Influence of retrospective sorting on image quality in respiratory correlated computed tomography

Purpose: To evaluate the influence of retrospective sorting on image quality in four-dimensional respiratory correlated CT. Materials and methods: Twelve patients with intrapulmonary tumors were examined using a 24-slice CT-scanner in helical mode. Images were reconstructed after retrospective sorting based on five algorithms: amplitude-based sorting with definition of peak-exhalation and peak-inhalation separately/locally for all breathing cycles (LAS) and globally for the time of image acquisition (GAS). Drifts of the breathing signal were corrected in dc-GAS. In phase-based (PS) and cycle-based (CS) algorithm the projections were sorted relative to time. Motion artifacts were scored by a radiologist. The tumor volumes were measured using automatic image segmentation. Results: Averaged over all breathing phases, LAS and PS achieved significantly improved image quality and lowest tumor volume variability compared to GAS, dc-GAS and CS. Imaging redundancy of 5 s was not sufficient for GAS and dc-GAS: missing corresponding amplitude positions in one or several breathing cycles resulted in incomplete reconstruction of peak-ventilation images in 11/12 and 10/12 patients with GAS and dc-GAS, respectively. Limiting the analysis to midventilation phases showed GAS and dc-GAS as the most reliable algorithms. Conclusions: LAS and PS are suggested as a compromise between image quality and radiation dose. (c) 2007 Elsevier Ireland Ltd. All rights reserved.