Noninvasive assessment of regional lung ventilation is of critical importance in quantifying the severity of disease and evaluating response to therapy in many pulmonary diseases. This work presents for the first time the implementation of a hyperpolarized (HP) gas MRI technique for measuring whole-lung regional fractional ventilation (r) in Yorkshire pigs (n = 5) through the use of a gas mixing and delivery device in supine position. The proposed technique utilizes a series of back-to-back HP gas breaths with images acquired during short end-inspiratory breath-holds. In order to decouple the RF pulse decay effect from ventilatory signal build-up in the airways, regional distribution of flip angle (α) was estimated in the imaged slices by acquiring a series of back-to-back images with no inter-scan time delay during a breath-hold at the tail-end of the ventilation sequence. Analysis was performed to assess the multi-slice ventilation model sensitivity to noise, oxygen and number of flip angle images. The optimal α value was determined based on minimizing the error in r estimation; αopt = 5–6° for the set of acquisition parameters in pigs. The mean r values for the group of pigs were 0.27±0.09, 0.35±0.06, 0.40±0.04 for ventral, middle and dorsal slices, respectively, (excluding conductive airways r > 0.9). A positive gravitational (ventral-dorsal) ventilation gradient effect was present in all animals. The trachea and major conductive airways showed a uniform near-unity r value, with progressively smaller values corresponding to smaller diameter airways, and ultimately leading to lung parenchyma. Results demonstrate the feasibility of measurements of fractional ventilation in large species, and provides a platform to address technical challenges associated with long breathing time scales through the optimization of acquisition parameters in species with a pulmonary physiology very similar to that of human beings.
Keywords: Pulmonary ventilation, Quantitative lung imaging, Fractional ventilation, Hyperpolarized gas MRI, Mechanical ventilation