TH-C-18A-03: Novel Technique for Dynamic Lung Ventilation Imaging Based On Wide Coverage 4D CT




An emerging lung ventilation imaging method based on conventional 4D CT has a high translational potential and advantages over other competing modalities, however suffers from binning artifacts and irregular breathing during a scan. We propose a novel technique to compute dynamic ventilation based upon wide coverage 320-slice 4D CT, which provides high spatial and temporal resolution and binning artifact-free images.


Wide coverage 4D CT images were acquired using a commercial 320-slice CT scanner, with 160 mm craniocaudal coverage and 0.35 s rotation time, during tidal breathing for five patients with thoracic cancer. The image at each of 51 time points was deformably registered to a peak-exhalation phase image using B-spline deformable image registration (DIR). For each time-point, the Jacobian determinant of deformation acted as a surrogate for regional ventilation. Dynamic ventilation was then computed by comparing time-resolved ventilation images. The accuracy of DIR was quantified by calculating target registration errors (TREs) of 100 anatomic landmarks per patient.


The proposed technique provided regional ventilation information of high spatial and temporal resolution. The average TRE of five patients was 1.4±1.3 mm. Dynamic properties of regional ventilation were found to be spatially heterogeneous. For example, ventilation increased during inhalation and decreased during exhalation in well-ventilated normal lung regions. However, in poorly-ventilated emphysematous regions, ventilation showed relatively minor changes with time around zero. Furthermore, ventilation resolved at this timescale demonstrated a signal that appeared to come from the heartbeat, especially in proximity to the heart.


320-slice 4D CT-based ventilation imaging provides regional ventilation information of high spatial and temporal resolution. Dynamic ventilation information obtained by this technique may be useful in creating a model of dynamic ventilation that could be used to compensate for errors in conventional 4D CT-based ventilation imaging, and may also provide new insights into respiratory physiology.

Supported in part by Free to Breathe Young Investigator Research Grant.