomechanical Engineering. 1995; 117(3): 269-276.
16. Lisiak-Myszke M, Marciniak D, Bieliński M, et al. Application of Finite Element Analysis in Oral and Maxillofacial Surgery—A Literature Review. Materials. 2020; 13(14): 3063. doi: 10.3390/ma13143063
17. Wu T, Hung APL, Mithraratne K. Generating facial expressions using an anatomically accurate biomechanical model. IEEE Trans Biomed Eng. 2014; 20(11): 1519-1529. doi: 10.1109/TVCG.2014.2339835
18. Zeng XS, Dwarakanath S, Lu W, Nakada M, et al. Neuromuscular Control of the Face-Head-Neck Biomechanical Complex With Learning-Based Expression Transfer From Images and Videos. arXiv preprint arXiv:2111.06517. 2021. doi: 10.48550/arXiv.2111.06517
19. Kim H, Jürgens P, Weber S, et al. A new soft-tissue simulation strategy for cranio-maxillofacial surgery using facial muscle template model. Progress in Biophysics and Molecular Biology. 103(2–3): 284-291.
20. Belabed Z, Tounsi A, Bousahla AA, et al. Accurate free and forced vibration behavior prediction of functionally graded sandwich beams with variable cross-section: A finite element assessment. Mechanics Based Design of Structures and Machines. 2024; 52(11): 9144-9177. doi: 10.1080/15397734.2024.2337914
21. Tounsi A, Belabed Z, Bounouara F, et al. A Finite Element Approach for Forced Dynamical Responses of Porous FG Nanocomposite Beams Resting on Viscoelastic Foundations. International Journal of Structural Stability and Dynamics. 2024. doi: 10.1142/s0219455426500781
22. Belabed Z, Bousahla AA, Tounsi A, et al. Free vibration analysis of Bi-Directional Functionally Graded Beams using a simple and efficient finite element model. Struct Eng Mech. 2024; 90(3): 233–252.
23. Belabed Z, Bousahla AA, Tounsi A. Vibrational and elastic stability responses of functionally graded carbon nanotube reinforced nanocomposite beams via a new Quasi-3D finite element model. Comput Concr. 2024; 34(5): 625–648.
24. Lakhdar Z, Chorfi SM, Belalia SA, et al. Free vibration and bending analysis of porous bi-directional FGM sandwich shell using a TSDT p-version finite element method. Acta Mechanica. 2024; 235(6): 3657-3686. doi: 10.1007/s00707-024-03909-y
Copyright (c) 2025 Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright on all articles published in this journal is retained by the author(s), while the author(s) grant the publisher as the original publisher to publish the article.
Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International, which means they can be shared, adapted and distributed provided that the original published version is cited.
Submit a Paper
