Keywords: Vascular/Vessel Wall, Lung, Pulmonary Vasculature, Proton MRI, Pulmonary Hypertension, COPD, 2D-U-Net Segmentation
Motivation: Chronic lung diseases like chronic obstructive pulmonary disease and pulmonary hypertension remodel the pulmonary vasculature, affecting lung function and right heart performance.
Goal(s): This study aimed to analyze the central pulmonary vasculature using automated 2D-U-Net segmentation in free-breathing lung MRI, assessing reproducibility and disease-related differences.
Approach: Data from healthy participants, COPD-, and PH-patients were used to calculate dynamic vessel parameters, including vessel voxel counts, expansion between systole and diastole and phase shifts using 2D U-Net segmentation.
Results: Significant differences were observed in vessel size variability and phase shift between groups, highlighting potential non-invasive markers for distinguishing lung diseases.
Impact: This study demonstrates the potential of automated MRI-based vessel analysis to identify distinct hemodynamic changes in chronic lung diseases like COPD and PH. It could offer a non-invasive method to differentiate disease subtypes and monitor treatment responses in clinical practice.
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