SU‐GG‐J‐54: Evaluation of Residual Errors in Online Guidance of Primary and Nodal Targets in Lung Cancer

Abstract

Purpose: To evaluate the accuracy of online guidance for primary and nodal lung cancer targets. Method and Materials: Weekly CT scans under active breathing control were acquired during treatment for 18 patients enrolled as research subjects. Separate primary gross tumor volume (GTVP) and involved lymph node GTVs (GTVLN) were delineated by a physician on all images. Each weekly online image was aligned to the reference (planning) image automatically using a rigid image‐based registration. Four rectangular regions of interest were evaluated for the ability to match the target structures: the whole image; the GTVP + 1 cm; the GTVLN + 1 cm; and both the GTVP and GTVLN + 1 cm. The GTVs on the online images were translated according to this new registration, and the centroid displacements of the delineated GTVs were calculated to measure the residual error after image‐based alignment. Results: The mean absolute error was 5.1 ± 4.7 mm for the GTVP and 6.4 ± 6.9 mm for the GTVLN. The combined mean absolute error was 5.7 ± 5.9 mm for both structures. Rigid registration of GTVP + 1 cm yielded the smallest residual error (RE) for the primary tumor of 3.3 ± 3.9 mm, with a RE of 4.8 ± 4.8 mm for the lymph nodes. Registration of GTVLN + 1 cm provided the smallest RE for the lymph nodes of 4.1 ± 5.8 mm, though the primary tumor RE was 5.0 ± 4.9. The smallest combined RE for both structures was 4.0 ± 4.5, which was obtained using rigid registration of the GTVP + 1 cm. Conclusion: Shape, volume, and relative position change of multiple targets introduces error into soft‐tissue localization in locally‐advanced lung cancer, although tumor regression was the dominant source of error. Deformable registration methods may be required to improve localization accuracy.