Biomechanical considerations in RPD design: application and perspective of finite element method in distal extension removable partial denture rehabilitation.

IF 1.8 Q3 DENTISTRY, ORAL SURGERY & MEDICINE
Frontiers in dental medicine Pub Date : 2025-10-03 eCollection Date: 2025-01-01 DOI:10.3389/fdmed.2025.1667504
Yixuan Zhu, Jiangqi Hu, Bin Luo, Yafei Yuan, Qingsong Jiang
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Abstract

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.

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RPD设计中的生物力学考虑:有限元法在远端可摘局部义齿康复中的应用与展望。
可摘局部义齿(RPDs)仍然是一种广泛使用和经济有效的解决方案,用于牙列缺损患者。然而,它们的长期成功,特别是在远端伸展病例中,很大程度上取决于生物力学性能。有限元分析(FEA)已成为评估应力分布和指导RPD设计的一种有价值的工具。这篇综述综合了基于有限元的关键生物力学参数的见解,包括基台选择、卡环几何形状、静止位置、主要连接器刚度和材料特性,特别关注Kennedy I类和II类场景,并特别关注种植体支持的rpd (isrpd)。数字工作流程的最新发展,如口腔内扫描和CAD/CAM制造,进一步实现了个性化建模和快速优化。此外,人工智能(AI)与有限元分析的集成在自动化框架生成、预测应力结果和支持闭环设计优化方面显示出前景。虽然这些技术提供了令人兴奋的潜力,但目前的模型仍然缺乏对患者特异性因素的整合,如粘膜特性、唾液和呕吐反射,这导致了模拟和临床结果之间的差异。通过改进建模和数据驱动方法来弥合这一差距,将是提供个性化、生物力学优化的RPD解决方案的关键。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.10
自引率
0.00%
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审稿时长
13 weeks
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