SU‐E‐T‐286: A Case Study of More Accurate Phase Re‐Assignment for 4DCT Images

Abstract

Purpose: We present a case study of an improved phase re‐assignment approach for a challenging 4DCT image data set on a commercial system.Methods: The Varian RPM system was used to produce the respiratory traces for phase binning the raw 4DCT images acquired from a GE LightSpeedRT CT scanner. The RPM system uses a predictive approach to generate a *.vxp file containing details of the respiratory signal for correlation with the raw 4DCT images. The *.vxp file was read in using a program written in C++, and respiratory phases were re‐assigned using an approach which retrospectively detects individual max and min of the respiratory signal. The re‐binned file was used to reprocess the raw 4DCT data and generate a set of new phase binned images, which were compared with those from the original *.vxp files.Results: For one challenging clinical case, we demonstrate how the current predictive method can inadvertently assign a grossly incorrect phase after a highly irregular breathing cycle has occurred. The new image sets were seen to be significantly more accurate in representation of particular smooth internal structures. Seven additional patients were retrospectively studied using the same re‐binning approach, with none of these patients demonstrating significant image quality improvement. This suggests that the vendorˈs currently employed phase assignment method produces reasonable results for the majority of scenarios, but may suffer significantly for unusual cases where extreme breathing anomalies occur. Conclusions: The vendorˈs standard phase assignment method which uses a predictive breathing cycle algorithm can be challenged in instances where highly anomalous breathing cycles of much longer period are encountered. This can introduce a rippling, or ‘piano key’, effect on subsequent images. We presented a simple retrospective method for improving the accuracy of phase binning in these circumstances and demonstrated improved image fidelity on one challenging clinical case.