With this technique and the computing power of high throughput computing (HTC) combined, researchers can obtain thousands of simulations to study the pathology of tendons and ligaments.

A recent paper published in the Journal of the Mechanical Behavior of Biomedical Materials by former Ph.D. student in the Department of Mechanical Engineering (and current post-doctoral researcher at the University of Pennsylvania) Jonathon Blank and John Bollinger Chair of Mechanical Engineering Darryl Thelen used the Center for High Throughput Computing (CHTC) to obtain their results. Results that, Blank says, would not have been obtained at the same scale without HTC. “[This project], and a number of other projects, would have had a very small snapshot of the problem at hand, which would not have allowed me to obtain the understanding of shear waves that I did. Throughout my time at UW, I ran tens of thousands of simulations — probably even hundreds of thousands.”

Using noninvasive sensors called shear wave tensiometers, researchers on this project applied HTC to study tendon structure and function. Currently, research in this field is hard to translate because most assessments of tendon and ligament structure-function relationships are performed on the benchtop in a lab, Blank explains. To translate the benchtop experiments into studying tendons in humans, the researchers use tensiometers as a measurement tool, and this study developed from trying to better understand these measurements and how they can be applied to humans. “Tendons are very complex materials from an engineering perspective. When stretched, they can bear loads far exceeding your body weight, and interestingly, even though they serve their roles in transmitting force from muscle to bone really well, the mechanisms that give rise to injury and pathology in these tissues aren’t well understood.”

In living organisms, researchers have used tensiometers to study the loading of muscles and tendons, including the triceps surae, which connects to the Achilles tendon, Blank notes. Since humans are variable regarding the size, stiffness, composition, and length of their tendons or ligaments, it’s “challenging to use a model to accurately represent a parameter space of human biomechanics in the real world. High throughput computing is particularly useful for our field just because we can readily express that variability at a large scale” through HTC. With Thelen and Orthopedics and Rehabilitation assistant professor Josh Roth, Blank developed a pipeline for simulating shear wave propagation in tendons and ligaments with HTC, which Blank and Thelen used in the paper.

With HTC, the researchers of this paper were able to further explore the mechanistic causes of changes in wave speed. “The advantage of this technique is being able to fully explore an input space of different stiffnesses, geometries, microstructures, and applied forces. The advantage of the capabilities offered by the CHTC is that we can fill the entire input space, not just between two data points, and thereby study changes in shear wave speed due to physiological factors and the mechanical underpinning driving those changes,” Blank elaborates.

It wasn’t challenging to implement, Blank states, since facilitators were readily available to help and meet with him. When he first started using HTC, Blank attended the CHTC office hours to get answers to his questions, even during COVID-19; during this time, there were also numerous one-on-one meetings. Having this backbone of support from the CHTC research facilitators propelled Blank’s research and made it much easier. “For a lot of modeling studies, you’ll have this sparse input space where you change a couple of parameters and investigate the sensitivity of your model that way. But it’s hard to interpret what goes on in between, so the CHTC quite literally saved me a lot of time. There were some 1,000 simulations in the paper, and HTC by scaling out the workload turned a couple thousand hours of simulation time into two or three hours of wall clock time. It’s a unique tool for this kind of research.”

The next step from this paper’s findings, Blank describes, is providing subject-specific measurements of wave speeds. This involves “understanding if when we use a tensiometer on someone’s Achilles tendon, for example, can we account for the tendon’s shape, size, injury status, etcetera — all of these variables matter when measuring shear wave speeds.” Researchers from the lab can then use wearable tensiometers to measure tension in the Achilles and other tendons to study human movement in the real world.

From his CHTC-supported studies, Blank learned how to design computational research, diagnose different parameter spaces, and manage data. “For my field, it [HTC] is very important because people are extremely variable — so our models should be too. The automation and capacity enabled by HTC makes it easy to understand whether our models are useful, and if they are, how best to tune them to inform human biomechanics,” Blank says.