Creation of 4D imaging data using open source image registration software

4D images (3 spatial dimensions plus time) using CT or MRI will play a key role in radiation medicine as techniques for respiratory motion compensation become more widely available. Advance knowledge of the motion of a tumor and its surrounding anatomy will allow the creation of highly conformal dose distributions in organs such as the lung, liver, and pancreas. However, many of the current investigations into 4D imaging rely on synchronizing the image acquisition with an external respiratory signal such as skin motion, tidal flow, or lung volume, which typically requires specialized hardware and modifications to the scanner. We propose a novel method for 4D image acquisition that does not require any specific gating equipment and is based solely on open source image registration algorithms. Specifically, we use the Insight Toolkit (ITK) to compute the normalized mutual information (NMI) between images taken at different times and use that value as an index of respiratory phase. This method has the advantages of (1) being able to be implemented without any hardware modification to the scanner, and (2) basing the respiratory phase on changes in internal anatomy rather than external signal. We have demonstrated the capabilities of this method with CT fluoroscopy data acquired from a swine model.