Early Changes of T2* Measures in Lung Tissues using deltaTE-UTE MRI on healthy and COPD Patients

Chronic Obstructive Pulmonary Disease (COPD) is a respiratory condition that poses significant global health challenges. It is often caused by long-term exposure to irritants that damage the lungs and airways, such as air pollution, cigarette smoke, occupational dust, exposure to chemicals, and frequent lower respiratory infections during childhood. The pathology of COPD involves changes in the structure of the lung parenchyma, including the destruction of the alveolar walls (emphysema) and inflammation and thickening of the airway walls (chronic bronchitis). These changes lead to reduced elastic recoil of the lungs, airflow obstruction, and difficulty in breathing. As the disease progresses, patients may experience chronic cough, sputum production, and frequent respiratory infections, eventually leading to a decline in lung function and quality of life. Diagnostically, COPD has traditionally been assessed using spirometry, which measures the volume and flow of air as the patient inhales and exhales. A spirometry test can detect COPD even before symptoms are noticeable and is essential for proper diagnosis and staging of the disease. Imaging studies, such as chest X- rays and computed tomography (CT) scans, are frequently used to detect emphysema. However, these methods expose patients to ionizing radiation and may not capture the early microstructural changes in the lung tissue. With COPD affecting millions and projections indicating a substantial increase in cases in the upcoming years even in the developed countries, there is a pressing need for advanced imaging techniques that can offer precise lung assessments without the risks associated with ionizing radiation. In response to this need we propose a novel Ultrashort Echo-Time (UTE) Magnetic Resonance Imaging (MRI) technique 𝛿TE-UTE. This method is designed to accurately map T2* values in lung parenchyma, overcoming current hardware limitations by acquiring images with closely spaced echo-time intervals within a single scan. Acquiring multiple echoes below 2 milliseconds is essential for precise T2* mapping of lung parenchyma and may potentially allow for the early detection of structural changes in lung. To shorten the scan time, we propose integration of a Deep Learning-Variational Network (DL-VN) for reconstructing under-sampled data, aiming to preserve image quality and precision of T2* mapping while reducing scan times. In addition to technical developments, we will investigate the application of 𝛿TE-UTE technique to both healthy individuals and COPD patients, with the results being compared to those obtained from a standard multi- echo UTE. This comparison aims to validate the effectiveness and accuracy of 𝛿TE-UTE in capturing detailed lung structures and any pathological changes. Additionally, the findings will be correlated with pulmonary function tests to establish a relationship between the imaging results and the patients' respiratory capabilities, offering a comprehensive understanding of how 𝛿TE-UTE can contribute to the diagnosis and monitoring of COPD. Project Number: 1K99HL177415-01 | Fiscal Year: 2025 | NIH Institute/Center: National Heart Lung and Blood Institute (NHLBI) | Principal Investigator: Vadim Malis | Institution: UNIVERSITY OF CALIFORNIA, SAN DIEGO, LA JOLLA, CA | Award Amount: $108,003 | Activity Code: K99 | Study Section: Special Emphasis Panel[ZHL1 CSR-Z (O2)] View on NIH RePORTER: https://reporter.nih.gov/project-details/1K99HL17741501