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Title: Automatic Segmentation and Online virtualCT in Head-and-Neck Adaptive Radiation Therapy

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 evidencemore » 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.« less

Authors:
 [1];  [2];  [3];  [1];  [4]; ;  [2];  [1];  [4];  [2];  [4];  [4]
  1. Department of Bioengineering, Politecnico di Milano, Milano (Italy)
  2. Advanced Radiotherapy Center, European Institute of Oncology, Milano (Italy)
  3. Department of Experimental and Clinical Medicine, Universita degli Studi Magna Graecia, Catanzaro (Italy)
  4. (Italy)
Publication Date:
OSTI Identifier:
22149615
Resource Type:
Journal Article
Journal Name:
International Journal of Radiation Oncology, Biology and Physics
Additional Journal Information:
Journal Volume: 84; Journal Issue: 3; Other Information: Copyright (c) 2012 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0360-3016
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; ALGORITHMS; CALORIMETRY; CAT SCANNING; DECISION MAKING; GLANDS; HEAD; IMAGES; JAW; NECK; NEOPLASMS; PATIENTS; RADIOTHERAPY; SIMULATION

Citation Formats

Peroni, Marta, E-mail: marta.peroni@mail.polimi.it, Ciardo, Delia, Spadea, Maria Francesca, Riboldi, Marco, Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, Comi, Stefania, Alterio, Daniela, Baroni, Guido, Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, Orecchia, Roberto, Universita degli Studi di Milano, Milano, and Medical Department, Centro Nazionale di Adroterapia Oncologica, Pavia. Automatic Segmentation and Online virtualCT in Head-and-Neck Adaptive Radiation Therapy. United States: N. p., 2012. Web. doi:10.1016/J.IJROBP.2012.04.003.
Peroni, Marta, E-mail: marta.peroni@mail.polimi.it, Ciardo, Delia, Spadea, Maria Francesca, Riboldi, Marco, Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, Comi, Stefania, Alterio, Daniela, Baroni, Guido, Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, Orecchia, Roberto, Universita degli Studi di Milano, Milano, & Medical Department, Centro Nazionale di Adroterapia Oncologica, Pavia. Automatic Segmentation and Online virtualCT in Head-and-Neck Adaptive Radiation Therapy. United States. doi:10.1016/J.IJROBP.2012.04.003.
Peroni, Marta, E-mail: marta.peroni@mail.polimi.it, Ciardo, Delia, Spadea, Maria Francesca, Riboldi, Marco, Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, Comi, Stefania, Alterio, Daniela, Baroni, Guido, Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, Orecchia, Roberto, Universita degli Studi di Milano, Milano, and Medical Department, Centro Nazionale di Adroterapia Oncologica, Pavia. Thu . "Automatic Segmentation and Online virtualCT in Head-and-Neck Adaptive Radiation Therapy". United States. doi:10.1016/J.IJROBP.2012.04.003.
@article{osti_22149615,
title = {Automatic Segmentation and Online virtualCT in Head-and-Neck Adaptive Radiation Therapy},
author = {Peroni, Marta, E-mail: marta.peroni@mail.polimi.it and Ciardo, Delia and Spadea, Maria Francesca and Riboldi, Marco and Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia and Comi, Stefania and Alterio, Daniela and Baroni, Guido and Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia and Orecchia, Roberto and Universita degli Studi di Milano, Milano and Medical Department, Centro Nazionale di Adroterapia Oncologica, Pavia},
abstractNote = {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.},
doi = {10.1016/J.IJROBP.2012.04.003},
journal = {International Journal of Radiation Oncology, Biology and Physics},
issn = {0360-3016},
number = 3,
volume = 84,
place = {United States},
year = {2012},
month = {11}
}