There is growing evidence that the fluctuations in a system may convey critical information about the health of the system. Developments in nonlinear science have provided new insights on the dynamics of many different systems, such as ecological systems and climate. Nonlinear systems have the potential for a much wider range of dynamic behavior than simple linear systems, including multiple states and dramatic transitions between them in response to exogenous forces. We propose to test whether the mathematical analysis tools focused on characterization of underlying nonlinear behavior can provide new metrics for evaluating the human pulmonary circulation. If successful, this may provide biomarkers for the early detection and classification of disease, and a framework for developing new methods of evaluation. This proposal brings together 1) our novel noninvasive magnetic resonance imaging technique using arterial spin labeling that allows measurement of fluctuations in the spatial distribution of pulmonary blood flow and 2) mathematical tools for assessing underlying nonlinear mechanisms in time series data based on nonlinear forecasting developed by our collaborator Dr. Sugihara. Dr. Sugihara has previously shown that nonlinear control of heart rate of pre-term infants increased with maturation, and was lost in brain death suggesting that nonlinear control is a critical feature of a healthy human cardiovascular system. Nonlinear forecasting yields a set of metrics that provide information on the type of nonlinear interactions, the number of interacting factors involved, and even the strength of interactions between factors. We propose to test the feasibility of this new approach for evaluating the pulmonary circulation in healthy human subjects and those with a known abnormality of the pulmonary circulation-previous sufferers of high altitude pulmonary edema (HAPE). In HAPE a previously healthy individual, develops a florid pulmonary edema at altitude. HAPE may be fatal, but HAPE patients rapidly regain normal function with decent and treatment. We will lay a foundation for future clinical applications, answering three basic questions: Are the new metrics reproducible? What are the effects of noise and artifact. Do they change in specific ways in response to physiological stressors? Do they distinguish healthy subjects from those susceptible to HAPE? We will test the hypothesis that the healthy human pulmonary circulation exhibits patterns of behavior consistent with nonlinear control mechanisms and that this behavior is altered in a reproducible way by physiological challenges and in HAPE susceptible subjects. Our team is composed of experts from MR imaging, Nonlinear Forecasting, Pulmonary Vascular Disease, and Physiology who will collaborate on this proposal. Relevance: Successful completion of this project will provide a high reward: a foundation for an entirely new means of evaluating pulmonary vascular disease. Since pulmonary vascular disease is largely silent until it is advanced, ultimately this work may lead to a new screening tool for high-risk patient populations, or a new way of identifying populations for targeted therapies.

Public Health Relevance

This proposal uses novel magnetic resonance imaging of fluctuations in pulmonary blood flow combined with mathematical analysis (nonlinear forecasting), to provide new metrics for evaluating the pulmonary circulation, evaluating reproducibility, changes with physiological stimuli and in an example of disease.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21HL118539-01A1
Application #
8582165
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Lin, Sara
Project Start
2013-08-15
Project End
2015-05-31
Budget Start
2013-08-15
Budget End
2014-05-31
Support Year
1
Fiscal Year
2013
Total Cost
$221,340
Indirect Cost
$78,540
Name
University of California San Diego
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Miller, G Wilson; Mugler 3rd, John P; Sá, Rui C et al. (2014) Advances in functional and structural imaging of the human lung using proton MRI. NMR Biomed 27:1542-56