Optimized projection binning for improved helical amplitude- and phase-based 4DCT reconstruction in the presence of breathing irregularity

Respiration-correlated CT (4DCT) forms the basis of clinical 4D radiotherapy workflows for patients with thoracic and abdominal lesions. 4DCT image data, however, often suffers from motion artifacts due to unfulfilled assumptions during reconstruction and image/projection data sorting. In this work and focusing on low-pitch helical scanning protocols, two questionable assumptions are addressed: (1) the need for regular breathing patterns and (2) a constant correlation between the external breathing signal acquired for image/projection sorting and internal motion patterns. To counteract (1), a patient-specific upper breathing signal amplitude threshold is introduced to avoid artifacts due to unusual deep inspiration (helpful for both amplitude- and phase-based reconstruction). In addition, a projection data binning algorithm based on a statistical analysis of the patient's breathing signal is proposed to stabilize phase-based sorting. To further alleviate the need for (2), an image artifact metric is incorporated into and minimized during the reconstruction process. The optimized reconstruction is evaluated using 30 clinical 4DCT data sets and demonstrated to significantly reduce motion artifacts.