If patients receiving intensive care or undergoing major surgery develop excessively high or low blood pressure, they could suffer serious organ dysfunction. It’s not enough for the medical team to know that the pressure is abnormal. To choose the right drug to treat the problem, doctors need to know why the blood pressure has changed. A new study from MIT presents the mathematical framework needed to obtain that crucial information accurately and in real time.
The mathematical approach, described in a recent study in IEEE Transactions on Biomedical Engineeringproduces proportional estimates of the two critical factors underlying blood pressure changes: the heart rate of blood output (cardiac output) and the arterial system’s resistance to that blood flow (systemic vascular resistance). By applying the new method to data previously collected from animal models, the researchers show that their estimates, derived from minimally invasive measurements of peripheral blood pressure, accurately matched estimates made using additional information from an invasive flow probe placed in the aorta. Moreover, the estimates accurately tracked changes induced in the animals by the various medications that doctors use to correct aberrant blood pressure.
“The estimates of resistance and cardiac output obtained from our method provide information that can be readily used to guide hemodynamic management decisions in real time,” the study authors wrote.
The authors said that with further testing leading to regulatory approval, the method would be applicable during cardiac surgeries, liver transplants, intensive care unit treatments and many other procedures that affect cardiovascular function or blood volume.
“Any patient undergoing cardiac surgery could use this,” said senior study author Emery N. Brown, the Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience at MIT’s Picower Institute for Learning and Memory, Institute for Medical Engineering and Science, and Department of Brain and Cognitive Sciences. Brown is also an anesthesiologist at Massachusetts General Hospital and a professor of anesthesiology at Harvard Medical School. “The same could be true for any patient undergoing more normal surgery who may have a compromised cardiovascular system, such as ischemic heart disease. You can’t have wildly variable blood pressure.”
The study’s lead author is Taylor Baum, a graduate student in electrical engineering and computer science (EECS), who is co-supervised by Brown and Munther Dahleh, the William A. Coolidge Professor in EECS.
Algorithmic breakthrough
The idea that cardiac output and systemic resistance are the two key components of blood pressure comes from the Windkessel two-element model. The new study is not the first to use the model to estimate these components from blood pressure measurements, but previous attempts faced a dilemma between rapid updates to estimates and accuracy of estimates; the methods would either provide more erroneous estimates at each heartbeat or more reliable estimates that are updated on time scales of minutes. Led by Baum, the MIT team overcame the dilemma with a new approach of applying statistical and signal processing techniques such as “state space” modeling.
“Our estimates, updated every beat, are not just based on the current beat, but also incorporate how things were in previous beats,” Baum said. “It’s that combination of past history and current observations that produces a more reliable estimate, even though it maintains a beat-to-beat time scale.”
It is noteworthy that the resulting estimates of cardiac output and systemic resistance are “proportional,” meaning that each is inextricably linked in the calculation with another cofactor, rather than calculated on its own. But application of the new method to data collected in an earlier study of six animals showed that proportional estimates from recordings made with minimally invasive catheters provide comparable information for management of the cardiovascular system.
A key finding was that proportional estimates made based on blood pressure readings from catheters inserted at various sites remote from the heart (e.g., the leg or arm) mirrored estimates derived from more invasive catheters placed within the aorta. The significance of this finding is that a system using the new estimation method could, in some cases, rely on a minimally invasive catheter in multiple peripheral arteries, thereby avoiding the need for riskier placement of a central artery catheter or a pulmonary artery catheter directly into the heart—the clinical gold standard for estimating cardiovascular status.
Another key finding was that when animals were given each of the five drugs that doctors use to regulate systemic vascular resistance or cardiac output, the proportional estimates adequately tracked the resulting changes. The finding therefore suggests that the proportional estimates of each factor accurately reflect their physiological changes.
Towards the clinic
With these encouraging results, Baum and Brown said, the current method can be easily implemented in clinical settings to inform perioperative care teams about the underlying causes of critical changes in blood pressure. They are actively seeking regulatory approval for use of this method in a clinical device.
In addition, researchers are conducting further animal studies to validate an advanced blood pressure management approach using this method.
They have developed a closed-loop system, based on this estimation framework, to precisely regulate blood pressure in an animal model. Once the animal studies are complete, they will apply for regulatory approval to test the system in humans.
In addition to Baum, Dahleh and Brown, the other authors of the paper are Elie Adam, Christian Guay, Gabriel Schamberg, Mohammadreza Kazemi and Thomas Heldt.
The National Science Foundation, the National Institutes of Health, a Mathworks grant, the Picower Institute for Learning and Memory, and the JPB Foundation supported the study.