Abstract

The article aims to determine if a prospective acquisition algorithm can be used to find the ideal set of free-breathing phases for fast-helical model-based 4D-CT. A retrospective five-patient dataset that consisted of 25 repeated free breathing CT scans per patient was used. The sum of the square root amplitude difference between all the breathing phases was defined as an objective function to determine the optimality of sets of breathing phases. The objective function was intended to determine if a specific set of breathing phases would yield a motion model that could accurately predict the motion in all 25 CT scans. Voxel specific motion models were calculated using all combinations of N scans from 25 breathing trajectories, (3 ⩽ N ⩽ 25), and the minimum number of scans required to absolutely characterize the motion model was analyzed. This analysis suggests that the number of scans could potentially be reduced to as few as five scans. When the objective function was large, the resulting motion model provided an excellent approximation to the motion model created using all 25 scans.

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