A new mathematical approach, validated through experimental animal studies, offers a speedy, dependable, and minimally invasive method to manage critical blood pressure fluctuations during surgical procedures or intensive care.
When patients in intensive care or those undergoing major surgeries experience dangerously high or low blood pressure, they risk serious organ damage. Simply identifying that blood pressure is off is insufficient; healthcare providers need to understand the reasons behind these changes to select the appropriate treatment. A recent study from MIT introduces a mathematical framework that enables accurate and real-time insights into these vital changes.
This mathematical technique, outlined in a recent article in IEEE Transactions on Biomedical Engineering, yields proportional assessments of two essential factors affecting blood pressure: the heart’s blood output (cardiac output) and the resistance of the arterial system to that blood flow (systemic vascular resistance). By applying this innovative method to pre-existing data from animal models, the researchers demonstrated that their estimations, which derive from minimally invasive measurements of peripheral arterial blood pressure, corresponded accurately with readings obtained from a more invasive aortic flow probe. Additionally, these estimates effectively mirrored the physiological changes in animals caused by various medications typically used to normalize blood pressure.
“The resistance and cardiac output estimates generated by our method offer actionable insights for real-time hemodynamic management,” the authors of the study noted.
The researchers believe that, following further testing and regulatory approval, this technique could be applied in various medical scenarios, including cardiac surgeries, liver transplants, intensive care unit treatments, and numerous other procedures impacting cardiovascular health or blood volume.
“Any patient undergoing cardiac surgery could potentially benefit from this,” said senior author Emery N. Brown, who holds the Edward Hood Taplin Professorship in Medical Engineering and Computational Neuroscience at MIT’s Picower Institute for Learning and Memory. Brown is also an anesthesiologist at Massachusetts General Hospital and a professor of anesthesiology at Harvard Medical School. “Patients undergoing standard surgeries may also require it, especially if they have existing cardiovascular conditions like ischemic heart disease. Consistent blood pressure is crucial.”
The lead author of the study 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 Innovation
The concept that cardiac output and systemic resistance are fundamental to blood pressure regulation is based on the two-element Windkessel model. While previous studies have utilized this model to estimate these parameters from blood pressure data, they faced a conflict between the speed of updates and the accuracy of those estimates; typically, methods either provided quick but imprecise estimates or slower yet more reliable ones. Under Baum’s leadership, the MIT team resolved this conflict through advanced statistical and signal processing methodologies like “state-space” modeling.
“Our estimates, updated with each heartbeat, integrate both current data and historical information,” stated Baum. “It’s this blend of past context and real-time data that enhances the reliability of the estimates, while still maintaining a rapid beat-by-beat update frequency.”
Importantly, the derived estimates of cardiac output and systemic resistance are “proportional,” meaning they are interlinked mathematically with another co-factor, rather than being estimated independently. Testing the new method on data from a prior study involving six animals showed that estimates derived from minimally invasive catheter readings matched well with those obtained from more invasive central catheter placements.
A significant finding was that the proportional estimates based on arterial blood pressure measurements from catheters placed in remote sites (for instance, the legs or arms) aligned closely with readings from central aortic catheters. This suggests that a system employing the new estimation method could potentially operate using less invasive catheter placements, thus minimizing the risks associated with traditional methods that involve inserting catheters into central arteries or directly into the heart, which are considered standard practice in assessing cardiovascular health.
Another notable outcome was that when animals were administered each of the five drugs typically used to modify systemic vascular resistance or cardiac output, the proportional estimates accurately reflected the consequent physiological alterations. This indicates that these estimates reliably represent physiological changes.
Clinical Application
Encouraged by these results, Baum and Brown expressed that the current methodology could be effectively implemented in clinical environments to enhance the understanding of critical blood pressure variations for perioperative care teams. They are actively working towards obtaining regulatory approval for clinical devices that utilize this method.
Furthermore, the researchers are conducting additional animal studies to validate this advanced approach for blood pressure management.
They have created a closed-loop system guided by this estimation framework to precisely regulate blood pressure in an animal model. Following the completion of these animal trials, they plan to seek regulatory clearance to test the system in human subjects.
In addition to Baum, Dahleh, and Brown, the author list includes Elie Adam, Christian Guay, Gabriel Schamberg, Mohammadreza Kazemi, and Thomas Heldt.
The study received support from the National Science Foundation, the National Institutes of Health, a Mathworks Fellowship, The Picower Institute for Learning and Memory, and The JPB Foundation.
