Premium
Localization accuracy from automatic and semi‐automatic rigid registration of locally‐advanced lung cancer targets during image‐guided radiation therapy
Author(s) -
Robertson Scott P.,
Weiss Elisabeth,
Hugo Geoffrey D.
Publication year - 2012
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3671929
Subject(s) - image registration , centroid , radiation treatment planning , nuclear medicine , radiation therapy , lung cancer , medicine , medical imaging , artificial intelligence , computer vision , radiology , computer science , image (mathematics) , pathology
Purpose: To evaluate localization accuracy resulting from rigid registration of locally‐advanced lung cancer targets using fully automatic and semi‐automatic protocols for image‐guided radiation therapy. Methods: Seventeen lung cancer patients, fourteen also presenting with involved lymph nodes, received computed tomography (CT) scans once per week throughout treatment under active breathing control. A physician contoured both lung and lymph node targets for all weekly scans. Various automatic and semi‐automatic rigid registration techniques were then performed for both individual and simultaneous alignments of the primary gross tumor volume (GTV P ) and involved lymph nodes (GTV LN ) to simulate the localization process in image‐guided radiation therapy. Techniques included “standard” (direct registration of weekly images to a planning CT), “seeded” (manual prealignment of targets to guide standard registration), “transitive‐based” (alignment of pretreatment and planning CTs through one or more intermediate images), and “rereferenced” (designation of a new reference image for registration). Localization error (LE) was assessed as the residual centroid and border distances between targets from planning and weekly CTs after registration. Results: Initial bony alignment resulted in centroid LE of 7.3 ± 5.4 mm and 5.4 ± 3.4 mm for the GTV P and GTV LN , respectively. Compared to bony alignment, transitive‐based and seeded registrations significantly reduced GTV P centroid LE to 4.7 ± 3.7 mm ( p = 0.011) and 4.3 ± 2.5 mm ( p < 1 × 10 −3 ), respectively, but the smallest GTV P LE of 2.4 ± 2.1 mm was provided by rereferenced registration ( p < 1 × 10 −6 ). Standard registration significantly reduced GTV LN centroid LE to 3.2 ± 2.5 mm ( p < 1 × 10 −3 ) compared to bony alignment, with little additional gain offered by the other registration techniques. For simultaneous target alignment, centroid LE as low as 3.9 ± 2.7 mm and 3.8 ± 2.3 mm were achieved for the GTV P and GTV LN , respectively, using rereferenced registration. Conclusions: Target shape, volume, and configuration changes during radiation therapy limited the accuracy of standard rigid registration for image‐guided localization in locally‐advanced lung cancer. Significant error reductions were possible using other rigid registration techniques, with LE approaching the lower limit imposed by interfraction target variability throughout treatment.