Design Optimization of Reduced-Diameter Implants in Simulated and Cadaver Bone

项目摘要 缩小直径的牙种植体的外径小于3.75毫米。它们可用于替换 颈部直径较小的牙齿，特别是在前部。在前面，是指 牙槽脊通常不足以放置标准直径的种植体，所以缩小直径的种植体避免了 需要骨增强手术，从而避免了额外的成本和植入前六个月的等待 放置。然而，直径较小的植入物有更高的机械性发病率。 与标准直径植入物相比，并发症较多。这些并发症包括松动和/或 种植体-基台连接器螺丝断裂。幸运的是，我们的初步数据表明， 直径较小的种植体中的种植体-基台连接可以进行优化以延长其寿命。 我们之前进行了一个为期五年的项目，研究更有效的方法来评估机械可靠性 通过(1)验证使用有限元进行的种植体寿命预测的准确性 结合疲劳后处理软件的应力分析和(2)加速寿命验证 使用超应力加速和使用率组合进行的物理样品测试 加速。我们实现了这些目标，这为我们提供了一套强大的工具来解决 小径种植体的设计优化。 在目前提出的项目中，我们将使用有限元建模来筛选25个种植体设计参数 为确定在减速器设计优化中应采用哪些参数作为试验因素。 直径的牙科植入物。通过四种类型减速器的疲劳试验，确定了候选参数。 牙种植体直径和测试设计参数与疲劳寿命显著相关。第二, 我们将确定与最大预测值相对应的设计参数的最佳组合 小直径牙种植体的疲劳寿命。我们将使用人工神经网络 使用我们的有限元分析结果进行培训以执行设计优化，并将比较 方法采用响应面方法。第三，我们将使用Accelerated验证虚拟模型 物理标本的寿命测试(ALT)，以比较我们优化的种植体和 商业上可以买到的模拟骨骼基准。第四，我们还将在 以验证我们的新型模拟骨托材料，以用于未来的种植体疲劳研究。

Project Summary Reduced-diameter dental implants have an outer diameter less than 3.75 mm. They are useful for replacing teeth that have small cervical diameters, especially in anterior locations. In the anterior, the width of the alveolar ridge is often insufficient to place a standard-diameter implant, so reduced-diameter implants avoid the need for bone augmentation surgery and thus avoid the additional cost and six-month wait prior to implant placement. However, reduced-diameter implants suffer from a much greater incidence of mechanical complications compared with standard-diameter implants. These complications include loosening and/or fracture of the implant-abutment connector screw. Fortunately, our preliminary data suggest that the design of the implant-abutment connection in reduced-diameter implants can be optimized to increase their lifetime. We previously conducted a five-year project on more efficient methods of evaluating the mechanical reliability of dental implants by (1) validating the accuracy of implant lifetime prediction performed using finite element stress analysis combined with fatigue post-processing software and (2) validating the accelerated lifetime testing of physical specimens performed using a combination of overstress acceleration and usage rate acceleration. We accomplished those aims, which provided us with a powerful set of tools for addressing the design optimization of reduced-diameter dental implants. In the currently proposed project, we will use finite element modeling to screen 25 implant design parameters to determine which parameters should be used as experimental factors in design optimization of reduced- diameter dental implants. The candidate parameters were identified by fatigue testing of four types of reduced- diameter dental implants and testing design parameters for significant association with fatigue lifetime. Second, we will identify the optimal combination of design parameters that corresponds to the maximum predicted fatigue lifetime for reduced-diameter dental implants. We will use Artificial Neural Networks that have been trained using the results of our finite element analyses to perform design optimization and will compare that method with Response Surface Methodology. Third, we will validate the virtual models by using accelerated lifetime testing (ALT) of physical specimens to compare the performance of our optimized implant with a commercially available benchmark in simulated bone. Fourth, we will also test our optimized prototype in cadaver bone to validate our novel simulated bone holder material for future implant fatigue studies.