Pancreatic gross tumor volume contouring on computed tomography (CT) compared with magnetic resonance imaging (MRI): Results of an international contouring conference.

PURPOSE: Accurate identification of the gross tumor volume (GTV) in pancreatic adenocarcinoma is challenging. We sought to understand differences in GTV delineation using pancreatic computed tomography (CT) compared with magnetic resonance imaging (MRI). METHODS AND MATERIALS: Twelve attending radiation oncologists were convened for an international contouring symposium. All participants had a clinical and research interest in pancreatic adenocarcinoma. CT and MRI scans from 3 pancreatic cases were used for contouring. CT and MRI GTVs were analyzed and compared. Interobserver variability was compared using Dice's similarity coefficient (DSC), Hausdorff distances, and Jaccard indices. Mann-Whitney tests were used to check for significant differences. Consensus contours on CT and MRI scans and constructed count maps were used to visualize the agreement. Agreement regarding the optimal method to determine GTV definition using MRI was reached. RESULTS: Six contour sets (3 from CT and 3 from MRI) were obtained and compared for each observer, totaling 72 contour sets. The mean volume of contours on CT was significantly larger at 57.48 mL compared with a mean of 45.76 mL on MRI, P = .011. The standard deviation obtained from the CT contours was significantly larger than the standard deviation from the MRI contours (P = .027). The mean DSC was 0.73 for the CT and 0.72 for the MRI (P = .889). The conformity index measurement was similar for CT and MRI (P = .58). Count maps were created to highlight differences in the contours from CT and MRI. CONCLUSIONS: Using MRI as a primary image set to define a pancreatic adenocarcinoma GTV resulted in smaller contours compared with CT. No differences in DSC or the conformity index were seen between MRI and CT. A stepwise method is recommended as an approach to contour a pancreatic GTV using MRI.

Duke Scholars

Author Manisha Palta Radiation Oncology