Validation of a CT-based motion model with in-situ fluoroscopy for lung surface deformation estimation.

Physics in Medicine and Biology
M RanjbarL D Timmie Topoleski

Abstract

Many surrogate-based motion models (SMMs), proposed to guide motion management in radiotherapy, are constructed by correlating motion of an external surrogate and internal anatomy during CT-simulation. Changes in this correlation define model break down. We validate a methodology that incorporates fluoroscopic (FL) images acquired during treatment for SMM construction and update. Under a prospective IRB, 4DCT scans, VisionRT (VRT) surfaces, and orthogonal FLs were collected from five lung cancer patients. VRT surfaces and two FL time-series were acquired pre- and post-treatment. A simulated annealing optimization scheme was used to estimate optimal lung deformations by maximizing the mutual information (MI) between digitally reconstructed radiographs (DRRs) of the SMM-estimated 3D images and FLs. Our SMM used partial-least-regression and was trained using the optimal deformations and VRT surfaces from the first breathing-cycle. SMM performance was evaluated using the MI score between reference FLs and the corresponding SMM or phase-assigned 4DCT DRRs. The Hausdorff distance for contoured landmarks was used to evaluate target position estimation error. For four out of five patients, two principal components approximated lung sur...Continue Reading

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