Purpose: Current respiratory motion monitoring devices used for motion synchronization in medical imaging and radiotherapy provide either 1D respiratory signal over a specific region or 3D information based on few external or internal markers. On the other hand, newer technology may offer the potential to monitor the entire patient external surface in real time. The main objective of this study was to assess the motion correlation between such an external patient surface and internal anatomical landmarks motion.
Methods: Four dimensional computed tomography (4D CT) volumes for ten patients were used in this study. Anatomical landmarks were manually selected in the thoracic region across the 4D CT datasets by two experts. The landmarks included normal structures as well as the tumor location. In addition, a distance map representing the entire external patient surface, which corresponds to surfaces acquired by a time of flight (ToF) camera or similar devices, was created by segmenting the skin of all 4D CT volumes using a thresholding algorithm. Finally, the correlation between the internal landmarks and external surface motion was evaluated for different regions (placement and size) throughout a patient's surface.
Results: Significant variability was observed in the motion of the different parts of the external patient surface. The larger motion magnitude was consistently measured in the central regions of the abdominal and the thoracic areas for the different patient datasets considered. The highest correlation coefficients were observed between the motion of these external surface areas and internal landmarks such as the diaphragm and mediastinum structures as well as the tumor location landmarks (0.8 +/- 0.18 and 0.72 +/- 0.12 for the abdominal and the thoracic regions, respectively). Worse correlation was observed when one considered landmarks not significantly influenced by respiratory motion such as the apex and the sternum.
Conclusions: There were large differences in the motion correlation observed considering different regions of interest placed over a patients' external surface and internal anatomical landmarks. The positioning of current devices used for respiratory motion synchronization may reduce such correlation by averaging the motion over correlated and poorly correlated external regions. The potential of capturing in real-time the motion of the complete external patient surface as well as choosing the area of the surface that correlates best with the internal motion should allow reducing such variability and associated errors in both respiratory motion synchronization and subsequent motion modeling processes.