Purpose
4D computed tomography (4DCT) is the clinical standard to image organ motion in radiotherapy, although it is limited in imaging breathing variability. We propose a method to transfer breathing motion across longitudinal imaging datasets to include intra-patient variability and verify its performance in lung cancer patients.

Methods
Five repeated control 4DCTs for 6 non-small cell lung cancer patients were combined into multi-breath datasets (m4DCT) by merging stages of deformable image registration to isolate respiratory motion. The displacement of the centre of mass of the primary tumour and its volume changes were evaluated to quantify intra-patient differences. Internal target volumes defined on the m4DCT were compared with those conventionally drawn on the 4DCT.

Results
Motion analysis suggests no discontinuity at the junction between successive breaths, confirming the method's ability to merge repeated imaging into a continuum. Motion (variability) is primarily in superior-inferior direction and goes from 14.4 mm (8.7 mm) down to 0.1 mm (0.6 mm), respectively for tumours located in the lower lobes or most apical ones. On average, up to 65% and 74% of the tumour volume was subject to expansion or contraction in the inhalation and exhalation phases. These variations lead to an enlargement of the ITV up to 8% of its volume in our dataset.

Conclusion
4DCT can be extended to model variable breathing motion by adding synthetic phases from multiple time-resolved images. The inclusion of this improved knowledge of patients' breathing allows better definition of treatment volumes and their margins for radiation therapy.