Using MRI to Observe Lung Changes in Infants With CF Compared to Infants Without CF

Cystic fibrosis (CF) is a well characterized multi-organ disease producing mucus obstruction, chronic lung infection, inflammation, and oxidant stress. These processes result in airway damage, chronic pulmonary symptoms, and ultimately death in young adulthood. These processes are largely silent in the infant and toddler CF population, and ultimately result in lung damage and symptoms of CF. Detection and monitoring of lung disease in infants and toddlers with CF is currently limited, and is a major barrier to advancements in care and research for this population.

This study will be performed in CF and non-CF controls age 6 months - 4.5 years, with repeated measures in CF patients over this window. We intend to examine new techniques to evaluate the lung of CF infants based on magnetic resonance imaging (MRI) that incorporates measurements of lung structure and blood flow. In the CF group, we will augment MRI images with CT images to determine structural relationships between MR and CT (a gold standard to assess lung structure in CF). We will correlate imaging data with core peripheral biomarkers of CF using an unbiased, metabolomic and proteomic-based approach. It is hoped that the results of this study will provide support for the use of MRI to monitor lung structure and blood flow in early CF lung disease, potentially providing a modality to monitor disease status independent of radiation exposure.

We hypothesize that MRI of the lung and pulmonary circulation has the potential to serve as a sensitive and portable tool to monitor early CF lung disease. We will examine three functional aspects of pulmonary blood flow (total and regional pulmonary perfusion, vascular resistance, and aortopulmonary collateral blood flow) compared with structural assessment of the lung by MRI and CT.

This proposal couples advancements in magnetic resonance imaging (MRI) techniques with the emerging technologies of metabolomics and proteomics, linking new MR imaging to candidate and novel pathway analysis. We will use the new technologies (metabolomics and proteomics - performed on peripheral blood samples) to determine if altered signaling pathways detected in the blood are related to changes in the lung. We hypothesize that changes in pulmonary perfusion and/or structure can be correlated with peripheral biomarkers identified by metabolomics and proteomic methodology.

Candidate metabolomic pathways that have been shown to segregate CF from non-CF conditions (including oxidative status, purinergic signaling, and glucose metabolism) will be the focus of initial biomarker analysis, with advanced bioinformatic techniques applied to define novel relationships between the metabolome and imaging. Proteomics will serve a validating function, helping to assign enzyme pathways to metabolomics alterations.

The study design includes 30 CF subjects divided into 2 age groups (6 to 12 month old and 24 to 36 month old) who will receive chest CT and High Resolution CT (HRCT) at baseline and 12 months later. They will be compared to 30 age matched non-CF subjects who will have one visit of MRI with contrast. The non-CF group only includes subjects scheduled for MRI for clinical reasons and will have an additional chest imaging at the end of their scheduled MRI. Both groups will have blood drawn to measure metabolomic and proteomic markers.

Inclusion criteria

CF

• Age at enrollment 6 to 12 months or 24 to 52 months.
• Diagnosed with two CF-causing mutations ('severe' mutations, classes 1, 2, or 3).

Non-CF

• Age at enrollment 6 months to 52 months
• Clinically scheduled for MRI neuroimaging
• Negative history of renal abnormalities

Exclusion criteria

CF

• Pulmonary exacerbation
• Any known intracardiac defects
• Serum creatinine > 1.5 times the upper limit of normal for age
• Cystatin C > 0.53 (cutoff for normal range)

Non-CF

• Active lung disease as determined by assessment of anesthesiologist
• Any known intracardiac defects
• Results of the most recent serum creatinine within past 12 months above normal range for age