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 出血性休克是创伤后可预防死亡的主要原因，占91％ 创伤后军事和35％的平民死亡。不可压缩的腔内区域受伤，例如 由于缺乏适当的干预措施，躯干和腹部是一个主要的临床挑战，代表30- 早期死亡的40％。为了解决这个问题，血管内出血控制（EHC）设备和最少 侵入性技术，例如主动脉（REBOA）的复苏性血管内气囊闭塞（REBOA） 越来越多地采用。 REBOA涉及在主动脉中的气球导管的完全充气，这限制了血液流动 闭塞远端，从而最大程度地减少出血。虽然Reboa有效地恢复近端 灌注，血液流量的减少会导致缺血 - 再灌注损伤，从而增加 随后的肾衰竭。因此，有迫切需要确定最佳的闭塞大小，时机和持续时间 Reboa部署。迄今为止，这些重要的知识差距受到昂贵且耗时的限制 大型动物模型会减慢创新速度。为了解决这一主要差距，我们建议开发和 验证一种新型的多尺度计算模型，该模型将使我们能够模拟体内生理反应 要出血性休克。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与物理相关的模型。 这些方法先前已用于告知心血管支架和下腔静脉的设计 过滤器，但据我们所知，尚未探索用于评估REBOA或任何其他EHC设备的过滤器。 我们的中心假设是主动脉和全身血管内血流的计算建模 网络将在5％误差范围内产生压力，流量和剪切速率的准确和稳健值 模仿体内行为。目的是使用此计算框架来：1）量化本地和 在活动阶段 出血，带有REBOA的主动脉闭塞和复苏，2）识别容易受到伤害的血管区域 由于血液动力学改变而导致缺血性损害，3）预测与 血管顺应性，氧气递送和肾脏自动调节在出血和主动脉闭塞过程中，4） 确定最佳主动脉闭塞大小和部分的持续时间与完全闭塞策略，以防止缺血 - 再灌注损伤和肾衰竭。在计算机模型中成功开发和验证将大大 有助于EHC设备的临床前测试和优化，最大程度地减少了对大型动物研究的需求 并为研究心血管系统中其他瞬时血液动力学状况的研究打开门。