Optimizing the Design and Implementation of Endovascular Hemorrhage Control Devices Using a Novel Computational Platform
Abstract
Traumatic injuries are the leading cause of death in people under the age of 45 years, in both military and civilian populations. Individuals suffering from major bleeding, or hemorrhage, as a result of their traumatic injury are at the highest risk of early fatalities, usually dying within 6-24 hours after their injury. Given this short window of time, it is vitally important to administer life-saving interventions as early as possible. The main guiding principles in delivering life-saving interventions for major hemorrhage are: (1) stop and control the site of bleeding, and (2) deliver resuscitation fluid and/or blood transfusions to restore blood volume lost. When the site of injury is one’s arm or leg, tourniquets can be easily applied to reduce the amount of bleeding. In these situations, one applies direct pressure to the site of injury and is able to significantly reduce bleeding. However, in cases where an injury is sustained to the chest and/or abdominal regions and the patient is experiencing severe internal bleeding, a traditional pressure-induced tourniquet cannot be used. In these situations, alternative hemorrhage control strategies have been developed to minimize blood loss internally. Two of the most common hemorrhage control strategies for internal bleeding are Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) and Endovascular Variable Aortic Control (EVAC). Both techniques involve the insertion of a catheter (or line) in a large blood vessel near the groin region (i.e., leg/pelvic area), which is then carefully pushed up towards the aorta (i.e., main blood vessel off the heart, located in the chest). Once the catheter is in place, a balloon is inflated within the blood vessel to slow down blood flow at the site of injury, thereby reducing the amount of internal bleeding. The inflated balloon creates a temporary blockage in the aorta; in REBOA it is generally fully occlusive, whereas in EVAC the degree of occlusion can vary. While both REBOA and EVAC have been shown to be effective in slowing the rate of internal bleeding, there are severe consequences and limitations of this hemorrhage control strategy. By creating a blockage in the aorta, blood flow is drastically reduced beyond the balloon occlusion. This results in reduced transport of blood and oxygen to the rest of the body during REBOA or EVAC procedures, which can impose serious harm. This can be especially dangerous for the areas of the blood vessels (including the cells lining the blood vessels) and organs that receive less blood flow. For example, the kidneys often experience a drastic reduction in blood flow and oxygen transport that can cause kidney failure or worse, organ damage. Therefore, there is a need to improve existing REBOA and EVAC methods to improve control over internal bleeding while minimizing the risk of damage to the blood vessels and organs. Currently, experiments with large animals (e.g., pigs) are often used to test the efficacy of REBOA and EVAC methods, but these are very technically challenging, time-consuming, and expensive. In this grant application, we propose a less expensive and more readily accessible approach to test for REBOA and EVAC hemorrhage control strategies. Specifically, we aim to develop and confirm an accurate computational model that will simulate the circulatory system’s response during normal, active bleeding, occluded phases (i.e., partial vs. full aortic occlusion with REBOA devices) and resuscitation. In this study, we propose a series of animal and computational experiments to test, develop, and validate a new computer-based model that can simulate the response to bleeding. This model will use anatomically accurate geometries of the blood vessels and sophisticated feedback loop systems to model both large and smaller blood vessels in the blood circulatory system. First, we will perform experiments in pigs to collect continuous blood flow and pressure values from different regi
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210310
Entities
People
- C. Alberto Figueroa
Organizations
- United States Army
- University of Michigan