Mathematics and biomedical engineering professor Jennifer Mueller is leading a study using Electrical Impedance Tomography to image the lungs of severely ill COVID-19 patients.
Photos by Allie Ruckman/College of Natural Sciences
COVID-19 is a respiratory illness that can lead to lung failure, requiring some patients to be sedated and placed on mechanical ventilation.
Helping extremely ill patients like this is the motivation behind a new study led by Jennifer Mueller, a professor in the Department of Mathematics and the School of Biomedical Engineering, and a Professor Laureate in the College of Natural Sciences. Mueller specializes in a noninvasive pulmonary imaging technology called Electrical Impedance Tomography, and her goal is to help patients receive more targeted care and have better chances of recovery.
Teaming up with Dr. Ellen Burnham, a professor at the University of Colorado School of Medicine on the CU Anschutz Medical Campus, Mueller is supported by the National Institutes of Health on a COVID-focused study aimed at proving the clinical relevance of Electrical Impedance Tomography, or EIT. Using an investigational EIT system produced by collaborators at GE Research, Mueller and colleagues are examining the lungs of COVID patients undergoing mechanical ventilation to help doctors make decisions about individual patients’ care.
As part of the study, Mueller is also partnering with Dr. Julie Dunn at the UCHealth Medical Center of the Rockies. There, Dunn will lead imaging of patients suspected of having pulmonary embolism, or a blood clot in the lung, in order to validate EIT for computing ventilation perfusion ratios. These are measures of how well both air and blood are reaching the lungs.
The project is supplemental to ongoing NIH-funded work Mueller has led in collaboration with Dr. Emily DeBoer at Children’s Hospital Colorado, in which they’ve used EIT to image the lungs of patients with cystic fibrosis, spinal muscular atrophy and bronchopulmonary dysplasia. In the cystic fibrosis studies, the researchers used EIT to look for regions of air trapping, which is a major concern for those patients.
In the wake of the COVID-19 pandemic, Mueller received the supplemental NIH funding that allowed her to shift her EIT research to studying COVID patients suffering from Acute Respiratory Distress Syndrome. EIT, Mueller said, could provide doctors with, simple, safe, targeted ventilation and intervention strategies for COVID patients. COVID respiratory distress has posed unique challenges that differ from more typical respiratory problems, so the project aims to give doctors a larger toolbox of personalized care for such patients.
Bringing EIT to the clinic
EIT is not currently used in clinical settings in the United States. For over two decades, Mueller has led pioneering studies aimed at proving out the technology and getting it ready for use in hospitals and doctor’s offices. Mueller says the NIH-funded work could pave the wave for the first commercial EIT system available in the U.S.
Mueller demonstrates the updated EIT machine, which she is using for the COVID-19 study.
For imaging inside the body, doctors typically use gold-standard imaging like computerized tomography – which involves a large amount of X-ray radiation – or magnetic resonance imaging. Both require expensive machinery and are not suitable in all settings, particularly with children. EIT, on the other hand, is noninvasive, non-ionizing, and provides real-time data.
“Although the resolution of EIT cannot compete with that of CT and MRI,” Mueller said, “the images still provide real-time regional maps of ventilation and perfusion in the lungs. This can’t be obtained with any other imaging modality, and you can do it safely and continuously at the bedside, for as long as you want. Any age is fine, including kids and babies.”
Using a new, portable, hospital-friendly imaging platform made by GE Research, Burnham will lead data collection on about 40 patients with COVID-19 at the CU Anschutz Medical Campus. The researchers are seeking to answer several questions, including: Does proning (turning patients on their stomachs) help them breathe better and get them off the ventilator faster? Could real-time imaging someday help doctors make more informed decisions on whether a patient is ready to wean off a ventilator?
From algorithm to clinic
Mueller is a mathematician who co-pioneered a reconstruction algorithm called D-bar that forms the basis of her current EIT platform. D-bar is different from traditional EIT algorithms. “Instead of approaching the correct solution stepwise, D-bar goes straight to the solution,” Mueller explained. The method allows the imager to directly visualize all or part of a lung and to gather conductivity information like breathing and perfusion maps, rather than having to employ a model simulation.
Mueller has worked in Electrical Impedance Tomography since 2000 when she was a postdoctoral researcher at Rensselaer Polytechnic Institute and worked with Jonathan Newell and David Isaacson, who are pioneers in the technology. She started in this field on the mathematical side working on the D-bar and other algorithms but was drawn toward the clinical applications, with the goal of making a real impact with patients.
“The overall goal of my research is to provide a technology that will truly help doctors treat patients with lung conditions,” she said.
After serving as a faculty member for several years at CSU, Mueller founded the EIT lab in 2011. She has continued collaborating with partners at RPI and the University of Albany, as well as with Samuli Siltanen, a researcher at the University of Helsinki with whom she recently co-authored a book about linear and nonlinear inverse problems. Her other collaborators are at the University of San Paulo in Brazil, with whom she was first funded by the NIH and who helped get her lab at CSU started.