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Validation of a Cranial Neurosurgery Simulator and Assessment of Minimally Invasive Techniques

Validation of a Cranial Neurosurgery Simulator and Assessment of Minimally Invasive Techniques
颅神经外科模拟器的验证和微创技术的评估
批准号:
9908660
负责人:
Jonathan Jay Stone
金额:
$22.4万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-30 至 2021-03-31

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中文摘要
翻译
项目摘要 模拟训练的独特之处在于它能够重复练习各种情景并反映 在不危及病人安全的情况下发挥作用。手术技能模拟器在桥接中取得了成功 当前培训模式的差距;然而,这些模拟器不能提供完整的操作人员 经验。手术暴露与活体患者仍然是实践临床培训的先锋。在……下面 监督和指导,培训外科医生在实习期间内在地练习和完善患者的技能, 使他们暴露在不必要的风险中。需要新的仿真工具来验证和实施新的 外科技术,包括微创颅神经外科技术。以提高效率、安全性 和全面的微创手术训练,我们建议开发一种无生命的颅脑 采用3D打印技术中的新概念的神经外科模型。我们设计了一个模型来模拟 从脑中排出血块,我们建议修改这个模型来模拟大脑切除 肿瘤。通过这种模式,可以实现全面的程序性培训和能力先于 手术暴露。我们计划通过比较经验者的几个临床指标来验证该模型。 外科医生和实习生。我们还将通过测试机械和电子设备来验证该模型的物理真实性 相对于人体组织的成像特性。
英文摘要
Project Summary Simulation training is unique in its ability for repetitive practice of a wide variety of scenarios and to reflect on performance without jeopardizing a patient’s safety. Surgical skills simulators have been successful in bridging gaps of the current training model; however, these simulators fall short of offering a complete operative experience. Operative exposure with live patients still remains the vanguard of hands-on clinical training. Under supervision and guidance, training surgeons inherently practice and refine skills on patients during residency, exposing them to unnecessary risks. Novel simulation tools are needed to both validate and implement novel surgical techniques, including those for minimally invasive cranial neurosurgery. To enhance the efficiency, safety and comprehensiveness of minimally invasive surgical training, we propose to develop an inanimate cranial neurosurgery model utilizing novel concepts in 3D printing technology. We have engineered a model to simulate evacuation of a blood clot from the brain, and we propose to modify this model to simulate resection of a brain tumor. Through this model, comprehensive procedural training and competence can be achieved prior to operative exposure. We plan to validate this models by comparing several clinical metrics in experienced surgeons and trainees. We will also validate the physical realism of this model by testing the mechanical and imaging properties relative to human tissue.
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