A Cleveland Clinic research team is developing virtual models of human knee joints to better understand how tissues and their individual cells react to heavy loads – virtual models that someday can be used to understand damage mechanisms caused by the aging process or debilitating diseases, such as osteoarthritis.
The team is leveraging the powerful computing systems of the Ohio Supercomputer Center to develop state-of-the-art computational representations of the human body to understand how movement patterns and loads on the joints deform the surrounding tissues and cells.
Many macro-scale studies have looked at how the various components of a knee joint – cartilage, menisci, ligaments and bone – respond to weight and other external loads. However, researchers wanted to better understand how those large mechanical forces correspond to the related deformation of individual cartilage cells – or chondrocytes – within the knee. Previous micro-scale studies of cartilage have not commonly been based on data from body-level scales, in particular, by the musculoskeletal mechanics of the knee joint.
In addition, calculated deformations typically have been for a single cell at the center of a 100-cubic-micrometer block of simulated tissue; researchers used an anatomically based representation that calculated deformations for 11 cells distributed within the same volume.
The teams method proved to be highly scalable because of micro-scale model independence that allowed exploitation of distributed memory computing architecture. As a result, a research engineer was able to leverage the computational muscle of OSC’s IBM 1350 Glenn Cluster. At the time, the 9,500 nodes of the Glenn Cluster provided 75 teraflops of computing power, tech-speak for 75 trillion calculations per second.
This story is reprinted from material from Ohio Supercomputer Center, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier. Link to original source.