Chronic lung diseases, such as cystic fibrosis (CF), emphysema, asthma, and idiopathic pulmonary fibrosis (IPF), place a significant burden on the U.S. health care system (~$150 billion overall). Despite a variety of etiologies, a common feature of many pulmonary diseases is repeated pulmonary infections or insults leading to declining respiratory function, and ultimately, death. Unfortunately, currently available clinical assessments of lung diseases are either invasive (bronchoalveolar lavage [BAL]), expose patients to significant repeated doses of ionizing radiation (X-ray and/or Computed Tomography [CT]), or offer limited sensitivity to detect regional lung disease (BAL, spirometry). Therefore, the development of sensitive, noninvasive, and radiation- free measures of acute lung infections, as well as physiologic remodeling associated with chronic lung disease, especially at early stages, offers the promise of improved health care for patients. Magnetic Resonance Imaging (MRI) is a safe, non-invasive technique capable of providing quantitative assessments of CF lung disease without the ionizing radiation of Xray/CT. For example, multiple imaging studies have also shown that reduced pulmonary perfusion / vascularization is associated with chronic lung disease and declining pulmonary function. Unfortunately, these conventional MRI techniques typically require multiple signal averages to obtain reliable quantitative assessments and are therefore susceptible to respiratory motion artifacts. There are still no established, widely available lung MRI techniques that: 1) can specifically detect the progression/resolution of acute lung infections; and 2) are resistant to respiratory motion artifacts. The MRI research group at CWRU has pioneered a transformative MRI technology called Magnetic Resonance Fingerprinting (MRF).22 In the initial clinical study (Nature 2013), MRF was shown to generate dynamic tissue-specific signal evolution profiles resulting in simultaneous generation of T1, T2 relaxation time maps in ~10 seconds. We have recently implemented this multi-parametric MRF methodology on preclinical MRI scanners and have demonstrated that MRF may be resistant to respiratory motion artifacts.23 The overall objective of this project is to develop and validate Ultrashort Echo Time (UTE)-MRF assessments of acute lung infection (Aim 1) and pulmonary perfusion (Aim 2) in mouse models of lung disease. We will also evaluate the sensitivity of these techniques to longitudinally monitor acute and chronic lung disease progression in a genetic mouse model of cystic fibrosis. These quantitative multi-parametric MRF measurements will provide the basis for future mechanistic/therapeutic studies in mouse models as well as eventual translation to studies in patients with lung disease.

Public Health Relevance

Chronic lung diseases, such as asthma, and cystic fibrosis (CF) affect millions of children and adults in the U.S, and share common features such as repeated acute lung infections leading to tissue damage and ultimately lung dysfunction. Unfortunately, currently available techniques for longitudinal assessment of lung disease provide limited sensitivity to regional lung disease, expose patients to significant does of radiation, or are invasive. The overall objective of this project is to develop and validate novel Magnetic Resonance Fingerprinting (MRF) techniques to safely and sensitively detect and monitor acute lung infections as well as pulmonary perfusion in mouse models of lung disease, with eventual translation to patients.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21HL130839-02
Application #
9329475
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Sheridan, John T
Project Start
2016-08-08
Project End
2019-04-30
Budget Start
2017-05-01
Budget End
2019-04-30
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Case Western Reserve University
Department
Type
Schools of Nursing
DUNS #
077758407
City
Cleveland
State
OH
Country
United States
Zip Code
44106
Anderson, Christian E; Wang, Charlie Y; Gu, Yuning et al. (2018) Regularly incremented phase encoding - MR fingerprinting (RIPE-MRF) for enhanced motion artifact suppression in preclinical cartesian MR fingerprinting. Magn Reson Med 79:2176-2182
Darrah, R; Bonfield, T; LiPuma, J J et al. (2017) Cystic Fibrosis Mice Develop Spontaneous Chronic Bordetella Airway Infections. J Infect Pulm Dis 3: