Cleveland Researchers Study Joints at Tissue, Cellular Level

A research team at the Cleveland Clinic is busy developing virtual models of human knee joints. These models will provide us with a more complete picture of how the tissues and individual cells react to heavy loads. Researchers are hopeful that down the road, these models will be used to understand how certain mechanisms of the joint are damaged during the aging process or from debilitating diseases like osteoarthritis.

The research team is being led by Dr. Ahmet Erdemir, director of the Computational Biomodeling Core (CoBi) as well as faculty member in the Department of Biomedical Engineering at the Lerner Research Institute (LRI) in Cleveland, Ohio. The team hopes to leverage the immense computing capabilities of the Ohio Supercomputer Center in order to develop state-of-the-art computer generated representations of the human body. Utilizing these virtual models, the researchers will be able to understand much more about how certain movements and loads on the joints can deform the surrounding tissues and cells.

Medical researchers already know that certain diseases and the aging process can have a deteriorating effect on many aspects of the mechanical function in the human body. Over time, there is a change in the way our muscles, joints, tissues, and even cells handle the natural load exerted on the body during everyday activities. According to Dr. Erdemir, utilizing these computational techniques, researchers are able to gain additional insights into these body mechanics at several spatial scales.

There have already been a number of macro-scale studies which have examined how the numerous components of the knee joint (ligaments, cartilage, menisci, and bone) respond to various amounts of weight and other external loads. However, Dr. Erdemir and his colleague, Scott C. Sibole, wanted to learn how these large mechanical forces conformed to the deformation of singular cartilage cells (known as chondrocytes) located within the knee. In these prior micro-scale studies of the cartilage, most of the results had not been based on data collected from body-level scales, like the musculoskeletal mechanics of the knee joint.

Additionally, the calculated deformations usually were for a single cell at the middle of a 100-cubic-micrometer block of simulated tissue. Dr. Erdemir and his team used an anatomically correct representation which was able to calculate deformations for 11 cells delivered within the same value.

In comparison to the macro-scale tests, the cartilage cells experienced enhanced deformations in both micro-scale approaches. This had been predicted by simulating the compression of the tissues in the knee joint from the weight of the body.

Dr. Erdemir found that all the cells in the 11 cell case experienced less deformation than the single cell case, while at the same time exhibiting a larger degree of variance in deformation compared to the other cells located in the same block. Dr. Erdemir’s method proved to be quite scalable due to the independence of the micro-scale model which allows for exploitation of distributed memory computing architecture. Provided with this model, Sibole, a research engineer at LRI, was able to effectively utilize the pure computational muscle of OSC’s IBM 1350 Glenn Cluster. At the time, the Glenn Cluster provided Sibole access to 75 teraflops of computing power (or 75 trillion calculations per second!). Now the center has an even more powerful HP-Intel Xeon Oakley Cluster, so the old Glenn Cluster has been partially decommissioned.

Both of the flagship computing systems for the Ohio Supercomputer Center (OSC) were specifically designed to support innovative biomedical applications, just like the ones used by Dr. Erdemir. According to the OSC interim co-executive director, Ashok Krishnamurthy, they are helping to meet the demands of today’s medical researcher team. Researchers working at the various medical centers around Ohio need an ever-increasing amount of computational capability in order to handle their new studies and analyses.

The Ohio Supercomputer Center, a current member of the Ohio Technology Consortium of the Ohio Board of Regents, has been working to address the ever-increasing computational demands of the research community. They provide an ever-improving shred infrastructure with proven expertise in advanced simulation, modeling, and analysis. Today’s research teams need to be able to effectively leverage computational science in order to remain a competitive force in the clinical research industry.