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Acta Oncologica Volume 54, 2015 - Issue 3
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Lung cancer

Impact of target volume segmentation accuracy and variability on treatment planning for 4D-CT-based non-small cell lung cancer radiotherapy

Spencer MartinDepartment of Medical Biophysics, University of Western Ontario, London, Ontario, Canada
,
Carol JohnsonLondon Regional Cancer Program, London Health Sciences Center, London, Ontario, Canada
,
Mark BrophyDepartment of Computer Science, University of Western Ontario, London, Ontario, Canada
,
David A. PalmaDepartment of Oncology, University of Western Ontario, London, Ontario, Canada;Department of Radiation Oncology, London Regional Cancer Program, London, Ontario, Canada
,
John L. BarronDepartment of Computer Science, University of Western Ontario, London, Ontario, Canada
,
Steven S. BeaucheminDepartment of Computer Science, University of Western Ontario, London, Ontario, Canada
,
Alexander V. LouieDepartment of Oncology, University of Western Ontario, London, Ontario, Canada;Department of Radiation Oncology, London Regional Cancer Program, London, Ontario, Canada
,
Edward YuDepartment of Oncology, University of Western Ontario, London, Ontario, Canada;Department of Radiation Oncology, London Regional Cancer Program, London, Ontario, Canada
,
Brian YaremkoDepartment of Oncology, University of Western Ontario, London, Ontario, Canada;Department of Radiation Oncology, London Regional Cancer Program, London, Ontario, Canada
,
Belal AhmadDepartment of Oncology, University of Western Ontario, London, Ontario, Canada;Department of Radiation Oncology, London Regional Cancer Program, London, Ontario, Canada
,
George B. RodriguesDepartment of Medical Biophysics, University of Western Ontario, London, Ontario, Canada;Department of Epidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada;Department of Oncology, University of Western Ontario, London, Ontario, Canada;Department of Radiation Oncology, London Regional Cancer Program, London, Ontario, Canada
&
Stewart GaedeDepartment of Medical Biophysics, University of Western Ontario, London, Ontario, Canada;Department of Oncology, University of Western Ontario, London, Ontario, Canada;Department of Radiation Oncology, London Regional Cancer Program, London, Ontario, CanadaCorrespondence[email protected]
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Pages 322-332 | Received 16 Jun 2014, Accepted 24 Sep 2014, Published online: 28 Oct 2014

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Cai Grau, Morten Høyer, Per Rugaard Poulsen, Ludvig Paul Muren, Stine Sofia Korreman, Kari Tanderup, Jacob Christian Lindegaard, Jan Alsner & Jens Overgaard. (2017) Rethink radiotherapy – BIGART 2017. Acta Oncologica 56:11, pages 1341-1352.
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Articles from other publishers (13)

Jennifer Robbins, Marcel van Herk, Björn Eiben, Andrew Green & Eliana Vásquez Osorio. (2023) Probabilistic evaluation of plan quality for time-dependent anatomical deformations in head and neck cancer patients. Physica Medica 109, pages 102579.
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Yagiz Yedekci, Melis Gültekin, Sezin Yuce Sari & Ferah Yildiz. (2023) Improving normal tissue sparing using scripting in endometrial cancer radiation therapy planning. Radiation and Environmental Biophysics.
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Benjamin J. Rich, Benjamin O. Spieler, Yidong Yang, Lori Young, William Amestoy, Maria Monterroso, Lora Wang, Alan Dal Pra & Fei Yang. (2022) Erring Characteristics of Deformable Image Registration-Based Auto-Propagation for Internal Target Volume in Radiotherapy of Locally Advanced Non-Small Cell Lung Cancer. Frontiers in Oncology 12.
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Anning Yang, Na Lu, Huayong Jiang, Diandian Chen, Yanjun Yu, Yadi Wang, Qiusheng Wang & Fuli Zhang. (2022) Automatic delineation of organs at risk in non-small cell lung cancer radiotherapy based on deep learning networks*. Oncology and Translational Medicine 8:2, pages 83-88.
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Fuli Zhang, Qiusheng Wang, Anning Yang, Na Lu, Huayong Jiang, Diandian Chen, Yanjun Yu & Yadi Wang. (2022) Geometric and Dosimetric Evaluation of the Automatic Delineation of Organs at Risk (OARs) in Non-Small-Cell Lung Cancer Radiotherapy Based on a Modified DenseNet Deep Learning Network. Frontiers in Oncology 12.
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Florian Charlier, Thomas Descamps, Yolande Lievens, Xavier Geets, Vincent Remouchamps, Maarten Lambrecht & Luigi Moretti. (2022) ProCaLung – Peer review in stage III, mediastinal node-positive, non-small-cell lung cancer: How to benchmark clinical practice of nodal target volume definition and delineation in Belgium☆. Radiotherapy and Oncology 167, pages 57-64.
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Shadab Momin, Yang Lei, Zhen Tian, Tonghe Wang, Justin Roper, Aparna H. Kesarwala, Kristin Higgins, Jeffrey D. Bradley, Tian Liu & Xiaofeng Yang. (2021) Lung tumor segmentation in 4D CT images using motion convolutional neural networks. Medical Physics 48:11, pages 7141-7153.
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Valerio Nardone, Francesca Maria Giugliano, Alfonso Reginelli, Angelo Sangiovanni, Maria Mormile, Luciano Iadanza, Salvatore Cappabianca & Cesare Guida. (2020) 4D CT analysis of organs at risk (OARs) in stereotactic radiotherapy. Radiotherapy and Oncology 151, pages 10-14.
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Eric Aliotta, Hamidreza Nourzadeh & Jeffrey Siebers. (2019) Quantifying the dosimetric impact of organ-at-risk delineation variability in head and neck radiation therapy in the context of patient setup uncertainty. Physics in Medicine & Biology 64:13, pages 135020.
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Nadine Wong Yuzhen & Sarah Barrett. (2019) A review of automatic lung tumour segmentation in the era of 4DCT. Reports of Practical Oncology & Radiotherapy 24:2, pages 208-220.
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Jingjing Zhang, Svetlana Markova, Alejandro Garcia, Kirk Huang, Xingyu Nie, Wookjin Choi, Wei Lu, Abraham Wu, Andreas Rimner & Guang Li. (2018) Evaluation of automatic contour propagation in T2-weighted 4DMRI for normal-tissue motion assessment using internal organ-at-risk volume (IRV). Journal of Applied Clinical Medical Physics 19:5, pages 598-608.
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Spencer Martin, Ricky O’ Brien, Christian Hofmann, Paul Keall & John Kipriditis. (2018) An in silico performance characterization of respiratory motion guided 4DCT for high-quality low-dose lung cancer imaging . Physics in Medicine & Biology 63:15, pages 155012.
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Marc Niethammer, Kilian M. Pohl, Firdaus Janoos & William M. Wells III. (2017) Active Mean Fields for Probabilistic Image Segmentation: Connections with Chan--Vese and Rudin--Osher--Fatemi Models. SIAM Journal on Imaging Sciences 10:3, pages 1069-1103.
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