SCH: INT: Collaborative Research: Computer Guided Laparoscopy Training

SCH：INT：协作研究：计算机引导腹腔镜检查培训

• 批准号: 1622589
• 负责人: Jerzy Rozenblit
• 金额: $ 111.89万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2021-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1622589&HistoricalAwards=false
• 关键词: SCH; INT; Collaborative; Research; Computer

Laparoscopic surgery, when performed by a well-trained surgeon, is a remarkably effective procedure that minimizes complications associated with open incisions, blood loss and post-operative pain. It also reduces recovery time. However, the procedure is more challenging than conventional surgery due to restricted vision, hand-eye coordination problems, limited working space, and lack of tactile sensation. Therefore, effective training and guidance methods are needed to minimize the potential risks inherent in such procedures. The goal of this project is to develop and validate techniques for computer-guided laparoscopic surgical training in a simulated, non-patient based environment. A computer-aided surgical trainer (CAST) will physically guide trainees' instruments during surgical skills practice sessions by utilizing assistive force with augmented reality displays. Guided training will be validated through a pilot experimental study, in which the expertise of computer-guided trainees will be compared to that of instructor-guided trainees. Data such as the time it takes a trainee to execute a particular surgical task, how accurate he or she is, etc., will be collected to analyze task performance precisely and objectively. New scientific methods for motion trajectory planning and path following using assistive force and augmented reality techniques will result from this work. It is anticipated that computer-guided practice will speed up learning and reinforce appropriate techniques, ultimately, leading to better surgical outcomes and improved patient safety. The CAST system should serve as a sophisticated, yet still low-cost, training solution for fundamental medical skills training. The specific objectives are a) to refine and implement a memory- and time-efficient hybrid offline-online optimal path planner for computer-guided training of basic laparoscopic skills. In this task, collision-free trajectory planning methods (such as those used in robotics) will be generated by incorporating offline-online hybrid techniques with memory and computational time efficient path repository. Thus, basic laparoscopic tasks can be planned and guided automatically, using haptic force and augmented reality visualization; b) to design and implement an intelligent, adaptive guidance controller for surgical space navigation, where a fuzzy logic and machine learning-based methods will be developed that will take into account trainees' skill levels so that optimal amount of training assistance can be provided in mastering surgical tasks; c) to design and implement visual guidance techniques through augmented reality overlays that provide 'navigational' cues, supplementing force-based control of surgical instruments; and d) to validate guided training through a pilot study. In this task, trainees' performance using computer guidance methods will be compared, using statistical analysis, to that of unguided trainees. The principal investigators will aim to increase the participation of undergraduate students, and in particular of underrepresented groups, through collaboration with the well-established programs at both PIs' institutions and through sponsorship of senior projects and independent study courses.

腹腔镜手术由训练有素的外科医生进行时，是一种非常有效的手术，可最大限度地减少与开放切口、失血和术后疼痛相关的并发症。它还缩短了恢复时间。然而，由于视力受限、手眼协调问题、工作空间有限和缺乏触觉，该手术比传统手术更具挑战性。因此，需要有效的培训和指导方法，以尽量减少此类程序固有的潜在风险。这个项目的目标是开发和验证技术，计算机引导腹腔镜手术培训在一个模拟的，非病人为基础的环境。计算机辅助手术培训师（CAST）将在手术技能练习期间通过使用具有增强现实显示的辅助力量来实际指导学员的器械。将通过一项试验性研究验证指导培训，在这项研究中，将对计算机指导的受训者的专门知识与计算机指导的受训者的专门知识进行比较。数据，例如学员执行特定手术任务所需的时间、他或她的准确性等，将被收集，以准确和客观地分析任务绩效。这项工作将产生使用辅助力量和增强现实技术进行运动轨迹规划和路径跟踪的新科学方法。预计计算机引导的实践将加快学习和加强适当的技术，最终导致更好的手术结果和提高患者的安全性。CAST系统应作为一个先进的，但仍然是低成本的，基本医疗技能培训的培训解决方案。 具体目标是：a）改进和实施一种记忆和时间效率高的混合离线-在线最佳路径规划器，用于基本腹腔镜技能的计算机引导培训。在这项任务中，无碰撞轨迹规划方法（如机器人中使用的）将通过将离线-在线混合技术与内存和计算时间有效的路径存储库相结合来生成。B）设计和实现用于外科手术空间导航的智能自适应引导控制器，其中将开发基于模糊逻辑和机器学习的方法，其将考虑受训者的技能水平，使得可以在掌握外科手术任务时提供最佳量的训练辅助; c）通过增强现实覆盖设计和实施视觉引导技术，提供“导航”提示，补充基于力的手术器械控制; d）通过试点研究验证引导培训。在这项任务中，学员使用计算机指导方法的表现将进行比较，使用统计分析，以无指导的学员。主要研究人员将致力于通过与两个PI机构的成熟项目合作以及通过赞助高级项目和独立学习课程，增加本科生的参与，特别是代表性不足的群体。