On many occasions, it is desirable to image lungs in vivo to perform a pulmonary physiology study. Since the lungs are moving, gating with respect to the ventilatory phase has to be performed in order to minimize motion artifacts. Gating can be done in real time, similar to cardiac imaging in clinical applications, however, there are technical problems that have lead us to investigate different approaches. The problems include breath-to-breath inconsistencies in tidal volume, which makes the precise detection of ventilatory phase difficult, and the relatively high ventilation rates seen in small animals (rats and mice have ventilation rates in the range of a hundred cycles per minute), which challenges the capture rate of many imaging systems (this is particularly true of our system which utilizes cone-beam geometry and a 2 dimensional detector). Instead of pre-capture ventilation gating we implemented a method of post-acquisition gating. We acquire a sequence of projections images at 30 frames per second for each of 360 viewing angles. During each capture sequence the rat undergoes multiple ventilation cycles. Using the sequence of projection images, an automated region of interest algorithm, based on integrated grayscale intensity, tracts the ventilatory phase of the lungs. In the processing of an image sequence, multiple projection images are identified at a particular phase and averaged to improve the signal-to-ratio. The resulting averaged projection images are input to a Feldkamp cone-beam algorithm reconstruction algorithm in order to obtain isotropic image volumes. Minimal motion artifact data sets improve qualitative and quantitative analysis techniques useful in physiologic studies of pulmonary structure and function
