Keywords: Quantitative Imaging, Hyperpolarized MR (Gas), Dynamic ventilation imaging
Motivation: High spatiotemporal resolution dynamic ventilation imaging with hyperpolarized 129Xe MRI can well-depict the airflow process in the lung during the respiratory. However, there is a lack of quantitative assessment methods that correlate dynamic ventilation images with pulmonary physiology.
Goal(s): We aimed to translate the dynamic ventilation images into quantitative parameters that could assess the ventilation function.
Approach: The signal-time curve was used to explain the airflow rate and optical flow method was utilized to generate airflow field for each frame to depict the orientation and magnitude.
Results: Gas distribution and airflow process could be quantified through dynamic ventilation images.
Impact: Regional dynamic ventilation function was quantified using signal-time curves and optical flow methods in vivo, and these preliminary results might be helpful for assessing the lung pathological changes that related to airflow restriction, obstruction, or air trapping.
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