An evaluation of an automated 4D-CT contour propagation tool to define an internal gross tumour volume for lung cancer radiotherapy

Background and purpose: To evaluate an automated 4D-CT contouring propagation tool by its impact on the inter- and intra-physician variability in lung tumour delineation.

Materials and methods: In a previous study, six radiation oncologists contoured the gross tumour volume (GTV) and nodes on 10 phases of the 4D-CT dataset of 10 lung cancer patients to examine the intra- and inter-physician variability. In this study, a model-based deformable image registration algorithm was used to propagate the GTV and nodes on each phase of the same 4D-CT datasets. A blind review of the contours was performed by each physician and edited. Inter- and intra-physician variability for both the manual and automated methods was assessed by calculating the centroid motion of the GTV using the Pearson correlation coefficient and the variability in the internal gross tumour volume (IGTV) overlap using the Dice similarity coefficient (DSC).

Results: The time for manual delineation was (42.7±18.6)min versus (17.7±5.4)min when the propagation tool was used. A significant improvement in the mean Pearson correlation coefficient was also observed. There was a significant decrease in mean DSC in only 1 out of 10 primary IGTVs and 2 out of 10 nodal IGTVs. Intra-physician variability was not significantly impacted (DSC>0.742).

Conclusions: Automated 4D-CT propagation tools can significantly decrease the IGTV delineation time without significantly decreasing the inter- and intra-physician variability.