MINI REVIEW article
Front. Dent. Med.
Sec. Reconstructive Dentistry
Volume 6 - 2025 | doi: 10.3389/fdmed.2025.1667504
Biomechanical Considerations in RPD Design: Application and Perspective of Finite Element Method in Distal Extension Removable Partial Denture Rehabilitation
Provisionally accepted- 1School of Stomatology, Capital Medical University, Beijing, China
- 2Department of Prosthodontics, Beijing Stomatological Hospital, Capital Medical University, Beijing, China
- 3Beijing Stomatological Hospital Affiliated to Capital Medical University, Beijing, China
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Removable partial dentures (RPDs) remain a widely used and cost-effective solution for patients with dentition defects. However, their long-term success, particularly in distal extension cases, depends heavily on biomechanical performance. Finite element analysis (FEA) has emerged as a valuable tool for evaluating stress distribution and guiding RPD design. This review synthesizes FEA-based insights into key biomechanical parameters—including abutment selection, clasp geometry, rest position, major connector stiffness, and material properties—with a particular focus on Kennedy Class I and II scenarios, and special attention to implant-supported RPDs (ISRPDs). Recent developments in digital workflows, such as intraoral scanning and CAD/CAM fabrication, have further enabled personalized modeling and rapid optimization. In addition, the integration of artificial intelligence (AI) with FEA shows promises in automating framework generation, predicting stress outcomes, and supporting closed-loop design optimization. While these technologies offer exciting potential, current models still lack integration of patient-specific factors such as mucosal properties, saliva, and gag reflex, contributing to discrepancies between simulations and clinical outcomes. Bridging this gap through improved modeling and data-driven approaches will be key to delivering personalized, biomechanically optimized RPD solutions.
Keywords: Removable Partial Denture (RPD)1, Finite Element Analysis (FEA)2, biomechanics3, Digital Dentistry4, Artificial intelligence (AI) 5
Received: 16 Jul 2025; Accepted: 15 Sep 2025.
Copyright: © 2025 Zhu, HU, Luo, Yuan and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yafei Yuan, lit2fei@163.com
QingSong Jiang, qsjiang@ccmu.edu.cn
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.