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

基本信息

批准号：
10412269
负责人：
Elaheh Rahbar
金额：
$ 74.92万
依托单位：
WAKE FOREST UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
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/10412269
关键词：
3-Dimensional Abdomen 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 Inferior vena cava structure Injury 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 shear stress simulation environment tool

项目摘要

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.

项目概要失血性休克是创伤性损伤后可预防死亡的主要原因，占创伤性损伤后可预防死亡的 91% 军事人员和 35% 的平民因外伤而死亡，例如腔内不可压缩区域。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，代表了 30- 40% 的早期死亡患者需要使用血管内出血控制 (EHC) 装置来解决这一问题。诸如主动脉复苏性血管内球囊闭塞术 (REBOA) 等侵入性技术 REBOA 涉及主动脉内球囊导管的完全膨胀，从而限制血流。 REBOA 可有效恢复近端闭塞部位，从而最大限度地减少出血。灌注时，血流量减少可能导致缺血再灌注损伤，从而增加以下风险：因此，迫切需要确定最佳的闭塞大小、时机和持续时间。迄今为止，这些重要的知识差距受到昂贵且耗时的阻碍。大型动物模型减缓了创新的步伐，为了解决这一重大差距，我们建议开发和利用大型动物模型。验证一种新颖的多尺度计算模型，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反应函数以呈现生理相关模型。这些方法以前曾用于指导心血管支架和下腔静脉的设计过滤器，但据我们所知，尚未用于评估 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血流的计算模型网络将生成精确且稳健的压力、流量和剪切速率值，误差在  5% 以内，模仿体内行为的目标是使用该计算框架来：1）量化局部和活动阶段的全身血流动力学（即压力、流速、剪切应力、氧输送等）出血、REBOA 主动脉闭塞和复苏，2) 识别易受伤害的血管区域血流动力学改变导致的缺血性损伤，3) 预测与以下相关的关键生理反应出血和主动脉闭塞期间的血管顺应性、氧输送和肾脏自动调节，以及 4) 确定最佳主动脉闭塞大小以及部分与完全闭塞策略的持续时间以防止缺血再灌注损伤和肾衰竭的计算机模型的成功开发和验证将极大地发挥作用。有助于 EHC 设备的临床前测试和优化，最大限度地减少大型动物研究的需求也为心血管系统内其他瞬时血流动力学条件的研究打开了大门。