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

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    Author
    Ranjbar, M
    Sabouri, P
    Mossahebi, S
    Sawant, A
    Mohindra, P
    Lasio, G
    Topoleski, L D Timmie
    Date
    2021-02-11
    Journal
    Physics in Medicine and Biology
    Publisher
    IOP Publishing Ltd
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1088/1361-6560/abcbcf
    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- A nd 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 surface deformations with submillimeter accuracy. Analysis of the MI score between more than 4000 pairs of FL and DRR demonstrated that our model led to more similarity between the FL and DRR images compared to 4DCT and DRR images from a model based on an a priori correlation model. Our SMM consistently displayed lower mean and 95th percentile Hausdorff distances. For one patient, 95th percentile Hausdorff distance was reduced by 11 mm. Patient-averaged reductions in mean and 95th percentile Hausdorff distances were 3.6 mm and 7 mm for right-lung, and 3.1 mm and 4 mm for left-lung targets. FL data were used to evaluate model performance and investigate the feasibility of model update. Despite variability in breathing, use of post-treatment FL preserved model fidelity and consistently outperformed 4DCT for position estimation. © 2021 Institute of Physics and Engineering in Medicine.
    Keyword
    4dct
    Capturing cycle to cycle variation
    Image guided radiotherapy
    Lung motion models
    Respiratory motion management in radiotherapy
    Surface monitoring
    Surrogate-based motion model
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/14977
    ae974a485f413a2113503eed53cd6c53
    10.1088/1361-6560/abcbcf
    Scopus Count
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    UMB Open Access Articles 2021

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