Development of a Multi-scale closed loop model for hemorrhagic shock: a platform to assess REBOA performance

失血性休克多尺度闭环模型的开发：评估 REBOA 性能的平台

• 批准号: 10669644
• 负责人: Elaheh Rahbar
• 金额: $ 70.67万
• 依托单位: WAKE FOREST UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10669644
• 关键词: 3-Dimensional; Abdomen; Acceleration; Address; Adopted; Animal Experimentation; Animal Model; Animals; Aorta; Balloon Occlusion; Baroreflex; Behavior; Biological; Biological Markers; Blood Vessels; Blood Volume; Blood flow; Cardiac Output; Cardiovascular system; Catheters; Cessation of life; Chest; Clinical; Computer Models; Computer software; Coupled; Development; Devices; Distal; Engineering; Environment; Evaluation; Family suidae; Feedback; Growth; Hemorrhage; Hemorrhagic Shock; Homeostasis; Injury; Institution; Intervention; Ischemia; Kidney; Kidney Failure; Knowledge; Liquid substance; Mechanics; Methods; Military Personnel; Modeling; Oxygen; Performance; Perfusion; Phase; Physicians; Physiological; Pre-Clinical Model; Preclinical Testing; Renal function; Reperfusion Injury; Reperfusion Therapy; Research; Resuscitation; Risk; Scientist; Shock; Stents; Sum; Techniques; Testing; Time; Training; Trauma; Traumatic injury; Validation; Vena Cava Filters; Venous; Work; computer framework; computerized tools; design; hemodynamics; improved; in silico; in vivo; indexing; innovation; minimally invasive; multi-scale modeling; multidisciplinary; next generation; novel; open source; oxygen transport; porcine model; pressure; prevent; preventable death; response; risk mitigation; shear stress; simulation environment; tool

Project Summary Hemorrhagic shock is the leading cause of preventable death after a traumatic injury, and accounts for 91% of military and 35% of civilian fatalities after trauma. Injuries to non-compressible intracavity regions, such as the torso and abdomen, are a major clinical challenge due to a lack of appropriate interventions, and represent 30- 40% of early fatalities. To address this problem, endovascular hemorrhage control (EHC) devices and minimally invasive techniques such as Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) have been increasingly adopted. REBOA involves full inflation of a balloon catheter in the aorta, which restricts blood flow distal to the occlusion and consequently minimizes bleeding. While REBOA is effective at restoring proximal perfusion, the reductions in blood flow can result in ischemia-reperfusion injuries that increase the risk of subsequent renal failure. As such, there is a pressing need to identify optimal occlusion size, timing, and duration of REBOA deployment. To date, these important knowledge gaps are hindered by expensive and time intensive large animal models that slow the pace of innovation. To address this major gap, we propose to develop and validate a novel multi-scale computational model that will allow us to simulate the in vivo physiologic response to hemorrhagic shock. Using a 3D-0D closed loop approach of the cardiovascular system, we will be able to simulate the critical feedback loops and biologic response functions to render a physiologically relevant model. These methods have been previously used to inform the design of cardiovascular stents and inferior vena cava filters, but none to our knowledge have been exploited for the evaluation of REBOA or any other EHC device. Our central hypothesis is that computational modeling of blood flow within the aorta and systemic vascular network will generate accurate and robust values for pressure, flow and shear rates within  5% error, closely mimicking in vivo behavior. The objective is to use this computational framework to: 1) quantify the local and systemic hemodynamics (i.e., pressure, flow rate, shear stress, oxygen transport, etc.) during phases of active hemorrhage, aortic occlusion with REBOA, and resuscitation, 2) identify vascular regions that are vulnerable to ischemic damage as a result of the altered hemodynamics, 3) predict key physiologic responses related to vascular compliance, oxygen delivery and renal autoregulation during hemorrhage and aortic occlusion, and 4) determine optimal aortic occlusion size and duration of partial vs. full occlusion strategies to prevent ischemia- reperfusion injuries and renal failure. Successful development and validation of this in silico model will greatly contribute to the preclinical testing and optimization of EHC devices, minimizing the need for large animal studies and also open doors for the study of other transient hemodynamic conditions within the cardiovascular system.

项目摘要 失血性休克是创伤后可预防死亡的主要原因，占91% 军人和35%的平民在创伤后死亡。对不可压缩腔内区域的损伤，例如 躯干和腹部，由于缺乏适当的干预措施，是一个主要的临床挑战，占30- 40%的早期死亡病例。为了解决这个问题，血管内出血控制(EHC)设备和最低限度 诸如复苏性血管内球囊闭塞(REBOA)等侵入性技术已经被 越来越多地被采用。Reboa涉及到主动脉中气囊导管的充分充气，这限制了血流。 在阻塞的远端，从而最大限度地减少出血。虽然REBOA在修复近端牙周组织中是有效的 血流减少可导致缺血-再灌注损伤，从而增加 随后的肾功能衰竭。因此，迫切需要确定最佳遮挡大小、时间和持续时间 REBOA部署。到目前为止，这些重要的知识差距由于昂贵和时间密集而受到阻碍 放慢创新步伐的大型动物模型。为了解决这一重大差距，我们建议开发和 验证一个新的多尺度计算模型，它将允许我们模拟体内的生理反应 失血性休克。使用心血管系统的3D-0D闭环方法，我们将能够 模拟关键反馈回路和生物响应函数，以呈现生理上相关的模型。 这些方法以前被用来指导心血管支架和下腔静脉的设计 过滤器，但据我们所知，没有一个过滤器被用于评估REBOA或任何其他EHC设备。 我们的中心假设是，主动脉和全身血管内的血液流动的计算模型 网络将为压力、流量和剪切率生成准确而稳健的值，误差在5%以内，接近 模仿体内的行为。目标是使用这个计算框架来：1)量化本地和 全身血流动力学(即压力、流速、切应力、氧气输送等)在活动阶段 出血、主动脉阻断、REBOA和复苏，2)确定易患血管病变的区域 血流动力学改变导致的缺血性损害，3)预测与以下相关的关键生理反应 出血和主动脉阻断时的血管顺应性、氧输送和肾脏自动调节；4) 确定预防缺血的部分和完全阻断策略的最佳主动脉阻断大小和持续时间 再灌注损伤和肾功能衰竭。在Silico模型中成功地开发和验证这一点将极大地 有助于EHC设备的临床前测试和优化，最大限度地减少对大型动物研究的需求 也为研究心血管系统内其他瞬时血流动力学状况打开了大门。