PITTSBURGH (Feb. 16, 2020) ... An abdominal aortic aneurysm (AAA) can be a ticking time
bomb if undiscovered in time. However, researchers at the University of
Pittsburgh are developing a new model to better predict at-risk patients. And
the tools they are using apply mechanical testing to the human body - which is
itself a complex machine.
An AAA occurs when the aorta weakens and begins to
irreversibly dilate, like a slowly inflating balloon. If left untreated, the
risk of rupture increases and has a 90 percent rate of mortality, making AAA the
15th
leading cause of death in the United States with more than 15,000 deaths
reported annually.
Once diagnosed, clinicians must determine whether the aorta requires
surgery, using the AAA diameter to decide if an aneurysm is clinically
relevant. A diameter 5.5 centimeters or larger typically calls for surgical
intervention, barring other contraindications, but this one-size-fits-all
approach misses nearly 25 percent of patients who experience a rupture at a
smaller size.
Pitt bioengineer David A. Vorp received an award from the
National Institutes of Health to track the natural evolution of small AAA and
develop a predictive model to improve patient prognosis. His Vascular
Bioengineering Lab at the university’s Swanson School of Engineering is focused
on finding novel diagnoses and treatments for these silent killers.
“It’s a ticking time bomb,” explained Timothy Chung, a post-doctoral
associate in Vorp’s lab. “Once you diagnose an abdominal aortic aneurysm, you
don’t know when or if it’s going to rupture.
“Imagine you’re blowing up a balloon, and it pops. This
event involves the mechanics and forces that are interacting with the wall of
the balloon,” continued Chung, who will help lead the project. “We’re
interested in the biomechanics of why elevated pressure or a weakening of the
aneurysm wall might lead to rupture or accelerated growth.”
The research team hopes that CT scans and other data from a
rare, longitudinal clinical trial (“Non-Invasive Treatment
of Abdominal Aortic Aneurysm Clinical Trial”) will help them identify the
risks of elevated growth rate or eventual rupture.
Vorp’s lab group will create 3D geometric reconstructions
and perform biomechanical simulations on patient datasets at each imaging scan
interval (every six months) to learn how small AAA progresses over time. They
will then use the scans and unique software tools from their lab to perform shape
analyses that will determine which geometries may lead to poor patient
outcomes.
“Currently, clinicians are simply applying a one-dimensional
shape analysis, using diameter as a threshold for clinical intervention,” said
Chung. “The tools developed in the Vascular Bioengineering Lab can help us extract
more than one-dimensional measurements. They allow us to create two- and three-dimensional
shape indices derived from image-based surface reconstructions, allowing for a
more robust analysis.”
The team will then feed data from the shape analysis and
biomechanical simulations to train a machine learning algorithm to classify
different types of aneurysm outcomes. This will be used to develop a predictive
model that can help guide clinicians and determine the need for surgical
intervention.
“Early in my career, the advent of finite element analysis –
a computational method to predict mechanical wall stress distribution in
complex shapes both biological and human-made – provided a game-changing tool to better
understand the role of biomechanics in AAA disease,” said Vorp, Associate Dean
for Research and John A. Swanson Professor of Bioengineering. “Now, machine
learning technologies can not only help us better understand the combination of
factors that lead toward rupture or clinical intervention, but also package
that knowledge into a true, personalized health tool for those afflicted with this
potentially lethal condition.”
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2/16/2021
Contact: Leah Russell