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WE‐AB‐303‐11: Verification of a Deformable 4DCT Motion Model for Lung Tumor Tracking Using Different Driving Surrogates
Author(s) -
Woelfelschneider J,
Seregni M,
Fassi A,
Baroni G,
Riboldi M,
Bert C
Publication year - 2015
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 - 10.1118/1.4925876
Subject(s) - ground truth , image registration , match moving , scale invariant feature transform , artificial intelligence , tracking (education) , nuclear medicine , computer vision , computer science , mathematics , motion (physics) , medicine , feature extraction , image (mathematics) , psychology , pedagogy
Purpose: Tumor tracking is an advanced technique to treat intra‐fractionally moving tumors. The aim of this study is to validate a surrogate‐driven model based on four‐dimensional computed tomography (4DCT) that is able to predict CT volumes corresponding to arbitrary respiratory states. Further, the comparison of three different driving surrogates is evaluated. Methods: This study is based on multiple 4DCTs of two patients treated for bronchial carcinoma and metastasis. Analyses for 18 additional patients are currently ongoing. The motion model was estimated from the planning 4DCT through deformable image registration. To predict a certain phase of a follow‐up 4DCT, the model considers for inter‐fractional variations (baseline correction) and intra‐fractional respiratory parameters (amplitude and phase) derived from surrogates. In this evaluation, three different approaches were used to extract the motion surrogate: for each 4DCT phase, the 3D thoraco‐abdominal surface motion, the body volume and the anterior‐posterior motion of a virtual single external marker defined on the sternum were investigated. The estimated volumes resulting from the model were compared to the ground‐truth clinical 4DCTs using absolute HU differences in the lung volume and landmarks localized using the Scale Invariant Feature Transform (SIFT). Results: The results show absolute HU differences between estimated and ground‐truth images with median values limited to 55 HU and inter‐quartile ranges (IQR) lower than 100 HU. Median 3D distances between about 1500 matching landmarks are below 2 mm for 3D surface motion and body volume methods. The single marker surrogates Result in increased median distances up to 0.6 mm. Analyses for the extended database incl. 20 patients are currently in progress. Conclusion: The results depend mainly on the image quality of the initial 4DCTs and the deformable image registration. All investigated surrogates can be used to estimate follow‐up 4DCT phases, however uncertainties decrease for three‐dimensional approaches. This work was funded in parts by the German Research Council (DFG) ‐ KFO 214/2.