Advanced Colonoscopy Training Developed Through Manikin Sensorization and Computational Optimization Modeling

通过人体模型传感和计算优化建模开发的高级结肠镜检查培训

• 批准号: 10719474
• 负责人: Scarlett Miller
• 金额: $ 47.19万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10719474
• 关键词: 3-Dimensional; Adult; American; Anatomy; Benchmarking; Cancer Detection; Cecum; Characteristics; Colon; Colon Carcinoma; Colonoscopy; Colorectal Cancer; Complex; Computed Tomographic Colonography; Computer Simulation; Data; Data Set; Detection; Development; Device or Instrument Development; Diagnosis; Disease; Education; Endoscopes; Evaluation; Feedback; Friction; Geometry; Goals; Health; Health Care Costs; Hospitalization; Intubation; Knowledge; Learning; Light; Malignant Neoplasms; Manikins; Measures; Medical; Medical Education; Medical Residency; Medical center; Methods; Modeling; Operative Surgical Procedures; Organ; Patients; Physicians; Polyps; Procedures; Research Personnel; Residencies; System; Technical Expertise; Techniques; Testing; The Cancer Imaging Archive; Time; Tissues; Trainers Training; Training; Training Programs; Training Technics; Trauma; Validation; Variant; Visualization; Work; adenoma; aged; cost; design; health care quality; human study; improved; innovation; instrument; interactive feedback; iterative design; large datasets; minimally invasive; novel; patient safety; personalized learning; programs; screening; sensor; simulation; skills; success; user-friendly; virtual assessment; virtual coach; virtual patient

Project Summary/Abstract More than 19 million colonoscopies are performed in the US each year, with 60% of adults between 55-75 years having at least one within the last decade (1-3). These procedures provide physicians with minimally invasive access to diagnose and treat diseases such as colon cancer. While routine, colonoscopies are the most expensive screening test routinely performed on healthy Americans, with a mean cost of $2,125 (4). Furthering the cost is the wide variation in successful completion rates that occur based on the physician skill– While the acceptable physician success rate is only 90%, this modest target today is only achieved after physicians complete hundreds of patient cases (5-7). In light of this, the investigators have developed the Manikin Advanced Feedback Trainer (MAFT) to improve patient health and reduce healthcare costs through efficient and effective colonoscopy training. Efficient learning is produced using a high fidelity sensorized manikin trainer and a virtual “coach” that uses optimization-based feedback developed through optimization modeling. MAFT is rigorously developed through 3 Aims below: Specific Aim 1: Develop and validate an extensive colon geometry dataset and a refined sensorization system for the MAFT. Colon geometry of 959 patient virtual colonoscopies from The Cancer Imaging Archive (TCIA) will be computationally measured with a user-friendly automated organ geometry centerline program. In addition, this aim will advance MAFT through the refinement of sensor processing. Specific Aim 2: Develop, validate, and execute a 3D optimization model to solve for optimal endoscope steering control. For each specific colon geometry there exists an optimal set of endoscope steering controls to successfully insert an endoscope to reach the cecum in optimal time and with minimal trauma. An Optimization model will be developed to solve for this optimum, and then this program will be executed across the large colon dataset. Specific Aim 3: Develop and experimentally assess virtual coach to provide personalized and progressive learning for the Manikin Advanced Feedback Trainer. Hypothesis (H1): MAFT system of interactive feedback provided by a virtual coach will improve a physician’s cecal intubation rate (CIR), Adenoma Detection Rate (ADR) through improved visualizations, and reduce endoscope forces that can cause colon damage. The virtual coach will be developed and validated through Human Study 1 and 2 that utilizes both attending physicians and residents. In Human Study 3 MAFT will be implemented into the surgical residency program at Hershey Medical Center in Years 4 and 5, and residents’ skills at performing colonoscopy will be assessed based on the well-established metrics of CIR, ADR, and GAGES assessment to validate H1.

项目摘要/摘要 每年美国进行超过1900万个结肠镜检查，成年人中有60％在55-75之间 在过去十年（1-3）中至少有一个。这些程序为医生提供了最少的 侵入性获取诊断和治疗诸如结肠癌等疾病。虽然例行，但结肠镜是最大的 昂贵的筛选测试通常会对健康的美国人进行，平均成本为2,125美元（4）。进一步 成本是基于身体技能的成功完成率的广泛差异 - 而 可接受的实物成功率仅为90％，今天的这个适度目标才能实现 数百例患者病例（5-7）。 鉴于此，调查人员已经开发了Manikin Advanced Revewback Trainer（MAFT）以改进 患者的健康并通过高效有效的结肠镜检查降低医疗费用。有效的学习 使用高保真感应的Manikin培训师和使用基于优化的虚拟“教练”生产 通过优化建模开发反馈。 MAFT通过以下3个目标进行严格开发： 特定目标1：开发和验证广泛的结肠几何数据集和精制 MAFT的传感系统。 959例患者虚拟结肠镜的结肠几何形状来自癌症 成像档案（TCIA）将通过用户友好的自动化器官几何形状来计算测量 中心线计划。此外，此目标将通过传感器处理的细化来提高MAFT。 特定目标2：开发，验证和执行3D优化模型以解决最佳 内窥镜转向控制。对于每个特定的结肠几何形状，都存在一组最佳内窥镜 转向控制以成功插入内窥镜以在最佳时间内到达盲肠 创伤。将开发一个优化模型以解决此最佳限度，然后该程序将是 在大型结肠数据集中执行。 特定目标3：开发和实验评估虚拟教练，以提供个性化和 Manikin高级反馈培训师的渐进学习。假设（H1）：MAFT系统 虚拟教练提供的交互式反馈将提高物理插管率（CIR）， 腺瘤检测率（ADR）通过改进的可视化，并减少可能导致的内窥镜力 结肠损伤。虚拟教练将通过人类研究1和2进行开发和验证 都会与医师和居民一起。在人类研究中，3 MAFT将被实施到手术中 4年级和5年级的好时医学中心的长期计划，以及居民进行结肠镜检查的技能 将根据CIR，ADR和GAGES评估的公认指标进行评估以验证H1。