Purpose: To develop robust, novel segmentation and co-registration software to analyze
temporally overlapping CT angiography datasets, with an aim to permit automated measurement
of regional aortic pulsatility in patients with abdominal aortic aneurysms.
Methods: We perform retrospective gated CT angiography in patients with abdominal aortic
aneurysms. Multiple, temporally overlapping, time-resolved CT angiography datasets are
reconstructed over the cardiac cycle, with aortic segmentation performed using a priori anatomic
assumptions for the aorta and heart. Visual quality assessment is performed following automatic
segmentation with manual editing. Following subsequent centerline generation, centerlines are
cross-registered across phases, with internal validation of co-registration performed by
examining registration at the regions of greatest diameter change (i.e. when the second derivative
Results: We have performed gated CT angiography in 60 patients. Automatic seed placement is
successful in 79% of datasets, requiring either no editing (70%) or minimal editing (less than 1
minute; 12%). Causes of error include segmentation into adjacent, high-attenuating, nonvascular
tissues; small segmentation errors associated with calcified plaque; and segmentation of
non-renal, small paralumbar arteries. Internal validation of cross-registration demonstrates
appropriate registration in our patient population. In general, we observed that aortic pulsatility
can vary along the course of the abdominal aorta. Pulsation can also vary within an aneurysm as
well as between aneurysms, but the clinical significance of these findings remain unknown.
Conclusions: Visualization of large vessel pulsatility is possible using ECG-gated CT
angiography, partial scan reconstruction, automatic segmentation, centerline generation, and coregistration
of temporally resolved datasets.