Emerging Technologies for Assessing Anthropometric and Dental Variables in the Aging Face - A Scoping Review
Main Article Content
Abstract
Age-related changes in craniofacial morphology—such as skeletal resorption, soft tissue volume loss, altered occlusion, and progressive tooth loss—profoundly affect the vertical dimension and overall aesthetic balance of the ageing face. For plastic surgeons seeking comprehensive facial rejuvenation, these anatomical alterations present both challenges and opportunities. Traditional assessment methods, including two-dimensional imaging and manual anthropometry, often fall short in capturing the complex, three-dimensional interplay between facial structures and dentition. Recent advances in digital technologies—such as three-dimensional facial scanning, cone-beam computed tomography, digital intraoral scanning, and artificial intelligence -driven morphometric analysis—offer high-resolution, reproducible, and non-invasive alternatives for evaluating these variables with greater accuracy.
This scoping review examined how such technologies enhance the assessment of craniofacial and dental parameters in adults aged, with a focus on optimizing vertical dimension and facial aesthetics. Using the Patient Intervention Comparison Outcome framework, relevant studies (n = 70) were identified through a structured search and evaluated for methodological rigor and clinical relevance. The findings from n=21 studies were synthesized using Bloom’s Taxonomy as a cognitive framework, enabling a deeper understanding of how these tools contribute to knowledge acquisition, clinical application, and innovation in aesthetic planning.
The review highlighted the diagnostic and planning benefits of integrating digital dental data into facial aesthetic procedures, thereby promoting interdisciplinary collaboration between prosthodontists and plastic surgeons. Ultimately, this study emphasized the significance of emerging technologies in enabling personalized, evidence-based approaches to facial rejuvenation in aging populations, with a specific focus on restoring vertical dimension and attaining harmonious aesthetic results.
Keywords:
Ageing face, vertical dimension, facial aesthetics, digital anthropometry, prosthodontic rehabilitation, 3D facial scanning, interdisciplinary rejuvenation
Article Details
How to Cite
CHATZIDOU, Panagiota et al.
Emerging Technologies for Assessing Anthropometric and Dental Variables in the Aging Face - A Scoping Review.
Medical Research Archives, [S.l.], v. 13, n. 9, sep. 2025.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/6898>. Date accessed: 08 dec. 2025.
doi: https://doi.org/10.18103/mra.v13i9.6898.
Section
Review Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
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2. Srinivasan M, Handel S, Bronzino I, Kamnoedboon P, McKenna G, Leles CR. Comparing analog and 3D measurements of vertical dimension in edentulous subjects. Journal of dentistry. 2025;154:105566. https://doi.org/10.1016/j.jdent.2025.105566
3. Yiallouridou I, Sarafidou K, Theocharidou A, Menexes G, Anastassiadou V. Anthropometric vs. dental variables of the ageing face: A clinical study. Applied Sciences. 2023;13(19):10860. https://doi.org/10.3390/app131910860
4. Srinivasan M, Berisha F, Bronzino I, Kamnoedboon P, Leles CR. Reliability of a face scanner in measuring the vertical dimension of occlusion. Journal of dentistry. 2024;146:105016. https://doi.org/10.1016/j.jdent.2024.105016
5. Kim SW, Ko KH, Huh YH, Cho LR, Park CJ. Evaluation of perceptual and anthropometrical facial changes according to increase in vertical dimension of occlusion. Journal of oral rehabilitation. 2025;52(6):833–839. https://doi.org/10.1111/joor.13937
6. Goldstein G, Goodacre C, MacGregor K. Occlusal vertical dimension: Best evidence consensus statement. Journal of prosthodontics: official journal of the American College of Prosthodontists. 2021;30(S1):12–19. https://doi.org/10.1111/jopr.13315
7. Morata C, Pizarro A, Gonzalez H, Frugone-Zambra R. A craniometry-based predictive model to determine occlusal vertical dimension. The Journal of prosthetic dentistry. 2020;123(4):611–617. https://doi.org/10.1016/j.prosdent.2019.05.009
8. Biascamano V, Chuy V, Srinivasan M, Morata C, Naveau A. Development of craniometry-based predictive model to determine occlusal vertical dimension by using the eye-ear distance in a French population. The Journal of prosthetic dentistry. 2025;134(1):207–213. https://doi.org/10.1016/j.prosdent.2023.09.006
9. Iwuchukwu M. Literature review and use of Benjamin Bloom’s taxonomy. Literature Review and Use of Benjamin Bloom's Taxonomy. 2016;1(2). 2356-5926.
10. Tuma F, Nassar AK. Applying Bloom’s taxonomy in clinical surgery: Practical examples. Annals of medicine and surgery (2012). 2021;69:102656. https://doi.org/10.1016/j.amsu.2021.102656
11. Gibelli D, Dolci C, Cappella A, Sforza C. Reliability of optical devices for three-dimensional facial anatomy description: a systematic review and meta-analysis. International journal of oral and maxillofacial surgery. 2020;49(8):1092–1106. https://doi.org/10.1016/j.ijom.2019.10.019
12. Jacobs R, Salmon B, Codari M, et al. Cone beam computed tomography in implant dentistry: recommendations for clinical use. BMC Oral Health. 2018;18:88. https://doi.org/10.1186/s12903-018-0523-5
13. Schuster AJ, da Rosa Possebon AP, Schinestsck AR, Chagas-Júnior OL, Faot F. Circumferential bone level and bone remodeling in the posterior mandible of edentulous mandibular overdenture wearers: influence of mandibular bone atrophy in a 3-year cohort study. Clinical oral investigations. 2022;26(3):3119–3130. https://doi.org/10.1007/s00784-021-04294-9
14. Bilgin MS, Baytaroğlu EN, Erdem A, Dilber E. A review of computer-aided design/computer-aided manufacture techniques for removable denture fabrication. European journal of dentistry. 2016;10(2):286–291. https://doi.org/10.4103/1305-7456.178304
15. Srivastava G, Padhiary SK, Mohanty N, Molinero-Mourelle P, Chebib N. Accuracy of intraoral scanner for recording completely edentulous arches: a systematic review. Dentistry journal. 2023;11(10):241. https://doi.org/10.3390/dj11100241
16. Kavousinejad S, Dalaie K, Behnaz M, et al. Developing an artificial intelligence-based progressive growing GAN for high-quality facial profile generation and evaluation through Turing test and aesthetic analysis. Sci Rep. 2025;15:26611. https://doi.org/10.1038/s41598-025-11172-x
17. Myers M, Brown MD, Badirli S, et al. Long-term predictive modelling of the craniofacial complex using machine learning on 2D cephalometric radiographs. International dental journal. 2025;75(1):236–247. https://doi.org/10.1016/j.identj.2024.12.023
18. Kim E, Kuroda Y, Soeda Y, Koizumi S, Yamaguchi T. Validation of machine learning models for craniofacial growth prediction. Diagnostics (Basel, Switzerland). 2023;13(21):3369. https://doi.org/10.3390/diagnostics13213369
19. Chou JC, Thompson GA, Aggarwal HA, Bosio JA, Irelan JP. Effect of occlusal vertical dimension on lip positions at smile. The Journal of prosthetic dentistry. 2014;112(3):533–539. https://doi.org/10.1016/j.prosdent.2014.04.009
20. Imani M, Bani Hassan E, Vogrin S, et al. Validation of a semiautomatic image analysis software for the quantification of musculoskeletal tissues. Calcified tissue international. 2022;110(3):294–302. https://doi.org/10.1007/s00223-021-00914-4
21. Kouveliotis G, Tasopoulos T, Karoussis I, Silva NR, Zoidis P. Complete denture digital workflow: Combining basic principles with a CAD-CAM approach. The Journal of prosthetic dentistry. 2022;127(4):550–555. https://doi.org/10.1016/j.prosdent.2020.12.024
22. Sun J, Lin YC, Lee JD, Lee SJ. Effect of increasing occlusal vertical dimension on lower facial form and perceived facial esthetics: A digital evaluation. The Journal of prosthetic dentistry. 2021;126(4):546–552. https://doi.org/10.1016/j.prosdent.2020.07.013
23. Zhou TF, Yang X, Wang RJ, et al. [Title in Chinese]. Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences. 2023;55(1):101–107. https://doi.org/10.19723/j.issn.1671-167X.2023.01.015
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