TU-C-141-04: Evaluation of Clinical Acceptability of DIR Mapped Contours for Adaptive Radiotherapy with 4D Cone-Beam CT

Abstract

Purpose: To evaluate clinical acceptability of contours generated using deformable image registration of 4D fan beam (4DFBCT) to 4D cone beam (4DCBCT) images for image-guided adaptive radiotherapy (IGART). Methods: Sixteen locally advanced non-small cell lung cancer (NSCLC) patients underwent one planning 4DFBCT and weekly 4DCBCT scans. 4DFBCT to 4DCBCT registrations were performed using two intensity-driven deformable image registration (DIR) algorithms: 1) small deformation, inverse consistent linear elastic (SICLE) algorithm and 2) Insight Toolkit diffeomorphic demons (DEMONS). Multiple physicians delineated the gross tumor volume in all images (MANUAL). Manual contours were mapped from 4DFBCT to 4DCBCT for two scans in each patient, and were compared with manual contours using Dice similarity coefficient (DSC), average symmetric distance (ASD), false positive (FP), false negative (FN) and percentage volume difference (%VD). A physician was asked to rate DIR generated and manual contours as A) clinically acceptable (CA) B) clinically acceptable after minor modifications (CAMM) and C) clinically unacceptable (CU) using planning CT contour as reference. Reviewing physician was unaware that some of the contours were manual. The results were analyzed with respect to similarity measures, volume and regression characteristics of the tumor. Results: No contours were rated as CU by the physician. The number of contours rated as CA and CAMM was respectively 14 (44%) and 18 (56%) for SICLE, 3 (9%) and 29 (91%) for DEMONS, and 26 (81%) and 6 (19%) for MANUAL. No correlation was observed between physician ratings and DSC, ASD, FP, FN, %VD, tumor shrinkage, day of CBCT scan, and volume of the GTV. Conclusion: DIR generated contours were considered clinically acceptable for IGART, but may require some manual adjustment prior to use. Volume and surface similarity measures did not correlate with physician judgment of clinical acceptability. Supported by NIH Grant P01 CA 116602; This work was supported by a grant (P01CA116602) from the National Cancer Institute. Gary E. Christensen holds a papent related to the SICLE registration algorithm; E. Weiss and J. Williamson has grants from Varian medical systems and Philips Radiation Oncology Systems.