Literature DB >> 22672753

Automatic segmentation and online virtualCT in head-and-neck adaptive radiation therapy.

Marta Peroni1, Delia Ciardo, Maria Francesca Spadea, Marco Riboldi, Stefania Comi, Daniela Alterio, Guido Baroni, Roberto Orecchia.   

Abstract

PURPOSE: The purpose of this work was to develop and validate an efficient and automatic strategy to generate online virtual computed tomography (CT) scans for adaptive radiation therapy (ART) in head-and-neck (HN) cancer treatment.
METHOD: We retrospectively analyzed 20 patients, treated with intensity modulated radiation therapy (IMRT), for an HN malignancy. Different anatomical structures were considered: mandible, parotid glands, and nodal gross tumor volume (nGTV). We generated 28 virtualCT scans by means of nonrigid registration of simulation computed tomography (CTsim) and cone beam CT images (CBCTs), acquired for patient setup. We validated our approach by considering the real replanning CT (CTrepl) as ground truth. We computed the Dice coefficient (DSC), center of mass (COM) distance, and root mean square error (RMSE) between correspondent points located on the automatically segmented structures on CBCT and virtualCT.
RESULTS: Residual deformation between CTrepl and CBCT was below one voxel. Median DSC was around 0.8 for mandible and parotid glands, but only 0.55 for nGTV, because of the fairly homogeneous surrounding soft tissues and of its small volume. Median COM distance and RMSE were comparable with image resolution. No significant correlation between RMSE and initial or final deformation was found.
CONCLUSION: The analysis provides evidence that deformable image registration may contribute significantly in reducing the need of full CT-based replanning in HN radiation therapy by supporting swift and objective decision-making in clinical practice. Further work is needed to strengthen algorithm potential in nGTV localization.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22672753     DOI: 10.1016/j.ijrobp.2012.04.003

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  14 in total

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10.  Feasibility of automated proton therapy plan adaptation for head and neck tumors using cone beam CT images.

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