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

模拟骨和尸体骨中直径减小的植入物的设计优化

• 批准号: 10378763
• 负责人: JASON A GRIGGS
• 金额: $ 35.91万
• 依托单位: UNIVERSITY OF MISSISSIPPI MED CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10378763
• 关键词: Acceleration; Address; Alveolar ridge; Anterior; Benchmarking; Cadaver; Caliber; Cervical; Computer software; Confidence Intervals; Data; Dental Implants; Elements; Equipment; Fatigue; Finite Element Analysis; Fracture; Future; Goals; Implant; Implantation procedure; Incidence; Incisor; Lateral; Linear Regressions; Lip structure; Location; Maxilla; Measures; Mechanics; Methodology; Methods; Modeling; Operative Surgical Procedures; Oral Surgeon; Patients; Performance; Research Personnel; Resistance; Site; Specimen; Stress; Surface; System; Testing; Tooth structure; Training; Variant; Width; artificial neural network; bone; cost; design; experience; healing; implant design; member; metallicity; novel; prototype; response; tool; virtual model

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.

项目概要 缩径牙种植体的外径小于 3.75 毫米。它们对于替换很有用 牙颈直径较小的牙齿，尤其是前牙位置的牙齿。在前面，宽度 牙槽嵴通常不足以放置标准直径的种植体，因此直径减小的种植体可以避免 需要进行骨增量手术，从而避免额外费用和植入前六个月的等待 放置。然而，直径减小的种植体遭受机械损伤的发生率要高得多。 与标准直径种植体相比的并发症。这些并发症包括松动和/或 种植体基台连接器螺钉断裂。幸运的是，我们的初步数据表明，设计 可以优化直径减小的种植体中的种植体-基台连接，以延长其使用寿命。 我们之前进行了一个为期五年的项目，研究更有效的机械可靠性评估方法 通过 (1) 验证使用有限元进行的种植体寿命预测的准确性 应力分析与疲劳后处理软件相结合，以及 (2) 验证加速寿命 使用过应力加速度和使用率的组合进行物理样本测试 加速度。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 减小直径的牙种植体的设计优化。 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 确定哪些参数应用作简化设计优化中的实验因素 直径的牙种植体。候选参数是通过四种类型的简化疲劳测试确定的： 直径牙种植体并测试与疲劳寿命显着相关的设计参数。第二， 我们将确定与最大预测相对应的设计参数的最佳组合 减小直径的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训练来执行设计优化，并将进行比较 方法采用响应面法。第三，我们将使用加速来验证虚拟模型 对物理样本进行寿命测试 (ALT)，以将我们优化的植入物的性能与 商业上可用的模拟骨骼基准。第四，我们还将测试我们的优化原型 尸体骨来验证我们的新型模拟骨支架材料，用于未来的植入物疲劳研究。