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Computational Models of the Cardiovascular System and its Response to Microgravity and Disease

Principal Investigator:
Roger G. Mark, M.D., Ph.D.

Massachusetts Institute of Technology
Harvard-MIT Division of Health Sciences and Technology

Many astronauts cannot stand up after landing due to orthostatic intolerance, the inability to maintain adequate blood pressure. Dr. Roger G. Mark is designing and evaluating a computational model of the cardiovascular system that accounts for this behavior in response to sudden orthostatic stress such as standing up. The model will be used to evaluate the physiological hypotheses for orthostatic intolerance, to integrate the multiple effects of space flight and to predict countermeasure effectiveness.

NASA Taskbook Entry

Technical Summary

Experimental studies of the cardiovascular system in humans, and even in laboratory animals, are necessarily limited in scope because of restrictions on the types of measurements that can be made. Often, the true parameter of interest cannot be measured directly so it must be inferred from other measures. Even when appropriate measurements can be made, the cause of a particular observation may not be evident because of the complexity of the interactions between the numerous components of the system. These and other issues can often be addressed more effectively with the aid of a computational model that simulates the critical components and behaviors of the cardiovascular system. Models depend upon experiments for refinement and specification of their parameters, but also illuminate and enhance the interpretation of experimental results. We view the experiments and computational models as highly synergistic in that the value of one is greatly enhanced by the existence of the other. It could be argued that these are not merely advantages, but essential aspects of a study of orthostatic intolerance.

The primary objectives of this project are to develop a general, modular model of cardiovascular function that contains the essential features associated with the effects of gravity, and to use this model to examine the short term effects of changes in posture before and after exposure to the microgravity environment. The objective of the currently funded project was to extend a previously developed computational model of the cardiovascular system and to use this model to investigate the short-term (0--5 mins) beat-to-beat hemodynamic response of the cardiovascular system to abrupt orthostatic stress --- such as head-up tilt (HUT) or lower body negative pressure (LBNP). The project aimed at facilitating the understanding of the physiology and treatment (prevention) of orthostatic intolerance in post-flight astronauts.

We proposed to:

  • Enhance the current version of the cardiovascular simulation to better represent the short-term effects of abrupt orthostatic stress;
  • Verify the model and use it to investigate and evaluate various hypotheses of orthostatic intolerance, and predict the effects of countermeasures, requiring extensive collection and archiving of experimental data from collaborators;
  • Complete, document, and disseminate to other investigators a form of the model implemented in JAVA, and;
  • Apply the cardiovascular model to the clinical problem of intelligent patient monitoring with particular emphasis on establishing an enhanced research database of multiparameter hemodynamic data from intensive care patients.

Earth Applications

While the primary purpose of the proposed modeling effort is to provide a tool for use in studies of orthostatic hypotension and countermeasures, the resulting models will have value in other settings as well. As a clinical tool, models enhance the quality of measurement, both in the context of remote clinical monitoring in the space environment and in the ground-based clinical setting. Continuous hemodynamic monitoring in the ICU could be augmented by the use of models capable of tracking a particular patient's status. The challenge of rapidly assessing the pathophysiologic state of an unstable patient is made more difficult as a result of the density of the available data, and its frequent lack of logical and coherent organization. Quantitative hemodynamic models of the type developed here can provide a rational structure around which to present the data to clinicians, providing the basis for more sophisticated and sensitive alarms, and playing a pivotal role in developing decision support paradigms to guide therapy. Computational models of cardiovascular function are also valuable educational tools for students in high school, college, university, and medical school.

This project's funding ended in 2004