Physician Uses Multiphysics Simulation to Improve Dialyzer Designs

Steven Conrad, MD, PhD, an emergency and critical care physician at Louisiana State University Health Science Center, New Orleans, is not your typical physician. When he’s not conducting rounds on patients or teaching residents in internal medicine, emergency medicine, or pediatrics, this biomedical engineer is using multiphysics simulation to optimize the design of artificial kidneys. Using COMSOL Multiphysics, Dr. Conrad simulates the hollow fibers that make up a dialyzer, using computer aided engineering (CAE) tools to advance the design of artificial kidneys. The simulations that he creates don’t just optimize current dialyzer designs—his simulations improve upon them by taking into account physical properties that weren’t considered in previous designs, and even allow for dialyzer improvements and optimizations on a patient by patient basis. By improving the functionality of artificial kidneys, he hopes to create artificial kidneys that will revolutionize the dialysis process.

■ Multiphysics Simulation Transforms Biomedical Practices

Fig. 1 – Hemodialysis taking place through a hemodialyzer, which is composed of hollow fibers and a fluid called dialysate. Blood is pumped from a vascular access graft in an arteriovenous fistula and waste products are filtered into the dialysate.
Until recently, artificial organs were frequently designed empirically, with little or no simulation involved in the design process. As multiphysics simulation software emerged as a valuable analysis tool for scientists and engineers, its capacity for improving biomedical designs became apparent as well. The versatility and flexibility of the multiphysics approach allowed doctors to simulate biological processes and incorporate more physics into a design than was previously possible. In the past decade, multiphysics simulation has been used to study heat transport in organs, fluid-structure interaction in the brain, and musculoskeletal structural analysis, among others. Multiphysics not only allows more than one physics in the simulation process, but also takes into account resulting interactions that occur between coupled physics effects.

As multiphysics simulation was used to improve on various applications in medicine and biology, Dr. Conrad decided that they could prove vital to designing accurate and efficient dialyzers as well. Using COMSOL Multiphysics, he simulated, analyzed, and optimized artificial kidney designs. “I felt that by using simulation in the design process, I could create artificial kidneys with higher efficiencies than the ones that were currently being used,” he stated.

■ Renal Replacement Therapies

One in nine American adults currently suffer from chronic kidney disease (CKD). Nearly half a million of those patients have progressed from CKD into end-stage renal disease (ESRD), and currently require dialysis or transplant therapies just to stay alive. With the number of patients entering ESRD increasing by 5 to 10 percent per year, providing efficient and cost-effective dialysis treatments is a growing issue in the medical field.

A healthy kidney filters fluids at a rate of 90 mL per minute or more, a process that is measured by the glomerular filtration rate (GFR). A patient with renal failure has a decreased filtration rate described in stages, with Stage 5 (GFR of <15) defined as ESRD, and requires dialysis. When a patient is diagnosed with ESRD, they begin dialysis treatments three to five times per week. However, recent studies have found that even these treatments, which last anywhere from three to five hours per treatment, may not be doing enough. By optimizing and improving the effectiveness of dialysis treatments, doctors may be able to not only improve upon a patient’s quality of life, but their life expectancies when on dialysis as well.

Figs. 2a and b – Cross section of a hollow fiber and its associated interior blood region and exterior dialysate region (top). Magnitude of velocity in a hemodiafilter (bottom). The simulation was implemented as a 2D axisymmetric representation and included the hollow fiber, its interior blood path, and exterior dialysis fluid path, as well as a membrane that is 50 μm thick.
Renal replacement therapies, such as dialysis, involve the removal of electrolytes, excess water, and metabolites that build up in the body due to kidney failure. There are a few different types of renal replacement therapies, but three of the most common are hemodialysis, hemofiltration, and peritoneal dialysis.

Hemodialysis and hemofiltration are the most common, and use an external dialyzer to filter blood, usually removed from an arteriovenous fistula in the patient’s arm. Hemodialysis is the more traditional form of dialysis, relying on diffusive transport and low porosity membranes to remove small, toxic, and easily diffusible solutes from the blood, such as creatinine and urea. (See Figure 1)

Hemofiltration relies on convective transport to clear solutes, and is able to remove larger or mid-sized solutes, now known to contribute to toxicity, in addition to smaller solutes. Using hydrostatic pressure, hemofiltration drives both small and large molecules through a filtration compartment where molecules are removed by a porous membrane made up of hollow fibers.

Currently, therapies involving a combination of both hemofiltration and hemodialysis, called hemodiafiltration, are common and result in a more complete removal of both small and large toxins.

■ How to Improve Hemodiafilter Design

A hemodiafilter is a dialyzer used in the hemodiafiltration process. The dialyzer is composed of axisymmetric hollow fibers that make up an artificial membrane and a fluid called the dialysate that catches and separates the toxins and solutes from the blood. Using COMSOL Multiphysics, Dr. Conrad simulates the interaction between hollow fibers, blood, and dialysate fluid, which are non-Newtonian fluids. By creating an accurate model of the hemodiafilter, and incorporating all important physical effects into one simulation, he is able to create designs that more accurately predict fluid flow and solute transport during the dialysis process.