Sriram Chandrasekaran Receives Research Scout Grant

U-M BME’s Sriram Chandrasekaran, Associate Professor of Biomedical Engineering, has a research project being funded by Research Scouts. 

Research Scouts is an agile, low-burden funding program from the Office of Research in the U-M Medical School which gives money to scientists (the “Scouts”) to invest in other scientists’ bold ideas. It’s an investment in the “Bold Science” objective of Michigan Medicine’s research strategic plan, “Great Minds, Greater Discoveries,” and is modeled on the Hypothesis Fund. The goals of the program are to: 

·Spark new scientific conversations and connections 

·Unleash the creativity of our scientists 

·Test bold ideas that may otherwise go unexplored 

·Have fun while facilitating new lines of investigation 

From diverse disciplines across the Medical School, Research Scouts are given funding and are empowered and motivated to support their fellow researchers’ bold ideas. Scouts are searching for early-stage ideas that can transform our current understanding of a scientific concept or field, challenge common dogma, or are wildly new and imaginative. 

“With $150k to invest, I wanted to fund Mars Shots – ideas that are a little out there and would never be funded by NIH but, if successful, could be game changers for Michigan Medicine and beyond,” says Peter Scott, Professor of Radiology and a Research Scout. 

Dr. Chandrasekaran’s lab examines ways that AI can be integrated into biomedical engineering research. “I was thinking through what the big medical challenges might be 25 years from now in my field, and I thought about the future of drug discovery and how the treatment of diseases such as cancer or infectious disease might change,” he said. “Clinicians are trying to use multiple types of treatment, not just drugs, but they are also giving their patients new immune therapies or changing their diets. During the last decade, there are different types of new treatments that people are exploring. For example, people use microbiome treatment and natural products. You can compare that to traditional drug treatments, and even combine them to see how they work well together.” 

Dr. Chandrasekaran’s formal Research Scout proposal says that by the year 2050, society may lose 50 million people a year to climate-change-associated health emergencies, such as the spread of drug-resistant pathogens. Suboptimal diet, lifestyle, and pollution will significantly dampen people’s immunity, while accelerating the spread of infections and immune disorders. Importantly, the pace of drug discovery has not kept up with the rapid emergence of these diseases. 

Future treatments for complex diseases such as cancer and drug-resistant infections will likely involve a combination of multiple therapeutic modalities targeting immunological and metabolic processes. Yet researchers lack a rational basis to design such multimodal treatments. For example, how should precision diets be designed to potentiate immunotherapies or antibiotics? 

To address this challenge, Dr. Chandrasekaran proposes developing integrative models that bridge cutting-edge simulation tools from various biomedical domains. His team will utilize hybrid AI methods to integrate mechanistic biochemical models and machine learning to impact a wide range of biological fields. 

Dr. Chandrasekaran noted that the use of AI algorithms tackles issues without traditional knowledge or bias. The AI algorithm recommends solutions purely based on the data present, not with preconceived ideas of the way processes or products may have traditionally worked. 

“Machine-learning algorithms can find the best way to combine different modalities, such as how you combine changes in metabolism or integrate a drug treatment,” he said. “We are trying to put completely different things together using AI to find the best treatment or combination of treatments to produce the best outcome.” 

Dr. Scott thinks Dr. Chandrasekaran’s idea to use Artificial Intelligence to revolutionize drug discovery is one such “Mars Shot.” “The idea of combining multiple therapies with environmental factors such as diet and lifestyle is the foundation of Precision Health,” Dr. Scott observes. Although the data exists, we currently lack a rational basis to design such individualized therapies. “Sriram’s proposal to use neural networks and high-throughput experimentation to crunch the data and identify multimodal therapies for the most complex diseases facing our patients was a light-bulb moment,” Dr. Scott notes. “If his lab is successful, it could cause a paradigm shift for drug discovery. I’m excited to see what they come up with!” 

Surgeon uses academic development time to collaborate with Biomedical Engineering

Drew Braet is a fourth-year resident in Vascular Surgery and is taking his two-year academic development time to work with C. Alberto Figueroa, the Edward B Diethrich M.D. Research Professor of Biomedical Engineering and Vascular Surgery, professor of surgery, Medical School and professor of biomedical engineering, Medical School and College of Engineering. Dr. Braet’s goal from this collaboration is to gain a better understanding of determining which patients are most likely to benefit from surgical intervention. 

“I sought to work with Biomedical Engineering, and Dr. Figueroa, specifically, by choice,” Dr. Braet said. “Early in my training, I became frustrated with the lack of information we often have about vascular disease, particularly when looking at which patients we should or should not offer surgery to. It’s pretty typical in medicine that things aren’t black and white, and that there are many gray areas. We’re really lacking clear data in a lot of different realms that can help us with decision making.”

“It is not typical that a surgeon would do research in an engineering laboratory like ours,” said Dr. Figueroa. “To have someone who goes from operating on patients to then spending two years learning analytical tools–imaging tools, modeling tools and computational tools–is somewhat unique.” A two-year research period is mandatory at U-M, but most people in the training program do not end up focusing on Engineering. “Historically, most trainees do time working in a basic science wet laboratory,” he added. 

Dr. Braet was researching information in his quest to learn more ways data analysis can inform surgical interventions, and through a Google search, came upon Dr. Figueroa’s lab. 

“I thought what he was doing in using computational methods in advanced imaging analysis would really help me,” Dr. Braet said. “I wanted to learn a tool set to be able to explore some of the questions I had. I ultimately want to improve our understanding and to provide better patient care. We met early on in my intern year. I heard about some of the work they were doing in the lab and explained some of the things I was interested in. In my intern year, we started doing a smaller project. Dr. Nick Burris, a radiologist, and I worked on that for a year, and we were able to publish a paper. From there, we started thinking about a bigger project that we could do during my dedicated time, and that led us to do my current project and current NIH F32 fellowship, where I’m looking at patients with high-grade asymptomatic carotid artery disease.”

The carotid artery is the artery in your neck that goes to your brain. “Patients who have narrowings in that artery have buildup of cholesterol plaque, the same kind of plaque that can lead to heart attacks,” Dr. Braet said. “That plaque can break off, and cause a stroke. The way that we think about these plaques in medicine is based on historical studies which suggest that the percentage of narrowing of the carotid artery is related to the risk of having a stroke. When I think about that from a biophysical and biomechanical standpoint, it doesn’t make sense. Not to discredit the studies that were previously done, this is what science has shown and we have helped a lot of people by thinking that way. But when you really boil it down to the biophysics of blood flow, that doesn’t make sense, because plaques rupture when the forces exerted on them exceed the strength of the tissue. We’re doing a computational modeling study by looking at the pressure differences, the velocity differences and the wall shear stress on carotid artery plaques to try to get a better understanding of the hemodynamic strains and stresses of the plaque and thus the risk of stroke. This could potentially lead to an entirely new way of looking at the way patients present with this particular issue. In a perfect world, 20 years from now, it would be great if the medical field could be using some of the things that we’re studying today. These kinds of engineering, imaging and modeling analyses, I think, will help us do a much better job with risk stratification that ultimately will determine whether to perform surgery or to watch a patient more conservatively.”

Dr. Braet noted that it is “refreshing” to learn to examine problems in a different way. ”In the big picture, if more surgeons and more doctors learned to look at challenges differently, we might be able to be more creative in the treatments that we can offer,” Dr. Braet said. The analysis of big data and the use of technological innovations are playing increasingly important roles in medicine, and Dr. Braet wants to understand how Engineering can assist the profession.

Dr. Figueroa noted the value of this type of mentorship for the mentor as well as the mentee. “It’s interesting because someone like Drew has a very different background and very different ways of seeing a problem than someone from a traditional engineering background,” he said. “Everybody talks about translation and reaching out, and when you are in engineering, you want to have your tools applied, but it’s actually quite difficult to do because of how distant the training and the day-to-day professional thought processes these two groups have. In engineering, you typically say you want to talk to clinicians because at the end, they are your customers for developing a new device or a new diagnostic procedure. Eventually, they’re going to have to use it and understand it, right?”

The fact that the University of Michigan has a Biomedical Engineering Department that is jointly in both the Medical School and in the College of Engineering enhances these opportunities for collaboration. There are a lot of institutions out there where perhaps they have a biomedical engineering department, but they don’t have a medical school,” Dr. Figueroa said. “In those institutions, this understanding is much harder to achieve because the engineering folks are kind of isolated and they don’t have ready access to clinical peers.”

Dr. Figueroa added that the opportunity to serve as a mentor is a rewarding experience, professionally and personally. “To me, it’s important that when I one day finish my career, I will have contributed to training a small group of clinicians who have an engineering thought process,” he said.

Closest look yet at killer T-cell activity could yield new approach to tackling antibiotic resistance An in-depth look at the work of T-cells, the body's bacteria killers, could provide a roadmap to effective drug treatments.

In a study that could provide a roadmap for combatting the rising threat of drug-resistant pathogens, researchers have discovered the specific mechanism the body’s T-Cells use to kill bacteria.

University of Michigan researchers, in collaboration with colleagues at Harvard University, have discovered a key difference between the way immune cells attack bacteria and the way antibiotics do. Where drugs typically attack a single process within bacteria, T-Cells attack a host of processes at the same time.

On Thursday, the journal Cell published findings from a team headed by U-M’s Sriram Chandrasekaran and Harvard’s Judy Lieberman. It’s a study with potential implications for drug-resistant pathogens—a problem projected to kill as many as 10 million people annually across the globe by the year 2050.

“We have a huge crisis of antibiotic resistance right now in that most drugs that treat diseases like tuberculosis or listeria, or pathogens like E.coli, are not effective,” said Chandrasekaran, an assistant professor of biomedical engineering. “So there is a huge need for figuring out how the immune system does its work. We hope to design a drug that goes after bacteria in a similar way.”

We’ve reached a point where we take what antibiotics can do for granted, and we can’t do that anymore.Sriram Chandrasekaran

Killer T-Cells, formally known as cytotoxic lymphocytes, attack infected cells by producing the enzyme granzyme B. How this enzyme triggers death in bacteria has not been well understood, Chandrasekaran said.

Proteomics – a technique that measures protein levels in a cell—and computer modeling, allowed researchers to see granzyme B’s multi-pronged attack targeting multiple processes.

Chandrasekaran and his team monitored how T-Cells deal with three different threats: E. coli, listeria and tuberculosis.

“When exposed to granzyme B, the bacteria were unable to develop resistance to the multi-pronged attack, even after exposure over multiple generations,” Chandrasekaran said. “This enzyme breaks down multiple proteins that are essential for the bacteria to survive.

“It’s essentially killing several birds with one stone.”

The possible applications of the new findings on T-Cells run the gamut from the creation of new medications to the re-purposing of previously-approved drugs in combination to fight infections by mimicking granzyme B.

Chandrasekaran’s team is now looking at how bacteria hide to avoid T-Cell attacks.

And the need for a new approach in some form is dire. World Health Organization officials describe antibiotic resistance as “one of the biggest threats to global health, food security and development today.”

Sriram Chandrasekaran, Assistant Professor of Biomedical Engineering, shows a computer model of a pathway for a potential disease or infection. Photo: Joseph Xu

Each year, an estimated 700,000 deaths are linked to antibiotic-resistant bacteria, according to the World Health Organization. Projections show that number skyrocketing to 10 million by 2050.

England’s top health official, Sally Davies, recently said the lost effectiveness of antibiotics would mean “the end of modern medicine.”

“We really are facing—if we don’t take action now—a dreadful post-antibiotic apocalypse,” she was quoted saying earlier this month. “I don’t want to say to my children that I didn’t do my best to protect them and their children.”

Of particular concern is the fact that there are few new antibiotics in the pipeline. The heyday of new antibiotics occurred the 1940s through the 1960s, with releases eventually grinding almost to a halt by the end of the twentieth century.

“We’ve reached a point where we take what antibiotics can do for granted, and we can’t do that anymore,” Chandrasekaran said. “We’re taking inspiration from the human immune system, which has been fighting infections for thousands of years.”

The paper is titled, “Granzyme B disrupts central metabolism and protein synthesis in bacteria to promote an immune cell death program.” The research is funded by the National Institutes of Health, Harvard University and the University of Michigan.


Understanding pediatric pulmonary hypertension Creating new imaging and modeling tools to improve diagnosis and management

Image caption: Multi-scale modeling framework of the cardiopulmonary system. Credit: Figueroa et al.

by Kim Roth

Pulmonary hypertension (PH), a lung disorder that causes high blood pressure in the pulmonary arteries, affects an estimated 15 million to 50 million individuals worldwide. Its progressive nature, impact on quality of life, and life-threatening long-term consequences make it an important focus of basic scientific and translational research.

“Pulmonary hypertension is a relatively rare disease, but the incidence is likely underestimated, since definitive diagnosis currently requires an invasive heart catheterization” says C. Alberto Figueroa, the Edward B. Diethrich M.D. Associate Professor of Biomedical Engineering and Vascular Surgery.

In addition, non-invasive diagnostic tests, and those used to assess severity, can be highly subjective. Existing treatments mainly target symptoms rather than the underlying cause, which can also be hard to identify. Over time, PH can lead to heart failure; in many cases, patients require a heart or lung transplant.

Particularly in children, diagnosing and treating PH poses unique challenges. Their smaller size and faster heart rate make imaging more difficult than in adult patients.

With U-M colleague Adam Dorfman, MD, associate professor of pediatric cardiology, and colleagues at Michigan State University and Nationwide Children’s Hospital, Figueroa is developing a comprehensive multiscale model of the cardiopulmonary system in pediatric PH.

Using data from MRI and heart catheterization studies in 25 patients – 20 with PH and five cardiac transplant controls – computational models will integrate clinical information, including vessel stiffness and geometry and heart structure and function. The result will be high-resolution simulations of both blood flow dynamics and tissue mechanics of the entire cardiopulmonary system.

Over the four-year study, the team will investigate well-known mechanistic factors at work in PH.

“We know that PH is characterized by smooth muscle hypertrophy, endothelial dysfunction and deposition of collagen and elastin, which result in biomechanical alterations in the system, such as increased resistance and stiffness. While we know that these mechanistic parameters play a critical role, we don’t yet have a full understanding of how they interact and potentially lead to decompensated right ventricular failure,” says Figueroa. “One of our goals is to identify a series of mechanistic markers – rather than the existing subjective assessment tools – to use for patient stratification.”

The work builds upon Figueroa’s previous research. Prior to joining the U-M faculty in 2014, he developed new algorithms to perform simulations of fluid-structure interactions in cardiovascular models constructed from image data. Thanks to the algorithms, simulation of blood flow and artery dynamics in full-scale models became possible.

The exceptional computational resources within the College of Engineering and the world-class clinical expertise in PH management, in both adult and pediatric populations, make U-M the right place to carry out this latest study, Figueroa says.

Ultimately, the goal is to create new imaging and computational modeling tools to improve diagnosis and management of PH on a patient-specific basis.

“If our effort is successful, we might reduce or eliminate the need for risky and invasive catheterization procedures,” -Alberto Figueroa

“If our effort is successful, we might reduce or eliminate the need for risky and invasive catheterization procedures,” says Figueroa. The findings also will be applicable to systemic hypertension, which affects some 36 percent of Americans.

Longer term, Figueroa and Dorfman hope to create a patient-specific computational framework to test the efficacy of new drugs.

“Once we understand the mechanisms better,” says Dorfman, “we can work toward more effective ways of treating pediatric PH. Because, really, at the end of the day, we’re trying to help kids be kids.”

The effort is funded by a $2.4 million U01 grant from the National Institutes of Health, U01HL135842: Image-Based Multi-Scale Modeling Framework of the Cardiopulmonary System: Longitudinal Calibration and Assessment of Therapies in Pediatric Pulmonary Hypertension.

Keeping drugs on the job

Mandal’s simulation shows how well the polymers slow down the formation of crystals. Polymers are shown in red and green while drug molecules are maize and blue.
Computer simulations developed at the University of Michigan reveal how well drug additives stop the active ingredients from crystallizing in the digestive tract. They tested these simulations on the anti-seizure drug phenytoin.

“Most drugs are hydrophobic, so the mix of water and drugs is not stable,” said Taraknath Mandal, a research fellow in chemical engineering. “They spontaneously form a crystal.”

In the water-based environment of the stomach and small intestine, the active ingredients stick together, and then they don’t make it into the bloodstream. Pharma companies add polymers to drugs to get in the way of crystal growth, but the range of possible designs for these polymers is huge.

The computer simulations enable researchers to try out different polymers, looking for the best performance.

“These tools have never been used before on this problem,” said Ron Larson, the A. H. White Distinguished University Professor of Chemical Engineering and the George Granger Brown Professor of Chemical Engineering, who led the work. He and his team worked closely with researchers at Dow Chemical Company in Midland, Michigan, including WW (Trey) Porter, the team lead on the Dow side.

They tested the simulation with several drugs, focusing on how phenytoin interacted with a cellulose-based polymer – the stuff that makes up the cell walls in plants. They compared how different side groups on the cellulose chain affected how well the polymer kept phenytoin from crystallizing in the simulated gut environment.

The team tested two side-groups head to head – succinyl and acetyl. Both are needed to make a polymer effective in both the acidic environment of the stomach and the more neutral environment of the small intestine.

In the stomach, the succinyl groups have the full complement of hydrogen atoms, so they are not charged. They help the polymer interact with a hydrophobic drug like phenytoin. A charged polymer will be attracted to the water rather than the drug.

But once the polymers hit the small intestine, some hydrogen atoms strike out on their own, leaving the succinyl with a negative charge. Here, the acetyl groups take over helping to keep the polymer groups together even as the neutral succinyl groups expand. Larson and his group developed computer models to find the best balance.

Of course, patients don’t gain anything if the drug additives keep the drug from crystallizing but instead traps it in a web of polymers. Or, if the drugs are released too quickly, they can crystallize in the small intestine. Wenjun Huang, a doctoral student in chemical engineering, created a second simulation to test how well drugs leave the polymer webs.

“Our simulation results are the first ones to directly show the role of each individual functional group in the polymer,” said Huang. “We can see the polymer-drug aggregates form, and we can see how drugs are released from the aggregates.”

Green and red polymers help keep maize and blue drug molecules from crystallizing. Credit: Taraknath Mandal, Larson Lab, University of Michigan.
Again, a balance between the succinyl and acetyl groups is needed to achieve the right pace, and the balance is different for different drugs.

“We are beginning to learn how to determine computationally which modifications to the polymer will be most effective at interacting with a given drug and thereby help in the design of better polymers to enhance drug delivery,” said Larson.

These studies were funded primarily by the Dow Chemical Company. The team also relied on Advanced Research Computing at U-M, funded by the National Science Foundation.

The paper on the model that investigates how well different polymers work to prevent drug crystallization is titled “A framework for multi-scale simulation of crystal growth in the presence of polymers,” and it was published in Soft Matter.

The paper on the computer model that explores whether drugs are released from the web of polymers is titled “Computational Modeling of Hydroxypropyl-Methylcellulose Acetate Succinate (HPMCAS) and Phenytoin Interactions: A Systematic Coarse-Graining Approach,” and it was published in the journal Molecular Pharmaceutics.

Larson is also a professor of macromolecular science and engineering, biomedical engineering, and mechanical engineering, and is a member of the Biointerfaces program.

From: Kate McAlpine, Michigan Engineering


‘5-D protein fingerprinting’ could give insights into Alzheimer’s, Parkinson’s

ANN ARBOR—In research that could one day lead to advances against neurodegenerative diseases like Alzheimer’s and Parkinson’s, University of Michigan engineering researchers have demonstrated a technique for precisely measuring the properties of individual protein molecules floating in a liquid.

Proteins are essential to the function of every cell. Measuring their properties in blood and other body fluids could unlock valuable information, as the molecules are a vital building block in the body. The body manufactures them in a variety of complex shapes that can transmit messages between cells, carry oxygen and perform other important functions.

Sometimes, however, proteins don’t form properly. Scientists believe that some types of these misshapen proteins, called amyloids, can clump together into masses in the brain. The sticky tangles block normal cell function, leading to brain cell degeneration and disease.

But the processes of how amyloids form and clump together are not well understood. This is due in part to the fact that there’s currently not a good way to study them. Researchers say current methods are expensive, time-consuming and difficult to interpret, and can only provide a broad picture of the overall level of amyloids in a patient’s system.

The University of Michigan and University of Fribourg researchers who developed the new technique believe that it could help solve the problem by measuring an individual molecule’s shape, volume, electrical charge, rotation speed and propensity for binding to other molecules.

They call this information a “5-D fingerprint” and believe that it could uncover new information that may one day help doctors track the status of patients with neurodegenerative diseases and possibly even develop new treatments. Their work is detailed in a paper published in Nature Nanotechnology.

“Imagine the challenge of identifying a specific person based only on their height and weight,” said David Sept, a U-M biomedical engineering professor who worked on the project. “That’s essentially the challenge we face with current techniques. Imagine how much easier it would be with additional descriptors like gender, hair color and clothing. That’s the kind of new information 5-D fingerprinting provides, making it much easier to identify specific proteins.”

Michael Mayer, the lead author on the study and a former U-M researcher who’s now a biophysics professor at Switzerland’s Adolphe Merkle Institute, says identifying individual proteins could help doctors keep better tabs on the status of a patient’s disease, and it could also help researchers gain a better understanding of exactly how amyloid proteins are involved with neurodegenerative disease.

This illustration depicts the device used to measure individual protein. The inset shows proteins (in red) flowing through a nanopore.

To take the detailed measurements, the research team uses a nanopore 10-30 nanometers wide—so small that only one protein molecule can fit through at a time. The researchers filled the nanopore with a salt solution and passed an electric current through the solution.

As a protein molecule tumbles through the nanopore, its movement causes tiny, measurable fluctuations in the electric current. By carefully measuring this current, the researchers can determine the protein’s unique five-dimensional signature and identify it nearly instantaneously.

“Amyloid molecules not only vary widely in size, but they tend to clump together into masses that are even more difficult to study,” Mayer said. “Because it can analyze each particle one by one, this new method gives us a much better window to how amyloids behave inside the body.”

Ultimately, the team aims to develop a device that doctors and researchers could use to quickly measure proteins in a sample of blood or other body fluid. This goal is likely several years off; in the meantime, they are working to improve the technique’s accuracy, honing it in order to get a better approximation of each protein’s shape. They believe that in the future, the technology could also be useful for measuring proteins associated with heart disease and in a variety of other applications as well.

“I think the possibilities are pretty vast,” Sept said. “Antibodies, larger hormones, perhaps pathogens could all be detected. Synthetic nanoparticles could also be easily characterized to see how uniform they are.”

The study is titled “Real-time shape approximation and fingerprinting of single proteins using a nanopore.” Funding for the project was provided by the Miller Faculty Scholar Award, Air Force Office of Scientific Research, National Institutes of Health, National Human Genome Research Institute, a Rackham Pre-Doctoral Fellowship from U-M and the Microfluidics in Biomedical Sciences Training Program from the National Institutes of Health and National Institute of Biomedical Imaging and Bioengineering.


More information:

Taking the Guesswork out of Surgical Planning How BME professor Alberto Figueroa’s patient-specific blood flow simulations help clinicians find the ideal surgical path

by Aimee Balfe

Alberto Figueroa’s BME lab has achieved an important goal – using computer-generated blood flow simulations to plan complex cardiovascular procedures.

“We’re now using virtual surgical planning in the clinical realm, not as a retrospective theoretical exercise,” says Figueroa.

Using patients’ medical and imaging data, Figueroa can create a model of their unique vasculature and blood flow, then use it to guide surgeons and cardiologists through specific operations and procedures. One type of procedure involves placing grafts in the inferior vena cava to help alleviate complications from pulmonary arteriovenous malformations (PAVMs).


PAVMs – abnormal connections between a patient’s veins and arteries – are a common complication of a procedure performed early in the lives of children born with only a single functioning ventricle. Called the Fontan procedure, the operation rewires patients’ pulmonary circulation so that the venous return bypasses the heart and is connected directly to the pulmonary arteries for transport to the lungs.

While these surgeries can be lifesavers, the long-term consequences depend heavily on how evenly blood flow is distributed between a patient’s lungs. Patients with ideal hemodynamics do well; those with less-than-perfect flow patterns suffer a sting of life-threatening complications, such as low blood oxygen and elevated cardiac output.

Figueroa’s technique can help those with complications by better balancing flow to the lungs.

Simulation & Outcome: A Perfect Match

“What we bring to the table in operations like this is, instead of going in blind, we can simulate multiple different ways of doing the procedure to see if there is an optimal one.”

Figueroa makes use of detailed anatomical data such as CT scans, Doppler data on velocity in various vessels, invasive catheterization data that shows pressures at multiple locations, and perfusion data from nuclear medicine tests. His lab creates hemodynamic models of each patient that match these data points precisely. They then simulate multiple different ways of placing a stent graft using U-M's high performance Flux computing cluster, provided by Advanced Research Computing, to identify the best outcome.

“During these procedures, the surgeons use angiograms to illuminate the blood flow,” says Figueroa. “This has shown that the results match what our computer simulation predicted.” (See image.)

“The clinicians were amazed, but we told them we were just solving Newton’s law.”  Alberto Figueroa


Before (left) and after (right) images from an angiogram (top) and a surgical simulation (bottom). Note the tight correlation between the simulations and angiograms as well as the significantly more even distribution of hepatic venous flow between the two lungs after a simulation-guided procedure. Credit: Kevin Lau, Alberto Figueroa.

Better Primary Surgeries

In addition to corrective surgeries, these simulation techniques can also allow surgeons to optimize initial procedures like the Fontan so that complications may never happen at all.

Of the tens of thousands of patients undergoing Fontan operations each year, he says, roughly half experience major complications after 10 years. That’s because it’s almost impossible for surgeons to know exactly how to perform the procedure on patients with vessels of various sizes, shapes, and flows.

By accounting for these differences, Figueroa hopes his simulations will show surgeons where in the vasculature to make the surgical connections so that blood flow is ideally balanced between the lungs in each patient. He plans to work with U-M colleagues on patient-specific Fontan planning.

And because his simulations add a layer of insight to any procedure where cardiologists and surgeons find that doing things the same way works in some patients and not others, Figueroa hopes they’ll soon become a ubiquitous precision planning tool, much like imaging is today.

Additional Applications

As promising as it is, surgical planning is only the tip of the iceberg for Figueroa. His lab also works to further develop its simulation software and to use it to understand disease progression, always with an eye toward devising better treatments.

In the software arena, his lab is working on enhancements that will account for dynamic changes in blood flow caused by anything from a change in posture to anesthesia.

One of the lab’s clinical fellows is studying how blood vessels remodel in response to the grafts used in thoracic aneurysm repair. Another is modeling aortic dissection, aiming to discover precisely how the flap that shears from the vessel wall moves, deforms the aorta, and affects blood flow. This understanding is a first step toward designing a device specifically for this condition.

His lab also hosts BME students who are developing tools to better understand blood flow in the brain, clot-development in veins, and the progression of hypertension, including which types of vessels sustain various degrees of damage over time. Figueroa has recently submitted a collaborative grant to explore the progression of pulmonary hypertension, as well.

The breadth and clinical relevance of his work are in many ways why Figueroa came to U-M from King’s College, London, two years ago. Named the Edward B. Diethrich M.D. Research Professor of Biomedical Engineering and Vascular Surgery, Figueroa, a PhD, was drawn by his 50/50 appointment in BME and vascular surgery at an institution where medicine and engineering are deeply integrated.

It’s because of this connection that rapid-response surgical planning is made possible, he says. It’s also given him ready access to talented students from the medical and engineering schools – and to usually hard-to-reach study participants, like aortic dissection patients, to gain critical insight into this and other life-threatening conditions.

$3.46M to Combine Supercomputer Simulations with Big Data

A new way of computing could lead to immediate advances in aerodynamics, climate science, cosmology, materials science and cardiovascular research. The National Science Foundation is providing $2.42 million to develop a unique facility for refining complex, physics-based computer models with big data techniques at the University of Michigan, with the university providing an additional $1.04 million.

The focal point of the project will be a new computing resource, called ConFlux, which is designed to enable supercomputer simulations to interface with large datasets while running. This capability will close a gap in the U.S. research computing infrastructure and place U-M at the forefront of the emerging field of data-driven physics. The new Center for Data-Driven Computational Physics will build and manage ConFlux.

Turbulence simulations for a vortex such as a tornado, a galaxy, or the swirls that form at the tips of airplane wings. Courtesy of Karthik Duraisamy, Aerospace Engineering.

Turbulence simulations for a vortex such as a tornado, a galaxy, or the swirls that form at the tips of airplane wings. Courtesy of Karthik Duraisamy, Aerospace Engineering.

Turbulence simulations for a vortex such as a tornado, a galaxy, or the swirls that form at the tips of airplane wings. Courtesy of Karthik Duraisamy, Aerospace Engineering.

Turbulence simulations for a vortex such as a tornado, a galaxy, or the swirls that form at the tips of airplane wings. Courtesy of Karthik Duraisamy, Aerospace Engineering.


The project will add supercomputing nodes designed specifically to enable data-intensive operations. The nodes will be equipped with next-generation central and graphics processing units, large memories and ultra-fast interconnects.

A three petabyte hard drive will seamlessly handle both traditional and big data storage. Advanced Research Computing – Technology Services at University of Michigan provided critical support in defining the technical requirements of ConFlux. The project exemplifies the objectives of President Obama’s new National Strategic Computing Initiative, which has called for the use of vast data sets in addition to increasing brute force computing power.

The common challenge among the five main studies in the grant is a matter of scale. The processes of interest can be traced back to the behaviors of atoms and molecules, billions of times smaller than the human-scale or larger questions that researchers want to answer.

Even the most powerful computer in the world cannot handle these calculations without resorting to approximations, said Karthik Duraisamy, an assistant professor of aerospace engineering and director of the new center. “Such a disparity of scales exists in many problems of interest to scientists and engineers,” he said.

But approximate models often aren’t accurate enough to answer many important questions in science, engineering and medicine. “We need to leverage the availability of past and present data to refine and improve existing models,” Duraisamy explained.

Turbulence simulations for a vortex such as a tornado, a galaxy, or the swirls that form at the tips of airplane wings. Courtesy of Karthik Duraisamy, Aerospace Engineering.

Data from hospital scans, when fed into a computer model of blood flow, can become a powerful predictor of cardiovascular disease. Courtesy of Alberto Figueroa, Biomedical Engineering.

Turbulence simulations for a vortex such as a tornado, a galaxy, or the swirls that form at the tips of airplane wings. Courtesy of Karthik Duraisamy, Aerospace Engineering.

Data from hospital scans, when fed into a computer model of blood flow, can become a powerful predictor of cardiovascular disease. Courtesy of Alberto Figueroa, Biomedical Engineering.


This data could come from accurate simulations with a limited scope, small enough to be practical on existing supercomputers, as well as from experiments and measurements. The new computing nodes will be optimized for operations such as feeding data from the hard drive into algorithms that use the data to make predictions, a technique known as machine learning.

“Big data is typically associated with web analytics, social networks and online advertising. ConFlux will be a unique facility specifically designed for physical modeling using massive volumes of data,” said Barzan Mozafari, an assistant professor of computer science and engineering, who will oversee the implementation of the new computing technology.

The faculty members spearheading this project come from departments across the University, but all are members of the Michigan Institute for Computational Discovery and Engineering (MICDE), which was launched in 2013.

“MICDE is the home at U-M of the so-called third pillar of scientific discovery, computational science, which has taken its place alongside theory and experiment,” said Krishna Garikipati, MICDE’s associate director for research.

The following projects will be the first to utilize the new computing capabilities:

  • Cardiovascular disease. Noninvasive imaging such as MRI and CT scans could enable doctors to deduce the stiffness of a patient’s arteries, a strong predictor of diseases such as hypertension. By combining the scan results with a physical model of blood flow, doctors could have an estimate for arterial stiffness within an hour of the scan. The study is led by Alberto Figueroa, the Edward B. Diethrich M.D. Research Professor of Biomedical Engineering and Vascular Surgery.
  • Turbulence. When a flow of air or water breaks up into swirls and eddies, the pure physics equations become too complex to solve. But more accurate turbulence simulation would speed up the development of more efficient airplane designs. It will also improve weather forecasting, climate science and other fields that involve the flow of liquids or gases. Duraisamy leads this project.
  • Clouds, rainfall and climate. Clouds play a central role in whether the atmosphere retains or releases heat. Wind, temperature, land use and particulates such as smoke, pollen and air pollution all affect cloud formation and precipitation. Derek Posselt, an associate professor of atmospheric, oceanic and space sciences, and his team plan to use computer models to determine how clouds and precipitation respond to changes in the climate in particular regions and seasons.
  • Dark matter and dark energy. Dark matter and dark energy are estimated to make up about 96 percent of the universe. Galaxies should trace the invisible structure of dark matter that stretches across the universe, but the formation of galaxies plays by additional rules – it’s not as simple as connecting the dots. Simulations of galaxy formation, informed by data from large galaxy-mapping studies, should better represent the roles of dark matter and dark energy in the history of the universe. August Evrard and Christopher Miller, professors of physics and astronomy, lead this study.
  • Material property prediction. Material scientists would like to be able to predict a material’s properties based on its chemical composition and structure, but supercomputers aren’t powerful enough to scale atom-level interactions up to bulk qualities such as strength, brittleness or chemical stability. An effort led by Garikipati and Vikram Gavini, a professor and an associate professor of mechanical engineering, respectively, will combine existing theories with the help of data on material structure and properties.

“It will enable a fundamentally new description of material behavior—guided by theory, but respectful of the cold facts of the data. Wholly new materials that transcend metals, polymers or ceramics can then be designed with applications ranging from tissue replacement to space travel,” said Garikipati, who is also a professor of mathematics.