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Blood for for trauma and inhalation of toxic agents in the lungs

platelet3D_demo

This project has two components.  One component is to study the adhesion of blood platelets to an injured vessel site. This is a critical initial stage for the formation of a platelet plug to stop bleeding.  The second component is to study the deposition of aerosol particles in the lungs to help study the effects of airborne pollutants, and infective and toxic agents.

Blood flow for trauma-related applications: Red blood cells play a critical role in influencing human bleeding time. Trauma remains the leading cause of mortality for soldiers in combats, and 25% to 35% trauma victims experience an initial bleeding diathesis upon presentation to a medical facility. In a bleeding event, blood vessel walls are damaged, which trigger platelets to travel to the site of injury and start the clotting process. Surprisingly, previous studies show that bleeding time is influenced more by the fraction of red blood cells (hematocrit) than the fraction of platelets.

In this project, we build a computer model to understand the physical chemistry of blood flow. Our findings offer insights into the mechanics of trauma injuries and blood disorders such as sickle cell anemia and malaria. Our computer model offers a quantitative explanation for how red blood cells can influence the near-wall concentration of platelets, and thus affect the traveling time of platelets in the event of bleeding. 

Our study is composed of building a high fidelity computer simulation of blood flow and deriving a simplified model for fast computations. This approach does not require the use of large volume of blood in conventional lab studies and avoids the noises and degradation in experimental samples. We also work closely with Army researchers who conduct experiments, as shown in Figure 3, to measure quantities such as the platelet adhesion rate. We can thus verify our model by comparing with those experimental data.

Inhalation of toxic agents in the lung:

Soldiers on and off the battlefield are exposed to dangerous substances in the air they breathe. Airborne debris and smoke from explosions may contain radioactive or toxic compounds. Soldiers may also be at risk from biological threats in the air such as anthrax or viruses like Ebola. The lung and its extended network of airways provide a portal of entry for these airborne contaminants.  Lung particle deposition is defined as the fraction of particles that do not deposit during inhalation and exhalation. The ability to predict this deposition is therefore critically important for understanding the fate of inhaled aerosols and its effect on pathogenesis in soldiers. The current project aims to develop HPC simulation capabilities to study the flow in the lungs and the deposition of minute particles. Detailed information about particle deposition in the lungs will enable more effective measures to protect human health.

To study inhalation, we developed a computer code that is capable of giving detailed airflow and particle deposition information in the lungs. The “Virtual Inhaler” code was developed in-house at Stanford with the objective to provide all of the necessary capabilities required by this complex application, including turbulence modeling and scalability. It is capable of predicting air dynamics in any lung. Given any person’s CT or MRI scan, it can compute that person’s specific breathing dynamics from the mouth and nose to generation 7 of the lungs. The code is also optimized for parallel computation, allowing it to run quickly and efficiently on massive supercomputers. Scalability of the computations is of great importance because of the geometrical complexity of the realistic airways, which require extremely large computational meshes. The separation-of-scales from the large trachea to the tiny alveoli requires us to develop low-order approximations to accurately model deposition in millions of small passages.

We have developed Large Eddy Simulation (LES) cases for the flow field in three human airways.  The first is an idealized model constructed to represent a statistically average human lung and provides generalizable results. We have also produced results in a healthy middle-aged male lung and the lung of a person diagnosed with sleep apnea. Additionally, in collaboration with Army researchers who perform animal inhalation experiments, we have also computed flow and deposition results in five Rhesus Macaque monkey lungs to better understand how experiments in monkeys compare to human lungs.