Integrated Radiographic and Metabolomics Risk Assessment in Patients With Interstitial Lung Diseases

Interstitial lung diseases (ILD) are a group of chronic, progressive lung disorders. The most common ILD is idiopathic pulmonary fibrosis (IPF) with an average survival ranging between 2.5-5 years after diagnosis. The term pulmonary fibrosis means scarring of the lung tissue and is the cause of worsening shortness of breath. IPF can frequently affect the tissue between the air sacs in the lung called the interstitium and many other areas in lung (blood vessels and air passage ways). Earlier diagnosis of ILD is a prerequisite for better long-term outcomes. However, disease detection and assessment of progression are reliant on many varying host and environmental influences. As a result, patients with ILD are often misdiagnosed early in the disease process. Moreover, patients diagnosed with ILD have different disease courses and predicting which patient is at risk of progression is a challenging problem. Many personalized medicine approaches are being developed but there is a lack of available biomarkers in clinical practice. Biomarkers comes from a new experimental technique called metabolomics which is becoming widely used in medicine and biology for studying living organisms. The method measures the levels of large numbers of naturally occurring small molecules (called metabolites) that are present in the blood, saliva, breath and tissues. The pattern, or fingerprint, of metabolites in human samples can be used to learn about the health of an organism and perhaps allow physicians to diagnose, treat, and follow the progress of specific diseases. Clinical and functional models lack predictive ability to detect patients at risk of disease progression. Thus, there is an urgent need to develop accurate prediction models for disease diagnosis and assess treatment effects.

CT-derived ventilation (CT-V) imaging includes quantitative lung function imaging and lung compliance imaging. CT-V is a newer image processing based technique that uses mathematical modeling and scientific computing to gather changes in lung tissue volumes during the breathing cycle. Beaumont is currently using CT-V for radiotherapy planning. CT-V produces a full 3D map of ventilation/breathing, has better image resolution, provides pertinent measurable imaging information, and does not require a contrast agent. Thus, high-resolution anatomical and functional information can be derived using CT-V.

To better understand the functional and radiographic changes seen in patients with ILD, there is a need to further examine the downstream changes occurring at the level of proteins and metabolites. Metabolomics provides a "snapshot" in time of all metabolites present in a biological sample. Proteins alone or integrated with other systems, is a particularly informative tool for understanding disease biology in ILD patients.Using an untargeted metabolomics platform and profiling serum and breathe from the patients will determine if additional or more robust biomarkers of disease can be identified and, in conjunction with the assessment of regional ventilation differences through CT-V, will provide a better insight into disease process and further help with accurate prognostication.

Participants who have consented for the study and have meet all the inclusion criteria and none of the exclusion criteria will have one full inspiration and expiration CT, and two 4D-CT scans under two different pressures (5 and 10 cm water), except for healthy volunteers. They will have their breath profiled using Owlstone platform and serum collected for metabolomics testing within one week period. Participants will be asked to refrain from smoking one day prior to the study date. All study related sampling will be done in a single visit if possible and if not possible all study procedures and samples will be collected within a one week period.

Disease progression will be assessed using chart review over the next 24 months to assess standard of care pulmonary function evaluation and corresponding CT features respiratory hospitalizations and mortality.