Charting new territory in personalized medicine
Advancing personalized care for patients with chest deformities using computational blood flow modeling
For many children and adults born with malformed ribs and sternum, vigorous activities such as running and biking are challenging or impossible due to impaired cardiac or respiratory function. These and other chest wall and spinal deformities are surprisingly common. An estimated 1 in 400 children are born with a pectus excavatum—a deformity that produces the appearance of a hollowed chest. This chest wall abnormality can also be seen in children with scoliosis and kyphosis. These irregularities can produce shortness of breath and contribute to difficulty participating in strenuous exercise or activities. Despite the frequent occurrence of these irregularities, the degree to which the deformities impact heart, lung and related functions is not well-understood.
Leading the charge
Enter Daniel Saltzman, associate professor of surgery and pediatrics, and chief of the Division of Pediatric Surgery in the Medical School; and Fotis Sotiropoulos, professor of civil engineering and director of the St. Anthony Falls Laboratory. This unlikely duo, along with an interdisciplinary team of researchers including surgeons, computational scientists, pulmonologists, cardiologists and radiologists, is leading the charge toward a better understanding of the effects of chest wall and spinal deformities on cardiac blood flow and pulmonary function.
Pilot study
With seed funding from the University’s Institute for Engineering in Medicine, a joint interdisciplinary research unit of the College of Science and Engineering and the Medical School, the team launched a pilot study with the goal to understand how cardiac function is affected in patients with these deformities and begin to quantify the impacts of surgical correction using cutting-edge computational modeling.
Two key hypotheses driving this research are: 1) that chest deformities impair the ability of the heart to pump blood efficiently; and 2) that the extent of the deformity is correlated with cardiac energy losses. To test these hypotheses and determine deformity thresholds requiring surgical intervention, it is critical to understand blood flow patterns and systematically quantify cardiac efficiency in the hearts of a variety of patients.
To address these challenges, the research team is advancing an approach based on patient-specific computational modeling of cardiac blood flow. Imaging techniques such as 4-D MRI and/or Computed Tomography (CT) are used to image the heart of patients with chest deformities and reconstruct three-dimensional computer models of both the heart wall shape and wall motion patterns. These virtual beating hearts are then used as input to the advanced computational fluid dynamics software developed by SAFL researchers—the University of Minnesota Computational Cardio-Fluid Dynamics (C2FD-UMN) code—to simulate blood flow patterns.
The computed flowfields can then be used to quantify the cardiac function of these patients relative to healthy hearts and correlate cardiac efficiency with the extent of chest deformities.
This study is an important first step toward improving patient-specific medical care by allowing physicians to monitor a patient’s heart function, refine the most effective surgical intervention to correct the deformity, conduct more comprehensive pre-operative planning, to better understand the cardiac energetics and how they correlate with the patient’s symptoms and predict surgical outcomes. Thus, SAFL’s innovative computational models have the potential to significantly enhance medical intervention across a broad spectrum of chest wall and spinal deformity conditions by optimizing monitoring and care of patients at the individual level.
Next steps
Saltzman and Sotiropoulos are initially focusing their efforts on a small test group to produce patient-specific computational models of deformities by compiling all available data both prior to and following surgical procedures. This pilot study will provide baseline data to allow the team to compete for National Institutes of Health funding for a large-scale clinical trial study to produce guidelines for deformity correction based on this multidisciplinary approach.