Development of a regional anesthesia guidance system to increase patient access to opioid-sparing analgesia for hip fracture pain

项目摘要/摘要 对于每年因髋部骨折而住院的33万美国人来说，疼痛和手术的快速治疗 干预对于恢复行动能力和降低死亡风险至关重要。非肠外阿片类药物是治疗的标准 注意管理急性髋部骨折疼痛，但增加不良事件和结果的风险，包括 精神错乱和反复使用阿片类药物。超声引导区域麻醉(UGRA)技术，如 囊周神经组(Peng)阻滞是阿片类药物的有效替代品，可用于治疗 患者每年减少阿片类药物的消费并改善结果。然而，UGRA在中国的利用 急诊科(ED)主要受到特定于急诊科的工作流程挑战以及无法访问 能力所需的培训。因此，显然需要增加对节约阿片类药物的UGRA的利用。 对于髋部骨折疼痛，很可能是一项减少培训和工作流程的技术进步 管理UGRA的要求就是为了满足这一需要。 在本项目中，将开发基于超声波的髋部区域麻醉引导系统 根据ISO 13485：2016年和21CFR Part 820认证的质量管理体系(QMS)。钥匙 支持该产品开发的技术创新包括：2D和3D 突出骨骼解剖和软组织地标、解剖识别能力的成像算法 自动选择注射部位，这是一种新型的双阵列超声探头，可以实现穿透探头 针轨迹，一种旨在简化工作流程的一次性无菌消耗品，以及针的可视化 成像模式，向用户突出显示前进的针头。早期的主要技术任务 项目期的各个阶段包括执行最终用户临床可用性研究，以指导技术 机器学习网络规范的开发与实施，指导彭块。 成功完成这些技术目标将导致制造预制系统 将在项目后期进行的临床验证研究。 临床前产品验证活动将包括在以下方面进行的身体和人体成像研究 与临床专家协作，他们将验证该系统是否符合临床要求 申请。临床前身体研究的主要终点是对准确性的直接测量 如CT成像所证实的，彭氏阻滞的置针位置。此外，第二项临床前研究 使用身体标本将表征达到系统能力所需的学习曲线 通过研究25名急诊科医生在多个模拟手术中达到的置针精度。 这项研究项目的完成将导致开发和制造一种人类临床- 试验就绪的3D超声成像系统支持方便地使用UGRA治疗髋部骨折疼痛 通过最大限度地减少培训和工作流程的使用障碍。

PROJECT SUMMARY/ABSTRACT For the >330,000 Americans that are hospitalized for hip fractures yearly, rapid treatment of pain and surgical intervention is critical to recover mobility and reduce the risk of death. Parenteral opioids are the standard of care to manage acute hip fracture pain but increase the risk of adverse events and outcomes, including delirium and recurrent opioid use. Ultrasound-guided regional anesthesia (UGRA) techniques, such as the pericapsular nerve group (PENG) block, are an effective alternative to opioids that could be used for > 300,000 patients annually to decrease consumption of opioids and improve outcomes. However, utilization of UGRA in the emergency department (ED) is primarily limited by ED-specific workflow challenges and lack of access to the training required for competency. Thus, there is a clear need to increase utilization of opioid-sparing UGRA for hip fracture pain, and it is likely that a technological advancement that reduces the training and workflow requirements of administering UGRA is required to meet this need. During this project, an ultrasound-based hip regional anesthesia guidance system will be developed under a quality management system (QMS) certified to ISO 13485:2016 and 21 CFR Part 820. The key technological innovations underpinning the development of this product include the following: 2D and 3D imaging algorithms that highlight bony anatomy and soft tissue landmarks, anatomical recognition capabilities that automate injection site selection, a novel dual-array ultrasound probe that enables ‘through-the-probe’ needle trajectories, a single-use sterile consumable designed to simplify workflow, and a needle-visualization imaging mode that highlights the advancing needle to the user. The primary technical tasks during the early stages of the project period include the execution of end-user clinical usability studies to guide technical specification development and implementation of machine learning networks to guide the PENG block. Successful completion of these technical aims will result in the fabrication of pre-production systems for pre- clinical validation studies that will be conducted later in the project period. Pre-clinical product validation activities will include cadaver and human-imaging studies performed in collaboration with clinical experts who will verify that the system meets the requirements for the clinical application. The primary endpoint for the pre-clinical cadaveric studies is a direct measurement of the accuracy of needle placement for the PENG block, as confirmed by CT imaging. Additionally, a second pre-clinical study using cadaveric specimens will characterize the learning curve required to reach competency with the system by studying the needle placement accuracy achieved by 25 ED physicians over multiple simulated procedures. Completion of this research project will result in the development and fabrication of a human clinical- trial-ready 3D-capable ultrasound-imaging system to support facile administration of UGRA for hip fracture pain by minimizing training and workflow barriers to utilization.